Bringing in Liberia Indicators data and updating to include Liberia in pipeline #18
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This file is not necessary. Use and if needed modify https://github.com/dime-worldbank/mega-indicators/blob/main/population/global_data_lab_subnational_population.r
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That file only brings in the data to MEGA, it doesn't actually retrieve country specific data
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There is a new file called read_subnational_population_gdl That implements functions to read from the table and write data
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That file only brings in the data to MEGA, it doesn't actually retrieve country specific data
Is that so? What is this code doing https://github.com/dime-worldbank/mega-indicators/blob/main/population/global_data_lab_subnational_population.r#L62 Why is there Albania subnational population data in table prd_mega.indicator.global_data_lab_subnational_population?
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This brings in all subnational data available in GDL. There is Albania subnational data there because it is in GDL. Note that the current code uses interpolation. Albania only has data for 2005, 2009, and 2017
| ddf['population'] = ddf.population.map(lambda x: x*1_000_000) | ||
| ddf['adm1_name'] = ddf['adm1_name'].str.lower() | ||
| ddf = ddf[ddf.adm1_name!='total'] | ||
| ddf['adm1_name'] = ddf['adm1_name'].str.strip().str.title() |
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@elysenko have you verified that after this transformation the adm1_names are matching those in BOOST?
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Boost has some rows that are blank or marked dfp which looks like an environmental tag that I can't trace to a specific region. However, the rows tied to one of the actual 15 admin1 levels in Liberia match the incoming data
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