# outputs that use both base year and future year values
for year in analysis_years:
df_year = get_multiyear_data(project_fc, project_type, outdf_base,
year)
# if it's base year, then append values to bottom of outdf_base,
# if it's future year, then left-join the values to the outdf.
# table has metrics as rows; years as columns (and will also append
if year == min(analysis_years):
out_df = outdf_base.rename(columns={0: 'projval_{}'.format(year)})
df_year = df_year.rename(columns={0: 'projval_{}'.format(year)})
out_df = out_df.append(df_year)
else:
df_year = df_year.rename(columns={0: 'projval_{}'.format(year)})
out_df = out_df.join(df_year)
out_df = utils.join_xl_import_template(template_xl,
params.xlsx_import_sheet, out_df)
# get community type and regional level data
df_aggvals = pd.read_csv(params.aggvals_csv, index_col='Unnamed: 0')
col_aggvals_year = 'year'
region_headname = 'REGION'
cols_ctype_reg = [project_ctype, region_headname]
aggval_headers = {
col: 'CommunityType'
for col in df_aggvals.columns if col != region_headname
}
for year in analysis_years:
df_agg_yr = df_aggvals[df_aggvals[col_aggvals_year] ==
year] # filter to specific year
df_agg_yr = df_agg_yr[
'travel_purpose', 'origin_blockgroup_id', 'destination_blockgroup_id',
'trip_primary_mode', 'trip_start_time'
] #fields to use from Replica trip data CSVs
df_tshed_data, link_trip_summary = make_trip_shed_report(
tripdata_files, trip_data_fields, csvcol_valfield, val_aggn_type,
csvcol_bgid, fc_bg_in, fc_tripshed_out, fc_poly_id_field, years,
[csvcol_mode, csvcol_purpose], run_full_shed_report)
if run_full_shed_report:
df_trip_modes = link_trip_summary.loc[link_trip_summary['category'] ==
csvcol_mode]
df_trip_purposes = link_trip_summary.loc[link_trip_summary['category']
== csvcol_purpose]
df_tshed_data_out = utils.join_xl_import_template(
xlsx_template, ws_tshed_data, df_tshed_data)
df_trip_modes_out = utils.join_xl_import_template(
xlsx_template, ws_trip_modes, df_trip_modes)
df_trip_purposes_out = utils.join_xl_import_template(
xlsx_template, ws_trip_purposes, df_trip_purposes)
# output_csv = os.path.join(xlsx_out_dir, 'PPA_TripShed_{}_{}.csv'.format(
# proj_name, timesufx)
# df_tshed_data.to_csv(output_csv) # probably not necessary to output to CSV if outputting to Excel.
utils.overwrite_df_to_xlsx(df_tshed_data_out,
xlsx_template,
xlsx_out,
ws_tshed_data,
start_row=0,
start_col=0)
