fixed lint

scripts/oecd/regional_demography/deaths/preprocess_csv.py

@@ -25,7 +25,6 @@
 _MODULE_DIR = os.path.dirname(os.path.abspath(__file__))
 flags.DEFINE_string('mode', '', 'Options: download or process')
 
-
 logging.basicConfig(level=logging.INFO)
 
 _MODULE_DIR = os.path.dirname(os.path.abspath(__file__))
@@ -149,7 +148,7 @@ def process_data(df, output_file_path):
     for col in columns_to_drop:
         if col in df_cleaned.columns:
             df_cleaned.drop(col, axis=1, inplace=True)
-    logging.info("Writing output to %s",output_file_path)
+    logging.info("Writing output to %s", output_file_path)
     df_cleaned.to_csv(output_file_path, index=False, quoting=csv.QUOTE_NONE)
 
     return df_cleaned
@@ -184,13 +183,17 @@ def main(_):
     filename = os.path.join(_MODULE_DIR, "REGION_DEMOGR_death_5Y.csv")
 
     if mode == "" or mode == "download":
-        download_data_to_file_and_df(url, filename, is_download_required=True,csv_filepath=None)
+        download_data_to_file_and_df(url,
+                                     filename,
+                                     is_download_required=True,
+                                     csv_filepath=None)
     if mode == "" or mode == "process":
         df = pd.read_csv(filename)
         output_file_path = os.path.join(_MODULE_DIR, "OECD_deaths_cleaned.csv")
         df_cleaned = process_data(df, output_file_path)
         filepath = os.path.join(_MODULE_DIR, "OECD_deaths.tmcf")
         generate_tmcf(df_cleaned, filepath)
-
+
+
 if __name__ == "__main__":
     app.run(main)

scripts/oecd/regional_demography/life_expectancy/preprocess_csv.py

@@ -76,7 +76,7 @@ def process_data(df, output_file_path):
 
     df_cleaned.rename(columns=VAR_to_statsvars, inplace=True)
     df_cleaned.drop(columns=["REG_ID"], inplace=True)
-    logging.info("Writing output to %s",output_file_path)
+    logging.info("Writing output to %s", output_file_path)
     df_cleaned.to_csv(output_file_path, index=False, quoting=csv.QUOTE_NONE)
     return df_cleaned
 
@@ -121,20 +121,25 @@ def generate_tmcf(df_cleaned, filepath):
                         'stat_var': stat_vars[i]
                     }))
 
+
 def main(_):
     mode = _FLAGS.mode
     url = "https://sdmx.oecd.org/public/rest/data/OECD.CFE.EDS,DSD_REG_DEMO@DF_LIFE_EXP,2.0/all?dimensionAtObservation=AllDimensions&format=csvfilewithlabels"
     filename = os.path.join(_MODULE_DIR, "REGION_DEMOGR_life_expectancy.csv")
 
     if mode == "" or mode == "download":
-        download_data_to_file_and_df(url, filename,  is_download_required=True,csv_filepath=None)
+        download_data_to_file_and_df(url,
+                                     filename,
+                                     is_download_required=True,
+                                     csv_filepath=None)
     if mode == "" or mode == "process":
         df = pd.read_csv(filename)
         output_file_path = os.path.join(_MODULE_DIR,
-                                    "OECD_life_expectancy_cleaned.csv")
+                                        "OECD_life_expectancy_cleaned.csv")
         df_cleaned = process_data(df, output_file_path)
         filepath = os.path.join(_MODULE_DIR, "OECD_life_expectancy.tmcf")
         generate_tmcf(df_cleaned, filepath)
 
+
 if __name__ == "__main__":
     app.run(main)

scripts/oecd/regional_demography/pop_density/preprocess_csv.py

@@ -72,7 +72,7 @@ def process_data(df, output_file_path):
     }
 
     df_cleaned.rename(columns=VAR_to_statsvars, inplace=True)
-    logging.info("Writing output to %s",output_file_path)
+    logging.info("Writing output to %s", output_file_path)
     df_cleaned.to_csv(output_file_path, index=False, quoting=csv.QUOTE_NONE)
 
 
@@ -82,11 +82,16 @@ def main(_):
     filename = os.path.join(_MODULE_DIR, "REGION_DEMOGR_pop_density.csv")
 
     if mode == "" or mode == "download":
-        download_data_to_file_and_df(url, filename, is_download_required=True,csv_filepath=None)
+        download_data_to_file_and_df(url,
+                                     filename,
+                                     is_download_required=True,
+                                     csv_filepath=None)
     if mode == "" or mode == "process":
         df = pd.read_csv(filename)
-        output_file_path = os.path.join(_MODULE_DIR, "OECD_pop_density_cleaned.csv")
+        output_file_path = os.path.join(_MODULE_DIR,
+                                        "OECD_pop_density_cleaned.csv")
         process_data(df, output_file_path)
 
+
 if __name__ == "__main__":
     app.run(main)

scripts/oecd/regional_demography/population/preprocess_csv.py

@@ -138,7 +138,7 @@ def process_data(df, output_file_path):
         if col not in csv_columns:
             drop_cols.append(col)
     df_cleaned.drop(columns=drop_cols, axis=0, inplace=True)
-    logging.info("Writing output to %s",output_file_path)
+    logging.info("Writing output to %s", output_file_path)
     df_cleaned.to_csv(output_file_path, index=False, quoting=csv.QUOTE_NONE)
     return df_cleaned
 
@@ -172,13 +172,17 @@ def main(_):
     filename = os.path.join(_MODULE_DIR, "REGION_DEMOGR_population.csv")
 
     if mode == "" or mode == "download":
-        download_data_to_file_and_df(url, filename, is_download_required=True,csv_filepath=None)
+        download_data_to_file_and_df(url,
+                                     filename,
+                                     is_download_required=True,
+                                     csv_filepath=None)
     if mode == "" or mode == "process":
         df = pd.read_csv(filename)
         csv_filepath = os.path.join(_MODULE_DIR, "OECD_population_cleaned.csv")
         df_cleaned = process_data(df, csv_filepath)
         tmcf_filepath = os.path.join(_MODULE_DIR, "OECD_population.tmcf")
         generate_tmcf(df_cleaned, tmcf_filepath)
 
-if __name__=="__main__":
+
+if __name__ == "__main__":
     app.run(main)