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| ==== Getting the article and population data ==== | | ==== Getting the article and population data ==== |
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| The first step is getting the data, which lives in several different places. The Wikipedia politicians by country dataset can be found [https://figshare.com/articles/Untitled_Item/5513449 on Figshare]. Read through the documentation for this repository, then download and unzip it to extract the data file, which is called <tt>page_data.csv</tt>. | | The first step is getting the data, which lives in several different places. The wikipedia politicians by country dataset can be found [https://figshare.com/articles/Untitled_Item/5513449 on Figshare]. Read through the documentation for this repository, then download and unzip it. |
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| The population data is available in CSV format in the [https://canvas.uw.edu/courses/1319253/files/ Files section of Canvas] under "A2: bias in data". This dataset is drawn from the [https://www.prb.org/international/indicator/population/table world population datasheet] published by the Population Reference Bureau. | | The population data is available in CSV format on Canvas. This dataset is drawn from the [https://www.prb.org/international/indicator/population/table world population datasheet] published by the Population Reference Bureau. |
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| ==== Cleaning the data ====
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| Both <tt>page_data.csv</tt> and <tt>WPDS_2018_data.csv</tt> contain some rows that you will need to filter out and/or ignore when you combine the datasets in the next step. In the case of <tt>page_data.csv</tt>, the dataset contains some page names that start with the string "Template:". These pages are ''not'' Wikipedia articles, and should not be included in your analysis.
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| Similarly, <tt>WPDS_2018_data</tt> contains some rows that provide cumulative regional population counts, rather than country-level counts. These rows are distinguished by having ALL CAPS values in the 'geography' field (e.g. AFRICA, OCEANIA). These rows won't match the country values in <tt>page_data</tt>, but you will want to retain them (either in the original file, or a separate file) so that you can report coverage and quality by region in the analysis section.
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| ==== Getting article quality predictions ==== | | ==== Getting article quality predictions ==== |