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News 2025.01.05-1
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@lgschuck
lgschuck committed Jan 5, 2025
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28 changes: 27 additions & 1 deletion NEWS.md
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Original file line number Diff line number Diff line change
Expand Up @@ -10,11 +10,37 @@ editor_options:

1 - use reactive instead of reactiveValues for datasets

## 2025.01.05-1

### Bug Fixes

1 - **Metadata - object color_fn not found**: new icon for logical and color format (function data_color) applied only if there is valid (non NA) min and max values ([#4](https://github.com/lgschuck/spada/issues/4)

2 - **Edit > Convert - error in preview complex variable convertion**: fixed converting complex to character in the preview given that gt table in opt_interactive does not show complex properly ([#5](https://github.com/lgschuck/spada/issues/5)

3 - **Edit > Filter: error in filtering complex**: now only show/allow operators '== (Equal)', '!= (Not Equal)', 'Is NA (is.na)', 'Not NA (! is.na)', 'In (%in%)' and 'Not In (! %in%)' (same for character and factors) ([#6](https://github.com/lgschuck/spada/issues/6)

4 - **Edit > Filter: accept blank value**: now the value must have length 1 or bigger ([#7](https://github.com/lgschuck/spada/issues/7)

### Improvements

1 - utils functions

2 - page_config_module: correction of a typo

3 - spada function

* new background color in sidebar

* new value boxes in Data > Highligths (rows, valid, unique, zeros) and better server side checking (returning None if absent)

* new itens in navbar: Options > Documentation link and Github link

## 2025.01.03-1

### Bug Fixes

1 - Data Overview - after Edit only refresh if updat in rows or sample: fixed with insertion of buttons inside output$pD_over_gt. Avaliate use of reactive instead of reactiveValues for datasets.
1 - Data Overview - after Edit only refresh if updat in rows or sample: fixed with insertion of buttons inside output$pD_over_gt. Avaliate use of reactive instead of reactiveValues for datasets. ([#3](https://github.com/lgschuck/spada/issues/3))

### Improvements

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2 changes: 1 addition & 1 deletion R/page_config_module.R
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@ page_config_ui <- function(id) {
),
plotOutput(ns('sample_plot'))
)), card(card_body(
h4('Size input files'),
h4('Size of input files'),
numericInput(ns('input_file_size'), 'Size in MB', 500, min = 0, step = 100),
btn_task(ns('btn_file_size'), 'Apply', icon('check'))
))
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179 changes: 131 additions & 48 deletions R/spada.R
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Original file line number Diff line number Diff line change
Expand Up @@ -73,6 +73,7 @@ spada <- function(...) {

# page sidebar ----------------------------------------------------------
sidebar = sidebar(
bg = '#e3e3e4',
open = F,
accordion(
open = T,
Expand Down Expand Up @@ -116,7 +117,7 @@ spada <- function(...) {
title = 'Factor Vars',
value = textOutput('pD_var_factor_vars'),
showcase = bs_icon('diagram-3'),
theme = 'bg-gradient-green-indigo'
theme = 'bg-gradient-green-blue'
),
value_box(
title = 'Date Vars',
Expand All @@ -127,36 +128,61 @@ spada <- function(...) {
),
layout_column_wrap(
value_box(
title = "Var with most NA's",
title = "Rows",
value = textOutput('pD_n_rows'),
showcase = bs_icon('list'),
theme = 'bg-gradient-blue-purple'
),
value_box(
title = "Most valid",
value = textOutput('pD_var_most_valid'),
showcase = bs_icon('list-check'),
theme = 'bg-gradient-indigo-yellow',
p('Number of valid:', textOutput('pD_var_most_valid_n_valid', inline = T))
) |> tooltip("Showing 1, there may be ties.", placement = 'top'),
value_box(
title = "Most unique",
value = textOutput('pD_var_most_unique'),
showcase = bs_icon('fingerprint'),
theme = 'bg-gradient-indigo-green',
p('Number of unique:', textOutput('pD_var_most_unique_n_unique', inline = T))
) |> tooltip("Showing 1, there may be ties.", placement = 'top'),
value_box(
title = "Most zeros",
value = textOutput('pD_var_most_zeros'),
showcase = bs_icon('0-circle'),
theme = 'bg-gradient-orange-indigo',
p('Number of zeros:', textOutput('pD_var_most_zeros_n_zeros', inline = T))
) |> tooltip("Showing 1, there may be ties.", placement = 'top')
),
layout_column_wrap(
value_box(
title = "Most NA's",
value = textOutput('pD_var_most_nas'),
showcase = bs_icon('database-x'),
theme = 'bg-gradient-red-indigo',
p(textOutput('pD_var_most_nas_n', inline = T), ' rows')
) |> tooltip("Showing 1, there may be ties.", placement = 'top'),
value_box(
title = "Var with biggest % of NA's",
value = textOutput('pD_var_biggest_perc_nas'),
showcase = bs_icon('percent'),
theme = 'light',
p(textOutput('pD_var_biggest_perc_nas_perc', inline = T), ' %')
p("Number of NA's:", textOutput('pD_var_most_nas_n', inline = T), ' rows')
) |> tooltip("Showing 1, there may be ties.", placement = 'top'),
value_box(
title = 'Var with max value',
title = 'Max value',
value = textOutput('pD_var_max_value', inline = T),
showcase = bs_icon('graph-up-arrow', placement = 'top'),
theme = 'bg-gradient-blue-green',
p('Max value:', textOutput('pD_max_value', inline = T))
) |> tooltip("Showing 1, there may be ties.", placement = 'top'),
value_box(
title = "Min value",
value = textOutput('pD_var_min_value'),
showcase = bs_icon('graph-down-arrow'),
theme = 'bg-gradient-pink-indigo',
p('Max value:', textOutput('pD_max_value', inline = T)),
hr(),
p(bs_icon('graph-down-arrow'), 'Var with min value'),
p(textOutput('pD_var_min_value', inline = T)),
p('Min value:', textOutput('pD_min_value', inline = T))
) |> tooltip("Showing 1, there may be ties.", placement = 'top'),
value_box(
title = "Var with biggest size",
title = "Biggest size",
value = textOutput('pD_var_biggest_size'),
showcase = bs_icon('sd-card'),
theme = 'bg-gradient-teal-indigo',
p(textOutput('pD_var_biggest_size_size', inline = T), 'Bytes')
p('Size:', textOutput('pD_var_biggest_size_size', inline = T), 'Bytes')
) |> tooltip("Showing 1, there may be ties.", placement = 'top')
)
)
Expand Down Expand Up @@ -317,7 +343,7 @@ spada <- function(...) {
card_footer(
layout_column_wrap(
btn_task('pE_btn_reset', 'Reset Dataset', icon('arrow-rotate-right')) |>
tooltip('Restore the original dataset to the Active dataset', placement = 'top'),
tooltip('Restore to previous state (before been set as the Active dataset)', placement = 'top'),
btn_task('pE_btn_bkp', 'Create Backup', icon('cloud-arrow-up')) |>
tooltip('Create a copy of the Active dataset', placement = 'top'),
btn_task('pE_btn_restore', 'Restore Backup', icon('cloud-arrow-down')) |>
Expand All @@ -335,7 +361,7 @@ spada <- function(...) {

nav_panel(
'Exploratory',
icon = bs_icon('bar-chart-fill'),
icon = bs_icon('bar-chart-line'),

card(
full_screen = T,
Expand Down Expand Up @@ -444,18 +470,31 @@ spada <- function(...) {
)
),
), # end of analysis menu
# page config -----------------------------------------------------------
# menu options ----------------------------------------------------------
nav_menu(
title = 'Options',
page_config_ui('pC'),
# page exit -------------------------------------------------------------
nav_item(
tags$a(
icon('book'),
'Documentation',
href = 'https://lgschuck.github.io/spada/',
target = '_blank'
)),
nav_panel(
value = 'exit',
title = 'Exit',
icon = bs_icon('x-square-fill')
icon = icon('person-walking-arrow-right')
),
),

nav_item(
tags$a(
icon('github'),
href = 'https://github.com/lgschuck/spada',
target = '_blank'
)),

nav_spacer(),
# active dataset --------------------------------------------------------
nav_item('Active dataset:'),
Expand Down Expand Up @@ -632,6 +671,51 @@ spada <- function(...) {
output$pD_var_factor_vars <- renderText(sapply(df$df_active, is.factor) |> sum())
output$pD_var_date_vars <- renderText(sapply(df$df_active, is_date) |> sum())

output$pD_n_rows <- renderText(
df$df_active |> nrow() |> f_num()
)
output$pD_var_most_valid <- renderText(
if(df_metadata() |> filter(n_valid > 0) |> nrow() < 1) { 'None'
} else {
df_metadata() |> arrange(-n_valid) |> head(1) |> pull(var)
}
)

output$pD_var_most_valid_n_valid <- renderText(
if(df_metadata() |> filter(n_valid > 0) |> nrow() < 1) { '0'
} else {
df_metadata() |> arrange(-n_valid) |> head(1) |> pull(n_valid) |> f_num()
}
)

output$pD_var_most_unique <- renderText(
if(df_metadata() |> filter(n_unique > 0) |> nrow() < 1) { 'None'
} else {
df_metadata() |> arrange(-n_unique) |> head(1) |> pull(var)
}
)

output$pD_var_most_unique_n_unique <- renderText(
if(df_metadata() |> filter(n_unique > 0) |> nrow() < 1) { '0'
} else {
df_metadata() |> arrange(-n_unique) |> head(1) |> pull(n_unique) |> f_num()
}
)

output$pD_var_most_zeros <- renderText(
if(df_metadata() |> filter(n_zero > 0) |> nrow() < 1) { 'None'
} else {
df_metadata() |> arrange(-n_zero) |> head(1) |> pull(var)
}
)

output$pD_var_most_zeros_n_zeros <- renderText(
if(df_metadata() |> filter(n_zero > 0) |> nrow() < 1) { '0'
} else {
df_metadata() |> arrange(-n_zero) |> head(1) |> pull(n_zero) |> f_num()
}
)

output$pD_var_most_nas <- renderText(
{
if(df_metadata() |> filter(n_nas > 0) |> nrow() < 1) { 'None'
Expand All @@ -650,38 +734,32 @@ spada <- function(...) {
}
)

output$pD_var_biggest_perc_nas <- renderText(
{
if(df_metadata() |> filter(perc_nas > 0) |> nrow() < 1) { 'None'
} else {
df_metadata() |> filter(perc_nas > 0)|> arrange(-perc_nas, -n_nas) |>
head(1) |> pull(var) }
}
)

output$pD_var_biggest_perc_nas_perc <- renderText(
{
if(df_metadata() |> filter(perc_nas > 0) |> nrow() < 1) { '0'
} else {
df_metadata() |> filter(perc_nas > 0)|> arrange(-perc_nas, -n_nas) |>
head(1) |> pull(perc_nas) * 100 }
}
)

output$pD_var_max_value <- renderText(
df_metadata() |> arrange(-max) |> head(1) |> pull(var)
if(df_metadata() |> filter(!is.na(max)) |> nrow() < 1) { 'None'
} else {
df_metadata() |> arrange(-max) |> head(1) |> pull(var)
}
)

output$pD_max_value <- renderText(
df_metadata() |> arrange(-max) |> head(1) |> pull(max) |> f_num(dig = 3)
if(df_metadata() |> filter(!is.na(max)) |> nrow() < 1) { '0'
} else {
df_metadata() |> arrange(-max) |> head(1) |> pull(max) |> f_num(dig = 3)
}
)

output$pD_var_min_value <- renderText(
df_metadata() |> arrange(min) |> head(1) |> pull(var)
if(df_metadata() |> filter(!is.na(min)) |> nrow() < 1) { 'None'
} else {
df_metadata() |> arrange(min) |> head(1) |> pull(var)
}
)

output$pD_min_value <- renderText(
df_metadata() |> arrange(min) |> head(1) |> pull(min) |> f_num(dig = 3)
if(df_metadata() |> filter(!is.na(min)) |> nrow() < 1) { '0'
} else {
df_metadata() |> arrange(min) |> head(1) |> pull(min) |> f_num(dig = 3)
}
)

output$pD_var_biggest_size <- renderText(
Expand Down Expand Up @@ -810,8 +888,10 @@ spada <- function(...) {
session, 'pE_filter_operator',
label = 'Operator',
choices =
if(df$df_active[[input$pE_filter_vars_filter]] |> is.factor() |
df$df_active[[input$pE_filter_vars_filter]] |> is.character()){
if(df$df_active[[input$pE_filter_vars_filter]] |> is.factor() ||
df$df_active[[input$pE_filter_vars_filter]] |> is.character() ||
df$df_active[[input$pE_filter_vars_filter]] |> is.complex()
){
c('',
'== (Equal)' = '==',
'!= (Not Equal)' = '!=',
Expand All @@ -837,8 +917,9 @@ spada <- function(...) {

# filter rows
observe({
if(input$pE_filter_vars_filter == '' | input$pE_filter_operator == ''){
msg('Choose a variable and an operator')
if(input$pE_filter_vars_filter == '' || input$pE_filter_operator == ''
|| length(pE_filter_value_temp()) == 0){
msg('Choose a variable, an operator and a value', 3)
} else if(length(pE_filter_value_temp()) > 1 & input$pE_filter_operator %in%
c('==', '!=', '>', '>=', '<', '<=')){
msg_error('Operator requires value of length 1')
Expand Down Expand Up @@ -998,6 +1079,8 @@ spada <- function(...) {
req(input$pE_convert_vars_sel)
if(input$pE_convert_vars_sel %in% names(df$df_active)){
pE_convert_preview_df() |>
lapply(\(x) if(is.complex(x)) as.character(x) else x) |>
as.data.frame() |>
gt() |>
opt_interactive(
use_sorting = F,
Expand Down
23 changes: 18 additions & 5 deletions R/utils.R
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Original file line number Diff line number Diff line change
Expand Up @@ -220,15 +220,28 @@ gt_info <- function(df){
'POSIXct/POSIXt', 'POSIXlt/POSIXt'), 'calendar',
class == 'factor', 'sitemap',
class == 'raw', 'sd-card',
class == 'complex', 'info')]
class == 'complex', 'info',
class == 'logical', 'puzzle-piece')]

df |>
gt::gt() |>
df_gt <- df |>
gt::gt()

# if all NA do nothing
if(!all(df$min |> is.na())){
df_gt <- df_gt |>
gt::data_color(columns = 'min', palette = yl_palette)
}

# if all NA do nothing
if(!all(df$max |> is.na())){
df_gt <- df_gt |>
gt::data_color(columns = 'max', palette = pk_palette)
}

df_gt |>
gt::fmt_percent(columns = c('perc_valid', 'perc_unique', 'perc_zero', 'perc_nas')) |>
gt::fmt_bytes(columns = 'size') |>
gt::data_color(columns = 'size', palette = blue_palette) |>
gt::data_color(columns = 'min', palette = yl_palette) |>
gt::data_color(columns = 'max', palette = pk_palette) |>
gt::data_color(columns = 'n_valid', palette = lg_palette) |>
gt::data_color(columns = 'n_unique', palette = dg_palette) |>
gt::data_color(columns = 'n_zero', palette = gray_palette) |>
Expand Down
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