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differences for PR #891
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actions-user committed May 16, 2024
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2 changes: 1 addition & 1 deletion 01-rstudio-intro.md
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Expand Up @@ -643,7 +643,7 @@ function (name, pos = -1L, envir = as.environment(pos), all.names = FALSE,
}
else all.names
}
<bytecode: 0x55c789de4918>
<bytecode: 0x5582676ebdb0>
<environment: namespace:base>
```

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2 changes: 1 addition & 1 deletion 02-project-intro.md
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Expand Up @@ -190,7 +190,7 @@ ls -lh data/gapminder_data.csv
```

```output
-rw-r--r-- 1 runner docker 80K May 12 15:14 data/gapminder_data.csv
-rw-r--r-- 1 runner docker 80K May 16 13:25 data/gapminder_data.csv
```

The file size is 80K.
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6 changes: 3 additions & 3 deletions 03-seeking-help.md
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Expand Up @@ -160,8 +160,8 @@ sessionInfo()
```

```output
R version 4.3.3 (2024-02-29)
Platform: x86_64-pc-linux-gnu (64-bit)
R version 4.4.0 (2024-04-24)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 22.04.4 LTS
Matrix products: default
Expand All @@ -181,7 +181,7 @@ attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] compiler_4.3.3 tools_4.3.3 yaml_2.3.8 knitr_1.46 xfun_0.43
[1] compiler_4.4.0 tools_4.4.0 yaml_2.3.8 knitr_1.46 xfun_0.43
[6] renv_1.0.7 evaluate_0.23
```

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17 changes: 11 additions & 6 deletions 12-dplyr.md
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Expand Up @@ -387,13 +387,14 @@ lifeExp_bycountry %>%

:::::::::::::::::::::::::

The function `group_by()` allows us to group by multiple variables. Let's group by `year` and `continent`.
The function `group_by()` allows us to group by multiple variables. If you don't `ungroup()` after summarizing with multiple grouping variables, you may get a warning telling you the data are still partially grouped. Let's group by `year` and `continent`.


```r
gdp_bycontinents_byyear <- gapminder %>%
group_by(continent, year) %>%
summarize(mean_gdpPercap = mean(gdpPercap))
summarize(mean_gdpPercap = mean(gdpPercap)) %>%
ungroup()
```

```output
Expand All @@ -410,7 +411,8 @@ gdp_pop_bycontinents_byyear <- gapminder %>%
summarize(mean_gdpPercap = mean(gdpPercap),
sd_gdpPercap = sd(gdpPercap),
mean_pop = mean(pop),
sd_pop = sd(pop))
sd_pop = sd(pop)) %>%
ungroup()
```

```output
Expand Down Expand Up @@ -503,7 +505,8 @@ gdp_pop_bycontinents_byyear <- gapminder %>%
mean_pop = mean(pop),
sd_pop = sd(pop),
mean_gdp_billion = mean(gdp_billion),
sd_gdp_billion = sd(gdp_billion))
sd_gdp_billion = sd(gdp_billion)) %>%
ungroup()
```

```output
Expand All @@ -530,7 +533,8 @@ gdp_pop_bycontinents_byyear_above25 <- gapminder %>%
mean_pop = mean(pop),
sd_pop = sd(pop),
mean_gdp_billion = mean(gdp_billion),
sd_gdp_billion = sd(gdp_billion))
sd_gdp_billion = sd(gdp_billion)) %>%
ungroup()
```

```output
Expand All @@ -545,7 +549,8 @@ gdp_future_bycontinents_byyear_high_lifeExp <- gapminder %>%
mutate(gdp_futureExpectation = ifelse(lifeExp > 40, gdpPercap * 1.5, gdpPercap)) %>%
group_by(continent, year) %>%
summarize(mean_gdpPercap = mean(gdpPercap),
mean_gdpPercap_expected = mean(gdp_futureExpectation))
mean_gdpPercap_expected = mean(gdp_futureExpectation)) %>%
ungroup()
```

```output
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95 changes: 0 additions & 95 deletions config.yaml
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50 changes: 25 additions & 25 deletions md5sum.txt
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@@ -1,26 +1,26 @@
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