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Merged
amandaha8 merged 4 commits into from
Jul 3, 2026
Merged

IIJA #2113

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0f62ab6
figuring out why rows dont match
amandaha8 Jun 29, 2026
5ea433e
figured out why unable to condense project down to 1 row
amandaha8 Jun 30, 2026
03c1720
pulled list of projects with unique values for chris
amandaha8 Jun 30, 2026
f048b74
reran script
amandaha8 Jul 1, 2026
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27 changes: 10 additions & 17 deletions dla/iija/_script_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -71,26 +71,19 @@ def add_county_abbrev(df, county_name_col):
### read county data in from the shared_data catalog
catalog = intake.open_catalog("../../_shared_utils/shared_utils/shared_data_catalog.yml")

# counties = to_snakecase((catalog.ca_counties.read()))[["name", "cnty_fips"]]
# counties.cnty_fips = counties.cnty_fips.astype(int)

counties = to_snakecase((catalog.ca_counties.read()))[["name"]]
counties = to_snakecase((catalog.ca_counties.read()))
county_codes = to_snakecase((pd.read_excel(f"{GCS_FILE_PATH}/CountyNameToCodeLookUp.xlsx")))

### create dict to map
county_mapping = pd.merge(county_codes, counties, left_on ="county_name", right_on = "name",how = "inner")
county_mapping = county_mapping.drop(columns = ["name"])
county_mapping = pd.merge(county_codes, counties, on = ["county_name"], how = "inner")
county_mapping = county_mapping.rename(columns = {"rca_county_code":"county_name_abbrev"})

# There are 2 county_codes now.
df = df.rename(columns = {"county_code":'og_county_code'})
df = pd.merge(df, county_mapping, on = ["county_name"], how = "left")

# df = df.drop(columns = ["cnty_fips"])

### map values to the df
#df[f"{county_name_col}_abbrev"] = df[county_name_col].map(county_mapping)

#df[f"{county_name_col}_abbrev"] = df[f"{county_name_col}_abbrev"].fillna('NA')


df = df.drop(columns = ["county_code"])
df = df.rename(columns = {"og_county_code":'county_code'})
return df


Expand Down Expand Up @@ -583,7 +576,7 @@ def get_new_desc_title(df):

#remove project method column values so that the title function wont double count
proj_unique_cat.loc[proj_unique_cat['project_type'] == 'Project', 'project_method'] = ""
proj_unique_cat['project_type'] = proj_unique_cat['project_type'].replace('Project', np.NaN)
proj_unique_cat['project_type'] = proj_unique_cat['project_type'].replace('Project', np.nan)

#update for the projects not in the first round of descriptions
proj_unique_cat_title = add_description_4_no_match(proj_unique_cat, 'improvement_type_description')
Expand Down Expand Up @@ -686,10 +679,10 @@ def get_clean_data(df, full_or_agg = ''):

return df

def run_script_original(file_name, recipient_column, df_agg_level):
def run_script_original(file_name:str, sheet:str, recipient_column:str, df_agg_level:str):

### Read in data
proj_list = to_snakecase(pd.read_excel(f"{GCS_FILE_PATH}/{file_name}"))
proj_list = to_snakecase(pd.read_excel(f"{GCS_FILE_PATH}/{file_name}", sheet_name = sheet))
proj_list = proj_list.rename(columns = {"summary_recipient": "summary_recipient_defined_text_field_1_value"})

### run function to get new program codes
Expand Down
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