refactor: replace month dropdown with week dropdown and update related components

feat: add feedback functionality and modal for category feedback
style: add feedback button styles in CSS
docs: add explanation tab for dashboard usage instructions

.gitignore

@@ -1,5 +1,9 @@
+.env
 **/*.pyc
 .coverage
 htmlcov
 **/.DS_Store
-**/*.log
+**/*.log
+
+.codegpt
+*/bin

.python-version

@@ -0,0 +1 @@
+3.11

LICENSE

@@ -1,13 +1,6 @@
 MIT License
 
-Copyright (c) 2022 ArjanCodes and Mark Todisco
 
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
 
 The above copyright notice and this permission notice shall be included in all
 copies or substantial portions of the Software.

README.md

@@ -1,3 +1,4 @@
+#
 # Dash App Tutorial
 
 ## Running the app

assets/style.css

@@ -58,4 +58,18 @@ hr {
     .dropdown-container {
         grid-template-columns: 1fr;
     }
-}
+}
+
+.feedback-button {
+    background-color: #007bff;
+    color: white;
+    border: none;
+    padding: 5px 10px;
+    text-align: center;
+    text-decoration: none;
+    display: inline-block;
+    font-size: 12px;
+    margin: 2px 2px;
+    cursor: pointer;
+    border-radius: 4px;
+}

data/.Rhistory

@@ -0,0 +1,290 @@
+install.packages("tidyverse")
+install.packages("qcc")
+install.packages("skimr")
+install.packages("rmarkdown")
+x=seq(1,10)
+y=seq(sapply(1:10,random(1,1)))
+?Random
+install.packages(DT)
+install.packages("DT")
+if (!require("DT")) install.packages('DT')
+library(DT)
+?DT
+class(datatable(iris))
+?htmlwidget
+??htmlwidget
+install.packages("palletteer")
+install.packages("paletteer")
+install.packages("gapminder")
+install.packages("ggthemes")
+install.packages("collapsebleTree")
+devtools::install_github("AdeelK93/collapsibleTree")
+install.packages("devtools")
+devtools::install_github("AdeelK93/collapsibleTree")
+install.packages("ggthemes")
+names(iris)
+?theme_tufte()
+names(iris)
+library(gapminder)
+attach(gapminder)
+gapminder<-gapminder %>%
+filter(year) %>%
+arrange(-pop) %>%
+slice(1:50) %>%
+mutate(GDP=gdpPercap*Pop)
+library(dplyr)
+gapminder<-gapminder %>%
+filter(year) %>%
+arrange(-pop) %>%
+slice(1:50) %>%
+mutate(GDP=gdpPercap*Pop)
+rlang::last_error
+rlang::last_error()
+names(gapminder)
+table(gapminder$year)
+class(gapminder$year)
+library(usethis)
+library(ggplot2)
+install.packages(c("bit", "boot", "brew", "broom", "bslib", "cachem", "callr", "class", "cli", "cluster", "codetools", "colorspace", "commonmark", "cpp11", "crayon", "curl", "data.table", "dbplyr", "devtools", "digest", "dplyr", "DT", "dtplyr", "evaluate", "fansi", "fastmap", "flexdashboard", "fontawesome", "forcats", "foreign", "fs", "gapminder", "gargle", "gert", "ggplot2", "gh", "gtable", "haven", "highr", "hms", "htmltools", "htmlwidgets", "httpuv", "httr", "isoband", "jsonlite", "knitr", "lifecycle", "lubridate", "markdown", "MASS", "Matrix", "mgcv", "modelr", "nlme", "nnet", "openssl", "paletteer", "pillar", "pkgbuild", "pkgdown", "pkgload", "processx", "ps", "purrr", "ragg", "Rcpp", "readr", "readxl", "repr", "reprex", "rlang", "rmarkdown", "roxygen2", "rpart", "rstudioapi", "rvest", "sass", "scales", "shiny", "skimr", "sourcetools", "spatial", "stringi", "stringr", "survival", "sys", "testthat", "tibble", "tidyr", "tidyselect", "tidyverse", "tinytex", "utf8", "vctrs", "viridisLite", "vroom", "whisker", "xfun", "yaml", "zip"))
+install.packages(c("bit", "boot", "brew", "broom", "bslib", "cachem", "callr", "class", "cli", "cluster", "codetools", "colorspace", "commonmark", "cpp11", "crayon", "curl", "data.table", "dbplyr", "devtools", "digest", "dplyr", "DT", "dtplyr", "evaluate", "fansi", "fastmap", "flexdashboard", "fontawesome", "forcats", "foreign", "fs", "gapminder", "gargle", "gert", "ggplot2", "gh", "gtable", "haven", "highr", "hms", "htmltools", "htmlwidgets", "httpuv", "httr", "isoband", "jsonlite", "knitr", "lifecycle", "lubridate", "markdown", "MASS", "Matrix", "mgcv", "modelr", "nlme", "nnet", "openssl", "paletteer", "pillar", "pkgbuild", "pkgdown", "pkgload", "processx", "ps", "purrr", "ragg", "Rcpp", "readr", "readxl", "repr", "reprex", "rlang", "rmarkdown", "roxygen2", "rpart", "rstudioapi", "rvest", "sass", "scales", "shiny", "skimr", "sourcetools", "spatial", "stringi", "stringr", "survival", "sys", "testthat", "tibble", "tidyr", "tidyselect", "tidyverse", "tinytex", "utf8", "vctrs", "viridisLite", "vroom", "whisker", "xfun", "yaml", "zip"))
+install.packages(c("bit", "boot", "brew", "broom", "bslib", "cachem", "callr", "class", "cli", "cluster", "codetools", "colorspace", "commonmark", "cpp11", "crayon", "curl", "data.table", "dbplyr", "devtools", "digest", "dplyr", "DT", "dtplyr", "evaluate", "fansi", "fastmap", "flexdashboard", "fontawesome", "forcats", "foreign", "fs", "gapminder", "gargle", "gert", "ggplot2", "gh", "gtable", "haven", "highr", "hms", "htmltools", "htmlwidgets", "httpuv", "httr", "isoband", "jsonlite", "knitr", "lifecycle", "lubridate", "markdown", "MASS", "Matrix", "mgcv", "modelr", "nlme", "nnet", "openssl", "paletteer", "pillar", "pkgbuild", "pkgdown", "pkgload", "processx", "ps", "purrr", "ragg", "Rcpp", "readr", "readxl", "repr", "reprex", "rlang", "rmarkdown", "roxygen2", "rpart", "rstudioapi", "rvest", "sass", "scales", "shiny", "skimr", "sourcetools", "spatial", "stringi", "stringr", "survival", "sys", "testthat", "tibble", "tidyr", "tidyselect", "tidyverse", "tinytex", "utf8", "vctrs", "viridisLite", "vroom", "whisker", "xfun", "yaml", "zip"))
+yes
+library(ggplot2)
+install.packages("usethis")
+usethis:edit_r_profile()
+library(usethis)
+usethis:edit_r_profile()
+usethis::edit_r_profile()
+options(
+usethis.description = list(
+`Authors@R` = 'person("jack", "leene", email = "jack@leene.dev", role = c("aut", "cre"))',
+License = "MIT + file LICENSE",
+Version = "0.0.0.9000"
+),
+usethis.full_name = "First Last",
+usethis.protocol = "https",
+vsc.rstudioapi = TRUE,
+warnPartialMatchArgs = TRUE,
+warnPartialMatchDollar = TRUE,
+warnPartialMatchAttr = TRUE
+)
+if (interactive()) {
+suppressMessages(require(devtools))
+suppressMessages(require(usethis))
+}
+p<-ggplot(iris,aes(Sepal.Length,Sepal.Width))+geom_line()
+p<-ggplot(iris,aes(Sepal.Length,Sepal.Width))+geom_line()
+p<-ggplot(iris,aes(Sepal.Length,Sepal.Width))+geom_line()
+library(ggplot2)
+library(DT)
+library(ggthemes)
+library(gapminder)
+p<-ggplot(iris,aes(Sepal.Length,Sepal.Width))+geom_line()
+q<-ggplot(iris,aes(Sepel.Width,Sepal.Length))+geom_line()+theme_tufte()
+(p)
+theme_tufte()
+data(gapminder)
+q
+theme_tufte()
+#gapminder<-gapminder %>%
+#  filter(year) %>%
+#  arrange(-pop) %>%
+#  slice(1:50) %>%
+#  mutate(GDP=gdpPercap*Pop)
+#Column {data-width=450}
+p=datatable((iris))
+print(p)
+library(ggplot2)
+library(DT)
+library(ggthemes)
+library(gapminder)
+p<-ggplot(iris,aes(Sepal.Length,Sepal.Width))+geom_line()
+q<-ggplot(iris,aes(Sepel.Width,Sepal.Length))+geom_line()+theme_tufte()
+p=datatable((iris))
+print(p)
+(p)
+theme_tufte()
+#gapminder<-gapminder %>%
+#  filter(year) %>%
+#  arrange(-pop) %>%
+#  slice(1:50) %>%
+#  mutate(GDP=gdpPercap*Pop)
+#Column {data-width=450}
+theme_tufte()
+library(ggplot2)
+library(DT)
+library(ggthemes)
+library(gapminder)
+p<-ggplot(iris,aes(Sepal.Length,Sepal.Width))+geom_line()
+q<-ggplot(iris,aes(Sepel.Width,Sepal.Length))+geom_line()+theme_tufte()
+p=datatable((iris))
+print(p)
+(p)
+#theme_tufte()
+#gapminder<-gapminder %>%
+#  filter(year) %>%
+#  arrange(-pop) %>%
+#  slice(1:50) %>%
+#  mutate(GDP=gdpPercap*Pop)
+#Column {data-width=450}
+table(iris$Species)
+usethis::edit_rstudio_snippets("r")
+usethis::edit_rstudio_prefs()
+usethis::edit_r_profile()
+install.packages(c("class", "KernSmooth", "MASS", "nnet"))
+mtcars
+a<-mtcars
+a
+nrow(mtcars)
+floor(12/4-2)
+floor(2:32/4-2)
+floor(2:32/4-1)
+floor((1:32)/4-1)
+floor((1:32)/4)
+floor((1:32-1)/4)
+a$group=floor((1:32-1)/4)
+a
+a$group1=mod((1:32-1),4)
+((1:32-1)//4)
+((1:32-1)\\4)
+1\\4
+1//4
+mod(1,4()
+mod(1,4
+mod(1,4)
+mod(1 %%4)
+(1 %% 4)
+a$group1=(1:32 %% 4)
+a
+a$group1=(1:32 %% 4)+1
+a$group1=(0:31 %% 4)+1
+a$group1=(0:31 %% 4)
+a$group1=(1:32 %% 4)
+a<-mtcars
+floor(12/4-2)
+a$group=floor((1:32-1)/4)
+a
+a$group=floor((1:32-1) %% 4)
+a$group=floor((1:32-1)/4)
+a$group=floor((1:32-1)/4)
+a
+a$group2=((1:32-1)%% 4)
+a
+names(a)
+head(a)
+ddply(a,.(group,group2),sumc=sum(cyl))
+library(tidyverse)
+installed.packages("tidyverse")
+install.package("tidyverse")
+install.packages("tidyverse")
+library(tidyverse)
+head(a)
+ddply(a,.(group,group2),sumc=sum(cyl))
+library(dplyr)
+ddply(a,.(group,group2),sumc=sum(cyl))
+library(dplyr)
+ddply(a,.(group,group2),sumc=sum(cyl))
+ddplyr(a,.(group,group2),sumc=sum(cyl))
+ddply
+library(dplyr)
+library(plyr)
+install.packages("plyr")
+library(plyr)
+names(a)
+ddply(a,.(group,group2),summarize,sumc=sum(cyl),paste(.group,.group2,col="",sep="_")=sum(cyl))
+ddply(a,.(group,group2),summarize,sumc=sum(cyl),paste(.group,.group2,col="",sep="_")=sum(cyl))
+starwars %>%
+select(name, mass, species) %>%
+mutate(mass_norm = mass / mean(mass, na.rm = TRUE))
+head(a)
+a %>% pivot_wider()
+?pivot_wider
+map(a$group,function(x){sprinft(x)})
+map(a$group,function(x){sprinf(x)})
+map(a$group,function(x){prinf(x)})
+sprintf
+map(a$group,prinf(x))
+map(a$group,sprinf(x))
+map(a$group,sprinfs(x))
+help("paste")
+map(a$group,paste(x))
+map(a$group,paste(.x))
+map(a$group,paste(x))
+?map
+map(a$group,x)
+map(a$group,.x)
+set_names(c("foo", "bar")) |> map_chr(paste0, ":suffix")
+l1 <- list(list(a = 1L), list(a = NULL, b = 2L), list(b = 3L))
+ll
+l1
+l1 |> map("a", .default = "???")
+list(num = 1:3,     letters[1:3])
+1:10 |>
+map(rnorm, n = 10)
+1:10 |>
+map(\(x) rnorm(10, x))
+letters[1:10] |>
+map(\(x) sprintf("wafer_%03d",x))
+letters[1:10] |>
+map(\(int(x)) sprintf("wafer_%03d",x))
+letters[1:10] |>
+map(int(x) sprintf("wafer_%03d",x))
+letters[1:10] |>
+map(.x, sprintf("wafer_%03d",x))
+letters[1:10] |>
+map(x, sprintf("wafer_%03d",x))
+letters
+letters[1:10]
+letters[1:10] |>
+map(\x, sprintf("wafer_%03d",x))
+letters[1:10] |>
+map(\(x), sprintf("wafer_%03d",x))
+letters[1:10] |>
+map(\x, sprintf("wafer_%03d",x))
+letters[1:10] |>
+map(x, sprintf("wafer_%03d",x))
+[1:10] |>
+1:10 |> map(x, sprintf("wafer_%03d",x))
+1:10 |> map(x, sprintf("wafer_%03d", x))
+1:10 |> map_chr(x, sprintf("wafer_%03d", x))
+1:10 |> map_in5(x, sprintf("wafer_%03d", x))
+1:10 |> map_int(x, sprintf("wafer_%03d", x))
+1:10 |> map(x, sprintf("wafer_%03d", x))
+l2 <- list(
+list(num = 1:3,     letters[1:3]),
+list(num = 101:103, letters[4:6]),
+list()
+)
+l2 |> map(c(2, 2))
+l2 |> map(list("num", 3))
+l2 |> map_int(list("num", 3), .default = NA)
+paste(sprintf("wafer_%03d",1:10))
+seq(paste(sprintf("wafer_%03d",1:10)),3)
+paste(sprintf("wafer_%03d",seq(1:10,3))
+)
+paste(sprintf("wafer_%03d",seq(1:10,3))
+)
+seq(3,1:2)
+seq(1:2,2)
+seq(1:2,a:b)
+seq(a,b)
+seq(1,3)
+R
+which R
+setwd("/Users/jackleene/2024-dash_v1")
+setwd("/Users/jackleene/2024-dash_v1/data")
+a=read_csv("spc_mod.csv")
+library(readr)
+a=read_csv("spc_mod.csv")
+library(arrow)
+install.packages("arrow")
+install.packages("arrow")
+install.packages("sparklyr")
+install.packages("sparklyr")
+install.packages("arrow")
+table(a$timestamp)
+install.packages("arrow")
+names(a)
+class(a)
+lapply(a,class)
+lapply(a,class)

data/feedback.csv

@@ -0,0 +1,2 @@
+timestamp,category,comment
+2025-09-07 20:02:38,groceries,"ABZT please change this air to P1231313"

data/spc_data_full.csv

@@ -651,4 +651,4 @@ Batch,Speed,BatchQty,Para1Tgt,Para1,Para2Tgt,Para2,Para3,Para4,Para5,Para6,Para7
 650,98,121,0.421,0.432,312,312,314,51747,1549,0.43525,312.75,26510,872,0.433,315.75,964,0.443,317.5,1113,56.25,32.49266862,49.7005988,2.857142857,0.5,0.22,0.824601367,21
 651,98,25,0.421,0.424,313,315,306,42278,1433,0.424,307.25,19901,854,0.426,307.5,709,0.431,304,1046,61.68333333,37.33955659,68.13186813,2.923976608,0.27,0.69,0.700471698,22
 652,88,17,0.429,0.44425,311,318,314,50548,1496,0.4435,311.75,24853,864,0.4465,315.25,772,0.4475,313,1330,47.5,26.15384615,54.54545455,3.281334051,0.46,0.91,0.74715262,20
-653,90,95,0.421,0.42675,311,311,296,42970,1354,0.4245,294.25,19676,770,0.427,301,691,0.4275,287.5,1040,52.5,31.88073394,56.81818182,2.099580084,0.49,0.8,0.555288462,19
+653,90,95,0.421,0.42675,311,311,296,42970,1354,0.4245,294.25,19676,770,0.427,301,691,0.4275,287.5,1040,52.5,31.88073394,56.81818182,2.099580084,0.49,0.8,0.555288462,19

data/spc_mod.csv

@@ -0,0 +1,654 @@
+Batch,Speed,BatchQty,Para1,Para2,Para3,Para4,Para5,Para6,Para7,Para8,Para9,Para10,Para11,Para12,Para13,Para14,Para15,Para16,Para17,Para18,Para19,Para20,Para21,Para22,Para23,timestamp
+1,84,26,0.43025,324,314,49512,1759,0.42775,308.75,21557,810,0.4275,309,840,0.425,315.5,1564,75,25.52325581,55.42857143,4.074505239,0.26,0.62,0.588235294,23,2023-12-31T23:00:00Z
+2,100,26,0.433,319,400,47101,1746,0.43375,306.75,20512,824,0.4305,309,756,0.431,305.5,784,64.5,31.6,59.34065934,2.097505669,0.34,0.77,0.839907193,22,2023-12-31T23:00:00Z
+3,102,34,0.4285,323,316,60023,1482,0.428,311.75,24933,765,0.4325,319.75,863,0.4375,330.5,1166,76.3,27.47068677,44.27083333,2.888503755,0.33,0.78,0.681710214,24,2023-12-31T23:00:00Z
+4,96,21,0.43775,322,332,55428,1857,0.43925,322.75,24997,933,0.4375,321.5,780,0.4395,319.5,1362,71.58333333,26.38966873,55.55555556,2.392344498,0.35,0.63,0.65437788,22,2023-12-31T23:00:00Z
+5,94,23,0.41725,321,313,46442,1844,0.4185,312.5,20850,686,0.42175,305.75,791,0.4245,323.5,1334,60.15,28.84500299,47.31182796,2.951191827,0.23,0.66,0.722090261,22,2023-12-31T23:00:00Z
+6,98,97,0.44075,320,312,45539,1584,0.43875,309.25,20866,1400,0.445,311.25,684,0.445,314.5,868,55.16666667,36.03603604,68.92655367,2.37700387,0.31,0.78,0.702031603,20,2023-12-31T23:00:00Z
+7,98,43,0.42275,320,314,51492,1689,0.42625,311.75,20352,864,0.427,317.75,912,0.43,319.5,886,63.5,25.54285714,50.81081081,2.36653825,0.32,0.55,0.769931663,20,2023-12-31T23:00:00Z
+8,94,25,0.43175,321,310,47661,1782,0.428,301,21991,858,0.4325,307.75,812,0.435,299,984,61.33333333,47.98619102,62.90322581,1.81200453,0.44,0.52,0.687943262,20,2023-12-31T23:00:00Z
+9,102,65,0.44225,321,316,70638,1572,0.44,304.25,20352,252,0.446,319.5,901,0.441,319.5,1082,64.83333333,33.22014714,56.98924731,1.672433679,0.34,0.6,0.664444444,20,2023-12-31T23:00:00Z
+10,94,15,0.42875,321,304,45944,1377,0.4335,339.75,21059,255,0.4295,308,677,0.425,289,945,59.5,29.93555946,45.25139665,1.952662722,0.28,0.59,0.712230216,20,2023-12-31T23:00:00Z
+11,98,40,0.43925,325,330,56955,1848,0.43675,330.25,26300,968,0.4415,336.25,856,0.435,315.5,945,56.56666667,37.69363167,54.05405405,3.058438012,0.25,0.76,0.600431965,20,2023-12-31T23:00:01Z
+12,104,35,0.4245,320,312,37616,1689,0.431,314,20496,473,0.431,314,854,0.434,318.5,1127,52.16666667,32.51318102,56.7251462,1.87820148,0.29,0.77,0.811320755,20,2023-12-31T23:00:01Z
+13,95,46,0.43175,320,310,47953,1528,0.4325,321.25,23470,840,0.43125,318,763,0.429,305.5,1362,66.98333333,29.3202765,53.47593583,1.962983735,0.27,0.58,0.637813212,21,2023-12-31T23:00:01Z
+14,65,83,0.4295,320,324,51891,1913,0.43025,331.75,24162,1034,0.4305,326.5,947,0.4335,316.5,1554,87,23.18757192,43.40659341,2.306425041,0.25,0.73,0.583138173,20,2023-12-31T23:00:01Z
+15,98,23,0.43025,323,304,42608,1648,0.43125,306,21638,784,0.431,305.5,978,0.4295,298.5,1194,64,29.19075145,56.66666667,2.628571429,0.5,0.75,0.787185355,20,2023-12-31T23:00:01Z
+16,94,40,0.44275,321,312,60625,1470,0.44425,316,21107,796,0.445,320.75,870,0.443,320,1533,71.66666667,36.2400906,60.42780749,2.155172414,0.31,0.86,0.767184035,22,2023-12-31T23:00:01Z
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+652,88,17,0.44425,318,314,50548,1496,0.4435,311.75,24853,864,0.4465,315.25,772,0.4475,313,1330,47.5,26.15384615,54.54545455,3.281334051,0.46,0.91,0.74715262,20,2023-12-31T23:01:05Z
+653,90,95,0.42675,311,296,42970,1354,0.4245,294.25,19676,770,0.427,301,691,0.4275,287.5,1040,52.5,31.88073394,56.81818182,2.099580084,0.49,0.8,0.555288462,19,2023-12-31T23:01:05Z

main.py

@@ -1,20 +1,27 @@
+# initial commit
 from dash import Dash
-from dash_bootstrap_components.themes import BOOTSTRAP
+import dash_bootstrap_components as dbc
 
 from src.components.layout import create_layout
-from src.data.loader_gz import load_transaction_data
+from src.data.loader_gz import load_spc_data
+#from src.data.loader_gz import load_transition_data
 from json import load
+import os
+from dotenv import load_dotenv
 
+load_dotenv()
 config_file = "./config.json"
+
 with open(config_file) as config_f:
     config=load(config_f)
 
 def main() -> None:
-
+    print(os.getenv("MY_ENV_VAR"))
+    print(config["Startup"])
     # load the data and create the data manager
-    data = load_transaction_data(config["DATA_PATH"])
+    data = load_spc_data(config["DATA_PATH"])
 
-    app = Dash(external_stylesheets=[BOOTSTRAP])
+    app = Dash(external_stylesheets=[dbc.themes.LUX])
     app.title = "Reliability Dashboard"
     app.layout = create_layout(app, data)
     app.run()

poetry.lock

@@ -244,6 +244,20 @@ files = [
     {file = "dash_core_components-2.0.0.tar.gz", hash = "sha256:c6733874af975e552f95a1398a16c2ee7df14ce43fa60bb3718a3c6e0b63ffee"},
 ]
 
+[[package]]
+name = "dash-daq"
+version = "0.5.0"
+description = "DAQ components for Dash"
+category = "main"
+optional = false
+python-versions = "*"
+files = [
+    {file = "dash_daq-0.5.0.tar.gz", hash = "sha256:a1d85b6799f7b885652fbc44aebdb58c41254616a8d350b943beeb42ade4256a"},
+]
+
+[package.dependencies]
+dash = ">=1.6.1"
+
 [[package]]
 name = "dash-html-components"
 version = "2.0.0"
@@ -730,6 +744,21 @@ files = [
 [package.dependencies]
 six = ">=1.5"
 
+[[package]]
+name = "python-dotenv"
+version = "1.0.0"
+description = "Read key-value pairs from a .env file and set them as environment variables"
+category = "main"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "python-dotenv-1.0.0.tar.gz", hash = "sha256:a8df96034aae6d2d50a4ebe8216326c61c3eb64836776504fcca410e5937a3ba"},
+    {file = "python_dotenv-1.0.0-py3-none-any.whl", hash = "sha256:f5971a9226b701070a4bf2c38c89e5a3f0d64de8debda981d1db98583009122a"},
+]
+
+[package.extras]
+cli = ["click (>=5.0)"]
+
 [[package]]
 name = "pytz"
 version = "2023.3.post1"
@@ -901,4 +930,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.11"
-content-hash = "209b9534df1cea182a044844896ee039f12a6dccb440af3c4e1f498ba15325ec"
+content-hash = "7f3e66382a8e3dfd6c4b32282eb27fa714b79e8aa2ddbf66a6adfdae0e127732"

pyproject.toml

@@ -1,19 +1,11 @@
-[tool.poetry]
+[project]
 name = "2024-dash-v1"
 version = "0.1.0"
-description = ""
+description = "Add your description here"
-authors = ["jack leene <jack@leene.dev>"]
 readme = "README.md"
-packages = [{include = "2024_dash_v1"}]
+requires-python = ">=3.11"
-
+dependencies = [
-[tool.poetry.dependencies]
+    "dash>=3.2.0",
-python = "^3.11"
+    "dash-bootstrap-components>=2.0.4",
-dash = "^2.14.2"
+    "dotenv>=0.9.9",
-pydantic = "^2.5.3"
+]
-dash-bootstrap-components = "^1.5.0"
-pandas = "^2.1.4"
-
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"

src/components/bar_chart.py

@@ -12,15 +12,15 @@ def render(app: Dash, data: pd.DataFrame) -> html.Div:
         Output(ids.BAR_CHART, "children"),
         [
             Input(ids.YEAR_DROPDOWN, "value"),
-            Input(ids.MONTH_DROPDOWN, "value"),
+            Input(ids.WEEK_DROPDOWN, "value"),
             Input(ids.CATEGORY_DROPDOWN, "value"),
         ],
     )
     def update_bar_chart(
-        years: list[str], months: list[str], categories: list[str]
+        years: list[str], weeks: list[str], categories: list[str]
     ) -> html.Div:
         filtered_data = data.query(
-            "year in @years and month in @months and category in @categories"
+            "year in @years and week in @weeks and category in @categories"
         )
 
         if filtered_data.shape[0] == 0:
@@ -45,4 +45,4 @@ def render(app: Dash, data: pd.DataFrame) -> html.Div:
 
         return html.Div(dcc.Graph(figure=fig), id=ids.BAR_CHART)
 
-    return html.Div(id=ids.BAR_CHART)
+    return html.Div(id=ids.BAR_CHART)

src/components/category_dropdown.py

@@ -14,12 +14,12 @@ def render(app: Dash, data: pd.DataFrame) -> html.Div:
         Output(ids.CATEGORY_DROPDOWN, "value"),
         [
             Input(ids.YEAR_DROPDOWN, "value"),
-            Input(ids.MONTH_DROPDOWN, "value"),
+            Input(ids.WEEK_DROPDOWN, "value"),
             Input(ids.SELECT_ALL_CATEGORIES_BUTTON, "n_clicks"),
         ],
     )
-    def select_all_categories(years: list[str], months: list[str], _: int) -> list[str]:
+    def select_all_categories(years: list[str], weeks: list[str], _: int) -> list[str]:
-        filtered_data = data.query("year in @years and month in @months")
+        filtered_data = data.query("year in @years and week in @weeks")
         return sorted(set(filtered_data[DataSchema.CATEGORY].tolist()))
 
     return html.Div(
@@ -42,4 +42,4 @@ def render(app: Dash, data: pd.DataFrame) -> html.Div:
                 n_clicks=0,
             ),
         ],
-    )
+    )

src/components/data_table.py

@@ -0,0 +1,123 @@
+import pandas as pd
+from dash import Dash, dcc, html, dash_table, Input, Output, State, callback_context
+from datetime import datetime
+import os
+import dash_bootstrap_components as dbc
+
+from ..data.loader import DataSchema
+from . import ids
+
+def render(app: Dash, data: pd.DataFrame) -> html.Div:
+    @app.callback(
+        Output(ids.DATA_TABLE, "children"),
+        [
+            Input(ids.YEAR_DROPDOWN, "value"),
+            Input(ids.WEEK_DROPDOWN, "value"),
+            Input(ids.CATEGORY_DROPDOWN, "value"),
+        ],
+    )
+    def update_data_table(
+        years: list[str], weeks: list[str], categories: list[str]
+    ) -> html.Div:
+        filtered_data = data.query(
+            "year in @years and week in @weeks and category in @categories"
+        )
+
+        if filtered_data.shape[0] == 0:
+            return html.Div("No data selected.")
+
+        pt = filtered_data.pivot_table(
+            values=DataSchema.AMOUNT,
+            index=[DataSchema.CATEGORY],
+            aggfunc="sum",
+            fill_value=0,
+            dropna=False,
+        ).reset_index().sort_values(DataSchema.AMOUNT, ascending=False)
+
+        columns = [{"name": i.capitalize(), "id": i} for i in pt.columns]
+
+        return dash_table.DataTable(
+            id=ids.CATEGORY_TABLE,
+            data=pt.to_dict("records"),
+            columns=columns,
+            row_selectable='single',
+            selected_rows=[]
+        )
+
+    @app.callback(
+        Output(ids.FEEDBACK_MODAL, "is_open"),
+        Output(ids.FEEDBACK_MESSAGE, "children"),
+        Input(ids.CATEGORY_TABLE, "selected_rows"),
+        Input(ids.SAVE_FEEDBACK_BUTTON_POPUP, "n_clicks"),
+        Input(ids.CLOSE_FEEDBACK_BUTTON_POPUP, "n_clicks"),
+        State(ids.FEEDBACK_MODAL, "is_open"),
+        State(ids.CATEGORY_TABLE, "data"),
+        State(ids.FEEDBACK_INPUT, "value"),
+    )
+    def handle_feedback_modal(selected_rows, save_clicks, close_clicks, is_open, data, comment):
+        ctx = callback_context
+        if not ctx.triggered:
+            return False, ""
+
+        triggered_id = ctx.triggered[0]['prop_id'].split('.')[0]
+        
+        if triggered_id == ids.CATEGORY_TABLE and selected_rows:
+            return True, ""
+
+        if triggered_id == ids.SAVE_FEEDBACK_BUTTON_POPUP and selected_rows:
+            selected_row_data = data[selected_rows[0]]
+            category = selected_row_data[DataSchema.CATEGORY]
+            timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+            if not comment:
+                comment = ""
+            feedback_data = f'{timestamp},{category},"{comment}"\n'
+            file_path = "data/feedback.csv"
+            try:
+                is_new_file = not os.path.exists(file_path) or os.path.getsize(file_path) == 0
+                with open(file_path, "a") as f:
+                    if is_new_file:
+                        f.write("timestamp,category,comment\n")
+                    f.write(feedback_data)
+                message = f"Feedback for category '{category}' has been saved successfully at {timestamp}."
+                return False, message
+            except Exception as e:
+                return True, "An error occurred while saving feedback."
+
+        if triggered_id == ids.CLOSE_FEEDBACK_BUTTON_POPUP:
+            return False, ""
+
+        return is_open, ""
+
+    @app.callback(
+        Output("feedback-category-label", "children"),
+        Input(ids.CATEGORY_TABLE, "selected_rows"),
+        State(ids.CATEGORY_TABLE, "data"),
+        prevent_initial_call=True
+    )
+    def update_feedback_category_label(selected_rows, data):
+        if selected_rows:
+            category = data[selected_rows[0]][DataSchema.CATEGORY]
+            return f"Category: {category}"
+        return "Category: "
+
+    modal = dbc.Modal(
+        [
+            dbc.ModalHeader(dbc.ModalTitle("Submit Feedback")),
+            dbc.ModalBody([
+                html.H6("Category: ", id="feedback-category-label"),
+                dcc.Input(id=ids.FEEDBACK_INPUT, type='text', placeholder='Enter feedback...', style={'width': '100%'}),
+            ]),
+            dbc.ModalFooter([
+                dbc.Button("Save", id=ids.SAVE_FEEDBACK_BUTTON_POPUP, className="ms-auto", n_clicks=0),
+                dbc.Button("Close", id=ids.CLOSE_FEEDBACK_BUTTON_POPUP, className="ms-auto", n_clicks=0)
+            ]),
+        ],
+        id=ids.FEEDBACK_MODAL,
+        is_open=False,
+    )
+
+    return html.Div([
+        html.Div(id=ids.DATA_TABLE),
+        html.Div(id=ids.FEEDBACK_MESSAGE),
+        modal
+    ])

src/components/explanation_tab.py

@@ -0,0 +1,22 @@
+from dash import Dash, dcc, html
+
+def render(_: Dash) -> html.Div:
+    return html.Div([
+        dcc.Markdown("""
+            ### How to use this Dashboard
+
+            **Dashboard Tab:**
+            - Use the dropdowns at the top to filter the data by year, week, and category.
+            - The bar chart shows the total amount per category for the selected period.
+            - The data table shows the detailed data.
+
+            **Feedback:**
+            - In the data table on the Dashboard tab, you can select a row to provide feedback.
+            - A popup will appear where you can enter your comments for the selected category.
+            - Click "Save" to store your feedback.
+
+            **Feedback Tab:**
+            - This tab displays all the feedback that has been submitted.
+            - The table on this tab updates automatically every 5 seconds.
+        """)
+    ])

src/components/feedback_tab.py

@@ -0,0 +1,27 @@
+from dash import Dash, dcc, html, dash_table
+from dash.dependencies import Input, Output
+import pandas as pd
+
+def render(app: Dash) -> html.Div:
+    @app.callback(
+        Output("feedback-table-content", "children"),
+        Input("feedback-interval", "n_intervals")
+    )
+    def update_feedback_table(_):
+        try:
+            feedback_df = pd.read_csv("data/feedback.csv")
+            return dash_table.DataTable(
+                data=feedback_df.to_dict("records"),
+                columns=[{"name": i, "id": i} for i in feedback_df.columns],
+                page_size=10,
+            )
+        except FileNotFoundError:
+            return html.P("No feedback submitted yet.")
+        except Exception as e:
+            return html.P(f"An error occurred: {e}")
+
+    return html.Div([
+        html.H4("Submitted Feedback"),
+        html.Div(id="feedback-table-content"),
+        dcc.Interval(id="feedback-interval", interval=5 * 1000, n_intervals=0) # 5 seconds
+    ])

src/components/ids.py

@@ -1,11 +1,20 @@
 BAR_CHART = "bar-chart"
 PIE_CHART = "pie-chart"
+DATA_TABLE = "data-table"
 
 SELECT_ALL_CATEGORIES_BUTTON = "select-all-categories-button"
 CATEGORY_DROPDOWN = "category-dropdown"
 
-SELECT_ALL_MONTHS_BUTTON = "select-all-months-button"
-MONTH_DROPDOWN = "month-dropdown"
-
 YEAR_DROPDOWN = "year-dropdown"
 SELECT_ALL_YEARS_BUTTON = "select-all-years-button"
+
+WEEK_DROPDOWN = "week-dropdown"
+SELECT_ALL_WEEKS_BUTTON = "select-all-weeks-button"
+
+CATEGORY_TABLE = "category-table"
+
+FEEDBACK_INPUT = "feedback-input"
+FEEDBACK_MESSAGE = "feedback-message"
+FEEDBACK_MODAL = "feedback-modal"
+SAVE_FEEDBACK_BUTTON_POPUP = "save-feedback-button-popup"
+CLOSE_FEEDBACK_BUTTON_POPUP = "close-feedback-button-popup"

src/components/layout.py

@@ -1,29 +1,48 @@
 import pandas as pd
-from dash import Dash, html
+from dash import Dash, dcc, html
 from src.components import (
     bar_chart,
-    category_dropdown,
+    data_table,
-    month_dropdown,
-    pie_chart,
     year_dropdown,
+    week_dropdown,
+    category_dropdown,
+    feedback_tab,
+    explanation_tab,
 )
 
-
 def create_layout(app: Dash, data: pd.DataFrame) -> html.Div:
+    tab_content_style = {'height': 'calc(100vh - 220px)', 'overflowY': 'auto', 'padding': '15px'}
+
     return html.Div(
         className="app-div",
         children=[
             html.H1(app.title),
             html.Hr(),
-            html.Div(
+            dcc.Tabs(id="tabs", value='tab-dashboard', children=[
-                className="dropdown-container",
+                dcc.Tab(label='Dashboard', value='tab-dashboard', children=[
-                children=[
+                    html.Div(style=tab_content_style, children=[
-                    year_dropdown.render(app, data),
+                        html.Div(
-                    month_dropdown.render(app, data),
+                            className="dropdown-container",
-                    category_dropdown.render(app, data),
+                            children=[
-                ],
+                                year_dropdown.render(app, data),
-            ),
+                                week_dropdown.render(app, data),
-            bar_chart.render(app, data),
+                                category_dropdown.render(app, data),
-            pie_chart.render(app, data),
+                            ],
+                        ),
+                        bar_chart.render(app, data),
+                        data_table.render(app, data),
+                    ])
+                ]),
+                dcc.Tab(label='Feedback', value='tab-feedback', children=[
+                    html.Div(style=tab_content_style, children=[
+                        feedback_tab.render(app)
+                    ])
+                ]),
+                dcc.Tab(label='Explanation', value='tab-explanation', children=[
+                    html.Div(style=tab_content_style, children=[
+                        explanation_tab.render(app)
+                    ])
+                ]),
+            ]),
         ],
-    )
+    )

src/components/month_dropdown.py

@@ -1,40 +0,0 @@
-import pandas as pd
-from dash import Dash, dcc, html
-from dash.dependencies import Input, Output
-
-from ..data.loader import DataSchema
-from . import ids
-
-
-def render(app: Dash, data: pd.DataFrame) -> html.Div:
-    all_months: list[str] = data[DataSchema.MONTH].tolist()
-    unique_months = sorted(set(all_months))
-
-    @app.callback(
-        Output(ids.MONTH_DROPDOWN, "value"),
-        [
-            Input(ids.YEAR_DROPDOWN, "value"),
-            Input(ids.SELECT_ALL_MONTHS_BUTTON, "n_clicks"),
-        ],
-    )
-    def select_all_months(years: list[str], _: int) -> list[str]:
-        filtered_data = data.query("year in @years")
-        return sorted(set(filtered_data[DataSchema.MONTH].tolist()))
-
-    return html.Div(
-        children=[
-            html.H6("Month"),
-            dcc.Dropdown(
-                id=ids.MONTH_DROPDOWN,
-                options=[{"label": month, "value": month} for month in unique_months],
-                value=unique_months,
-                multi=True,
-            ),
-            html.Button(
-                className="dropdown-button",
-                children=["Select All"],
-                id=ids.SELECT_ALL_MONTHS_BUTTON,
-                n_clicks=0,
-            ),
-        ]
-    )

src/components/week_dropdown.py

@@ -0,0 +1,53 @@
+import pandas as pd
+from dash import Dash, dcc, html
+from dash.dependencies import Input, Output
+from datetime import datetime, timedelta
+
+from ..data.loader import DataSchema
+from . import ids
+
+def render(app: Dash, data: pd.DataFrame) -> html.Div:
+    all_weeks: list[str] = data[DataSchema.WEEK].tolist()
+    unique_weeks = sorted(set(all_weeks), reverse=True)
+
+    # determine default weeks (last 13)
+    today = datetime.now()
+    last_13_weeks = []
+    for i in range(13):
+        date = today - timedelta(weeks=i)
+        year, week, _ = date.isocalendar()
+        last_13_weeks.append(f"{year}{week:02d}")
+
+    default_weeks = [week for week in last_13_weeks if week in unique_weeks]
+    if not default_weeks and unique_weeks:
+        default_weeks = unique_weeks[:13]
+
+
+    @app.callback(
+        Output(ids.WEEK_DROPDOWN, "value"),
+        [
+            Input(ids.YEAR_DROPDOWN, "value"),
+            Input(ids.SELECT_ALL_WEEKS_BUTTON, "n_clicks"),
+        ],
+    )
+    def select_all_weeks(years: list[str], _: int) -> list[str]:
+        filtered_data = data.query("year in @years")
+        return sorted(set(filtered_data[DataSchema.WEEK].tolist()))
+
+    return html.Div(
+        children=[
+            html.H6("Week"),
+            dcc.Dropdown(
+                id=ids.WEEK_DROPDOWN,
+                options=[{"label": f"{week[:4]}-{week[4:]}", "value": week} for week in unique_weeks],
+                value=default_weeks,
+                multi=True,
+            ),
+            html.Button(
+                className="dropdown-button",
+                children=["Select All"],
+                id=ids.SELECT_ALL_WEEKS_BUTTON,
+                n_clicks=0,
+            ),
+        ]
+    )

src/data/loader.py

@@ -7,6 +7,7 @@ class DataSchema:
     DATE = "date"
     MONTH = "month"
     YEAR = "year"
+    WEEK = "week"
 
 
 def load_transaction_data(path: str) -> pd.DataFrame:
@@ -22,4 +23,8 @@ def load_transaction_data(path: str) -> pd.DataFrame:
     )
     data[DataSchema.YEAR] = data[DataSchema.DATE].dt.year.astype(str)
     data[DataSchema.MONTH] = data[DataSchema.DATE].dt.month.astype(str)
-    return data
+    data[DataSchema.WEEK] = (
+        data[DataSchema.DATE].dt.isocalendar().year.astype(str)
+        + data[DataSchema.DATE].dt.isocalendar().week.astype(str).str.zfill(2)
+    )
+    return data

src/data/loader_gz.py

@@ -1,15 +1,24 @@
 import pandas as pd
 
-
 class DataSchema:
     AMOUNT = "amount"
     CATEGORY = "category"
     DATE = "date"
     MONTH = "month"
     YEAR = "year"
+    WEEK = "week"
 
+class SPC_Schema:
+    FC = "FC"
+    Category1 = "Category1"
+    Category2 = "Category2"
+    Category3 = "Category3"
+    Batch = "Batch"
+    Lot = "Lot"
+    DateTime = "DateTime"
+    Value = "Value"
 
-def load_transaction_data(path: str) -> pd.DataFrame:
+def load_spc_data(path: str) -> pd.DataFrame:
     # load the data from the CSV file
     data = pd.read_csv(
         path,
@@ -22,4 +31,8 @@ def load_transaction_data(path: str) -> pd.DataFrame:
     )
     data[DataSchema.YEAR] = data[DataSchema.DATE].dt.year.astype(str)
     data[DataSchema.MONTH] = data[DataSchema.DATE].dt.month.astype(str)
-    return data
+    data[DataSchema.WEEK] = (
+        data[DataSchema.DATE].dt.isocalendar().year.astype(str)
+        + data[DataSchema.DATE].dt.isocalendar().week.astype(str).str.zfill(2)
+    )
+    return data

src/data/spc_loader.py

@@ -0,0 +1,71 @@
+import pandas as pd
+
+class spc_DataSchema:
+    BATCH = "batch",
+    SPEED = "speed",
+    BATCHQUANTITY = "numeric",
+    PARA1 = "numeric",
+    PARA2 = "character",
+    PARA3 = "numeric",
+    PARA4 = "numeric",
+    PARA5 = "numeric",
+    PARA6 = "numeric",
+    PARA7 = "numeric",
+    PARA8 = "numeric",
+    PARA9 = "numeric",
+    PARA10 ="numeric",
+    PARA11 ="numeric",
+    PARA12 ="numeric",
+    PARA13 ="numeric",
+    PARA14 ="numeric",
+    PARA15 ="numeric",
+    PARA16 ="numeric",
+    PARA17 ="numeric",
+    PARA18 ="numeric",
+    PARA19 ="numeric",
+    PARA20 ="numeric",
+    PARA21 ="numeric",
+    PARA22 ="character",
+    PARA23 ="numeric",
+    timestamp ="date" 
+    
+
+def load_eventlog_data(path: str) -> pd.DataFrame:
+    # load the data from the CSV file
+    data = pd.read_csv(
+        path,
+        dtype={
+        spc_DataSchema.BATCH : "batch",
+        spc_DataSchema.SPEED : "speed",
+        spc_DataSchema.BATCHQUANTITY : "numeric",
+        spc_DataSchema.PARA1 : "numeric",
+        spc_DataSchema.PARA2 : "character",
+        spc_DataSchema.PARA3 : "numeric",
+        spc_DataSchema.PARA4 : "numeric",
+        spc_DataSchema.PARA5 : "numeric",
+        spc_DataSchema.PARA6 : "numeric",
+        spc_DataSchema.PARA7 : "numeric",
+        spc_DataSchema.PARA8 : "numeric",
+        spc_DataSchema.PARA9 : "numeric",
+        spc_DataSchema.PARA10 :"numeric",
+        spc_DataSchema.PARA11 :"numeric",
+        spc_DataSchema.PARA12 :"numeric",
+        spc_DataSchema.PARA13 :"numeric",
+        spc_DataSchema.PARA14 :"numeric",
+        spc_DataSchema.PARA15 :"numeric",
+        spc_DataSchema.PARA16 :"numeric",
+        spc_DataSchema.PARA17 :"numeric",
+        spc_DataSchema.PARA18 :"numeric",
+        spc_DataSchema.PARA19 :"numeric",
+        spc_DataSchema.PARA20 :"numeric",
+        spc_DataSchema.PARA21 :"numeric",
+        spc_DataSchema.PARA22 :"character",
+        spc_DataSchema.PARA23 :"numeric",
+        spc_DataSchema.timestamp :"datetime" 
+        },
+        parse_dates=[spc_DataSchema.timestamp],
+    )
+    data['formatted_date'] = pd.to_datetime(data['datetime'])
+    data[DataSchema.wd] = data[data.timestamp].dt.isocalendar().week + 0.1 * data[DataSchema.timestamp].dt.weekday()
+    data[DataSchema.month] = data[DataSchema.DATE].dt.month
+    return data

src/data/statistic_ver.R

@@ -0,0 +1,3 @@
+library("ggplot2")
+
+read.csv("data\\")

tools/stat_check.R

@@ -0,0 +1,11 @@
+library(tidyverse)
+library(lubridate
+)
+print("Hello")
+
+setwd("~/code/2024-dash_v1/data")
+data <- read.csv("transactions.csv.gz")
+
+print(data)
+
+print("Goodbye")

uv.lock

@@ -0,0 +1,383 @@
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+revision = 1
+requires-python = ">=3.11"
+
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+    { name = "dash" },
+    { name = "dash-bootstrap-components" },
+    { name = "dotenv" },
+]
+
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+requires-dist = [
+    { name = "dash", specifier = ">=3.2.0" },
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