feat(A16): add pipeline #47
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I had trouble running the pipeline due to API limits.
Otherwise it looks fine to me.
Just my two comments about what I would leave in. But we can also merge and discuss this with @nooralahzadeh . Therefore I approve the PR.
scripts/A16.R
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| janitor::clean_names() %>% | ||
| dplyr::filter( | ||
| sex == "Sex - total" & | ||
| citizenship_category == "Citizenship (category) - total" |
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I think I would leave the citizenship category in, since it relates to the other columns, where as gender does not:
For example the out migration and in migration: it is interesting whether Swiss citizens left the country or came into it from another country or whether it was other nationalities that left or came.
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True, I will add it! thanks
scripts/A16.R
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| -change_of_population_type, | ||
| -population_on_31_december, | ||
| -natural_change, | ||
| -acquisition_of_swiss_citizenship |
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I would leave in acquisition_of_swiss_citizenship since this is interesting. Redundance is not an issue here, where you want to translate natural language question into sql. What ever term might resemble a natural language question should stay. Also you need to consider that the data in these tables is never complete.
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This is interesting, but the way this is coded is not intuitive.
I'll make sure to write queries that explicitely use it.
year canton acquisition_of_swiss_citi…¹ citizenship_category
<chr> <chr> <dbl> <chr>
1 1971 Aargau 0 Citizenship (catego…
2 1971 Aargau 746 Switzerland
3 1971 Aargau -746 Foreign country
4 1971 Appenzell Ausserrhoden 0 Citizenship (catego…
5 1971 Appenzell Ausserrhoden 73 Switzerland
6 1971 Appenzell Ausserrhoden -73 Foreign country
7 1971 Appenzell Innerrhoden 0 Citizenship (catego…
8 1971 Appenzell Innerrhoden 24 Switzerland
9 1971 Appenzell Innerrhoden -24 Foreign country
…p_category. Use assignment pipe
Adds the pipeline for dataset A16 (#39): Demographic balance by canton
Some columns were dropped as they were uninformative:
Observations prior to 1981 were discarded as they only contained a subset of variables, with others set to 0.