added funding type code

cal-itp · Jan 31, 2025 · c18b87a · c18b87a
1 parent 4183c25
commit c18b87a
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Showing 4 changed files with 639 additions and 3,797 deletions.
diff --git a/dla/iija/_data_utils.py b/dla/iija/_data_utils.py
@@ -195,14 +195,24 @@ def add_new_codes(df):
 
     ## adding updated program codes 1/30/25
     new_codes = update_program_code_list_2025()
-    code_map = dict(new_codes[['iija_program_code', 'program_name']].values)
-
-    df['program_code_description'] = df.program_code.map(code_map)
+    iija_code_map = dict(new_codes[['iija_program_code', 'program_name']].values)
+    df['program_code_description'] = df.program_code.map(iija_code_map)
+
+    # Add funding_type_code
+    funding_type_code_df = new_codes[[
+        'iija_program_code', 
+        'funding_type_code']].drop_duplicates()
+
+    df = pd.merge(df, funding_type_code_df, 
+                  left_on = "program_code",
+                  right_on = "iija_program_code",
+                  how = "left")
+    # Turn summary_recipient_defined_text_field_1_value to a string
     df['summary_recipient_defined_text_field_1_value'] = df['summary_recipient_defined_text_field_1_value'].astype(str)
 
     # Amanda: January 2025, notified this should be called emergency supplement funding
-    #df.loc[df.program_code =='ER01', 'program_code_description'] = 'Emergency Relieve Funding'
-    #df.loc[df.program_code =='ER03', 'program_code_description'] = 'Emergency Relieve Funding'
+    df.loc[df.program_code =='ER01', 'program_code_description'] = 'Emergency Supplement Funding'
+    df.loc[df.program_code =='ER03', 'program_code_description'] = 'Emergency Supplement Funding'
 
     return df
 

diff --git a/dla/iija/_script_utils.py b/dla/iija/_script_utils.py
@@ -258,9 +258,11 @@ def condense_df(df):
     # make sure columns are in string format
     df[['county_code', 'improvement_type',
      'implementing_agency_locode', 'district',
-     'program_code_description', 'recipient_project_number']] = df[['county_code', 'improvement_type',
+     'program_code_description', 'recipient_project_number',
+       "funding_type_code"]] = df[['county_code', 'improvement_type',
                                                                      'implementing_agency_locode', 'district',
-                                                                     'program_code_description', 'recipient_project_number']].astype(str)
+                                                                     'program_code_description', 'recipient_project_number',
+                                  "funding_type_code"]].astype(str)
     # copy county column over to use for project title name easier
     df['county_name_title'] = df['county_name'] 
     # copy program code column over to use for project description column easier
@@ -272,7 +274,7 @@ def condense_df(df):
            .groupby(['fmis_transaction_date','project_number', 'implementing_agency', 'summary_recipient_defined_text_field_1_value'
                     # , 'program_code', 'program_code_description'
                     ])
-           .agg({
+           .agg({'funding_type_code':lambda x:'|'.join(x.unique()),
                  'program_code':lambda x:'|'.join(x.unique()), # get unique values to concatenate                ##hashing this out to group by instead
                  'program_code_description':lambda x:'|'.join(x.unique()), # get unique values to concatenate    ##hashing this out to group by instead
                  'recipient_project_number':lambda x:'|'.join(x.unique()), #'first',