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Publish Ch 33 and 34
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‎assets/book/learn_python_with_jupyter.pdf

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‎assets/notebooks/33_purchases.txt

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20.00
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19.10
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‎assets/notebooks/33_rw_txt_file.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 33. Birthday presents\n",
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"\n",
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"## Reading and writing *.txt* files\n",
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"\n",
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"[Learn Python with Jupyter](https://learnpythonwithjupyter.com/) by [Serena Bonaretti](https://sbonaretti.github.io/) \n",
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"Narrative license: [CC BY-NC-SA](https://creativecommons.org/licenses/by-nc-sa/2.0/). Code license: [GNU-GPL v3](https://www.gnu.org/licenses/gpl-3.0.en.html) \n",
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"\n",
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"---"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"- Three of your friends celebrated their birthday this month, and you bought them presents online.\n",
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"Now, it’s time to perform a purchase analysis and save it in your records. The purchase amounts\n",
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"are in the file *33_purchases.txt*"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"---\n",
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"## 1. Reading a .txt file\n",
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"\n",
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"- Write a function that reads a `.txt` file containing one number per row and stores the numbers into a list:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def read_txt (file_name_in):\n",
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" \"\"\"Reads a .txt file with one number per row and returns them as a list\n",
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" \n",
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" Parameters\n",
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" ----------\n",
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" file_name_in: string\n",
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" Name of the file to read\n",
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" \n",
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" Returns\n",
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" -------\n",
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" numbers : list\n",
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" File content in a list of numbers\n",
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" \"\"\"\n",
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"\n",
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" # initialize output\n",
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" numbers = []\n",
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" \n",
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" # open the file\n",
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" with open(file_name_in, \"r\") as file:\n",
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" \n",
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" # read the file\n",
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" for line in file:\n",
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" print (\"line as read:\", line)\n",
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" \n",
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" # remove \"\\n\" from line\n",
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" line = line.rstrip(\"\\n\")\n",
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" print (\"line after stripping:\", line)\n",
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" print (\"-----\")\n",
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" \n",
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" # get only the non-empty lines\n",
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" if line != \"\":\n",
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" \n",
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" # transform the number to float\n",
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" number = float(line)\n",
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" \n",
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" # add to the output list\n",
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" numbers.append(number)\n",
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" \n",
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" # return the output\n",
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" return numbers\n",
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"\n",
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"# call the function and print the output\n",
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"purchases = read_txt(\"33_purchases.txt\")\n",
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"print (\"purchases:\", purchases)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"- More compact alternative:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def read_txt_compact (file_name_in):\n",
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" \"\"\"Reads a .txt file containing a column of numbers\n",
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" \n",
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" Parameters\n",
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" ----------\n",
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" file_name_in : string\n",
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" Name of the file to read\n",
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" \n",
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" Returns\n",
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" -------\n",
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" numbers : list\n",
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" File content in a list of numbers\n",
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" \"\"\"\n",
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" \n",
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" # open the file\n",
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" with open(file_name_in, \"r\") as file:\n",
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" \n",
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" # read the numbers and transform them into floats\n",
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" numbers = [float(number) for number in file.read().split()]\n",
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" \n",
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" # return the output\n",
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" return numbers\n",
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"\n",
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"# call the function and print the output\n",
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"purchases_compact = read_txt_compact(\"33_purchases.txt\")\n",
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"print (\"purchases:\", purchases_compact)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"--- \n",
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"## 2. Analyzing the numbers"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"- Write a function that takes a list of numbers as input and returns the minimum, maximum, and sum as separate variables."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def calculate_stats(numbers): \n",
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" \"\"\"Returning minimum, maximum, and sum of a list of numbers \n",
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" \n",
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" Parameters\n",
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" ----------\n",
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" numbers: list \n",
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" Contains numbers\n",
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" \n",
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" Returns\n",
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" -------\n",
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" minimum : float\n",
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" Minimum of the list\n",
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" maximum : float \n",
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" Maximum of the list\n",
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" total : float\n",
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" Sum of the list numbers\n",
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" \"\"\"\n",
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" \n",
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" # calculate the minimum\n",
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" minimum = min(numbers)\n",
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"\n",
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" # calculate the maximum\n",
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" maximum = max(numbers) \n",
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"\n",
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" # calculate the sum\n",
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" total = sum(numbers)\n",
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"\n",
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" # return the stats\n",
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" return minimum, maximum, total\n",
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"\n",
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"# call the function\n",
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"mn, mx, tot = calculate_stats(purchases)\n",
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"print (\"minimum:\", mn)\n",
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"print (\"maximum:\", mx)\n",
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"print (\"total:\", tot)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"---\n",
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"## 3. Saving the analysis \n",
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"\n",
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"- Create a function that given minimum, maximum, and total, writes them to file on three consecutive lines, specifying what they represent:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def write_txt(file_name_out, minimum, maximum, total):\n",
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" \"\"\"Writing minimum, maximum, and sum to a file\n",
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" \n",
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" Parameters\n",
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" ----------\n",
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" file_name_out: string\n",
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" Name of the file to write\n",
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" minimum: float\n",
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" Minimum of the list\n",
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" maximum: float \n",
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" Maximum of the list\n",
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" total: float\n",
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" Sum of the numbers in the list\n",
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" \"\"\"\n",
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" \n",
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" # open the file to write\n",
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" with open(file_name_out, \"w\") as file:\n",
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" \n",
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" # write the file content\n",
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" file.write (\"minimum: \" + str(minimum) + \"\\n\")\n",
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" file.write (\"maximum: \" + str(maximum) + \"\\n\")\n",
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" file.write (\"total: \" + str(total))\n",
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"\n",
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"# call the function\n",
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"write_txt(\"33_purchases_stats.txt\", mn, mx, tot) "
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.6"
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},
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {
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"state": {},
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"version_major": 2,
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"version_minor": 0
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

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