77 lines
2.0 KiB
Python
77 lines
2.0 KiB
Python
from iso3166 import countries as co
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from pandas import DataFrame, concat, read_csv
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from csv import QUOTE_NONNUMERIC
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from database.constants import ADMIN_PW
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def country_conversion(political_unit) -> str:
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if political_unit == "99":
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return "99"
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codes = co.get(political_unit)
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return codes.name
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def select_columns() -> DataFrame:
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min_year = 2010
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fields = [
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"POLITICAL_UNIT",
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"NAME",
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"WGMS_ID",
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"YEAR",
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"MEDIAN_ELEVATION",
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"AREA",
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"LENGTH",
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]
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iter_csv = read_csv(
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"../data/WGMS-FoG-2019-12-B-STATE.csv",
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skipinitialspace=True,
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usecols=fields,
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iterator=True,
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chunksize=100,
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converters={"POLITICAL_UNIT": country_conversion},
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)
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data = concat([chunk[chunk["YEAR"] > min_year] for chunk in iter_csv])
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return data
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def rename_fields(df_list):
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new_df_list = {}
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new_fields = {
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"POLITICAL_UNIT": "country",
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"NAME": "name",
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"WGMS_ID": "uid",
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"YEAR": "year",
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"MEDIAN_ELEVATION": "elevation",
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"AREA": "surface",
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"LENGTH": "length",
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}
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for key, value in df_list.items():
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new_df_list[key] = value.rename(columns=new_fields)
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return new_df_list
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def create_databases(df):
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user = {"uid": [7843], "username": ["admin"], "password": [ADMIN_PW]}
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files = {
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"glacier": "../data/glacier.csv",
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"annual_data": "../data/annual_data.csv",
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"user": "../data/user.csv",
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}
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dataframes = {
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"glacier": df[["POLITICAL_UNIT", "NAME", "WGMS_ID"]].drop_duplicates(),
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"annual_data": df[["WGMS_ID", "YEAR", "AREA", "MEDIAN_ELEVATION", "LENGTH"]],
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"user": DataFrame(user),
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}
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renamed_dfs = rename_fields(dataframes)
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for key, val in renamed_dfs.items():
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val.to_csv(files[key], index=False, quoting=QUOTE_NONNUMERIC)
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def main():
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df = select_columns()
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create_databases(df)
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if __name__ == "__main__":
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main()
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