Add: R code reproducibility sections to 111 existing articles

Backfilled all English articles with collapsible R code sections showing
how to extract and reproduce the data using the cansim package.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

Author: dshkol

docs/en/airline-passengers-august-2025/index.md

@@ -126,6 +126,26 @@ This is a backfill article covering August 2025 data, published as part of the D
 
 </div>
 
+<details>
+<summary>Reproducibility: R code for data extraction</summary>
+
+```r
+library(cansim)
+library(dplyr)
+
+# Fetch airline operating statistics
+airline <- get_cansim("23-10-0253")
+
+# Total passengers
+passengers <- airline %>%
+  filter(`Operating carrier` == "Total, all carriers",
+         `Operating statistics` == "Passengers") %>%
+  select(REF_DATE, VALUE) %>%
+  arrange(desc(REF_DATE))
+```
+
+</details>
+
 <div class="source-info">
 
 **Source:** Statistics Canada, [Table 23-10-0079](https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=2310007901)

docs/en/airline-passengers-october-2025/index.md

@@ -76,6 +76,26 @@ Data cover the operating and financial statistics for major Canadian air carrier
 
 </div>
 
+<details>
+<summary>Reproducibility: R code for data extraction</summary>
+
+```r
+library(cansim)
+library(dplyr)
+
+# Fetch airline operating statistics
+airline <- get_cansim("23-10-0253")
+
+# Total passengers
+passengers <- airline %>%
+  filter(`Operating carrier` == "Total, all carriers",
+         `Operating statistics` == "Passengers") %>%
+  select(REF_DATE, VALUE) %>%
+  arrange(desc(REF_DATE))
+```
+
+</details>
+
 <div class="source-info">
 
 **Source:** Statistics Canada, [Table 23-10-0079](https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=2310007901)

docs/en/airline-passengers-september-2025/index.md

@@ -128,6 +128,26 @@ This backfill article covers September 2025 data as part of The D-AI-LY historic
 
 </div>
 
+<details>
+<summary>Reproducibility: R code for data extraction</summary>
+
+```r
+library(cansim)
+library(dplyr)
+
+# Fetch airline operating statistics
+airline <- get_cansim("23-10-0253")
+
+# Total passengers
+passengers <- airline %>%
+  filter(`Operating carrier` == "Total, all carriers",
+         `Operating statistics` == "Passengers") %>%
+  select(REF_DATE, VALUE) %>%
+  arrange(desc(REF_DATE))
+```
+
+</details>
+
 <div class="source-info">
 
 **Source:** Statistics Canada, [Table 23-10-0079](https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=2310007901)

docs/en/building-permits-august-2025/index.md

@@ -133,6 +133,44 @@ This is a backfill article covering August 2025 data, published as part of the D
 
 </div>
 
+<details>
+<summary>Reproducibility: R code for data extraction</summary>
+
+```r
+library(cansim)
+library(dplyr)
+
+# Fetch building permits data
+permits <- get_cansim("34-10-0066")
+
+# Total building permits value
+total_permits <- permits %>%
+  filter(GEO == "Canada",
+         `Type of structure` == "Total residential and non-residential",
+         `Type of permit and value` == "Total permits, value") %>%
+  select(REF_DATE, VALUE) %>%
+  arrange(desc(REF_DATE))
+
+# By type of structure
+by_type <- permits %>%
+  filter(GEO == "Canada",
+         REF_DATE == "2025-08",
+         `Type of permit and value` == "Total permits, value") %>%
+  select(`Type of structure`, VALUE) %>%
+  arrange(desc(VALUE))
+
+# Provincial breakdown
+provincial <- permits %>%
+  filter(`Type of structure` == "Total residential and non-residential",
+         `Type of permit and value` == "Total permits, value",
+         REF_DATE == "2025-08",
+         GEO != "Canada") %>%
+  select(GEO, VALUE) %>%
+  arrange(desc(VALUE))
+```
+
+</details>
+
 <div class="source-info">
 
 **Source:** Statistics Canada, [Table 34-10-0292](https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3410029201)

docs/en/building-permits-october-2025/index.md

@@ -150,6 +150,44 @@ Data are seasonally adjusted to account for regular seasonal patterns in constru
 
 </div>
 
+<details>
+<summary>Reproducibility: R code for data extraction</summary>
+
+```r
+library(cansim)
+library(dplyr)
+
+# Fetch building permits data
+permits <- get_cansim("34-10-0066")
+
+# Total building permits value
+total_permits <- permits %>%
+  filter(GEO == "Canada",
+         `Type of structure` == "Total residential and non-residential",
+         `Type of permit and value` == "Total permits, value") %>%
+  select(REF_DATE, VALUE) %>%
+  arrange(desc(REF_DATE))
+
+# By type of structure
+by_type <- permits %>%
+  filter(GEO == "Canada",
+         REF_DATE == "2025-10",
+         `Type of permit and value` == "Total permits, value") %>%
+  select(`Type of structure`, VALUE) %>%
+  arrange(desc(VALUE))
+
+# Provincial breakdown
+provincial <- permits %>%
+  filter(`Type of structure` == "Total residential and non-residential",
+         `Type of permit and value` == "Total permits, value",
+         REF_DATE == "2025-10",
+         GEO != "Canada") %>%
+  select(GEO, VALUE) %>%
+  arrange(desc(VALUE))
+```
+
+</details>
+
 <div class="source-info">
 
 **Source:** Statistics Canada, [Table 34-10-0292](https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3410029201)

docs/en/building-permits-september-2025/index.md

@@ -135,6 +135,44 @@ This backfill article covers September 2025 data as part of The D-AI-LY historic
 
 </div>
 
+<details>
+<summary>Reproducibility: R code for data extraction</summary>
+
+```r
+library(cansim)
+library(dplyr)
+
+# Fetch building permits data
+permits <- get_cansim("34-10-0066")
+
+# Total building permits value
+total_permits <- permits %>%
+  filter(GEO == "Canada",
+         `Type of structure` == "Total residential and non-residential",
+         `Type of permit and value` == "Total permits, value") %>%
+  select(REF_DATE, VALUE) %>%
+  arrange(desc(REF_DATE))
+
+# By type of structure
+by_type <- permits %>%
+  filter(GEO == "Canada",
+         REF_DATE == "2025-09",
+         `Type of permit and value` == "Total permits, value") %>%
+  select(`Type of structure`, VALUE) %>%
+  arrange(desc(VALUE))
+
+# Provincial breakdown
+provincial <- permits %>%
+  filter(`Type of structure` == "Total residential and non-residential",
+         `Type of permit and value` == "Total permits, value",
+         REF_DATE == "2025-09",
+         GEO != "Canada") %>%
+  select(GEO, VALUE) %>%
+  arrange(desc(VALUE))
+```
+
+</details>
+
 <div class="source-info">
 
 **Source:** Statistics Canada, [Table 34-10-0292](https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3410029201)

docs/en/construction-wages-november-2025/index.md

@@ -169,6 +169,34 @@ The construction union wage rate index measures changes in basic wage rates nego
 
 </div>
 
+<details>
+<summary>Reproducibility: R code for data extraction</summary>
+
+```r
+library(cansim)
+library(dplyr)
+
+# Fetch construction wage rate index
+wages <- get_cansim("18-10-0140")
+
+# National index by trade
+by_trade <- wages %>%
+  filter(GEO == "Canada",
+         REF_DATE == "2025-11") %>%
+  select(`Type of trade`, VALUE) %>%
+  arrange(desc(VALUE))
+
+# By city
+by_city <- wages %>%
+  filter(`Type of trade` == "Composite",
+         REF_DATE == "2025-11",
+         GEO != "Canada") %>%
+  select(GEO, VALUE) %>%
+  arrange(desc(VALUE))
+```
+
+</details>
+
 <div class="source-info">
 
 **Source:** Statistics Canada, [Table 18-10-0140](https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1810014001)

docs/en/cpi-april-2025/index.md

@@ -122,6 +122,47 @@ This is a backfill article covering April 2025 data, published as part of the D-
 
 </div>
 
+<details>
+<summary>Reproducibility: R code for data extraction</summary>
+
+```r
+library(cansim)
+library(dplyr)
+
+# Fetch CPI data
+cpi <- get_cansim("18-10-0004")
+
+# National all-items CPI time series
+national_cpi <- cpi %>%
+  filter(GEO == "Canada",
+         `Products and product groups` == "All-items") %>%
+  select(REF_DATE, VALUE) %>%
+  arrange(desc(REF_DATE))
+
+# Year-over-year change calculation
+current <- national_cpi %>% filter(REF_DATE == "2025-04") %>% pull(VALUE)
+previous <- national_cpi %>% filter(REF_DATE == "2024-04") %>% pull(VALUE)
+yoy_change <- (current - previous) / previous * 100
+
+# Component breakdown
+components <- cpi %>%
+  filter(GEO == "Canada",
+         REF_DATE == "2025-04") %>%
+  select(`Products and product groups`, VALUE) %>%
+  arrange(desc(VALUE))
+
+# Provincial variation
+provincial <- cpi %>%
+  filter(`Products and product groups` == "All-items",
+         REF_DATE %in% c("2025-04", "2024-04"),
+         GEO != "Canada") %>%
+  select(GEO, REF_DATE, VALUE) %>%
+  pivot_wider(names_from = REF_DATE, values_from = VALUE) %>%
+  mutate(yoy_change = (`2025-04` - `2024-04`) / `2024-04` * 100)
+```
+
+</details>
+
 <div class="source-info">
 
 **Source:** Statistics Canada, [Table 18-10-0004](https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1810000401)

docs/en/cpi-august-2025/index.md

@@ -124,6 +124,47 @@ The CPI is not seasonally adjusted. Month-to-month movements can reflect seasona
 
 </div>
 
+<details>
+<summary>Reproducibility: R code for data extraction</summary>
+
+```r
+library(cansim)
+library(dplyr)
+
+# Fetch CPI data
+cpi <- get_cansim("18-10-0004")
+
+# National all-items CPI time series
+national_cpi <- cpi %>%
+  filter(GEO == "Canada",
+         `Products and product groups` == "All-items") %>%
+  select(REF_DATE, VALUE) %>%
+  arrange(desc(REF_DATE))
+
+# Year-over-year change calculation
+current <- national_cpi %>% filter(REF_DATE == "2025-08") %>% pull(VALUE)
+previous <- national_cpi %>% filter(REF_DATE == "2024-08") %>% pull(VALUE)
+yoy_change <- (current - previous) / previous * 100
+
+# Component breakdown
+components <- cpi %>%
+  filter(GEO == "Canada",
+         REF_DATE == "2025-08") %>%
+  select(`Products and product groups`, VALUE) %>%
+  arrange(desc(VALUE))
+
+# Provincial variation
+provincial <- cpi %>%
+  filter(`Products and product groups` == "All-items",
+         REF_DATE %in% c("2025-08", "2024-08"),
+         GEO != "Canada") %>%
+  select(GEO, REF_DATE, VALUE) %>%
+  pivot_wider(names_from = REF_DATE, values_from = VALUE) %>%
+  mutate(yoy_change = (`2025-08` - `2024-08`) / `2024-08` * 100)
+```
+
+</details>
+
 <div class="source-info">
 
 **Source:** Statistics Canada, Table 18-10-0004

docs/en/cpi-december-2024/index.md

@@ -122,6 +122,47 @@ This is a backfill article covering December 2024 data, published as part of the
 
 </div>
 
+<details>
+<summary>Reproducibility: R code for data extraction</summary>
+
+```r
+library(cansim)
+library(dplyr)
+
+# Fetch CPI data
+cpi <- get_cansim("18-10-0004")
+
+# National all-items CPI time series
+national_cpi <- cpi %>%
+  filter(GEO == "Canada",
+         `Products and product groups` == "All-items") %>%
+  select(REF_DATE, VALUE) %>%
+  arrange(desc(REF_DATE))
+
+# Year-over-year change calculation
+current <- national_cpi %>% filter(REF_DATE == "2024-12") %>% pull(VALUE)
+previous <- national_cpi %>% filter(REF_DATE == "2023-12") %>% pull(VALUE)
+yoy_change <- (current - previous) / previous * 100
+
+# Component breakdown
+components <- cpi %>%
+  filter(GEO == "Canada",
+         REF_DATE == "2024-12") %>%
+  select(`Products and product groups`, VALUE) %>%
+  arrange(desc(VALUE))
+
+# Provincial variation
+provincial <- cpi %>%
+  filter(`Products and product groups` == "All-items",
+         REF_DATE %in% c("2024-12", "2023-12"),
+         GEO != "Canada") %>%
+  select(GEO, REF_DATE, VALUE) %>%
+  pivot_wider(names_from = REF_DATE, values_from = VALUE) %>%
+  mutate(yoy_change = (`2024-12` - `2023-12`) / `2023-12` * 100)
+```
+
+</details>
+
 <div class="source-info">
 
 **Source:** Statistics Canada, [Table 18-10-0004](https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1810000401)