From de10307d6cbb1cc26485c1132468e145b6f53e06 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mine=20=C3=87etinkaya-Rundel?= Date: Thu, 2 May 2024 12:51:06 -0400 Subject: [PATCH] Re-render --- .../data-import/execute-results/html.json | 5 +- .../html/lubridate/execute-results/html.json | 9 +- _freeze/html/quarto/execute-results/html.json | 5 +- .../shiny-python/execute-results/html.json | 15 +++ .../html/sparklyr/execute-results/html.json | 9 +- html/images/logo-lubridate.png | Bin 20069 -> 19955 bytes html/images/logo-readr.png | Bin 16333 -> 16183 bytes html/images/logo-shiny.png | Bin 174038 -> 24710 bytes html/images/logo-sparklyr.png | Bin 56318 -> 56168 bytes html/quarto.qmd | 110 ++++++++++-------- 10 files changed, 93 insertions(+), 60 deletions(-) create mode 100644 _freeze/html/shiny-python/execute-results/html.json diff --git a/_freeze/html/data-import/execute-results/html.json b/_freeze/html/data-import/execute-results/html.json index 19176587..3df98ce3 100644 --- a/_freeze/html/data-import/execute-results/html.json +++ b/_freeze/html/data-import/execute-results/html.json @@ -1,7 +1,8 @@ { - "hash": "3dd83c708269f018503db15e7fe27d2e", + "hash": "0a1afa2ff53dbb8295d59babc8374cb1", "result": { - "markdown": "---\ntitle: \"Data import with the tidyverse :: Cheatsheet\"\ndescription: \" \"\nexecute:\n eval: true\n output: false\n warning: true\n---\n\n::: {.cell .column-margin}\n\"Hex\n

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\n* Bengali\n* Persian\n* Russian\n* Spanish\n* Turkish\n* Ukrainian\n* Uzbek\n:::\n\n\nOne of the first steps of a project is to import outside data into R.\nData is often stored in tabular formats, like csv files or spreadsheets.\n\n- The first half of this cheatsheet shows how to import and save text files into R using **readr**.\n- The second half shows how to import spreadsheet data from Excel files using **readxl** or Google Sheets using **googlesheets4**.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(readr)\nlibrary(readxl)\nlibrary(googlesheets4)\n```\n:::\n\n\nFor importing other types of data try one of the following packages:\n\n- **haven**: SPSS, Stata, and SAS files\n- **DBI**: databases\n- **jsonlite**: json\n- **xml2**: XML\n- **httr**: Web APIs\n- **rvest**: HTML (Web Scraping)\n- **readr::read_lines()**: text data\n\n## Read Tabular Data with readr\n\n\n\n\n\nSee `?read_delim`.\n\n``` r\nread_*(\n file, \n col_names = TRUE, col_types = NULL, col_select = NULL, \n show_col_types = TRUE\n id = NULL, locale, \n n_max = Inf, skip = 0, guess_max = min(1000, n_max), \n na = c(\"\", \"NA\")\n)\n```\n\n### Examples\n\n- Read files with any delimiter: `read_delim()`.\n If no delimiter is specified, it will automatically guess.\n\n - If the file you want to import is the following:\n\n ``` \n A|B|C\n 1|2|3\n 4|5|NA\n ```\n\n\n ::: {.cell}\n \n :::\n\n\n - Read it with `read_delim()` and it will look like the following when imported:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_delim(\"file.txt\", delim = \"|\", show_col_types = FALSE)\n ```\n :::\n\n\n - To make `file.txt`, run:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n write_file(\"A|B|C\\n1|2|3\\n4|5|NA\", file = \"file.txt\")\n ```\n :::\n\n\n- Read a comma delimited file with period decimal marks: `read_csv()`.\n\n - If the file you want to import is the following:\n\n ``` \n A,B,C\n 1,2,3\n 4,5,NA\n ```\n\n\n ::: {.cell}\n \n :::\n\n\n - Read it with `read_csv()` and it will look like the following when imported:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\"file.csv\", show_col_types = FALSE)\n ```\n :::\n\n\n - To make `file.csv`, run:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n write_file(\"A,B,C\\n1,2,3\\n4,5,NA\", file = \"file.csv\")\n ```\n :::\n\n\n- Read semicolon delimited files with comma decimal marks: `read_csv2()`.\n\n - If the file you want to import is the following:\n\n ``` \n A;B;C\n 1,5;2;3\n 4,5;5;NA\n ```\n\n\n ::: {.cell}\n \n :::\n\n\n - Read it with `read_csv2()` and it will look like the following when imported:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv2(\"file2.csv\", show_col_types = FALSE)\n ```\n :::\n\n\n - To make `file2.csv`, run:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n write_file(\"A;B;C\\n1,5;2;3\\n4,5;5;NA\", file = \"file2.csv\")\n ```\n :::\n\n\n- Read a tab delimited file: `read_tsv()` or `read_table()`.\n\n Read a fixed width file: `read_fwf(\"file.tsv\", fwf_widths(c(2, 2, NA)))`.\n\n - If the file you want to import is the following:\n\n ``` \n A B C\n 1 2 3\n 4 5 NA\n ```\n\n\n ::: {.cell}\n \n :::\n\n\n - Read it with `read_tsv()` and it will look like the following when imported:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_tsv(\"file.tsv\", show_col_types = FALSE)\n ```\n :::\n\n\n - To make `tsv`, run:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n write_file(\"A\\tB\\tC\\n1\\t2\\t3\\n4\\t5\\tNA\\n\", file = \"file.tsv\")\n ```\n :::\n\n\n### Useful read arguments\n\nSuppose you have the following CSV files that you want to read in, called `file.csv`:\n\n`file.csv`\n\n``` \nA,B,C\n1,2,3\n4,5,NA\n```\n\n`file3.csv`\n\n``` \nA,B,C\n7,8,9\nNA,11,12\n```\n\nTo make these files, run:\n\n\n::: {.cell}\n\n```{.r .cell-code}\nwrite_file(\"A,B,C\\n1,2,3\\n4,5,NA\", file = \"file.csv\")\nwrite_file(\"A,B,C\\n7,8,9\\nNA,11,12\", file = \"file3.csv\")\n```\n:::\n\n\n- No header: `col_names = FALSE`\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\"file.csv\", col_names = FALSE)\n ```\n :::\n\n\n- Provide header: `col_names = c(\"x\", \"y\", \"z\")`\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\"file.csv\", col_names = c(\"x\", \"y\", \"z\"))\n ```\n :::\n\n\n- Skip lines:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\"file.csv\", skip = 1)\n ```\n :::\n\n\n- Read a subset of lines:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\"file.csv\", skip = 1)\n ```\n :::\n\n\n- Read values as missing:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\"file.csv\", na = c(\"1\"))\n ```\n :::\n\n\n- Specify decimal marks:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_delim(\"file2.csv\", locale = locale(decimal_mark = \",\"))\n ```\n :::\n\n\n- Read multiple files into a single table:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(c(\"file.csv\", \"file3.csv\"), id = \"origin_file\")\n ```\n :::\n\n\n### Save data with readr\n\n``` r\nwrite_*(\n x, file, \n na = \"NA\", \n append, col_names, quote, escape, eol, num_threads, progress\n)\n```\n\n- Write files with any delimiter: `write_delim(x, file, delim = \" \")`\n- Write a comma delimited file: `write_csv(x, file)`\n- Write a semicolon delimited file: `write_csv2(x, file)`\n- Write a tab delimited file: `write_tsv(x, file)`\n\n### Column specification with readr\n\nColumn specifications define what data type each column of a file will be imported as.\nBy default readr will generate a column spec when a file is read and output a summary.\n\n`spec(df)`: Extract the full column specification for the given imported data frame.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nspec(df)\n# cols(\n# age = col_integer(), # age is an integer\n# edu = col_character(), # edu is a character\n# earn = col_double() # earn is a double (numeric)\n# )\n```\n:::\n\n\n#### Column types\n\nEach column type has a function and corresponding string abbreviation.\n\n- `col_logical() - \"l\"`\n- `col_integer() - \"i\"`\n- `col_double() - \"d\"`\n- `col_number() - \"n\"`\n- `col_character() - \"c\"`\n- `col_factor(levels, ordered = FALSE) - \"f\"`\n- `col_datetime(format = \"\") - \"T\"`\n- `col_date(format = \"\") - \"D\"`\n- `col_time(format = \"\") - \"t\"`\n- `col_skip() - \"-\", \"_\"`\n- `col_guess() - \"?\"`\n\n#### Useful column arguments\n\n- Hide col spec message:\n\n ``` r\n read_*(file, show_col_types = FALSE)\n ```\n\n- Select columns to import: Use names, position, or selection helpers.\n\n ``` r\n read_*(file, col_select = c(age, earn))\n ```\n\n- Guess column types: To guess a column type, `read_ *()` looks at the first 1000 rows of data.\n Increase with `guess_max`.\n\n ``` r\n read_*(file, guess_max = Inf)\n ```\n\n#### Define column specification\n\n- Set a default type:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\n file, \n col_type = list(.default = col_double())\n )\n ```\n :::\n\n\n- Use column type or string abbreviation:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\n file, \n col_type = list(x = col_double(), y = \"l\", z = \"_\")\n )\n ```\n :::\n\n\n- Use a single string of abbreviations:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n # col types: skip, guess, integer, logical, character\n read_csv(\n file, \n col_type = \"_?ilc\"\n )\n ```\n :::\n\n\n## Import spreadsheets with readxl\n\n### Read Excel files\n\nRead a .xls or .xlsx file based on the file extension, e.g. `read_excel(\"excel_file.xlsx\")`.\nSee [Useful read arguments] for more read arguments.\nAlso `read_xls()` and `read_xlsx()`.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nread_excel(path, sheet = NULL, range = NULL)\n```\n:::\n\n\n- If the Google sheet you want to import is the following:\n\n | A | B | C | D | E |\n |-----|-----|-----|-----|-----|\n | x1 | x2 | x3 | x4 | x5 |\n | x | | z | 8 | |\n | y | 7 | | 9 | 10 |\n\n : Spreadsheet with 5 columns (A through E) and three rows. First row reads x1 through x5. Second and third row have some missing values.\n\n- It will look like the following when imported:\n\n\n ::: {.cell}\n \n :::\n\n\n### Read sheets\n\n- Specify which sheet to read by position or name: `read_excel(path, sheet = NULL)`\n\n - `read_excel(path, sheet = 1)`\n - `read_excel(path, sheet = \"s1\")`\n\n- Get a vector of sheet names: `excel_sheets(path)`\n\n `excel_sheets(\"excel_file.xlsx\")`\n\n- To read multiple sheets:\n\n 1. Get a vector of sheet names from the file path.\n\n 2. Set the vector names to be the sheet names.\n\n 3. Use `purrr::map()` and `purrr::list_rbind()` to read multiple files into one data frame.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n path <- \"your_file_path.xlsx\"\n path |> \n excel_sheets() |>\n set_names() |>\n map(read_excel, path = path) |>\n list_rbind()\n ```\n :::\n\n\n### readxl column specification\n\n- Column specifications define what data type each column of a file will be imported as.\n\n- Use the `col_types` argument of `read_excel()` to set the column specification.\n\n- Guess column types: To guess a column type, `read_excel()` looks at the first 1000 rows of data.\n Increase with the `guess_max` argument.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_excel(path, guess_max = Inf)\n ```\n :::\n\n\n- Set all columns to same type, e.g. character:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_excel(path, col_types = \"text\")\n ```\n :::\n\n\n- Set each column individually:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_excel(\n path,\n col_types = c(\"text\", \"guess\", \"guess\",\"numeric\")\n )\n ```\n :::\n\n\n- **Column types:**\n\n | logical | numeric | text | date | list |\n |---------|---------|-------|------------|-------|\n | TRUE | 2 | hello | 1947-01-08 | hello |\n | FALSE | 3.45 | world | 1956-10-21 | 1 |\n\n : Table with 5 columns. Column headers are various data types (logical, numeric, text, date, and list). The data in two rows show examples of data for the given column type.\n\n - `skip`\n\n - `guess`\n\n - `logical`\n\n - `date`\n\n - `numeric`\n\n - `text`\n\n - Use `list`for columns that include multiple data types.\n See **tidyr** and **purrr** for list-column data.\n\n### Other useful Excel packages\n\n- For functions to write data to Excel files: **openxlsx** and **writexl**\n- For working with non-tabular Excel data: **tidyxl**\n\n## Import spreadsheets with googlesheets4\n\n### Read sheets\n\nRead a sheet from a URL, a Sheet ID, or a dribble samefrom the googledrive package.\nSee [Useful read arguments] for more read arguments.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nread_sheet(ss, sheet = NULL, range = NULL)\n```\n:::\n\n\nSame as `range_read()`.\n\n- If the Google sheet you want to import is the following:\n\n | A | B | C | D | E |\n |-----|-----|-----|-----|-----|\n | x1 | x2 | x3 | x4 | x5 |\n | x | | z | 8 | |\n | y | 7 | | 9 | 10 |\n\n : Spreadsheet with 5 columns (A through E) and three rows. First row reads x1 through x5. Second and third row have some missing values.\n\n- It will look like the following when imported:\n\n\n ::: {.cell}\n \n :::\n\n\n### Sheet metadata\n\n- **URLs** are in the form:\n\n ``` \n https://docs.google.com/spreadsheets/d/\n             SPREADSHEET_ID/edit#gid=SHEET_ID\n ```\n\n- Get spreadsheet meta data: `gs4_get(ss)`\n\n- Get data on all spreadsheet files: `gs4_find(...)`\n\n- Get a tibble of properties for each worksheet: `sheet_properties(ss)`.\n Also `sheet_names()`.\n\n### Write sheets\n\n- `write_sheet(data, ss = NULL, sheet = NULL)`**:** Write a data frame into a new or existing Sheet. \n- `gs4_create(name, ..., sheets = NULL)`: Create a new Sheet with a vector of names, a data frame, or a (named) list of data frames.\n- `sheet_append(ss, data, sheet = 1)`: Add rows to the end of a worksheet.\n\n### googlesheets4 column specification\n\nColumn specifications define what data type each column of a file will be imported as.\n\nUse the `col_types` argument of `read_sheet()`**/**`range_read()` to set the column specification.\n\n- Guess column types: To guess a column type `read_sheet()`/`range_read()` looks at the first 1000 rows of data.\n Increase with `guess_max`.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_sheet(path, guess_max = Inf)\n ```\n :::\n\n\n- Set all columns to same type, e.g. character:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_sheet(path, col_types = \"c\")\n ```\n :::\n\n\n- Set each column individually:\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n # col types: skip, guess, integer, logical, character\n read_sheets(ss, col_types = \"_?ilc\")\n ```\n :::\n\n\n- Column types:\n\n - skipped my lunch 🥙 🍱 and: \"\\_\" or \"-\"\n\n - guess: \"?\"\n\n - logical: \"l\"\n\n - integer: \"i\"\n\n - double: \"d\"\n\n - numeric: \"n\"\n\n - date: \"D\"\n\n - datetime: \"T\"\n\n - character: \"c\"\n\n - list-column: \"L\"\n\n - cell: \"C\" (returns list of raw cell data)\n\n - Use list for columns that include multiple data types.\n See **tidyr** and **purrr** for list-column data.\n\n### File level operations\n\n- **googlesheets4** also offers ways to modify other aspects of Sheets (e.g. freeze rows, set column width, manage (work)sheets). Go to [googlesheets4.tidyverse.org](https://googlesheets4.tidyverse.org/) to read more.\n- For whole-file operations (e.g. renaming, sharing, placing within a folder), see the tidyverse package **googledrive** at [googledrive.tidyverse.org](https://googledrive.tidyverse.org).\n\n## Cell specification for readxl and googlesheets4\n\nUse the **range** argument of **readxl::read_excel()** or **googlesheets4::read_sheet()** to read a subset of cells from a sheet.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nread_excel(path, range = \"Sheet1!B1:D2\")\nread_sheet(ss, range = \"B1:D2\")\n```\n:::\n\n\nAlso use the range argument with cell specification functions `cell_limits()`, `cell_rows()`, `cell_cols()`, and `anchored()`**.**\n\n------------------------------------------------------------------------\n\nCC BY SA Posit Software, PBC • [info\\@posit.co](mailto:info@posit.co) • [posit.co](https://posit.co)\n\nLearn more at\n\n- readr: [readr.tidyverse.org](https://readr.tidyverse.org)\n- readxl: [readxl.tidyverse.org](https://readxl.tidyverse.org/)\n- googlesheets4: [googlesheets4.tidyverse.org](https://googlesheets4.tidyverse.org/)\n\nUpdated: 2023-07.\n\n\n::: {.cell}\n\n```{.r .cell-code}\npackageVersion(\"readr\")\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] '2.1.4'\n```\n:::\n\n```{.r .cell-code}\npackageVersion(\"readxl\")\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] '1.4.3'\n```\n:::\n\n```{.r .cell-code}\npackageVersion(\"googlesheets4\")\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] '1.1.1'\n```\n:::\n:::\n\n\n------------------------------------------------------------------------\n\n\n\n", + "engine": "knitr", + "markdown": "---\ntitle: \"Data import with the tidyverse :: Cheatsheet\"\ndescription: \" \"\nexecute:\n eval: true\n output: false\n warning: true\n---\n\n::: {.cell .column-margin}\n\"Hex\n

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\n* Bengali\n* Persian\n* Portuguese\n* Russian\n* Spanish\n* Turkish\n* Ukrainian\n* Uzbek\n:::\n\n\n\n\nOne of the first steps of a project is to import outside data into R.\nData is often stored in tabular formats, like csv files or spreadsheets.\n\n- The first half of this cheatsheet shows how to import and save text files into R using **readr**.\n- The second half shows how to import spreadsheet data from Excel files using **readxl** or Google Sheets using **googlesheets4**.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(readr)\nlibrary(readxl)\nlibrary(googlesheets4)\n```\n:::\n\n\n\n\nFor importing other types of data try one of the following packages:\n\n- **haven**: SPSS, Stata, and SAS files\n- **DBI**: databases\n- **jsonlite**: json\n- **xml2**: XML\n- **httr**: Web APIs\n- **rvest**: HTML (Web Scraping)\n- **readr::read_lines()**: text data\n\n## Read Tabular Data with readr\n\n\n\n\n\n\n\n\n\nSee `?read_delim`.\n\n``` r\nread_*(\n file, \n col_names = TRUE, col_types = NULL, col_select = NULL, \n show_col_types = TRUE\n id = NULL, locale, \n n_max = Inf, skip = 0, guess_max = min(1000, n_max), \n na = c(\"\", \"NA\")\n)\n```\n\n### Examples\n\n- Read files with any delimiter: `read_delim()`.\n If no delimiter is specified, it will automatically guess.\n\n - If the file you want to import is the following:\n\n ``` \n A|B|C\n 1|2|3\n 4|5|NA\n ```\n\n\n\n\n ::: {.cell}\n \n :::\n\n\n\n\n - Read it with `read_delim()` and it will look like the following when imported:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_delim(\"file.txt\", delim = \"|\", show_col_types = FALSE)\n ```\n :::\n\n\n\n\n - To make `file.txt`, run:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n write_file(\"A|B|C\\n1|2|3\\n4|5|NA\", file = \"file.txt\")\n ```\n :::\n\n\n\n\n- Read a comma delimited file with period decimal marks: `read_csv()`.\n\n - If the file you want to import is the following:\n\n ``` \n A,B,C\n 1,2,3\n 4,5,NA\n ```\n\n\n\n\n ::: {.cell}\n \n :::\n\n\n\n\n - Read it with `read_csv()` and it will look like the following when imported:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\"file.csv\", show_col_types = FALSE)\n ```\n :::\n\n\n\n\n - To make `file.csv`, run:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n write_file(\"A,B,C\\n1,2,3\\n4,5,NA\", file = \"file.csv\")\n ```\n :::\n\n\n\n\n- Read semicolon delimited files with comma decimal marks: `read_csv2()`.\n\n - If the file you want to import is the following:\n\n ``` \n A;B;C\n 1,5;2;3\n 4,5;5;NA\n ```\n\n\n\n\n ::: {.cell}\n \n :::\n\n\n\n\n - Read it with `read_csv2()` and it will look like the following when imported:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv2(\"file2.csv\", show_col_types = FALSE)\n ```\n :::\n\n\n\n\n - To make `file2.csv`, run:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n write_file(\"A;B;C\\n1,5;2;3\\n4,5;5;NA\", file = \"file2.csv\")\n ```\n :::\n\n\n\n\n- Read a tab delimited file: `read_tsv()` or `read_table()`.\n\n Read a fixed width file: `read_fwf(\"file.tsv\", fwf_widths(c(2, 2, NA)))`.\n\n - If the file you want to import is the following:\n\n ``` \n A B C\n 1 2 3\n 4 5 NA\n ```\n\n\n\n\n ::: {.cell}\n \n :::\n\n\n\n\n - Read it with `read_tsv()` and it will look like the following when imported:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_tsv(\"file.tsv\", show_col_types = FALSE)\n ```\n :::\n\n\n\n\n - To make `tsv`, run:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n write_file(\"A\\tB\\tC\\n1\\t2\\t3\\n4\\t5\\tNA\\n\", file = \"file.tsv\")\n ```\n :::\n\n\n\n\n### Useful read arguments\n\nSuppose you have the following CSV files that you want to read in, called `file.csv`:\n\n`file.csv`\n\n``` \nA,B,C\n1,2,3\n4,5,NA\n```\n\n`file3.csv`\n\n``` \nA,B,C\n7,8,9\nNA,11,12\n```\n\nTo make these files, run:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nwrite_file(\"A,B,C\\n1,2,3\\n4,5,NA\", file = \"file.csv\")\nwrite_file(\"A,B,C\\n7,8,9\\nNA,11,12\", file = \"file3.csv\")\n```\n:::\n\n\n\n\n- No header: `col_names = FALSE`\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\"file.csv\", col_names = FALSE)\n ```\n :::\n\n\n\n\n- Provide header: `col_names = c(\"x\", \"y\", \"z\")`\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\"file.csv\", col_names = c(\"x\", \"y\", \"z\"))\n ```\n :::\n\n\n\n\n- Skip lines:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\"file.csv\", skip = 1)\n ```\n :::\n\n\n\n\n- Read a subset of lines:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\"file.csv\", n_max = 1)\n ```\n :::\n\n\n\n\n- Read values as missing:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\"file.csv\", na = c(\"1\"))\n ```\n :::\n\n\n\n\n- Specify decimal marks:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_delim(\"file2.csv\", locale = locale(decimal_mark = \",\"))\n ```\n :::\n\n\n\n\n- Read multiple files into a single table:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(c(\"file.csv\", \"file3.csv\"), id = \"origin_file\")\n ```\n :::\n\n\n\n\n### Save data with readr\n\n``` r\nwrite_*(\n x, file, \n na = \"NA\", \n append, col_names, quote, escape, eol, num_threads, progress\n)\n```\n\n- Write files with any delimiter: `write_delim(x, file, delim = \" \")`\n- Write a comma delimited file: `write_csv(x, file)`\n- Write a semicolon delimited file: `write_csv2(x, file)`\n- Write a tab delimited file: `write_tsv(x, file)`\n\n### Column specification with readr\n\nColumn specifications define what data type each column of a file will be imported as.\nBy default readr will generate a column spec when a file is read and output a summary.\n\n`spec(df)`: Extract the full column specification for the given imported data frame.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nspec(df)\n# cols(\n# age = col_integer(), # age is an integer\n# edu = col_character(), # edu is a character\n# earn = col_double() # earn is a double (numeric)\n# )\n```\n:::\n\n\n\n\n#### Column types\n\nEach column type has a function and corresponding string abbreviation.\n\n- `col_logical() - \"l\"`\n- `col_integer() - \"i\"`\n- `col_double() - \"d\"`\n- `col_number() - \"n\"`\n- `col_character() - \"c\"`\n- `col_factor(levels, ordered = FALSE) - \"f\"`\n- `col_datetime(format = \"\") - \"T\"`\n- `col_date(format = \"\") - \"D\"`\n- `col_time(format = \"\") - \"t\"`\n- `col_skip() - \"-\", \"_\"`\n- `col_guess() - \"?\"`\n\n#### Useful column arguments\n\n- Hide col spec message:\n\n ``` r\n read_*(file, show_col_types = FALSE)\n ```\n\n- Select columns to import: Use names, position, or selection helpers.\n\n ``` r\n read_*(file, col_select = c(age, earn))\n ```\n\n- Guess column types: To guess a column type, `read_ *()` looks at the first 1000 rows of data.\n Increase with `guess_max`.\n\n ``` r\n read_*(file, guess_max = Inf)\n ```\n\n#### Define column specification\n\n- Set a default type:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\n file, \n col_type = list(.default = col_double())\n )\n ```\n :::\n\n\n\n\n- Use column type or string abbreviation:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_csv(\n file, \n col_type = list(x = col_double(), y = \"l\", z = \"_\")\n )\n ```\n :::\n\n\n\n\n- Use a single string of abbreviations:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n # col types: skip, guess, integer, logical, character\n read_csv(\n file, \n col_type = \"_?ilc\"\n )\n ```\n :::\n\n\n\n\n## Import spreadsheets with readxl\n\n### Read Excel files\n\nRead a .xls or .xlsx file based on the file extension, e.g. `read_excel(\"excel_file.xlsx\")`.\nSee [Useful read arguments] for more read arguments.\nAlso `read_xls()` and `read_xlsx()`.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nread_excel(path, sheet = NULL, range = NULL)\n```\n:::\n\n\n\n\n- If the Google sheet you want to import is the following:\n\n | A | B | C | D | E |\n |-----|-----|-----|-----|-----|\n | x1 | x2 | x3 | x4 | x5 |\n | x | | z | 8 | |\n | y | 7 | | 9 | 10 |\n\n : Spreadsheet with 5 columns (A through E) and three rows. First row reads x1 through x5. Second and third row have some missing values.\n\n- It will look like the following when imported:\n\n\n\n\n ::: {.cell}\n \n :::\n\n\n\n\n### Read sheets\n\n- Specify which sheet to read by position or name: `read_excel(path, sheet = NULL)`\n\n - `read_excel(path, sheet = 1)`\n - `read_excel(path, sheet = \"s1\")`\n\n- Get a vector of sheet names: `excel_sheets(path)`\n\n `excel_sheets(\"excel_file.xlsx\")`\n\n- To read multiple sheets:\n\n 1. Get a vector of sheet names from the file path.\n\n 2. Set the vector names to be the sheet names.\n\n 3. Use `purrr::map()` and `purrr::list_rbind()` to read multiple files into one data frame.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n path <- \"your_file_path.xlsx\"\n path |> \n excel_sheets() |>\n set_names() |>\n map(read_excel, path = path) |>\n list_rbind()\n ```\n :::\n\n\n\n\n### readxl column specification\n\n- Column specifications define what data type each column of a file will be imported as.\n\n- Use the `col_types` argument of `read_excel()` to set the column specification.\n\n- Guess column types: To guess a column type, `read_excel()` looks at the first 1000 rows of data.\n Increase with the `guess_max` argument.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_excel(path, guess_max = Inf)\n ```\n :::\n\n\n\n\n- Set all columns to same type, e.g. character:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_excel(path, col_types = \"text\")\n ```\n :::\n\n\n\n\n- Set each column individually:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_excel(\n path,\n col_types = c(\"text\", \"guess\", \"guess\",\"numeric\")\n )\n ```\n :::\n\n\n\n\n- **Column types:**\n\n | logical | numeric | text | date | list |\n |---------|---------|-------|------------|-------|\n | TRUE | 2 | hello | 1947-01-08 | hello |\n | FALSE | 3.45 | world | 1956-10-21 | 1 |\n\n : Table with 5 columns. Column headers are various data types (logical, numeric, text, date, and list). The data in two rows show examples of data for the given column type.\n\n - `skip`\n\n - `guess`\n\n - `logical`\n\n - `date`\n\n - `numeric`\n\n - `text`\n\n - Use `list`for columns that include multiple data types.\n See **tidyr** and **purrr** for list-column data.\n\n### Other useful Excel packages\n\n- For functions to write data to Excel files: **openxlsx** and **writexl**\n- For working with non-tabular Excel data: **tidyxl**\n\n## Import spreadsheets with googlesheets4\n\n### Read sheets\n\nRead a sheet from a URL, a Sheet ID, or a dribble samefrom the googledrive package.\nSee [Useful read arguments] for more read arguments.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nread_sheet(ss, sheet = NULL, range = NULL)\n```\n:::\n\n\n\n\nSame as `range_read()`.\n\n- If the Google sheet you want to import is the following:\n\n | A | B | C | D | E |\n |-----|-----|-----|-----|-----|\n | x1 | x2 | x3 | x4 | x5 |\n | x | | z | 8 | |\n | y | 7 | | 9 | 10 |\n\n : Spreadsheet with 5 columns (A through E) and three rows. First row reads x1 through x5. Second and third row have some missing values.\n\n- It will look like the following when imported:\n\n\n\n\n ::: {.cell}\n \n :::\n\n\n\n\n### Sheet metadata\n\n- **URLs** are in the form:\n\n ``` \n https://docs.google.com/spreadsheets/d/\n             SPREADSHEET_ID/edit#gid=SHEET_ID\n ```\n\n- Get spreadsheet meta data: `gs4_get(ss)`\n\n- Get data on all spreadsheet files: `gs4_find(...)`\n\n- Get a tibble of properties for each worksheet: `sheet_properties(ss)`.\n Also `sheet_names()`.\n\n### Write sheets\n\n- `write_sheet(data, ss = NULL, sheet = NULL)`**:** Write a data frame into a new or existing Sheet. \n- `gs4_create(name, ..., sheets = NULL)`: Create a new Sheet with a vector of names, a data frame, or a (named) list of data frames.\n- `sheet_append(ss, data, sheet = 1)`: Add rows to the end of a worksheet.\n\n### googlesheets4 column specification\n\nColumn specifications define what data type each column of a file will be imported as.\n\nUse the `col_types` argument of `read_sheet()`**/**`range_read()` to set the column specification.\n\n- Guess column types: To guess a column type `read_sheet()`/`range_read()` looks at the first 1000 rows of data.\n Increase with `guess_max`.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_sheet(path, guess_max = Inf)\n ```\n :::\n\n\n\n\n- Set all columns to same type, e.g. character:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n read_sheet(path, col_types = \"c\")\n ```\n :::\n\n\n\n\n- Set each column individually:\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n # col types: skip, guess, integer, logical, character\n read_sheets(ss, col_types = \"_?ilc\")\n ```\n :::\n\n\n\n\n- Column types:\n\n - skipped my lunch 🥙 🍱 and: \"\\_\" or \"-\"\n\n - guess: \"?\"\n\n - logical: \"l\"\n\n - integer: \"i\"\n\n - double: \"d\"\n\n - numeric: \"n\"\n\n - date: \"D\"\n\n - datetime: \"T\"\n\n - character: \"c\"\n\n - list-column: \"L\"\n\n - cell: \"C\" (returns list of raw cell data)\n\n - Use list for columns that include multiple data types.\n See **tidyr** and **purrr** for list-column data.\n\n### File level operations\n\n- **googlesheets4** also offers ways to modify other aspects of Sheets (e.g. freeze rows, set column width, manage (work)sheets). Go to [googlesheets4.tidyverse.org](https://googlesheets4.tidyverse.org/) to read more.\n- For whole-file operations (e.g. renaming, sharing, placing within a folder), see the tidyverse package **googledrive** at [googledrive.tidyverse.org](https://googledrive.tidyverse.org).\n\n## Cell specification for readxl and googlesheets4\n\nUse the **range** argument of **readxl::read_excel()** or **googlesheets4::read_sheet()** to read a subset of cells from a sheet.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nread_excel(path, range = \"Sheet1!B1:D2\")\nread_sheet(ss, range = \"B1:D2\")\n```\n:::\n\n\n\n\nAlso use the range argument with cell specification functions `cell_limits()`, `cell_rows()`, `cell_cols()`, and `anchored()`**.**\n\n------------------------------------------------------------------------\n\nCC BY SA Posit Software, PBC • [info\\@posit.co](mailto:info@posit.co) • [posit.co](https://posit.co)\n\nLearn more at\n\n- readr: [readr.tidyverse.org](https://readr.tidyverse.org)\n- readxl: [readxl.tidyverse.org](https://readxl.tidyverse.org/)\n- googlesheets4: [googlesheets4.tidyverse.org](https://googlesheets4.tidyverse.org/)\n\nUpdated: 2024-05.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\npackageVersion(\"readr\")\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] '2.1.5'\n```\n\n\n:::\n\n```{.r .cell-code}\npackageVersion(\"readxl\")\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] '1.4.3'\n```\n\n\n:::\n\n```{.r .cell-code}\npackageVersion(\"googlesheets4\")\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] '1.1.1'\n```\n\n\n:::\n:::\n\n\n\n\n------------------------------------------------------------------------\n\n\n\n\n\n", "supporting": [ "data-import_files" ], diff --git a/_freeze/html/lubridate/execute-results/html.json b/_freeze/html/lubridate/execute-results/html.json index 09f6697a..5b434aea 100644 --- a/_freeze/html/lubridate/execute-results/html.json +++ b/_freeze/html/lubridate/execute-results/html.json @@ -1,8 +1,11 @@ { - "hash": "a6baed88ece4b5becc66a118f98cbfce", + "hash": "c96684669371dc2394925a346a059e92", "result": { - "markdown": "---\ntitle: \"Dates and times with lubridate :: Cheatsheet\"\ndescription: \" \"\nimage-alt: \"\"\nexecute:\n eval: true\n output: false\n warning: false\n---\n\n::: {.cell .column-margin}\n\"Hex\n

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\n* Russian\n* Spanish\n* Ukrainian\n* Vietnamese\n:::\n\n\n## Date-times\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(lubridate)\n```\n:::\n\n\n\n\nA **date-time** is a point on the timeline, stored as the number of seconds since 1970-01-01 00:00:00 UTC\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndt <- as_datetime(1511870400)\n```\n:::\n\n\nA **date** is a day stored as the number of days since 1970-01-01\n\n\n::: {.cell}\n\n```{.r .cell-code}\nd <- as_date(17498)\n```\n:::\n\n\nAn hms is a **time** stored as the number of seconds since 00:00:00\n\n\n::: {.cell}\n\n```{.r .cell-code}\nt <- hms::as_hms(85)\n```\n:::\n\n\n### Parse Date-Times\n\nConvert strings or numbers to date-times\n\n1. Identify the order of the year (**y**), month (**m**), day (**d**), hour (**h**), minute (**m**) and second (**s**) elements in your data.\n\n2. Use the function below whose name replicates the order.\n Each accepts a `tz` argument to set the time zone, e.g. `ymd(x, tz = \"UTC\")`.\n\n- `ymd_hms()`, `ymd_hm()`, `ymd_h()`\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n ymd_hms(\"2017-11-28T14:02:00\")\n ```\n :::\n\n\n- `ydm_hms()`, `ydm_hm()`, `ydm_h()`\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n ydm_hms(\"2017-22-12 10:00:00\")\n ```\n :::\n\n\n- `mdy_hms()`, `mdy_hm()`, `mdy_h()`\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n mdy_hms(\"11/28/2017 1:02:03\")\n ```\n :::\n\n\n- `dmy_hms()`, `dmy_hm()`, `dmy_h()`\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n dmy_hms(\"1 Jan 2017 23:59:59\")\n ```\n :::\n\n\n- `ymd()`, `ydm()`\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n ymd(20170131)\n ```\n :::\n\n\n- `mdy()`, `myd()`\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n mdy(\"July 4th, 2000\")\n ```\n :::\n\n\n- `dmy()`, `dym()`\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n dmy(\"4th of July '99\")\n ```\n :::\n\n\n- `yq()`: Q for quarter.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n yq(\"2001: Q3\")\n ```\n :::\n\n\n- `my()`, `ym()`\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n my(\"07-2020\")\n ```\n :::\n\n\n- `hms::hms()`: Also `lubridate::hms()`, `hm()`, and `ms()`, which return periods\\*.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n hms::hms(seconds = 0, minutes = 1, hours = 2)\n ```\n :::\n\n\n- `date_decimal(decimal, tz = \"UTC\")`\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n date_decimal(2017.5)\n ```\n :::\n\n\n- `now(tzone = \"\")`: Current time in tz (defaults to system tz).\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n now()\n ```\n :::\n\n\n- `today(tzone = \"\")`: Current date in a tz (defaults to system tz).\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n today()\n ```\n :::\n\n\n- `fast_strptime()`: Faster strptime.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n fast_strptime(\"9/1/01\", \"%y/%m/%d\")\n ```\n :::\n\n\n- `parse_date_time()`: Easier strptime.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n parse_date_time(\"09-01-01\", \"ymd\")\n ```\n :::\n\n\n### Get and Set Components\n\nUse an accessor function to get a component.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nd\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"2017-11-28\"\n```\n:::\n\n```{.r .cell-code}\nday(d)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 28\n```\n:::\n:::\n\n\nAssign into an accessor function to change a component in place.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nday(d) <- 1\nd\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"2017-11-01\"\n```\n:::\n:::\n\n\n- `date(x)`: Date component.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n date(dt)\n ```\n :::\n\n\n- `year(x)`: Year.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n year(dt)\n ```\n :::\n\n\n- `isoyear(x)`: The ISO 8601 year.\n\n- `epiyear(x)`: Epidemiological year.\n\n- `month(x, label, abbr)`: Month.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n month(dt)\n ```\n :::\n\n\n- `day(x)`: Day of the month.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n day(dt)\n ```\n :::\n\n\n- `wday(x, label, abbr)`: Day of week.\n\n- `qday(x)`: Day of quarter.\n\n- `hour(x)`: Hour.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n hour(dt)\n ```\n :::\n\n\n- `minute(x)`: Minutes.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n minute(dt)\n ```\n :::\n\n\n- `second(x)`: Seconds.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n second(dt)\n ```\n :::\n\n\n- `tz(x)`: Time zone.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n tz(dt)\n ```\n :::\n\n\n- `week(x)`: Week of the year.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n week(dt)\n ```\n :::\n\n\n- `isoweek()`: ISO 8601 week.\n\n- `epiweek()`: Epidemiological week.\n\n- `quarter(x)`: Quarter.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n quarter(dt)\n ```\n :::\n\n\n- `semester(x, with_year = FALSE)`: Semester.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n semester(dt)\n ```\n :::\n\n\n- `am(x)`: Is it in the am?\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n am(dt)\n ```\n :::\n\n\n- `pm(x)`: Is it in the pm?\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n pm(dt)\n ```\n :::\n\n\n- `dst(x)`: Is it daylight savings?\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n dst(d)\n ```\n :::\n\n\n- `leap_year(x)`: Is it a leap year?\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n leap_year(d)\n ```\n :::\n\n\n- `update(object, ..., simple = FALSE)`\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n update(dt, mday = 2, hour = 1)\n ```\n :::\n\n\n## Round Date-times\n\n- `floor_date(x, unit = \"second\")`: Round down to nearest unit.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n floor_date(dt, unit = \"month\")\n ```\n :::\n\n\n- `round_date(x, unit = \"second\")`: Round to nearest unit.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n round_date(dt, unit = \"month\")\n ```\n :::\n\n\n- `ceiling_date(x, unit = \"second\")`: Round up to the nearest unit.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n ceiling_date(dt, unit = \"month\")\n ```\n :::\n\n\nValid units are second, minute, hour, day, week, month, bimonth, quarter, season, halfyear and year.\n\n- `rollback(dates, roll_to_first = FALSE, preserve_hms = TRUE)`: Roll back to last day of previous month.\n Also `rollforward()`.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n rollback(dt)\n ```\n :::\n\n\n## Stamp Date-times\n\n`stamp()`: Derive a template from an example string and return a new function that will apply the template to date-times.\nAlso `stamp_date()` and `stamp_time()`.\n\n1. Derive a template, create a function\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n sf <- stamp(\"Created Sunday, Jan 17, 1999 3:34\")\n ```\n :::\n\n\n2. Apply the template to dates\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n sf(ymd(\"2010-04-05\"))\n ```\n \n ::: {.cell-output .cell-output-stdout}\n ```\n [1] \"Created Monday, Apr 05, 2010 00:00\"\n ```\n :::\n :::\n\n\n**Tip: use a date with day \\> 12**\n\n## Time Zones\n\nR recognizes \\~600 time zones.\nEach encodes the time zone, Daylight Savings Time, and historical calendar variations for an area.\nR assigns *one* time zone per vector.\n\nUse the `UTC` time zone to avoid Daylight Savings.\n\n- `OlsonNames()`: Returns a list of valid time zone names.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n OlsonNames()\n ```\n :::\n\n\n- `Sys.timezone()`: Gets current time zone.\n\n- `with_tz(time, tzone = \"\")`: Get the **same date-time** in a new time zone (a new clock time).\n Also `local_time(dt, tz, units)`.\n For example, 4:00 Pacific becomes 5:00 Mountain, or 6:00 Central, or 7:00 Eastern.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n with_tz(dt, \"US/Pacific\")\n ```\n :::\n\n\n- `force_tz(time, tzone = \"\")`: Get the **same clock time** in a new time zone (a new date-time).\n Also `force_tzs()`.\n For example, 7:00 Pacific becomes 7:00 Mountain, or 7:00 Central, or 7:00 Eastern.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n force_tz(dt, \"US/Pacific\")\n ```\n :::\n\n\n## Math with Date-times\n\nLubridate provides three classes of timespans to facilitate math with dates and date-times.\n\nMath with date-times relies on the **timeline**, which behaves inconsistently.\nConsider how the timeline behaves during:\n\n- A normal day:\n\n\n::: {.cell}\n\n```{.r .cell-code}\nnor <- ymd_hms(\"2018-01-01 01:30:00\", tz = \"US/Eastern\")\n```\n:::\n\n\n- The start of daylight savings (spring forward):\n\n\n::: {.cell}\n\n```{.r .cell-code}\ngap <- ymd_hms(\"2018-03-11 01:30:00\", tz = \"US/Eastern\")\n```\n:::\n\n\n- The end of daylight savings (fall back):\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlap <- ymd_hms(\"2018-11-04 00:30:00\", tz = \"US/Eastern\")\n```\n:::\n\n\n- Leap years and leap seconds:\n\n\n::: {.cell}\n\n```{.r .cell-code}\nleap <- ymd(\"2019-03-01\")\n```\n:::\n\n\n**Periods** track changes in clock times, which ignore time line irregularities.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nnor + minutes(90)\ngap + minutes(90)\nlap + minutes(90)\nleap + years(1)\n```\n:::\n\n\n**Durations** track the passage of physical time, which deviates from clock time when irregularities occur.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nnor + dminutes(90)\ngap + dminutes(90)\nlap + dminutes(90)\nleap + dyears(1)\n```\n:::\n\n\n**Intervals** represent specific intervals of the timeline, bounded by start and end date-times.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ninterval(nor, nor + minutes(90))\ninterval(gap, gap + minutes(90))\ninterval(lap, lap + minutes(90))\ninterval(leap, leap + years(1))\n```\n:::\n\n\nNot all years are 365 days due to **leap days**.\nNot all minutes are 60 seconds due to **leap seconds**.\nIt is possible to create an imaginary date by adding **months**, e.g.\nFebruary 31st.\n\n\n::: {.cell}\n\n```{.r .cell-code}\njan31 <- ymd(20180131)\njan31 + months(1)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] NA\n```\n:::\n:::\n\n\n`%m+%` and `%m-%` will roll imaginary dates to the last day of the previous month.\n\n\n::: {.cell}\n\n```{.r .cell-code}\njan31 %m+% months(1)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"2018-02-28\"\n```\n:::\n:::\n\n\n`add_with_rollback(e1, e2, roll_to_first = TRUE)` will roll imaginary dates to the first day of the new month.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nadd_with_rollback(jan31, months(1), roll_to_first = TRUE)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"2018-03-01\"\n```\n:::\n:::\n\n\n### Periods\n\nAdd or subtract periods to model events that happen a specific clock times, the the NYSE opening bell.\n\nMake a period with the name of a time unit **pluralized**, e.g.\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- months(3) + days(12)\n\n# Shows the number of months, number of days, etc.\np\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"3m 12d 0H 0M 0S\"\n```\n:::\n:::\n\n\n- `years(x = 1)`: x years.\n\n- `months(x = 1)`: x months.\n\n- `weeks(x = 1)`: x weeks.\n\n- `days(x = 1)`: x days.\n\n- `hours(x = 1)`: x hours.\n\n- `minutes(x = 1)`: x minutes.\n\n- `seconds(x = 1)`: x seconds.\n\n- `milliseconds(x = 1)`: x milliseconds.\n\n- `microseconds(x = 1)`: x microseconds.\n\n- `nanoseconds(x = 1)`: x nanoseconds.\n\n- `picoseconds(x = 1)`: x picoseconds.\n\n- `period(num = NULL, units = \"second\", ...)`: An automation friendly period constructor.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n period(5, unit = \"years\")\n ```\n :::\n\n\n- `as.period(x, unit)`: Coerce a timespan to a period, optionally in the specified units.\n Also `is.period()`.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n as.period(p)\n ```\n :::\n\n\n- `period_to_seconds(x)`: Convert a period to the \"standard\" number of seconds implied by the period.\n Also `seconds_to_period()`.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n period_to_seconds(p)\n ```\n :::\n\n\n### Durations\n\nAdd or subtract durations to model physical processes, like battery life.\nDurations are stored as seconds, the only time unit with a consistent length.\n**Difftimes** are a class of durations found in base R.\n\nMake a duration with the name of a period prefixed with a *d*, e.g.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndd <- ddays(14)\n\n# Shows the exact length in seconds, and the equivalent in common units\ndd\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"1209600s (~2 weeks)\"\n```\n:::\n:::\n\n\n- `dyears(x = 1)`: 31536000x seconds.\n\n- `dmonths(x = 1)`: 2629800x seconds.\n\n- `dweeks(x = 1)`: 604800x seconds.\n\n- `ddays(x = 1)`: 86400x seconds.\n\n- `dhours(x = 1)`: 3600x seconds.\n\n- `dminutes(x = 1)`: 60x seconds.\n\n- `dseconds(x = 1)`: x seconds.\n\n- `dmilliseconds(x = 1)`: x \\* 10^-3^ seconds.\n\n- `dmicroseconds(x = 1)`: x \\* 10^-6^ seconds.\n\n- `dnanoseconds(x = 1)`: x \\* 10^-9^ seconds.\n\n- `dpicoseconds(x = 1)`: x \\* 10^-12^ seconds.\n\n- `duration(num = NULL, units = \"second\", ...)`: An automation friendly duration constructor.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n duration(5, unit = \"years\")\n ```\n :::\n\n\n- `as.duration(x, ...)`: Coerce a timespan to a duration.\n Also `is.duration()`, `is.difftime()`.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n as.duration(p)\n ```\n :::\n\n\n- `make_difftime(x)`: Make diffime with the specified number of units.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n make_difftime(99999)\n ```\n :::\n\n\n### Intervals\n\nDivide an interval by a duration to determine its physical length, divide by an interval by a period to determine its implied length in clock time.\n\nMake an interval with `interval()` or `%--%`, e.g.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ni <- interval(ymd(\"2017-01-01\"), d)\ni\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 2017-01-01 UTC--2017-11-01 UTC\n```\n:::\n\n```{.r .cell-code}\n# Shows the exact length in seconds, and the equivalent in common units\nj <- d %--% ymd(\"2017-12-31\")\nj\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 2017-11-01 UTC--2017-12-31 UTC\n```\n:::\n:::\n\n\n- `a %within% b`: Does interval or dte0time `a` fall within interval `b`?\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n now() %within% i\n ```\n :::\n\n\n- `int_start(int)`: Access/set the start date-time of an interval.\n Also `int_end()`.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n int_start(i) <- now()\n int_start(i)\n ```\n :::\n\n\n- `int_aligns(int1, int2)`: Do two intervals share a boundary?\n Also `int_overlaps()`.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n int_aligns(i, j)\n ```\n :::\n\n\n- `int_diff(times)`: Make the intervals that occur between the date-times in a vector.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n v <- c(dt, dt + 100, dt + 1000)\n int_diff(v)\n ```\n :::\n\n\n- `int_flip(int)`: Reverse the direction of an interval.\n Also `int_standardize()`.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n int_flip(i)\n ```\n :::\n\n\n- `int_length(int)`: Length in seconds.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n int_length(i)\n ```\n :::\n\n\n- `int_shift(int, by)`: Shifts an interval up or down the timeline by a timespan.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n int_shift(i, days(-1))\n ```\n :::\n\n\n- `as.interval(x, start, ...)`: Coerce a timespan to an interval with the start date-time.\n Also `is.interval()`.\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n as.interval(days(-1), start = now())\n ```\n :::\n\n\n------------------------------------------------------------------------\n\nCC BY SA Posit Software, PBC • [info\\@posit.co](mailto:info@posit.co) • [posit.co](https://posit.co)\n\nLearn more at [lubridate.tidyverse.org](https://lubridate.tidyverse.org).\n\nUpdated: 2023-06.\n\n\n::: {.cell}\n\n```{.r .cell-code}\npackageVersion(\"lubridate\")\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] '1.9.2'\n```\n:::\n:::\n\n\n------------------------------------------------------------------------\n", - "supporting": [], + "engine": "knitr", + "markdown": "---\ntitle: \"Dates and times with lubridate :: Cheatsheet\"\ndescription: \" \"\nimage-alt: \"\"\nexecute:\n eval: true\n output: false\n warning: false\n---\n\n::: {.cell .column-margin}\n\"Hex\n

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\n* Portuguese\n* Russian\n* Spanish\n* Ukrainian\n* Vietnamese\n:::\n\n\n\n\n## Date-times\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(lubridate)\n```\n:::\n\n\n\n\n\n\nA **date-time** is a point on the timeline, stored as the number of seconds since 1970-01-01 00:00:00 UTC\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndt <- as_datetime(1511870400)\n```\n:::\n\n\n\n\nA **date** is a day stored as the number of days since 1970-01-01\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nd <- as_date(17498)\n```\n:::\n\n\n\n\nAn hms is a **time** stored as the number of seconds since 00:00:00\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nt <- hms::as_hms(85)\n```\n:::\n\n\n\n\n### Parse Date-Times\n\nConvert strings or numbers to date-times\n\n1. Identify the order of the year (**y**), month (**m**), day (**d**), hour (**h**), minute (**m**) and second (**s**) elements in your data.\n\n2. Use the function below whose name replicates the order.\n Each accepts a `tz` argument to set the time zone, e.g. `ymd(x, tz = \"UTC\")`.\n\n- `ymd_hms()`, `ymd_hm()`, `ymd_h()`\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n ymd_hms(\"2017-11-28T14:02:00\")\n ```\n :::\n\n\n\n\n- `ydm_hms()`, `ydm_hm()`, `ydm_h()`\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n ydm_hms(\"2017-22-12 10:00:00\")\n ```\n :::\n\n\n\n\n- `mdy_hms()`, `mdy_hm()`, `mdy_h()`\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n mdy_hms(\"11/28/2017 1:02:03\")\n ```\n :::\n\n\n\n\n- `dmy_hms()`, `dmy_hm()`, `dmy_h()`\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n dmy_hms(\"1 Jan 2017 23:59:59\")\n ```\n :::\n\n\n\n\n- `ymd()`, `ydm()`\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n ymd(20170131)\n ```\n :::\n\n\n\n\n- `mdy()`, `myd()`\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n mdy(\"July 4th, 2000\")\n ```\n :::\n\n\n\n\n- `dmy()`, `dym()`\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n dmy(\"4th of July '99\")\n ```\n :::\n\n\n\n\n- `yq()`: Q for quarter.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n yq(\"2001: Q3\")\n ```\n :::\n\n\n\n\n- `my()`, `ym()`\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n my(\"07-2020\")\n ```\n :::\n\n\n\n\n- `hms::hms()`: Also `lubridate::hms()`, `hm()`, and `ms()`, which return periods\\*.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n hms::hms(seconds = 0, minutes = 1, hours = 2)\n ```\n :::\n\n\n\n\n- `date_decimal(decimal, tz = \"UTC\")`\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n date_decimal(2017.5)\n ```\n :::\n\n\n\n\n- `now(tzone = \"\")`: Current time in tz (defaults to system tz).\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n now()\n ```\n :::\n\n\n\n\n- `today(tzone = \"\")`: Current date in a tz (defaults to system tz).\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n today()\n ```\n :::\n\n\n\n\n- `fast_strptime()`: Faster strptime.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n fast_strptime(\"9/1/01\", \"%y/%m/%d\")\n ```\n :::\n\n\n\n\n- `parse_date_time()`: Easier strptime.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n parse_date_time(\"09-01-01\", \"ymd\")\n ```\n :::\n\n\n\n\n### Get and Set Components\n\nUse an accessor function to get a component.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nd\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"2017-11-28\"\n```\n\n\n:::\n\n```{.r .cell-code}\nday(d)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 28\n```\n\n\n:::\n:::\n\n\n\n\nAssign into an accessor function to change a component in place.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nday(d) <- 1\nd\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"2017-11-01\"\n```\n\n\n:::\n:::\n\n\n\n\n- `date(x)`: Date component.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n date(dt)\n ```\n :::\n\n\n\n\n- `year(x)`: Year.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n year(dt)\n ```\n :::\n\n\n\n\n- `isoyear(x)`: The ISO 8601 year.\n\n- `epiyear(x)`: Epidemiological year.\n\n- `month(x, label, abbr)`: Month.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n month(dt)\n ```\n :::\n\n\n\n\n- `day(x)`: Day of the month.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n day(dt)\n ```\n :::\n\n\n\n\n- `wday(x, label, abbr)`: Day of week.\n\n- `qday(x)`: Day of quarter.\n\n- `hour(x)`: Hour.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n hour(dt)\n ```\n :::\n\n\n\n\n- `minute(x)`: Minutes.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n minute(dt)\n ```\n :::\n\n\n\n\n- `second(x)`: Seconds.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n second(dt)\n ```\n :::\n\n\n\n\n- `tz(x)`: Time zone.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n tz(dt)\n ```\n :::\n\n\n\n\n- `week(x)`: Week of the year.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n week(dt)\n ```\n :::\n\n\n\n\n- `isoweek()`: ISO 8601 week.\n\n- `epiweek()`: Epidemiological week.\n\n- `quarter(x)`: Quarter.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n quarter(dt)\n ```\n :::\n\n\n\n\n- `semester(x, with_year = FALSE)`: Semester.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n semester(dt)\n ```\n :::\n\n\n\n\n- `am(x)`: Is it in the am?\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n am(dt)\n ```\n :::\n\n\n\n\n- `pm(x)`: Is it in the pm?\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n pm(dt)\n ```\n :::\n\n\n\n\n- `dst(x)`: Is it daylight savings?\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n dst(d)\n ```\n :::\n\n\n\n\n- `leap_year(x)`: Is it a leap year?\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n leap_year(d)\n ```\n :::\n\n\n\n\n- `update(object, ..., simple = FALSE)`\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n update(dt, mday = 2, hour = 1)\n ```\n :::\n\n\n\n\n## Round Date-times\n\n- `floor_date(x, unit = \"second\")`: Round down to nearest unit.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n floor_date(dt, unit = \"month\")\n ```\n :::\n\n\n\n\n- `round_date(x, unit = \"second\")`: Round to nearest unit.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n round_date(dt, unit = \"month\")\n ```\n :::\n\n\n\n\n- `ceiling_date(x, unit = \"second\")`: Round up to the nearest unit.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n ceiling_date(dt, unit = \"month\")\n ```\n :::\n\n\n\n\nValid units are second, minute, hour, day, week, month, bimonth, quarter, season, halfyear and year.\n\n- `rollback(dates, roll_to_first = FALSE, preserve_hms = TRUE)`: Roll back to last day of previous month.\n Also `rollforward()`.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n rollback(dt)\n ```\n :::\n\n\n\n\n## Stamp Date-times\n\n`stamp()`: Derive a template from an example string and return a new function that will apply the template to date-times.\nAlso `stamp_date()` and `stamp_time()`.\n\n1. Derive a template, create a function\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n sf <- stamp(\"Created Sunday, Jan 17, 1999 3:34\")\n ```\n :::\n\n\n\n\n2. Apply the template to dates\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n sf(ymd(\"2010-04-05\"))\n ```\n \n ::: {.cell-output .cell-output-stdout}\n \n ```\n [1] \"Created Monday, Apr 05, 2010 00:00\"\n ```\n \n \n :::\n :::\n\n\n\n\n**Tip: use a date with day \\> 12**\n\n## Time Zones\n\nR recognizes \\~600 time zones.\nEach encodes the time zone, Daylight Savings Time, and historical calendar variations for an area.\nR assigns *one* time zone per vector.\n\nUse the `UTC` time zone to avoid Daylight Savings.\n\n- `OlsonNames()`: Returns a list of valid time zone names.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n OlsonNames()\n ```\n :::\n\n\n\n\n- `Sys.timezone()`: Gets current time zone.\n\n- `with_tz(time, tzone = \"\")`: Get the **same date-time** in a new time zone (a new clock time).\n Also `local_time(dt, tz, units)`.\n For example, 4:00 Pacific becomes 5:00 Mountain, or 6:00 Central, or 7:00 Eastern.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n with_tz(dt, \"US/Pacific\")\n ```\n :::\n\n\n\n\n- `force_tz(time, tzone = \"\")`: Get the **same clock time** in a new time zone (a new date-time).\n Also `force_tzs()`.\n For example, 7:00 Pacific becomes 7:00 Mountain, or 7:00 Central, or 7:00 Eastern.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n force_tz(dt, \"US/Pacific\")\n ```\n :::\n\n\n\n\n## Math with Date-times\n\nLubridate provides three classes of timespans to facilitate math with dates and date-times.\n\nMath with date-times relies on the **timeline**, which behaves inconsistently.\nConsider how the timeline behaves during:\n\n- A normal day:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nnor <- ymd_hms(\"2018-01-01 01:30:00\", tz = \"US/Eastern\")\n```\n:::\n\n\n\n\n- The start of daylight savings (spring forward):\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ngap <- ymd_hms(\"2018-03-11 01:30:00\", tz = \"US/Eastern\")\n```\n:::\n\n\n\n\n- The end of daylight savings (fall back):\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlap <- ymd_hms(\"2018-11-04 00:30:00\", tz = \"US/Eastern\")\n```\n:::\n\n\n\n\n- Leap years and leap seconds:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nleap <- ymd(\"2019-03-01\")\n```\n:::\n\n\n\n\n**Periods** track changes in clock times, which ignore time line irregularities.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nnor + minutes(90)\ngap + minutes(90)\nlap + minutes(90)\nleap + years(1)\n```\n:::\n\n\n\n\n**Durations** track the passage of physical time, which deviates from clock time when irregularities occur.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nnor + dminutes(90)\ngap + dminutes(90)\nlap + dminutes(90)\nleap + dyears(1)\n```\n:::\n\n\n\n\n**Intervals** represent specific intervals of the timeline, bounded by start and end date-times.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ninterval(nor, nor + minutes(90))\ninterval(gap, gap + minutes(90))\ninterval(lap, lap + minutes(90))\ninterval(leap, leap + years(1))\n```\n:::\n\n\n\n\nNot all years are 365 days due to **leap days**.\nNot all minutes are 60 seconds due to **leap seconds**.\nIt is possible to create an imaginary date by adding **months**, e.g.\nFebruary 31st.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\njan31 <- ymd(20180131)\njan31 + months(1)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] NA\n```\n\n\n:::\n:::\n\n\n\n\n`%m+%` and `%m-%` will roll imaginary dates to the last day of the previous month.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\njan31 %m+% months(1)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"2018-02-28\"\n```\n\n\n:::\n:::\n\n\n\n\n`add_with_rollback(e1, e2, roll_to_first = TRUE)` will roll imaginary dates to the first day of the new month.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nadd_with_rollback(jan31, months(1), roll_to_first = TRUE)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"2018-03-01\"\n```\n\n\n:::\n:::\n\n\n\n\n### Periods\n\nAdd or subtract periods to model events that happen at specific clock times, like the NYSE opening bell.\n\nMake a period with the name of a time unit **pluralized**, e.g.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- months(3) + days(12)\n\n# Shows the number of months, number of days, etc.\np\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"3m 12d 0H 0M 0S\"\n```\n\n\n:::\n:::\n\n\n\n\n- `years(x = 1)`: x years.\n\n- `months(x = 1)`: x months.\n\n- `weeks(x = 1)`: x weeks.\n\n- `days(x = 1)`: x days.\n\n- `hours(x = 1)`: x hours.\n\n- `minutes(x = 1)`: x minutes.\n\n- `seconds(x = 1)`: x seconds.\n\n- `milliseconds(x = 1)`: x milliseconds.\n\n- `microseconds(x = 1)`: x microseconds.\n\n- `nanoseconds(x = 1)`: x nanoseconds.\n\n- `picoseconds(x = 1)`: x picoseconds.\n\n- `period(num = NULL, units = \"second\", ...)`: An automation friendly period constructor.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n period(5, unit = \"years\")\n ```\n :::\n\n\n\n\n- `as.period(x, unit)`: Coerce a timespan to a period, optionally in the specified units.\n Also `is.period()`.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n as.period(p)\n ```\n :::\n\n\n\n\n- `period_to_seconds(x)`: Convert a period to the \"standard\" number of seconds implied by the period.\n Also `seconds_to_period()`.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n period_to_seconds(p)\n ```\n :::\n\n\n\n\n### Durations\n\nAdd or subtract durations to model physical processes, like battery life.\nDurations are stored as seconds, the only time unit with a consistent length.\n**Difftimes** are a class of durations found in base R.\n\nMake a duration with the name of a period prefixed with a *d*, e.g.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndd <- ddays(14)\n\n# Shows the exact length in seconds, and the equivalent in common units\ndd\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"1209600s (~2 weeks)\"\n```\n\n\n:::\n:::\n\n\n\n\n- `dyears(x = 1)`: 31536000x seconds.\n\n- `dmonths(x = 1)`: 2629800x seconds.\n\n- `dweeks(x = 1)`: 604800x seconds.\n\n- `ddays(x = 1)`: 86400x seconds.\n\n- `dhours(x = 1)`: 3600x seconds.\n\n- `dminutes(x = 1)`: 60x seconds.\n\n- `dseconds(x = 1)`: x seconds.\n\n- `dmilliseconds(x = 1)`: x \\* 10^-3^ seconds.\n\n- `dmicroseconds(x = 1)`: x \\* 10^-6^ seconds.\n\n- `dnanoseconds(x = 1)`: x \\* 10^-9^ seconds.\n\n- `dpicoseconds(x = 1)`: x \\* 10^-12^ seconds.\n\n- `duration(num = NULL, units = \"second\", ...)`: An automation friendly duration constructor.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n duration(5, unit = \"years\")\n ```\n :::\n\n\n\n\n- `as.duration(x, ...)`: Coerce a timespan to a duration.\n Also `is.duration()`, `is.difftime()`.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n as.duration(p)\n ```\n :::\n\n\n\n\n- `make_difftime(x)`: Make diffime with the specified number of units.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n make_difftime(99999)\n ```\n :::\n\n\n\n\n### Intervals\n\nDivide an interval by a duration to determine its physical length, divide by an interval by a period to determine its implied length in clock time.\n\nMake an interval with `interval()` or `%--%`, e.g.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ni <- interval(ymd(\"2017-01-01\"), d)\ni\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 2017-01-01 UTC--2017-11-01 UTC\n```\n\n\n:::\n\n```{.r .cell-code}\n# Shows the exact length in seconds, and the equivalent in common units\nj <- d %--% ymd(\"2017-12-31\")\nj\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 2017-11-01 UTC--2017-12-31 UTC\n```\n\n\n:::\n:::\n\n\n\n\n- `a %within% b`: Does interval or dte0time `a` fall within interval `b`?\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n now() %within% i\n ```\n :::\n\n\n\n\n- `int_start(int)`: Access/set the start date-time of an interval.\n Also `int_end()`.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n int_start(i) <- now()\n int_start(i)\n ```\n :::\n\n\n\n\n- `int_aligns(int1, int2)`: Do two intervals share a boundary?\n Also `int_overlaps()`.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n int_aligns(i, j)\n ```\n :::\n\n\n\n\n- `int_diff(times)`: Make the intervals that occur between the date-times in a vector.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n v <- c(dt, dt + 100, dt + 1000)\n int_diff(v)\n ```\n :::\n\n\n\n\n- `int_flip(int)`: Reverse the direction of an interval.\n Also `int_standardize()`.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n int_flip(i)\n ```\n :::\n\n\n\n\n- `int_length(int)`: Length in seconds.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n int_length(i)\n ```\n :::\n\n\n\n\n- `int_shift(int, by)`: Shifts an interval up or down the timeline by a timespan.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n int_shift(i, days(-1))\n ```\n :::\n\n\n\n\n- `as.interval(x, start, ...)`: Coerce a timespan to an interval with the start date-time.\n Also `is.interval()`.\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n as.interval(days(-1), start = now())\n ```\n :::\n\n\n\n\n------------------------------------------------------------------------\n\nCC BY SA Posit Software, PBC • [info\\@posit.co](mailto:info@posit.co) • [posit.co](https://posit.co)\n\nLearn more at [lubridate.tidyverse.org](https://lubridate.tidyverse.org).\n\nUpdated: 2024-05.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\npackageVersion(\"lubridate\")\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] '1.9.3'\n```\n\n\n:::\n:::\n\n\n\n\n------------------------------------------------------------------------\n", + "supporting": [ + "lubridate_files" + ], "filters": [ "rmarkdown/pagebreak.lua" ], diff --git a/_freeze/html/quarto/execute-results/html.json b/_freeze/html/quarto/execute-results/html.json index 53b9dbb9..61f354e2 100644 --- a/_freeze/html/quarto/execute-results/html.json +++ b/_freeze/html/quarto/execute-results/html.json @@ -1,7 +1,8 @@ { - "hash": "bcf58e7473223cdb5ba43bb16c3e8981", + "hash": "9639961638a419b0e8fac75c02f81177", "result": { - "markdown": "---\ntitle: \"Publish and Share with Quarto :: Cheatsheet\"\ndescription: \"QMD Edition\"\nimage-alt: \"\"\nengine: knitr\nexecute:\n eval: true\n output: false\n warning: false\ncode-overflow: wrap\n---\n\n\n::: column-margin\n\n```{=html}\n\"Hex\n

\n```\n\n:::\n\n\n::: {.cell .column-margin}\n\n

Download PDF

\n\"\"/\n\n

\n:::\n\n\n## Overview\n\n![](images/quarto-illustration.png){fig-alt=\"A schematic representing the multi-language input (e.g. Python, R, Observable, Julia) and multi-format output (e.g. PDF, html, Word documents, and more) versatility of Quarto.\"}[^credit] \n\n[^credit]: Artwork from \"Hello, Quarto\" keynote by Julia Lowndes and Mine Çetinkaya-Rundel, presented at RStudio Conference 2022. Illustrated by [Allison Horst](https://allisonhorst.com/allison-horst).\n\n* **Author**: Write and code in plain text. Author documents as .qmd files, or Jupyter notebooks. Write in a rich Markdown syntax.\n\n* **Render**: Generate documents, presentations and more. Produce HTML, PDF, MS Word, reveal.js, MS Powerpoint, Beamer, websites, blogs, books...\n\n* **Share**: Share your work with the world. Quickly deploy to GitHub Pages, Netlify, Quarto Pub, Posit Cloud, or Posit Connect.\n\n### Get Quarto\n\nGet Quarto from: \n\nOr, use version **bundled with RStudio.**\n\n### Get Started\n\n\n\n## Author\n\n### Source File: hello.qmd\n\n````{.markdown}\n---\ntitle: \"Hello, Penguins\"\nformat: html\nexecute:\n echo: false\n---\n\n## Meet the penguins\n\nThe `penguins` data contains size measurements for \npenguins from three islands in the Palmer Archipelago, \nAntarctica.\n\nThe three species of penguins have quite distinct \ndistributions of physical dimensions (@fig-penguins).\n\n```{{r}}\n#| label: fig-penguins\n#| fig-cap: \"Dimensions of penguins across three species.\"\n#| warning: false\nlibrary(tidyverse, quietly = TRUE)\nlibrary(palmerpenguins)\npenguins |>\n ggplot(aes(x = flipper_length_mm, y = bill_length_mm)) +\n geom_point(aes(color = species)) +\n scale_color_manual(\n values = c(\"darkorange\", \"purple\", \"cyan4\")) +\n theme_minimal()\n```\n````\n\n### Highlights in the source file\n\n* Set format(s) and options. Use YAML Syntax.\n \n ```` markdown\n ---\n title: \"Hello, Penguins\"\n format: html\n execute:\n echo: false\n ---\n ````\n\n* `## Write with **Markdown**` \n \n **RStudio**: Help > Markdown Quick Reference\n \n RStudio & VS Code: Use the **Visual Editor**\n\n ```` markdown\n ## Meet the penguins\n \n The `penguins` data contains size measurements for \n penguins from three islands in the Palmer Archipelago, \n Antarctica.\n \n The three species of penguins have quite distinct \n distributions of physical dimensions (@fig-penguins).\n ````\n \n* Include code. R, Python, Julia, Observable, or any language with a Jupyter kernel.\n\n ````markdown\n ```{{r}}\n #| label: fig-penguins\n #| fig-cap: \"Dimensions of penguins across three species.\"\n #| warning: false\n library(tidyverse, quietly = TRUE)\n library(palmerpenguins)\n penguins |>\n ggplot(aes(x = flipper_length_mm, y = bill_length_mm)) +\n geom_point(aes(color = species)) +\n scale_color_manual(\n values = c(\"darkorange\", \"purple\", \"cyan4\")) +\n theme_minimal()\n ```\n ````\n\n### Use a tool with a rich authoring experience\n\n[RStudio](https://posit.co/products/open-source/rstudio/), or \n[Visual Studio Code](https://code.visualstudio.com/) + [Quarto extension](https://marketplace.visualstudio.com/items?itemName=quarto.quarto)\n\n* **Run** code cells as you write\n* **Render** with a button or keyboard shortcut\n* Edit Quarto documents with a **Visual Editor** \n \n ![](images/quarto-visual-editor.png){fig-alt=\"Screenshot of the Visual Editor toolbar. Toolbar shows menu items: Normal with dropdown, bold, italics, code, bulleted list, numbered list, link, image, Format dropdown, Insert dropdown and Table dropdown.\"}\n \n - Apply formatting in Visual Editor. Saved as Markdown in source.\n \n - Insert elements like code cells, cross references, and more.\n\n### Or any text editor\n\nQuarto documents (.qmd) can be edited in any tool that edits text.\n\n## Render\n\n**Save,** then render to **preview** the document output. \n\n```{.bash filename=\"Terminal\"}\nquarto preview hello.qmd\n```\n\nRStudio & VS Code: Use **Render** button\n\nThe resulting HTML/PDF/MS Word/etc. document will be created and saved in the same directory as the source .qmd file.\n\n### Rendered output: hello.html\n\n![](images/quarto-rendered-output.png){fig-alt=\"Screenshot of a webpage with the title 'Hello, Penguins'. There is a subheading 'Meet the penguins' followed by a paragraph of text including a link to 'Figure 1', then a scatterplot.\"}\n\n### Highlights in the rendered output\n\n* Features for scientific publishing. Cross references, citations, equations, and more.\n\n* Output integrated into document. Control how output appears with special comments in your code.\n\n### Behind the Scenes\n\nWhen you render a document, Quarto:\n\n1. Runs the code and embeds results and text into an .md file with:\n - **Knitr**, if any `{r}` cells, or\n - **Jupyter**, if any other cells.\n \n2. Converts the .md file into the output format with Pandoc.\n\n## Publish\n\n``` {.bash filename=\"Terminal\"}\nquarto publish {venue} hello.qmd\n```\n\n`{venue}`: quarto-pub, connect, gh-pages, netlify, confluence, (*v1.4*) posit-cloud\n\nRStudio: Use **Publish** button ![](images/quarto-rstudio-publish.png){fig-alt=\"Publish button icon in RStudio\" width=\"10%\"}\n\n- [**Quarto Pub**](https://quartopub.com/) Free publishing service for Quarto content.\n\n- [**Posit Cloud**](https://posit.cloud/) Cloud-hosted, control access to project and output. ![](images/quarto-rstudio-publish.png){fig-alt=\"Push button publishing from RStudio\" width=\"10%\"}\n\n- [**Posit Connect**](https://posit.co/products/enterprise/connect/) Org-hosted, control access, schedule updates. ![](images/quarto-rstudio-publish.png){fig-alt=\"Push button publishing from RStudio\" width=\"10%\"}\n\n## Quarto Projects\n\n### Create websites, books and more\n\nA directory of Quarto documents + a configuration file (`_quarto.yml`)\n\nSee examples at: \n\nGet started from the command line:\n\n``` {.bash filename=\"Terminal\"}\nquarto create project {type}\n```\n\n`{type}`: default, website, blog, book, confluence, (*v1.4*) manuscript\n\nRStudio: Use **File** \\> **New Project**\n\n## Include Code\n\n### Code Cells\n\nCode cells start with ```` ```{language} ````, and end with ```` ``` ````.\n\nRStudio & VS Code: Use **Insert Code Chunk/Cell**.\n\n::: {layout-ncol=\"2\"}\n```{{r}}\n#| label: chunk-id\n```\n\n```{{python}}\n#| label: chunk-id\n```\n:::\n\nOther languages: `{julia}`, `{ojs}`\n\nAdd code cell options with `#|` comments.\n\nCell options control [**execution**](#execution), [figures](#figures), [tables](#tables), layout and more. See them all at: \n\n### Execution Options {#execution}\n\n+-----------+-----------+----------------------------------------------------------+\n| Option | Default | Effects |\n+===========+===========+==========================================================+\n| `echo` | `true` | `false`: hide code in output\\ |\n| | | `fenced`: include code cell syntax |\n+-----------+-----------+----------------------------------------------------------+\n| `eval` | `true` | `false`: don't run code |\n+-----------+-----------+----------------------------------------------------------+\n| `include` | `true` | `false`: don't include code or results |\n+-----------+-----------+----------------------------------------------------------+\n| `output` | `true` | `false`: don't include results\\ |\n| | | `asis`: treat results as raw markdown |\n+-----------+-----------+----------------------------------------------------------+\n| `warning` | `true` | `false`: don't include warnings in output |\n+-----------+-----------+----------------------------------------------------------+\n| `error` | `false` | `true`: include error in output and continue with render |\n+-----------+-----------+----------------------------------------------------------+\n\nSet execution options at the **cell level**:\n\n::: {layout-ncol=\"2\"}\n```{{r}}\n#| echo: false\n```\n\n```{{python}}\n#| echo: false\n```\n:::\n\nSet options in code cells with `#|` comments and YAML syntax: `key: value`.\n\nOr globally in the YAML header with the **execute** option:\n\n``` yaml\n---\nexecute:\n echo: false\n---\n```\n\n### Inline Code\n\nUse computed values directly in text sections. Code is evaluated at render and results appear as text.\n\n::: {layout-ncol=\"3\"}\n
\n\n#### Knitr\n\nValue is `` `r 2 + 2` ``.\n\n
\n\n
\n\n#### Jupyter\n\n[v1.4]{.small .muted}\n\nValue is `` `{python} 2 + 2` ``.\n\n
\n\n
\n\n#### Output\n\nValue is 4.\n\n
\n:::\n\n## Set Formats and Options\n\n::: {layout-ncol=2}\n\n::: {#set-options}\n### Set Format Options\n\n``` yaml\n---\ntitle: \"My Document\"\nformat: \n html: \n code-fold: true\n toc: true\n---\n```\n\n- Indent format 2 spaces\n- Indent options 4 spaces\n:::\n\n::: {#multiple-formats}\n\n### Multiple Formats\n\n``` yaml\n---\ntitle: \"My Document\"\ntoc: true\nformat: \n html: \n code-fold: true\n pdf: default\n---\n```\n\n- Top-level options (e.g. `toc`) apply to all formats\n\n:::\n:::\n\nCommon values for `format`: html, pdf[^2], docx, odt, rtf, gfm, pptx, revealjs, beamer[^3]\n\n[^2]: PDFs and Beamer slides require LaTeX, use:\n\n ``` {.bash filename=\"Terminal\"}\n quarto install tinytex\n ```\n\n[^3]: PDFs and Beamer slides require LaTeX, use:\n\n ``` {.bash filename=\"Terminal\"}\n quarto install tinytex\n ```\n\n\nRender **all** formats:\n\n``` {.bash filename=\"Terminal\"}\nquarto render hello.qmd\n```\n\nRender a **specific** format:\n\n``` {.bash filename=\"Terminal\"}\nquarto render hello.qmd --to pdf\n```\n\n\n### Output Options Table\n\n\n::: {.cell tbl-cap='Important Options. The first column is the option name, an \"X\" in the next three columns indicates whether the option applies to the format, the fourth column decribes the options and possible values, the final column indicates whether the options can also be set in a code cell.'}\n::: {.cell-output-display}\n```{=html}\n
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n \n \n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n \n \n \n\n\n\n\n\n \n\n\n\n\n\n \n \n \n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n \n \n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n \n \n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n \n \n
Optionhtml/revealjspdf/beamerdocx/pptxDescriptioncell level?
Navigation
tocXXX

Add a table of contents (true or false)

\n
toc-depthXXX

Lowest level of headings to add to table of contents (e.g. 2, 3)

\n
anchor-sectionsX

Show section anchors on mouse hover (true or false)

\n
Style
highlight-styleXXX

Syntax highlighting theme (e.g. arrow, pygments, kate, zenburn)

\n
mainfont, monofontXX

Font name. HTML: sets CSS font-family; LaTeX: via fontspec package

\n
themeX

Bootswatch theme name (e.g. cosmo, darkly, solar etc.)

\n
cssX

CSS or SCSS file to use to style the document (e.g. “style.css”)

\n
reference-docX

docx/pptx file containing template styles (e.g. file.docx, file.pptx)

\n
NA
include-in-headerXX

Files of content to include in header of output document, also include-before-body, include-after-body

\n
keep-mdXXX

Keep intermediate files (true or false), also keep-tex, keep-ipynb

\n
LaTeX
documentclassX

LaTeX document class, set document options with classoption

\n
pdf-engineX

LaTeX engine to produce PDF output (xelatex, pdflatex, lualatex)

\n
cite-methodX

Method used to format citations (citeproc, natbib, biblatex)

\n
Code
code-foldX

Let readers toggle the display of R code (false, true, or show)

\n
X
code-toolsX

Add menu for hiding, showing, and downloading code (true or false)

\n
code-overflowX

Display of wide code (scroll, or wrap)

\n
X
Figures
fig-alignXXdocx only

Alignment of figures (default, left, right, center)

\n
X
fig-width, fig-heightXXX

Default width and height for figures in inches

\n
Knitr only
fig-formatXXX

Format for Matplotlib or R figures (retina, png, jpeg, svg, or pdf)

\n
\n
\n```\n:::\n:::\n\n\nVisit to see all options by format\n\n\n## Add Content\n\n### Figures {#figures}\n\n#### Markdown\n\n``` markdown\n![CAP](image.png){#fig-LABEL fig-alt=\"ALT\"}\n```\n\n#### Computation\n\n```{{python}}\n#| label: fig-LABEL\n#| fig-cap: CAP\n#| fig-alt: ALT\n{{ plot code here }}\n```\n\nOr `{r}`\n\n### Tables {#tables}\n\n#### Markdown\n\n``` markdown\n|object | radius|\n|:------|------:|\n|Sun | 696000|\n|Earth | 6371|\n\n: CAPTION {#tbl-LABEL}\n```\n\n#### Computation\n\nOutput a markdown table or an HTML table from your code.\n\n::: {layout-ncol=\"2\"}\n
\n\n##### Knitr\n\nUse `knitr::kable()` to produce markdown:\n\n```{{r}}\n#| label: tbl-LABEL\n#| tbl-cap: CAPTION\n\nknitr::kable(head(cars))\n```\n\nAlso see the R packages: gt, flextable, kableExtra.\n\n
\n\n
\n\n##### Jupyter\n\nAdd `Markdown()` to Markdown output:\n\n```{{python}}\n#| label: tbl-LABEL\n#| tbl-cap: CAPTION\nimport pandas as pd, tabulate\nfrom IPython.display import Markdown\ndf = pd.DataFrame({\"A\": [1, 2], \n \"B\": [1, 2]})\nMarkdown(df.to_markdown(index=False))\n```\n\n
\n:::\n\n\n### Cross References\n\n1. **Add labels:**\n\n - **Code cell:** add option `label: prefix-LABEL`\n - **Markdown:** add attribute `#prefix-LABEL`\n\n2. **Add references:** `@prefix-LABEL`, e.g.\n\n ``` markdown\n You can see in @fig-scatterplot, that...\n ```\n\n| `prefix` | Renders |\n|----------|------------|\n| `fig-` | Figure 1 |\n| `tbl-` | Table 1 |\n| `eq-` | Equation 1 |\n| `sec-` | Section 1 |\n\n### Citations\n\n1. Add bibliography **file** to the YAML header:\n\n ``` yaml\n ---\n bibliography: references.bib\n ---\n ```\n\n2. Add citations: `[@citation]`, or `@citation`\n\nRStudio & VS Code: Use **Insert Citations** dialog in the Visual Editor. \nBuild your bibliography file from your Zotero library, DOI, Crossref, DataCite, or PubMed.\n\n### Callouts\n\n``` markdown\n::: {.callout-tip}\n## Title\n\nText\n:::\n```\n\nInstead of `tip` use one of: `note`, `caution`, `warning`, or `important`:\n\n::: callout-tip\n## tip\n:::\n\n::: callout-note\n## note\n:::\n\n::: callout-caution\n## caution\n:::\n\n::: callout-warning\n## warning\n:::\n\n::: callout-important\n## important\n:::\n\n### Shortcodes\n\n``` {.markdown shortcodes=\"false\"}\n{{< include _file.qmd >}} \n```\n\n``` {.markdown shortcodes=\"false\"}\n{{< embed file.ipynb#id >}}\n```\n\n``` {.markdown shortcodes=\"false\"}\n{{< video video.mp4 >}}\n```\n\n------------------------------------------------------------------------\n\nCC BY SA Posit Software, PBC • [info\\@posit.co](mailto:info@posit.co) • [posit.co](https://posit.co)\n\nLearn more at [quarto.org](https://quarto.org).\n\nQuarto 1.3\n\nUpdated: 2023-08.\n\n------------------------------------------------------------------------\n", + "engine": "knitr", + "markdown": "---\ntitle: \"Publish and Share with Quarto :: Cheatsheet\"\ndescription: \"QMD Edition\"\nimage-alt: \"\"\nengine: knitr\nexecute:\n eval: true\n output: false\n warning: false\ncode-overflow: wrap\n---\n\n\n\n::: column-margin\n\n\n```{=html}\n\"Hex\n

\n```\n\n\n:::\n\n\n\n::: {.cell .column-margin}\n\n

Download PDF

\n\"\"/\n\n

\n:::\n\n\n\n## Overview\n\n![](images/quarto-illustration.png){fig-alt=\"A schematic representing the multi-language input (e.g. Python, R, Observable, Julia) and multi-format output (e.g. PDF, html, Word documents, and more) versatility of Quarto.\"}[^1]\n\n[^1]: Artwork from \"Hello, Quarto\" keynote by Julia Lowndes and Mine Çetinkaya-Rundel, presented at RStudio Conference 2022.\n Illustrated by [Allison Horst](https://allisonhorst.com/allison-horst).\n\n- **Author**: Write and code in plain text.\n Author documents as .qmd files, or Jupyter notebooks.\n Write in a rich Markdown syntax.\n\n- **Render**: Generate documents, presentations and more.\n Produce HTML, PDF, MS Word, reveal.js, MS Powerpoint, Beamer, websites, blogs, books...\n\n- **Share**: Share your work with the world.\n Quickly deploy to GitHub Pages, Netlify, Quarto Pub, Posit Cloud, or Posit Connect.\n\n### Get Quarto\n\nGet Quarto from: \n\nOr, use version **bundled with RStudio.**\n\n### Get Started\n\n\n\n## Author\n\n### Source File: hello.qmd\n\n```` markdown\n---\ntitle: \"Hello, Penguins\"\nformat: html\nexecute:\n echo: false\n---\n\n## Meet the penguins\n\nThe `penguins` data contains size measurements for \npenguins from three islands in the Palmer Archipelago, \nAntarctica.\n\nThe three species of penguins have quite distinct \ndistributions of physical dimensions (@fig-penguins).\n\n```{{r}}\n#| label: fig-penguins\n#| fig-cap: \"Dimensions of penguins across three species.\"\n#| warning: false\nlibrary(tidyverse, quietly = TRUE)\nlibrary(palmerpenguins)\npenguins |>\n ggplot(aes(x = flipper_length_mm, y = bill_length_mm)) +\n geom_point(aes(color = species)) +\n scale_color_manual(\n values = c(\"darkorange\", \"purple\", \"cyan4\")) +\n theme_minimal()\n```\n````\n\n### Highlights in the source file\n\n- Set format(s) and options.\n Use YAML Syntax.\n\n ``` markdown\n ---\n title: \"Hello, Penguins\"\n format: html\n execute:\n echo: false\n ---\n ```\n\n- `## Write with **Markdown**`\n\n **RStudio**: Help \\> Markdown Quick Reference\n\n RStudio & VS Code: Use the **Visual Editor**\n\n ``` markdown\n ## Meet the penguins\n\n The `penguins` data contains size measurements for \n penguins from three islands in the Palmer Archipelago, \n Antarctica.\n\n The three species of penguins have quite distinct \n distributions of physical dimensions (@fig-penguins).\n ```\n\n- Include code.\n R, Python, Julia, Observable, or any language with a Jupyter kernel.\n\n ```` markdown\n ```{{r}}\n #| label: fig-penguins\n #| fig-cap: \"Dimensions of penguins across three species.\"\n #| warning: false\n library(tidyverse, quietly = TRUE)\n library(palmerpenguins)\n penguins |>\n ggplot(aes(x = flipper_length_mm, y = bill_length_mm)) +\n geom_point(aes(color = species)) +\n scale_color_manual(\n values = c(\"darkorange\", \"purple\", \"cyan4\")) +\n theme_minimal()\n ```\n ````\n\n### Use a tool with a rich authoring experience\n\n[RStudio](https://posit.co/products/open-source/rstudio/), or\\\n[Visual Studio Code](https://code.visualstudio.com/) + [Quarto extension](https://marketplace.visualstudio.com/items?itemName=quarto.quarto)\n\n- **Run** code cells as you write\n\n- **Render** with a button or keyboard shortcut\n\n- Edit Quarto documents with a **Visual Editor**\n\n ![](images/quarto-visual-editor.png){fig-alt=\"Screenshot of the Visual Editor toolbar. Toolbar shows menu items: Normal with dropdown, bold, italics, code, bulleted list, numbered list, link, image, Format dropdown, Insert dropdown and Table dropdown.\"}\n\n - Apply formatting in Visual Editor.\n Saved as Markdown in source.\n\n - Insert elements like code cells, cross references, and more.\n\n### Or any text editor\n\nQuarto documents (.qmd) can be edited in any tool that edits text.\n\n## Render\n\n**Save,** then render to **preview** the document output.\n\n``` {.bash filename=\"Terminal\"}\nquarto preview hello.qmd\n```\n\nRStudio & VS Code: Use **Render** button\n\nThe resulting HTML/PDF/MS Word/etc.\ndocument will be created and saved in the same directory as the source .qmd file.\n\n### Rendered output: hello.html\n\n![](images/quarto-rendered-output.png){fig-alt=\"Screenshot of a webpage with the title 'Hello, Penguins'. There is a subheading 'Meet the penguins' followed by a paragraph of text including a link to 'Figure 1', then a scatterplot.\"}\n\n### Highlights in the rendered output\n\n- Features for scientific publishing.\n Cross references, citations, equations, and more.\n\n- Output integrated into document.\n Control how output appears with special comments in your code.\n\n### Behind the Scenes\n\nWhen you render a document, Quarto:\n\n1. Runs the code and embeds results and text into an .md file with:\n - **Knitr**, if any `{r}` cells, or\n - **Jupyter**, if any other cells.\n2. Converts the .md file into the output format with Pandoc.\n\n## Publish\n\n``` {.bash filename=\"Terminal\"}\nquarto publish {venue} hello.qmd\n```\n\n`{venue}`: quarto-pub, connect, gh-pages, netlify, confluence, (*v1.4*) posit-cloud\n\nRStudio: Use **Publish** button ![](images/quarto-rstudio-publish.png){fig-alt=\"Publish button icon in RStudio\" width=\"10%\"}\n\n- [**Quarto Pub**](https://quartopub.com/) Free publishing service for Quarto content.\n\n- [**Posit Cloud**](https://posit.cloud/) Cloud-hosted, control access to project and output.\n ![](images/quarto-rstudio-publish.png){fig-alt=\"Push button publishing from RStudio\" width=\"10%\"}\n\n- [**Posit Connect**](https://posit.co/products/enterprise/connect/) Org-hosted, control access, schedule updates.\n ![](images/quarto-rstudio-publish.png){fig-alt=\"Push button publishing from RStudio\" width=\"10%\"}\n\n## Quarto Projects\n\n### Create websites, books and more\n\nA directory of Quarto documents + a configuration file (`_quarto.yml`)\n\nSee examples at: \n\nGet started from the command line:\n\n``` {.bash filename=\"Terminal\"}\nquarto create project {type}\n```\n\n`{type}`: default, website, blog, book, confluence, (*v1.4*) manuscript\n\nRStudio: Use **File** \\> **New Project**\n\n## Include Code\n\n### Code Cells\n\nCode cells start with ```` ```{language} ````, and end with ```` ``` ````.\n\nRStudio & VS Code: Use **Insert Code Chunk/Cell**.\n\n::: {layout-ncol=\"2\"}\n```{{r}}\n#| label: chunk-id\n```\n\n```{{python}}\n#| label: chunk-id\n```\n:::\n\nOther languages: `{julia}`, `{ojs}`\n\nAdd code cell options with `#|` comments.\n\nCell options control [**execution**](#execution), [figures](#figures), [tables](#tables), layout and more.\nSee them all at: \n\n### Execution Options {#execution}\n\n+-----------+-----------+----------------------------------------------------------+\n| Option | Default | Effects |\n+===========+===========+==========================================================+\n| `echo` | `true` | `false`: hide code in output\\ |\n| | | `fenced`: include code cell syntax |\n+-----------+-----------+----------------------------------------------------------+\n| `eval` | `true` | `false`: don't run code |\n+-----------+-----------+----------------------------------------------------------+\n| `include` | `true` | `false`: don't include code or results |\n+-----------+-----------+----------------------------------------------------------+\n| `output` | `true` | `false`: don't include results\\ |\n| | | `asis`: treat results as raw markdown |\n+-----------+-----------+----------------------------------------------------------+\n| `warning` | `true` | `false`: don't include warnings in output |\n+-----------+-----------+----------------------------------------------------------+\n| `error` | `false` | `true`: include error in output and continue with render |\n+-----------+-----------+----------------------------------------------------------+\n\nSet execution options at the **cell level**:\n\n::: {layout-ncol=\"2\"}\n```{{r}}\n#| echo: false\n```\n\n```{{python}}\n#| echo: false\n```\n:::\n\nSet options in code cells with `#|` comments and YAML syntax: `key: value`.\n\nOr globally in the YAML header with the **execute** option:\n\n``` yaml\n---\nexecute:\n echo: false\n---\n```\n\n### Inline Code\n\nUse computed values directly in text sections.\nCode is evaluated at render and results appear as text.\n\n::: {layout-ncol=\"3\"}\n
\n\n#### Knitr\n\nValue is `` `r 2 + 2` ``.\n\n
\n\n
\n\n#### Jupyter\n\n[v1.4]{.small .muted}\n\nValue is `` `{python} 2 + 2` ``.\n\n
\n\n
\n\n#### Output\n\nValue is 4.\n\n
\n:::\n\n## Set Formats and Options\n\n::: {layout-ncol=\"2\"}\n::: {#set-options}\n### Set Format Options\n\n``` yaml\n---\ntitle: \"My Document\"\nformat: \n html: \n code-fold: true\n toc: true\n---\n```\n\n- Indent format 2 spaces\n- Indent options 4 spaces\n:::\n\n::: {#multiple-formats}\n### Multiple Formats\n\n``` yaml\n---\ntitle: \"My Document\"\ntoc: true\nformat: \n html: \n code-fold: true\n pdf: default\n---\n```\n\n- Top-level options (e.g. `toc`) apply to all formats\n:::\n:::\n\nCommon values for `format`: html, pdf[^2], docx, odt, rtf, gfm, pptx, revealjs, beamer\n[^3]\n\n[^2]: PDFs and Beamer slides require LaTeX, use:\n\n ``` {.bash filename=\"Terminal\"}\n quarto install tinytex\n ```\n\n[^3]: PDFs and Beamer slides require LaTeX, use:\n\n ``` {.bash filename=\"Terminal\"}\n quarto install tinytex\n ```\n\nRender **all** formats:\n\n``` {.bash filename=\"Terminal\"}\nquarto render hello.qmd\n```\n\nRender a **specific** format:\n\n``` {.bash filename=\"Terminal\"}\nquarto render hello.qmd --to pdf\n```\n\n### Output Options Table\n\n\n\n::: {.cell tbl-cap='Important Options. The first column is the option name, an \"X\" in the next three columns indicates whether the option applies to the format, the fourth column decribes the options and possible values, the final column indicates whether the options can also be set in a code cell.'}\n::: {.cell-output-display}\n\n```{=html}\n
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n \n \n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n \n \n \n\n\n\n\n\n \n\n\n\n\n\n \n \n \n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n \n \n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n \n \n \n\n\n\n\n\n \n\n\n\n\n\n \n\n\n\n\n\n \n \n \n
Optionhtml/revealjspdf/beamerdocx/pptxDescriptioncell level?
Navigation
tocXXX

Add a table of contents (true or false)

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toc-depthXXX

Lowest level of headings to add to table of contents (e.g. 2, 3)

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anchor-sectionsX

Show section anchors on mouse hover (true or false)

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Style
highlight-styleXXX

Syntax highlighting theme (e.g. arrow, pygments, kate, zenburn)

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mainfont, monofontXX

Font name. HTML: sets CSS font-family; LaTeX: via fontspec package

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themeX

Bootswatch theme name (e.g. cosmo, darkly, solar etc.)

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cssX

CSS or SCSS file to use to style the document (e.g. “style.css”)

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reference-doc

X

docx/pptx file containing template styles (e.g. file.docx, file.pptx)

\n

NA
include-in-headerXX

Files of content to include in header of output document, also include-before-body, include-after-body

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keep-mdXXX

Keep intermediate files (true or false), also keep-tex, keep-ipynb

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LaTeX
documentclass
X

LaTeX document class, set document options with classoption

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pdf-engine
X

LaTeX engine to produce PDF output (xelatex, pdflatex, lualatex)

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cite-method
X

Method used to format citations (citeproc, natbib, biblatex)

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Code
code-foldX

Let readers toggle the display of R code (false, true, or show)

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X
code-toolsX

Add menu for hiding, showing, and downloading code (true or false)

\n

code-overflowX

Display of wide code (scroll, or wrap)

\n
X
Figures
fig-alignXXdocx only

Alignment of figures (default, left, right, center)

\n
X
fig-width, fig-heightXXX

Default width and height for figures in inches

\n
Knitr only
fig-formatXXX

Format for Matplotlib or R figures (retina, png, jpeg, svg, or pdf)

\n

\n
\n```\n\n:::\n:::\n\n\n\nVisit to see all options by format\n\n## Add Content\n\n### Figures {#figures}\n\n#### Markdown\n\n``` markdown\n![CAP](image.png){#fig-LABEL fig-alt=\"ALT\"}\n```\n\n#### Computation\n\n```{{python}}\n#| label: fig-LABEL\n#| fig-cap: CAP\n#| fig-alt: ALT\n{{ plot code here }}\n```\n\nOr `{r}`\n\n### Tables {#tables}\n\n#### Markdown\n\n``` markdown\n|object | radius|\n|:------|------:|\n|Sun | 696000|\n|Earth | 6371|\n\n: CAPTION {#tbl-LABEL}\n```\n\n#### Computation\n\nOutput a markdown table or an HTML table from your code.\n\n::: {layout-ncol=\"2\"}\n
\n\n##### Knitr\n\nUse `knitr::kable()` to produce markdown:\n\n```{{r}}\n#| label: tbl-LABEL\n#| tbl-cap: CAPTION\n\nknitr::kable(head(cars))\n```\n\nAlso see the R packages: gt, flextable, kableExtra.\n\n
\n\n
\n\n##### Jupyter\n\nAdd `Markdown()` to Markdown output:\n\n```{{python}}\n#| label: tbl-LABEL\n#| tbl-cap: CAPTION\nimport pandas as pd, tabulate\nfrom IPython.display import Markdown\ndf = pd.DataFrame({\"A\": [1, 2], \n \"B\": [1, 2]})\nMarkdown(df.to_markdown(index=False))\n```\n\n
\n:::\n\n### Cross References\n\n1. **Add labels:**\n\n - **Code cell:** add option `label: prefix-LABEL`\n - **Markdown:** add attribute `#prefix-LABEL`\n\n2. **Add references:** `@prefix-LABEL`, e.g.\n\n ``` markdown\n You can see in @fig-scatterplot, that...\n ```\n\n| `prefix` | Renders |\n|----------|------------|\n| `fig-` | Figure 1 |\n| `tbl-` | Table 1 |\n| `eq-` | Equation 1 |\n| `sec-` | Section 1 |\n\n### Citations\n\n1. Add bibliography **file** to the YAML header:\n\n ``` yaml\n ---\n bibliography: references.bib\n ---\n ```\n\n2. Add citations: `[@citation]`, or `@citation`\n\nRStudio & VS Code: Use **Insert Citations** dialog in the Visual Editor.\nBuild your bibliography file from your Zotero library, DOI, Crossref, DataCite, or PubMed.\n\n### Callouts\n\n``` markdown\n::: {.callout-tip}\n## Title\n\nText\n:::\n```\n\nInstead of `tip` use one of: `note`, `caution`, `warning`, or `important`:\n\n::: callout-tip\n## tip\n:::\n\n::: callout-note\n## note\n:::\n\n::: callout-caution\n## caution\n:::\n\n::: callout-warning\n## warning\n:::\n\n::: callout-important\n## important\n:::\n\n### Shortcodes\n\n\n\n------------------------------------------------------------------------\n\nCC BY SA Posit Software, PBC • [info\\@posit.co](mailto:info@posit.co) • [posit.co](https://posit.co)\n\nLearn more at [quarto.org](https://quarto.org).\n\nQuarto 1.3\n\nUpdated: 2024-05.\n\n------------------------------------------------------------------------\n", "supporting": [], "filters": [ "rmarkdown/pagebreak.lua" diff --git a/_freeze/html/shiny-python/execute-results/html.json b/_freeze/html/shiny-python/execute-results/html.json new file mode 100644 index 00000000..a62b7b7a --- /dev/null +++ b/_freeze/html/shiny-python/execute-results/html.json @@ -0,0 +1,15 @@ +{ + "hash": "40dc3403f4fb24778e2da69caafe04e2", + "result": { + "engine": "knitr", + "markdown": "---\ntitle: \"Shiny for Python :: Cheatsheet\"\ndescription: \" \"\nimage-alt: \"\"\nexecute:\n eval: true\n output: false\n warning: true\n---\n\n::: {.cell .column-margin}\n\"Hex\n

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\n:::\n\n\n\n\n## Build an App\n\nA **Shiny** app is an interactive web page (**ui**) powered by a live Python session run by a **server** (or by a browser with Shinylive).\n\nUsers can manipulate the UI, which will cause the server to update the UI's displays (by running Python code).\n\nSave your app as `app.py` in a directory with the files it uses.\n\n- **app-name:** The directory name is the app name\n\n\n\n- **app.py**\n\n- www/: Place images, CSS, etc. to share with the browser in a folder named \"www\"\n\n- Include any other scripts, data sets, or assets used by the app in the same directory.\n\nRun `shiny create .` in the terminal to generate a template `app.py` file\n\nLaunch apps with `shiny run app.py --reload`\n\n\n\n\n::: {.cell}\n\n```{.python .cell-code}\nfrom shiny import App, render, ui\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n# Nest Python functions to build an HTML interface\napp_ui = ui.page_fluid( # Layout the UI with Layout Functions\n \n # Add Inputs with ui.input_*() functions \n ui.input_slider(\n \"n\", \"Sample Size\", 0, 1000, 20\n ),\n # Add Outputs with ui.ouput_*() functions\n ui.output_plot(\"dist\")\n)\n\ndef server(input, output, session):\n \n # For each output, define a function that generates the output\n @output # Designate output functions with the @output decorator\n @render.plot # Specify the type of output with a @render. decorator\n def dist(): # Use the output id as the function name\n \n # Call the values of UI inputs with input.()\n x = np.random.randn(input.n()) \n plt.hist(x, range=[-3, 3])\n\n# Call App() to combine app_ui and server() into an interactive app\napp = App(app_ui, server)\n```\n:::\n\n\n\n\n## Share\n\nShare your app in three ways:\n\n1. Host it on [shinyapps.io](shinyapps.io), a cloud based service from Posit.\n To deploy Shiny apps:\n\n - Create a free or professional account at [shinyapps.io](shinyapps.io)\n - Use the reconnect-python package to publish with `rsconnect deploy shiny `\n\n2. Purchase Posit Connect, a publishing platform for R and Python.\n [posit.co/products/enterprise/connect/](posit.co/products/enterprise/connect/)\n\n3. Use open source deployment options.\n [shiny.posit.co/py/docs/deploy.html](https://shiny.posit.co/py/docs/deploy.html)\n\n## Shinylive\n\nShinylive apps use WebAssembly to run entirely in a browser--no need for a special server to run Python.\n\n- Edit and/or host Shinylive apps at shinylive.io\n- Create a Shinylive version of an app to deploy with `shinylive export myapp site`. Then deploy to a hosting site like Github or Netifly.\n- Embed Shinylive apps in Quarto sites, blogs, etc\n\nTo embed a Shinylive app in a Quarto doc, include the below syntax.\n\n````markdown\n---\nfilters:\n- shinylive\n---\n \nAn embedded Shinylive app:\n \n```{{r}}\n#| standalone: true\n# [App.py code here...]\n```\n````\n\n## Outputs\n\nMatch ui.output_\\* functions to @render.\\* decorators\n\n+-----------------------+-------------------------------------------------------------------------------+\n| decorator | function |\n+=======================+===============================================================================+\n| `@render.data_frame` | `ui.output_data_frame(id)` |\n+-----------------------+-------------------------------------------------------------------------------+\n| `@render.image` | `ui.output_image(id, width, height, click, dblclick, hover, brush, inline)` |\n+-----------------------+-------------------------------------------------------------------------------+\n| `@render.plot` | `ui.output_plot(id, width, height, click, dblclick, hover, brush, inline)` |\n+-----------------------+-------------------------------------------------------------------------------+\n| `@render.table` | `ui.output_table(id)` |\n+-----------------------+-------------------------------------------------------------------------------+\n| `@render.text` | `ui.output_text(id, container, inline)` also `ui.output_text_verbatim()` |\n+-----------------------+-------------------------------------------------------------------------------+\n| `@render.ui` | `ui.output_ui(id, inline, container, ...)` also `ui.output_html()` |\n+-----------------------+-------------------------------------------------------------------------------+\n| `@sessiom.download` | `ui.output_download_button(id, label, icon,...)` |\n+-----------------------+-------------------------------------------------------------------------------+\n\n: Table of `@render.*()` decorators and their associated `ui.output_*()` functions.\n\n## Inputs\n\nUse a `ui.input_*()` function to make an input widget that saves a value as `input.`. Input values are reactive and need to be called as `input.()`.\n\n- `ui.input_action_button(id, label, icon, width, ...)`\n\n- `ui.input_action_link(id, label, icon, ...)`\n\n- `ui.input_checkbox(id, label, value, width)`\n\n- `ui.input_checkbox_group(id, label, choices, selected, inline, width)`\n\n- `ui.input_date(id, label, value, min, max, format, startview, weekstart, language, width, autoclose, datesdisabled, daysofweekdisabled)`\n\n- `ui.input_date_range(id, label, start, end, min, max, format, startview, weekstart, language, separator, width, autoclose)`\n\n- `ui.input_file(id, label, multiple, accept, width, buttonLabel, placeholder, capture)`\n\n- `ui.input_numeric(id, label, value, min, max, step, width)`\n\n- `ui.input_password(id, label, value, width, placeholder)`\n\n- `ui.input_radio_buttons(id, label, choices, selected, inline, width)`\n\n- `ui.input_select(id, label, choices, selected, multiple, selectize, width, size) Also ui.input_selectize()`\n\n- `ui.input_slider(id, label, min, max, value, step, ticks, animate, width, sep, pre, post, timeFormat, timezone, dragRange)`\n\n- `ui.input_switch(id, label, value, width)`\n\n- `ui.input_text(id, label, value, width, placeholder, autocomplete, spellcheck) Also ui.input_text_area()`\n\n\n\n## Reactivity\n\nReactive values work together with reactive functions. Call a reactive value from within the arguments of one of these functions to avoid the error `No current reactive context`.\n\n![](images/reactivity-diagram-python.png){fig-align=\"center\"}\n\n::: {.callout-note appearance=\"minimal\" icon=\"false\" collapse=\"true\"}\n## Expand to read about the reactivity diagram {aria-hidden=\"true\"}\n\n### Phases in the reactivity diagram\n\n- Create your own reactive values\n - `ui.input_*()`\n - `reactive.Value()``\n - `@reactive.file_reader()`\n - `@reactive.poll()`\n- Perform side effects\n - `@reactive.Effect`\n- Schedule updates\n - `reactive.invalidate_later()`\n- Create reactive expressions\n - `reactive.Calc()`\n- Remove reactivity\n - `reactive.isolate()`\n- React based on event\n - `@reactive.event()`\n- Render reactive output\n - `@output`\n - `@render*`\n:::\n\n### Create Your own Reactive Values\n\n- `ui.input_*()` makes an input widget that saves a reactive value as `input.()`.\n- `reactive.value( )` Creates an object whose value you can set.\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n #...\n app_ui = ui.page_fluid(\n ui.input_text(\"a\", \"A\")\n )\n \n def server(input, output, session):\n rv = reactive.Value()\n rv.set(5) \n #...\n ```\n :::\n\n\n\n\n### Create Reactive Expressions\n\n- `@reactive.Calc` makes a function a reactive expression. Shiny notifies functions that use the expression when it becomes invalidated, triggering recomputation. Shiny caches the value of the expression while it is valid to avoid unnecessary computation.\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n #...\n def server(input, output, session ):\n @reactive.Calc\n def re():\n return input.a() + input.b()\n #...\n ```\n :::\n\n\n\n\n### React Based on Event\n\n- `@reactive.event()` Makes a function react only when a specified value is invalidated, here `input.a`.\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n #...\n def server(input, output, session ):\n @reactive.Calc \n @reactive.event(input.a) \n def re():\n return input.b() \n #...\n ```\n :::\n\n\n\n\n### Display Reactive Output\n\n- `ui.output_*()` adds an output element to the UI.\n- `@output`, `@render.*` are decorators to identify and render outputs\n- `def ():` A function to generate the output\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n app_ui = ui.page_fluid(\n ui.input_text(\"a\", \"A\"), \n ui.output_text(\"b\"),\n )\n \n def server(input, output, session ):\n @output \n @render.text \n def b():\n return input.a()\n ```\n :::\n\n\n\n\n### Perform Side Effects\n\n- `@reactive.Effect` Reactively trigger a function with a side effect. Call a reactive value or use `@reactive.event` to specify when the function will rerun.\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n #...\n def server(input, output, session ):\n @reactive.Effect\n @reactive.event(input.a) \n def print():\n print(\"Hi\") \n #...\n ```\n :::\n\n\n\n\n### Remove Reactivity\n\n- `reactive.isolate()`Create non-reactive context within a reactive function. Calling a reactive value within this context will not cause the calling function to re-execute should the value become invalid.\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n # ...\n def server(input, output, session):\n @output \n @render.text \n def a():\n with reactive.isolate():\n return input.a() \n #...\n ```\n :::\n\n\n\n\n## Layouts\n\nCombine multiple elements into a \"single element\" that has its own properties with a panel function:\n\n- `ui.panel_absolute()`\n- `ui.panel_conditional()`\n- `ui.panel_fixed()`\n- `ui.panel_main()`\n- `ui.panel_sidebar()`\n- `ui.panel_title()`\n- `ui.panel_well()`\n- `ui.row() / ui.column()`\n\n\n\n\n\n::: {.cell}\n\n```{.python .cell-code}\nui.panel_well(\n ui.input_date(...),\n ui.input_action_button(...)\n)\n```\n:::\n\n\n\n\nLayout panels with a layout function. Add elements as arguments of the layout functions.\n\n- `ui.layout_sidebar()`\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n app_ui = ui.page_fluid(\n ui.panel_title( ), \n ui.layout_sidebar(\n ui.panel_sidebar( ),\n )\n ) \n ```\n :::\n\n\n\n\n- `ui.row()`\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n app_ui = ui.page_fluid(\n ui.row(\n ui.column(width = 4), ui.column(width = 2, offset = 3),\n ),\n ui.row(\n ui.column(width = 12)\n )\n )\n ```\n :::\n\n\n\n\nLayer `ui.nav( )`s on top of each other, and navigate between them, with:\n\n\n\n\n::: {.cell}\n\n```{.python .cell-code}\n# navset tab\nui.page_fluid(\n ui.navset_tab(\n ui.nav(\"tab 1\", \"contents\"), \n ui.nav(\"tab 2\", \"contents\"), \n ui.nav(\"tab 3\", \"contents\")\n )\n)\n\n# navpill list\nui.page_fluid(\n ui.navset_pill_list(\n ui.nav(\"tab 1\", \"contents\"), \n ui.nav(\"tab 2\", \"contents\"), \n ui.nav(\"tab 3\", \"contents\")\n )\n)\n\n# navbar page\nui.page_navbar(\n ui.nav(\"tab 1\", \"contents\"), \n ui.nav(\"tab 2\", \"contents\"), \n ui.nav(\"tab 3\", \"contents\"), \n title = \"Page\"\n)\n```\n:::\n\n\n\n\n## Themes\n\nUse the shinyswatch package to add existing bootstrap themes to your Shiny app ui.\n\n\n\n\n::: {.cell}\n\n```{.python .cell-code}\nimport shinyswatch\n\napp_ui = ui.page_fluid(\n shinyswatch.theme.darkly(), \n # ...\n)\n```\n:::\n\n\n\n\n## Shiny for R Comparison\n\nShiny for Python is quite similar to Shiny for R with a few important differences:\n\n\n1. Call inputs as `input.()`\n\n- R\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n input$x\n ```\n :::\n\n\n\n\n- Python\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n input.x()\n ```\n :::\n\n\n\n\n2. Use decorators to create and render outputs. Define outputs as functions `def ():`\n\n- R\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n output$y <- \n renderText(z())\n ```\n :::\n\n\n\n\n- Python\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n @output \n @renderText \n def y():\n return z()\n ```\n :::\n\n\n\n\n3. To create a reactive expression, use `@reactive.Calc`\n\n- R\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n z <- reactive({ \n input$x + 1\n })\n ```\n :::\n\n\n\n\n- Python\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n @reactive.Calc \n def z():\n return input.x()+1\n ```\n :::\n\n\n\n \n4. To create an observer, use `@reactive.Effect`\n\n- R\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n a <- observe({ \n print(input$x)\n })\n ```\n :::\n\n\n\n\n- Python\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n @reactive.Effect \n def a():\n print(input.x())\n ```\n :::\n\n\n\n\n5. Combine these with `@reactive.event`\n\n- R\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n b <- eventReactive(\n input$goCue,\n {input$x + 1}\n )\n ```\n :::\n\n\n\n\n- Python\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n @reactive.Calc \n @reactive.event(input.go_cue )\n def b():\n return input.x() + 1\n ```\n :::\n\n\n\n \n6. Use `reactive.Value()` instead of `reactiveVal()`\n\n- R\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n reactiveVal(1)\n ```\n :::\n\n\n\n\n- Python\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n reactive.Value(1)\n ```\n :::\n\n\n\n\n7. Use `nav_*()` instead of `*Tab()`\n\n- R\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n insertTab() \n appendTab() \n # etc.\n ```\n :::\n\n\n\n\n- Python\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n nav_insert() \n nav_append() \n # etc.\n ```\n :::\n\n\n\n\n8. Functions are intuitively organized into submodules\n\n- R\n\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n dateInput() \n textInput() \n # etc.\n ```\n :::\n\n\n\n\n- Python\n\n\n\n\n ::: {.cell}\n \n ```{.python .cell-code}\n ui.input_date() \n ui.input_text() \n # etc.\n ```\n :::\n\n\n\n\n------------------------------------------------------------------------\n\nCC BY SA Posit Software, PBC • [info\\@posit.co](mailto:info@posit.co) • [posit.co](https://posit.co)\n\nLearn more at [shiny.posit.co/py/](https://shiny.posit.co/py/)\n\nUpdated: 2024-05.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\npackageVersion(\"shiny\")\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] '1.8.1.1'\n```\n\n\n:::\n:::\n\n\n\n\n------------------------------------------------------------------------\n", + "supporting": [], + "filters": [ + "rmarkdown/pagebreak.lua" + ], + "includes": {}, + "engineDependencies": {}, + "preserve": {}, + "postProcess": true + } +} \ No newline at end of file diff --git a/_freeze/html/sparklyr/execute-results/html.json b/_freeze/html/sparklyr/execute-results/html.json index a3157f0f..a19335b4 100644 --- a/_freeze/html/sparklyr/execute-results/html.json +++ b/_freeze/html/sparklyr/execute-results/html.json @@ -1,8 +1,11 @@ { - "hash": "838cdfa44affcebdd0f5c14a01a5344f", + "hash": "dfa5d20431126ba509f25c2253692592", "result": { - "markdown": "---\ntitle: \"Data science in Spark with sparklyr :: Cheatsheet\"\ndescription: \" \"\nimage-alt: \"\"\nexecute:\n eval: true\n output: false\n warning: false\n---\n\n::: {.cell .column-margin}\n\"Hex\n

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Translations (PDF)

\n* Chinese\n* Chinese\n* German\n* Japanese\n* Spanish\n:::\n\n\n\n\nHTML version coming soon! The PDF is available for download [here](../sparklyr.pdf)", - "supporting": [], + "engine": "knitr", + "markdown": "---\ntitle: \"Data science in Spark with sparklyr :: Cheatsheet\"\ndescription: \" \"\nimage-alt: \"\"\nexecute:\n eval: true\n output: false\n warning: false\n---\n\n::: {.cell .column-margin}\n\"Hex\n

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Translations (PDF)

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Use YAML Syntax. - - ```` markdown +- Set format(s) and options. + Use YAML Syntax. + + ``` markdown --- title: "Hello, Penguins" format: html execute: echo: false --- - ```` + ``` + +- `## Write with **Markdown**` + + **RStudio**: Help \> Markdown Quick Reference -* `## Write with **Markdown**` - - **RStudio**: Help > Markdown Quick Reference - RStudio & VS Code: Use the **Visual Editor** - ```` markdown + ``` markdown ## Meet the penguins - + The `penguins` data contains size measurements for penguins from three islands in the Palmer Archipelago, Antarctica. - + The three species of penguins have quite distinct distributions of physical dimensions (@fig-penguins). - ```` - -* Include code. R, Python, Julia, Observable, or any language with a Jupyter kernel. + ``` + +- Include code. + R, Python, Julia, Observable, or any language with a Jupyter kernel. - ````markdown + ```` markdown ```{{r}} #| label: fig-penguins #| fig-cap: "Dimensions of penguins across three species." @@ -135,17 +142,20 @@ penguins |> ### Use a tool with a rich authoring experience -[RStudio](https://posit.co/products/open-source/rstudio/), or +[RStudio](https://posit.co/products/open-source/rstudio/), or\ [Visual Studio Code](https://code.visualstudio.com/) + [Quarto extension](https://marketplace.visualstudio.com/items?itemName=quarto.quarto) -* **Run** code cells as you write -* **Render** with a button or keyboard shortcut -* Edit Quarto documents with a **Visual Editor** - +- **Run** code cells as you write + +- **Render** with a button or keyboard shortcut + +- Edit Quarto documents with a **Visual Editor** + ![](images/quarto-visual-editor.png){fig-alt="Screenshot of the Visual Editor toolbar. Toolbar shows menu items: Normal with dropdown, bold, italics, code, bulleted list, numbered list, link, image, Format dropdown, Insert dropdown and Table dropdown."} - - - Apply formatting in Visual Editor. Saved as Markdown in source. - + + - Apply formatting in Visual Editor. + Saved as Markdown in source. + - Insert elements like code cells, cross references, and more. ### Or any text editor @@ -154,15 +164,16 @@ Quarto documents (.qmd) can be edited in any tool that edits text. ## Render -**Save,** then render to **preview** the document output. +**Save,** then render to **preview** the document output. -```{.bash filename="Terminal"} +``` {.bash filename="Terminal"} quarto preview hello.qmd ``` RStudio & VS Code: Use **Render** button -The resulting HTML/PDF/MS Word/etc. document will be created and saved in the same directory as the source .qmd file. +The resulting HTML/PDF/MS Word/etc. +document will be created and saved in the same directory as the source .qmd file. ### Rendered output: hello.html @@ -170,9 +181,11 @@ The resulting HTML/PDF/MS Word/etc. document will be created and saved in the sa ### Highlights in the rendered output -* Features for scientific publishing. Cross references, citations, equations, and more. +- Features for scientific publishing. + Cross references, citations, equations, and more. -* Output integrated into document. Control how output appears with special comments in your code. +- Output integrated into document. + Control how output appears with special comments in your code. ### Behind the Scenes @@ -181,7 +194,6 @@ When you render a document, Quarto: 1. Runs the code and embeds results and text into an .md file with: - **Knitr**, if any `{r}` cells, or - **Jupyter**, if any other cells. - 2. Converts the .md file into the output format with Pandoc. ## Publish @@ -196,9 +208,11 @@ RStudio: Use **Publish** button ![](images/quarto-rstudio-publish.png){fig-alt=" - [**Quarto Pub**](https://quartopub.com/) Free publishing service for Quarto content. -- [**Posit Cloud**](https://posit.cloud/) Cloud-hosted, control access to project and output. ![](images/quarto-rstudio-publish.png){fig-alt="Push button publishing from RStudio" width="10%"} +- [**Posit Cloud**](https://posit.cloud/) Cloud-hosted, control access to project and output. + ![](images/quarto-rstudio-publish.png){fig-alt="Push button publishing from RStudio" width="10%"} -- [**Posit Connect**](https://posit.co/products/enterprise/connect/) Org-hosted, control access, schedule updates. ![](images/quarto-rstudio-publish.png){fig-alt="Push button publishing from RStudio" width="10%"} +- [**Posit Connect**](https://posit.co/products/enterprise/connect/) Org-hosted, control access, schedule updates. + ![](images/quarto-rstudio-publish.png){fig-alt="Push button publishing from RStudio" width="10%"} ## Quarto Projects @@ -240,7 +254,8 @@ Other languages: `{julia}`, `{ojs}` Add code cell options with `#|` comments. -Cell options control [**execution**](#execution), [figures](#figures), [tables](#tables), layout and more. See them all at: +Cell options control [**execution**](#execution), [figures](#figures), [tables](#tables), layout and more. +See them all at: ### Execution Options {#execution} @@ -276,7 +291,7 @@ Set execution options at the **cell level**: Set options in code cells with `#|` comments and YAML syntax: `key: value`. -Or globally in the YAML header with the **execute** option: +Or globally in the YAML header with the **execute** option: ``` yaml --- @@ -287,7 +302,8 @@ execute: ### Inline Code -Use computed values directly in text sections. Code is evaluated at render and results appear as text. +Use computed values directly in text sections. +Code is evaluated at render and results appear as text. ::: {layout-ncol="3"}
@@ -319,8 +335,7 @@ Value is `r 2*2`. ## Set Formats and Options -::: {layout-ncol=2} - +::: {layout-ncol="2"} ::: {#set-options} ### Set Format Options @@ -339,7 +354,6 @@ format: ::: ::: {#multiple-formats} - ### Multiple Formats ``` yaml @@ -354,11 +368,11 @@ format: ``` - Top-level options (e.g. `toc`) apply to all formats - ::: ::: -Common values for `format`: html, pdf[^2], docx, odt, rtf, gfm, pptx, revealjs, beamer[^3] +Common values for `format`: html, pdf[^2], docx, odt, rtf, gfm, pptx, revealjs, beamer +[^3] [^2]: PDFs and Beamer slides require LaTeX, use: @@ -372,7 +386,6 @@ Common values for `format`: html, pdf[^2], docx, odt, rtf, gfm, pptx, revealjs, quarto install tinytex ``` - Render **all** formats: ``` {.bash filename="Terminal"} @@ -385,7 +398,6 @@ Render a **specific** format: quarto render hello.qmd --to pdf ``` - ### Output Options Table ```{r} @@ -418,7 +430,6 @@ format_options |> Visit to see all options by format - ## Add Content ### Figures {#figures} @@ -494,7 +505,6 @@ Markdown(df.to_markdown(index=False))
::: - ### Cross References 1. **Add labels:** @@ -527,7 +537,7 @@ Markdown(df.to_markdown(index=False)) 2. Add citations: `[@citation]`, or `@citation` -RStudio & VS Code: Use **Insert Citations** dialog in the Visual Editor. +RStudio & VS Code: Use **Insert Citations** dialog in the Visual Editor. Build your bibliography file from your Zotero library, DOI, Crossref, DataCite, or PubMed. ### Callouts