render compile

data/01-sales.csv

@@ -0,0 +1,8 @@
+month,year,brand,item,n
+January,2019,1,1234,3
+January,2019,1,8721,9
+January,2019,1,1822,2
+January,2019,2,3333,1
+January,2019,2,2156,9
+January,2019,2,3987,6
+January,2019,2,3827,6

data/02-sales.csv

@@ -0,0 +1,7 @@
+month,year,brand,item,n
+February,2019,1,1234,8
+February,2019,1,8721,2
+February,2019,1,1822,3
+February,2019,2,3333,1
+February,2019,2,2156,3
+February,2019,2,3987,6

data/03-sales.csv

@@ -0,0 +1,7 @@
+month,year,brand,item,n
+March,2019,1,1234,3
+March,2019,1,3627,1
+March,2019,1,8820,3
+March,2019,2,7253,1
+March,2019,2,8766,3
+March,2019,2,8288,6

data/README_1.md

@@ -0,0 +1,3 @@
+# 数据文件夹
+
+存放规则

data/gapminder.R

@@ -0,0 +1,20 @@
+
+
+repurrrsive::gap_simple |>
+  count(year)
+
+by_year <- repurrrsive::gap_simple |>
+  group_by(year)
+paths <- by_year |>
+  group_keys() |>
+  mutate(path = str_glue("data/gapminder/{year}.xlsx")) |>
+  pull()
+paths
+
+years <- by_year |>
+  group_split() |>
+  map(\(df) select(df, -year))
+
+dir.create("data/gapminder")
+
+walk2(years, paths, writexl::write_xlsx)

data/ggplot2/carbon-footprint-travel.csv

@@ -0,0 +1,13 @@
+entity,emissions
+Domestic flight,254.93
+Medium car (petrol),192.28
+Medium car (diesel),170.61
+Short-haul flight (economy),155.73
+Long-haul flight (economy),149.81
+Bus,104.71
+Motorcycle (medium),102.89
+"Petrol car, 2 passengers",96.14
+Medium electric vehicle (UK electricity),53.17
+National rail,41.15
+Ferry (car passenger),129.518
+Eurostar (international rail),5.97

data/ggplot2/spending-jpmorgan.csv

@@ -0,0 +1,166 @@
+category,date,change
+Groceries,2020-01-04,-0.219780219780219
+Groceries,2020-01-11,-2.19780219780219
+Groceries,2020-01-18,-5.494505494505489
+Groceries,2020-01-25,0.6593406593406712
+Groceries,2020-02-01,-2.857142857142847
+Groceries,2020-02-08,-3.296703296703285
+Groceries,2020-02-15,1.4210854715202004e-14
+Groceries,2020-02-22,-1.758241758241752
+Groceries,2020-02-29,4.175824175824189
+Groceries,2020-03-07,13.626373626373637
+Groceries,2020-03-14,59.78021978021979
+Groceries,2020-03-21,61.09890109890111
+Groceries,2020-03-28,10.769230769230774
+Groceries,2020-04-04,15.384615384615389
+Groceries,2020-04-11,19.340659340659343
+Insurance,2020-01-04,15.60439560439562
+Insurance,2020-01-11,9.67032967032968
+Insurance,2020-01-18,6.15384615384616
+Insurance,2020-01-25,3.5164835164835324
+Insurance,2020-02-01,-2.857142857142847
+Insurance,2020-02-08,18.901098901098905
+Insurance,2020-02-15,-2.637362637362614
+Insurance,2020-02-22,11.868131868131885
+Insurance,2020-02-29,-19.120879120879124
+Insurance,2020-03-07,31.42857142857144
+Insurance,2020-03-14,-5.494505494505489
+Insurance,2020-03-21,8.791208791208803
+Insurance,2020-03-28,-16.04395604395603
+Insurance,2020-04-04,7.692307692307693
+Insurance,2020-04-11,-0.879120879120876
+Telecom,2020-01-04,3.2967032967033134
+Telecom,2020-01-11,3.07692307692308
+Telecom,2020-01-18,3.9560439560439704
+Telecom,2020-01-25,5.274725274725284
+Telecom,2020-02-01,7.692307692307693
+Telecom,2020-02-08,2.417582417582423
+Telecom,2020-02-15,1.5384615384615472
+Telecom,2020-02-22,5.054945054945065
+Telecom,2020-02-29,-6.59340659340657
+Telecom,2020-03-07,4.615384615384627
+Telecom,2020-03-14,-1.538461538461533
+Telecom,2020-03-21,-1.95342536357457
+Telecom,2020-03-28,5.934065934065956
+Telecom,2020-04-04,0.439560439560438
+Telecom,2020-04-11,-4.39560439560438
+Utilities,2020-01-04,2.6373626373626564
+Utilities,2020-01-11,5.934065934065956
+Utilities,2020-01-18,0.2197802197802332
+Utilities,2020-01-25,1.9780219780219992
+Utilities,2020-02-01,-0.219780219780219
+Utilities,2020-02-08,1.9780219780219992
+Utilities,2020-02-15,-2.417582417582409
+Utilities,2020-02-22,4.835164835164846
+Utilities,2020-02-29,-9.010989010988991
+Utilities,2020-03-07,0.6593406593406712
+Utilities,2020-03-14,-7.47252747252746
+Utilities,2020-03-21,0.6593406593406712
+Utilities,2020-03-28,-8.791208791208788
+Utilities,2020-04-04,-11.428571428571416
+Utilities,2020-04-11,-6.813186813186803
+Discount Stores,2020-01-04,2.417582417582423
+Discount Stores,2020-01-11,1.3186813186813282
+Discount Stores,2020-01-18,0.2197802197802332
+Discount Stores,2020-01-25,2.6373626373626564
+Discount Stores,2020-02-01,3.07692307692308
+Discount Stores,2020-02-08,-0.219780219780219
+Discount Stores,2020-02-15,3.2967032967033134
+Discount Stores,2020-02-22,2.417582417582423
+Discount Stores,2020-02-29,18.68131868131869
+Discount Stores,2020-03-07,33.84615384615386
+Discount Stores,2020-03-14,46.15384615384616
+Discount Stores,2020-03-21,14.945054945054965
+Discount Stores,2020-03-28,-12.087912087912072
+Discount Stores,2020-04-04,-7.47252747252746
+Discount Stores,2020-04-11,-9.670329670329664
+Pharmacy,2020-01-04,-4.175824175824175
+Pharmacy,2020-01-11,0.6593406593406712
+Pharmacy,2020-01-18,-0.879120879120876
+Pharmacy,2020-01-25,1.3186813186813282
+Pharmacy,2020-02-01,1.9780219780219992
+Pharmacy,2020-02-08,-1.758241758241752
+Pharmacy,2020-02-15,0.6593406593406712
+Pharmacy,2020-02-22,-3.516483516483504
+Pharmacy,2020-02-29,2.417582417582423
+Pharmacy,2020-03-07,12.52747252747254
+Pharmacy,2020-03-14,29.890109890109905
+Pharmacy,2020-03-21,25.71428571428572
+Pharmacy,2020-03-28,-13.626373626373606
+Pharmacy,2020-04-04,-18.461538461538453
+Pharmacy,2020-04-11,-17.582417582417563
+Hospitals,2020-01-04,8.35164835164835
+Hospitals,2020-01-11,11.208791208791226
+Hospitals,2020-01-18,13.846153846153854
+Hospitals,2020-01-25,9.010989010989007
+Hospitals,2020-02-01,11.42857142857143
+Hospitals,2020-02-08,8.571428571428584
+Hospitals,2020-02-15,8.571428571428584
+Hospitals,2020-02-22,6.373626373626379
+Hospitals,2020-02-29,0.8791208791208902
+Hospitals,2020-03-07,8.571428571428584
+Hospitals,2020-03-14,4.395604395604394
+Hospitals,2020-03-21,-16.483516483516482
+Hospitals,2020-03-28,-28.571428571428555
+Hospitals,2020-04-04,-32.30769230769231
+Hospitals,2020-04-11,-28.35164835164835
+Auto Repair,2020-01-04,6.373626373626379
+Auto Repair,2020-01-11,-0.6593406593406428
+Auto Repair,2020-01-18,-0.879120879120876
+Auto Repair,2020-01-25,1.3186813186813282
+Auto Repair,2020-02-01,1.5384615384615472
+Auto Repair,2020-02-08,-5.714285714285708
+Auto Repair,2020-02-15,-1.3186813186812998
+Auto Repair,2020-02-22,0.8791208791208902
+Auto Repair,2020-02-29,-2.637362637362614
+Auto Repair,2020-03-07,-1.0989010989010808
+Auto Repair,2020-03-14,-12.527472527472511
+Auto Repair,2020-03-21,-28.131868131868117
+Auto Repair,2020-03-28,-48.571428571428555
+Auto Repair,2020-04-04,-47.69230769230768
+Auto Repair,2020-04-11,-48.571428571428555
+Other Healthcare,2020-01-04,1.5384615384615472
+Other Healthcare,2020-01-11,6.813186813186817
+Other Healthcare,2020-01-18,5.054945054945065
+Other Healthcare,2020-01-25,6.373626373626379
+Other Healthcare,2020-02-01,4.615384615384627
+Other Healthcare,2020-02-08,5.494505494505503
+Other Healthcare,2020-02-15,4.615384615384627
+Other Healthcare,2020-02-22,7.692307692307693
+Other Healthcare,2020-02-29,-3.736263736263723
+Other Healthcare,2020-03-07,8.131868131868146
+Other Healthcare,2020-03-14,-6.373626373626365
+Other Healthcare,2020-03-21,-29.890109890109883
+Other Healthcare,2020-03-28,-54.72527472527472
+Other Healthcare,2020-04-04,-53.4065934065934
+Other Healthcare,2020-04-11,-57.14285714285714
+Fuel,2020-01-04,8.35164835164835
+Fuel,2020-01-11,8.571428571428584
+Fuel,2020-01-18,5.934065934065956
+Fuel,2020-01-25,8.571428571428584
+Fuel,2020-02-01,6.15384615384616
+Fuel,2020-02-08,1.9780219780219992
+Fuel,2020-02-15,3.07692307692308
+Fuel,2020-02-22,2.197802197802204
+Fuel,2020-02-29,-1.538461538461533
+Fuel,2020-03-07,-4.39560439560438
+Fuel,2020-03-14,-9.010989010988991
+Fuel,2020-03-21,-34.94505494505495
+Fuel,2020-03-28,-62.41758241758242
+Fuel,2020-04-04,-65.27472527472526
+Fuel,2020-04-11,-67.03296703296701
+Transit & Ground Transportation,2020-01-04,-9.89010989010987
+Transit & Ground Transportation,2020-01-11,-7.032967032967022
+Transit & Ground Transportation,2020-01-18,-7.252747252747241
+Transit & Ground Transportation,2020-01-25,-9.670329670329664
+Transit & Ground Transportation,2020-02-01,-13.846153846153824
+Transit & Ground Transportation,2020-02-08,-4.175824175824175
+Transit & Ground Transportation,2020-02-15,-8.351648351648336
+Transit & Ground Transportation,2020-02-22,-9.010989010988991
+Transit & Ground Transportation,2020-02-29,-15.384615384615373
+Transit & Ground Transportation,2020-03-07,-7.252747252747241
+Transit & Ground Transportation,2020-03-14,-32.74725274725273
+Transit & Ground Transportation,2020-03-21,-67.47252747252747
+Transit & Ground Transportation,2020-03-28,-83.5164835164835
+Transit & Ground Transportation,2020-04-04,-84.17582417582415
+Transit & Ground Transportation,2020-04-11,-89.010989010989

data/main.qmd

@@ -0,0 +1,23 @@
+---
+title: 数据分析
+---
+
+```{r}
+#| echo: false
+#| execute: false
+if (FALSE) {
+  require(cctdb)
+  require(tidyverse)
+  conn <- cctdb::get_dbconn("nationalairquality")
+  metadf <- tbl(conn, "metadf") |>
+    collect()
+  airqualitydf <- tbl(conn, "airqualitydf") |>
+    filter(datetime > "2024-03-18") |>
+    filter(datetime < "2024-03-20") |>
+    collect()
+  writexl::write_xlsx(list(metadf = metadf,
+    airqualitydf = airqualitydf),
+    "../data/airquality.xlsx")
+}
+```
+