How to use rename_columns method in pandera

Best Python code snippet using pandera_python

Chassis_Dashboard_Automated.py

Source:Chassis_Dashboard_Automated.py Github

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...131132all_chassis_total_wty,all_chassis_cpc_cpu, all_chassis_top_customers,all_chassis_top_dealers, all_chassis_seag_info = get_final_files(st_date, ed_date, data_for_active_units, chassis_claims, "All_chassis")133 134all_chassis_top_dealers.reset_index(inplace = True)135all_chassis_total_wty = rename_columns('total_wty', all_chassis_total_wty)136all_chassis_cpc_cpu = rename_columns('cpc_cpu', all_chassis_cpc_cpu)137all_chassis_top_customers = rename_columns('top_customers', all_chassis_top_customers)138all_chassis_top_dealers = rename_columns('top_dealers', all_chassis_top_dealers)139140all_chassis_cpc_cpu['CPC'] = all_chassis_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Total_Claims_cpc_cpu'] if x['Total_Claims_cpc_cpu'] > 0 else 0, axis =1)141all_chassis_cpc_cpu['CPU'] = all_chassis_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Active_Units'] if x['Active_Units'] >0 else 0, axis =1)142all_chassis = pd.concat([all_chassis_total_wty, all_chassis_cpc_cpu, all_chassis_top_customers,all_chassis_top_dealers,all_chassis_seag_info], axis =1)143all_chassis.to_csv(r'Z:/2000_Cost Management/2500_General Information/2502_Processes & Documentation/Tableau Documentation/All_dashboards_combined/All_chassis.csv', index = False)144 145p4_chassis_total_wty,p4_chassis_cpc_cpu, p4_chassis_top_customers,p4_chassis_top_dealers, p4_chassis_seag_info = get_final_files(st_date, ed_date, p4_contracts, p4_claims, "P4_chassis")146 147p4_chassis_top_dealers.reset_index(inplace = True)148p4_chassis_total_wty = rename_columns('total_wty', p4_chassis_total_wty)149p4_chassis_cpc_cpu = rename_columns('cpc_cpu', p4_chassis_cpc_cpu)150p4_chassis_top_customers = rename_columns('top_customers', p4_chassis_top_customers)151p4_chassis_top_dealers = rename_columns('top_dealers', p4_chassis_top_dealers)152153p4_chassis_cpc_cpu['CPC'] = p4_chassis_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Total_Claims_cpc_cpu'] if x['Total_Claims_cpc_cpu'] > 0 else 0, axis =1)154p4_chassis_cpc_cpu['CPU'] = p4_chassis_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Active_Units'] if x['Active_Units'] >0 else 0, axis =1)155p4_chassis = pd.concat([p4_chassis_total_wty, p4_chassis_cpc_cpu, p4_chassis_top_customers,p4_chassis_top_dealers,p4_chassis_seag_info], axis =1)156p4_chassis.to_csv(r'Z:/2000_Cost Management/2500_General Information/2502_Processes & Documentation/Tableau Documentation/All_dashboards_combined/p4_chassis.csv', index = False)157158159seal_oil_total_wty,seal_oil_cpc_cpu, seal_oil_top_customers,seal_oil_top_dealers, seal_oil_seag_info = get_final_files(st_date, ed_date, seal_oil_contracts, seal_oil_claims, "seal_oil")160seal_oil_top_dealers.reset_index(inplace = True)161seal_oil_total_wty = rename_columns('total_wty', seal_oil_total_wty)162seal_oil_cpc_cpu = rename_columns('cpc_cpu', seal_oil_cpc_cpu)163seal_oil_top_customers = rename_columns('top_customers', seal_oil_top_customers)164seal_oil_top_dealers = rename_columns('top_dealers', seal_oil_top_dealers)165166seal_oil_paid_amt_bld_yr, seal_oil_total_claims_fail_miles_isy ,seal_oil_paid_amt_mis = get_secondary_data(seal_oil_claims)167seal_oil_paid_amt_bld_yr = rename_columns('bld_yr', seal_oil_paid_amt_bld_yr)168seal_oil_total_claims_fail_miles_isy = rename_columns('fail_miles', seal_oil_total_claims_fail_miles_isy)169seal_oil_paid_amt_mis = rename_columns('mis', seal_oil_paid_amt_mis)170171seal_oil_cpc_cpu['CPC'] = seal_oil_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Total_Claims_cpc_cpu'] if x['Total_Claims_cpc_cpu'] > 0 else 0, axis =1)172seal_oil_cpc_cpu['CPU'] = seal_oil_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Active_Units'] if x['Active_Units'] >0 else 0, axis =1)173seal_oil = pd.concat([seal_oil_total_wty, seal_oil_cpc_cpu, seal_oil_top_customers,seal_oil_top_dealers,seal_oil_seag_info, seal_oil_paid_amt_bld_yr,seal_oil_total_claims_fail_miles_isy,seal_oil_paid_amt_mis], axis =1)174seal_oil.to_csv(r'Z:/2000_Cost Management/2500_General Information/2502_Processes & Documentation/Tableau Documentation/All_dashboards_combined/seal_oil.csv', index = False)175176177mirror_heated_convex_total_wty,mirror_heated_convex_cpc_cpu, mirror_heated_convex_top_customers,mirror_heated_convex_top_dealers, mirror_heated_convex_seag_info = get_final_files(st_date, ed_date, mirror_heated_convex_contracts, mirror_heated_convex_claims, "mirror_heated_convex")178mirror_heated_convex_top_dealers.reset_index(inplace = True)179mirror_heated_convex_total_wty = rename_columns('total_wty', mirror_heated_convex_total_wty)180mirror_heated_convex_cpc_cpu = rename_columns('cpc_cpu', mirror_heated_convex_cpc_cpu)181mirror_heated_convex_top_customers = rename_columns('top_customers', mirror_heated_convex_top_customers)182mirror_heated_convex_top_dealers = rename_columns('top_dealers', mirror_heated_convex_top_dealers)183184mirror_heated_convex_paid_amt_bld_yr, mirror_heated_convex_total_claims_fail_miles_isy ,mirror_heated_convex_paid_amt_mis = get_secondary_data(mirror_heated_convex_claims)185mirror_heated_convex_paid_amt_bld_yr = rename_columns('bld_yr', mirror_heated_convex_paid_amt_bld_yr)186mirror_heated_convex_total_claims_fail_miles_isy = rename_columns('fail_miles', mirror_heated_convex_total_claims_fail_miles_isy)187mirror_heated_convex_paid_amt_mis = rename_columns('mis', mirror_heated_convex_paid_amt_mis)188189mirror_heated_convex_cpc_cpu['CPC'] = mirror_heated_convex_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Total_Claims_cpc_cpu'] if x['Total_Claims_cpc_cpu'] > 0 else 0, axis =1)190mirror_heated_convex_cpc_cpu['CPU'] = mirror_heated_convex_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Active_Units'] if x['Active_Units'] >0 else 0, axis =1)191mirror_heated_convex = pd.concat([mirror_heated_convex_total_wty, mirror_heated_convex_cpc_cpu, mirror_heated_convex_top_customers,mirror_heated_convex_top_dealers,mirror_heated_convex_seag_info, mirror_heated_convex_paid_amt_bld_yr,mirror_heated_convex_total_claims_fail_miles_isy,mirror_heated_convex_paid_amt_mis], axis =1)192mirror_heated_convex.to_csv(r'Z:/2000_Cost Management/2500_General Information/2502_Processes & Documentation/Tableau Documentation/All_dashboards_combined/mirror_heated_convex.csv', index = False)193194195core_tank_radiator_total_wty,core_tank_radiator_cpc_cpu, core_tank_radiator_top_customers,core_tank_radiator_top_dealers, core_tank_radiator_seag_info = get_final_files(st_date, ed_date, core_tank_radiator_contracts, core_tank_radiator_claims, "core_tank_radiator")196core_tank_radiator_top_dealers.reset_index(inplace = True)197core_tank_radiator_total_wty = rename_columns('total_wty', core_tank_radiator_total_wty)198core_tank_radiator_cpc_cpu = rename_columns('cpc_cpu', core_tank_radiator_cpc_cpu)199core_tank_radiator_top_customers = rename_columns('top_customers', core_tank_radiator_top_customers)200core_tank_radiator_top_dealers = rename_columns('top_dealers', core_tank_radiator_top_dealers)201202core_tank_radiator_paid_amt_bld_yr, core_tank_radiator_total_claims_fail_miles_isy ,core_tank_radiator_paid_amt_mis = get_secondary_data(core_tank_radiator_claims)203core_tank_radiator_paid_amt_bld_yr = rename_columns('bld_yr', core_tank_radiator_paid_amt_bld_yr)204core_tank_radiator_total_claims_fail_miles_isy = rename_columns('fail_miles', core_tank_radiator_total_claims_fail_miles_isy)205core_tank_radiator_paid_amt_mis = rename_columns('mis', core_tank_radiator_paid_amt_mis)206207core_tank_radiator_cpc_cpu['CPC'] = core_tank_radiator_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Total_Claims_cpc_cpu'] if x['Total_Claims_cpc_cpu'] > 0 else 0, axis =1)208core_tank_radiator_cpc_cpu['CPU'] = core_tank_radiator_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Active_Units'] if x['Active_Units'] >0 else 0, axis =1)209core_tank_radiator = pd.concat([core_tank_radiator_total_wty, core_tank_radiator_cpc_cpu, core_tank_radiator_top_customers,core_tank_radiator_top_dealers,core_tank_radiator_seag_info, core_tank_radiator_paid_amt_bld_yr,core_tank_radiator_total_claims_fail_miles_isy,core_tank_radiator_paid_amt_mis], axis =1)210core_tank_radiator.to_csv(r'Z:/2000_Cost Management/2500_General Information/2502_Processes & Documentation/Tableau Documentation/All_dashboards_combined/core_tank_radiator.csv', index = False)211212213wiring_harness_total_wty,wiring_harness_cpc_cpu, wiring_harness_top_customers,wiring_harness_top_dealers, wiring_harness_seag_info = get_final_files(st_date, ed_date, wiring_harness_contracts, wiring_harness_claims, "wiring_harness")214wiring_harness_top_dealers.reset_index(inplace = True)215wiring_harness_total_wty = rename_columns('total_wty', wiring_harness_total_wty)216wiring_harness_cpc_cpu = rename_columns('cpc_cpu', wiring_harness_cpc_cpu)217wiring_harness_top_customers = rename_columns('top_customers', wiring_harness_top_customers)218wiring_harness_top_dealers = rename_columns('top_dealers', wiring_harness_top_dealers)219220wiring_harness_paid_amt_bld_yr, wiring_harness_total_claims_fail_miles_isy ,wiring_harness_paid_amt_mis = get_secondary_data(wiring_harness_claims)221wiring_harness_paid_amt_bld_yr = rename_columns('bld_yr', wiring_harness_paid_amt_bld_yr)222wiring_harness_total_claims_fail_miles_isy = rename_columns('fail_miles', wiring_harness_total_claims_fail_miles_isy)223wiring_harness_paid_amt_mis = rename_columns('mis', wiring_harness_paid_amt_mis)224225wiring_harness_cpc_cpu['CPC'] = wiring_harness_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Total_Claims_cpc_cpu'] if x['Total_Claims_cpc_cpu'] > 0 else 0, axis =1)226wiring_harness_cpc_cpu['CPU'] = wiring_harness_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Active_Units'] if x['Active_Units'] >0 else 0, axis =1)227wiring_harness = pd.concat([wiring_harness_total_wty, wiring_harness_cpc_cpu, wiring_harness_top_customers,wiring_harness_top_dealers,wiring_harness_seag_info, wiring_harness_paid_amt_bld_yr,wiring_harness_total_claims_fail_miles_isy,wiring_harness_paid_amt_mis], axis =1)228wiring_harness.to_csv(r'Z:/2000_Cost Management/2500_General Information/2502_Processes & Documentation/Tableau Documentation/All_dashboards_combined/wiring_harness.csv', index = False)229230 231heater_aux_total_wty,heater_aux_cpc_cpu, heater_aux_top_customers,heater_aux_top_dealers, heater_aux_seag_info = get_final_files(st_date, ed_date, heater_aux_contracts, heater_aux_claims, "heater_aux")232heater_aux_top_dealers.reset_index(inplace = True)233heater_aux_total_wty = rename_columns('total_wty', heater_aux_total_wty)234heater_aux_cpc_cpu = rename_columns('cpc_cpu', heater_aux_cpc_cpu)235heater_aux_top_customers = rename_columns('top_customers', heater_aux_top_customers)236heater_aux_top_dealers = rename_columns('top_dealers', heater_aux_top_dealers)237238heater_aux_paid_amt_bld_yr, heater_aux_total_claims_fail_miles_isy ,heater_aux_paid_amt_mis = get_secondary_data(heater_aux_claims)239heater_aux_paid_amt_bld_yr = rename_columns('bld_yr', heater_aux_paid_amt_bld_yr)240heater_aux_total_claims_fail_miles_isy = rename_columns('fail_miles', heater_aux_total_claims_fail_miles_isy)241heater_aux_paid_amt_mis = rename_columns('mis', heater_aux_paid_amt_mis)242243heater_aux_cpc_cpu['CPC'] = heater_aux_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Total_Claims_cpc_cpu'] if x['Total_Claims_cpc_cpu'] > 0 else 0, axis =1)244heater_aux_cpc_cpu['CPU'] = heater_aux_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Active_Units'] if x['Active_Units'] >0 else 0, axis =1)245heater_aux = pd.concat([heater_aux_total_wty, heater_aux_cpc_cpu, heater_aux_top_customers,heater_aux_top_dealers,heater_aux_seag_info, heater_aux_paid_amt_bld_yr,heater_aux_total_claims_fail_miles_isy,heater_aux_paid_amt_mis], axis =1)246heater_aux.to_csv(r'Z:/2000_Cost Management/2500_General Information/2502_Processes & Documentation/Tableau Documentation/All_dashboards_combined/heater_aux.csv', index = False)247248ac_compressor_total_wty,ac_compressor_cpc_cpu, ac_compressor_top_customers,ac_compressor_top_dealers, ac_compressor_seag_info = get_final_files(st_date, ed_date, ac_compressor_contracts, ac_compressor_claims, "ac_compressor")249ac_compressor_top_dealers.reset_index(inplace = True)250ac_compressor_total_wty = rename_columns('total_wty', ac_compressor_total_wty)251ac_compressor_cpc_cpu = rename_columns('cpc_cpu', ac_compressor_cpc_cpu)252ac_compressor_top_customers = rename_columns('top_customers', ac_compressor_top_customers)253ac_compressor_top_dealers = rename_columns('top_dealers', ac_compressor_top_dealers)254255ac_compressor_paid_amt_bld_yr, ac_compressor_total_claims_fail_miles_isy ,ac_compressor_paid_amt_mis = get_secondary_data(ac_compressor_claims)256ac_compressor_paid_amt_bld_yr = rename_columns('bld_yr', ac_compressor_paid_amt_bld_yr)257ac_compressor_total_claims_fail_miles_isy = rename_columns('fail_miles', ac_compressor_total_claims_fail_miles_isy)258ac_compressor_paid_amt_mis = rename_columns('mis', ac_compressor_paid_amt_mis)259260ac_compressor_cpc_cpu['CPC'] = ac_compressor_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Total_Claims_cpc_cpu'] if x['Total_Claims_cpc_cpu'] > 0 else 0, axis =1)261ac_compressor_cpc_cpu['CPU'] = ac_compressor_cpc_cpu.apply(lambda x: x['Total_Cost_cpc_cpu']/x['Active_Units'] if x['Active_Units'] >0 else 0, axis =1)262ac_compressor = pd.concat([ac_compressor_total_wty, ac_compressor_cpc_cpu, ac_compressor_top_customers,ac_compressor_top_dealers,ac_compressor_seag_info, ac_compressor_paid_amt_bld_yr,ac_compressor_total_claims_fail_miles_isy,ac_compressor_paid_amt_mis], axis =1) ...

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reader.py

Source:reader.py Github

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1from io import StringIO2import numpy as np3import pandas as pd4class TableDef:5 def __init__(self, table_id, end_table_tag, skip_rows=0, widths=None,6 df_drop_top_rows=None, df_drop_tail_rows=None, reset_header=False,7 rename_columns=None, convert_numerics=False, int_columns=None,8 index_col=None9 ):10 self.table_id = table_id11 self.end_table_tag = end_table_tag12 self.skip_rows = skip_rows13 self.widths = widths14 self.df_drop_top_rows = df_drop_top_rows15 self.df_drop_tail_rows = df_drop_tail_rows16 self.reset_header = reset_header17 self.rename_columns = rename_columns18 self.convert_numerics = convert_numerics19 self.int_columns = int_columns20 self.index_col = index_col21_table_parameters = {22 '1.02': TableDef('1.02', ' Adjustment of', skip_rows=3, df_drop_top_rows=1,23 df_drop_tail_rows=4, reset_header=False,24 rename_columns=None, convert_numerics=False, 25 int_columns=['BoardCount'],26 index_col=None),27 '2.04': TableDef('2.04', 'COUNT', skip_rows=10, df_drop_top_rows=1,28 df_drop_tail_rows=2, rename_columns={'Unnamed: 0': 'origin'},29 index_col = 'origin', convert_numerics=True,30 ),31 '2.05': TableDef('2.05',end_table_tag='-----------', skip_rows=5,32 df_drop_top_rows=1,df_drop_tail_rows=1,33 rename_columns={'Unnamed: 0': 'origin'}, index_col='origin',34 convert_numerics=True),35 '2.07': TableDef('2.07', end_table_tag='-----------', skip_rows=8, # 'df_drop_top_rows': 1,36 df_drop_tail_rows=1, reset_header=True, widths=[7, 11, 11, 11, 11],37 rename_columns={38 0: 'station_group',39 1: 'pre_calib_board',40 2: 'station_count',41 3: 'station_target',42 4: 'post_calib_board'43 },44 convert_numerics=True,int_columns='station_group', index_col='station_group'),45 '2.08': TableDef('2.08', end_table_tag='Number of unique', skip_rows=8, # 'df_drop_top_rows': 1,46 df_drop_tail_rows=1, reset_header=True, widths=[6, 22, 11, 11, 11, 10],47 rename_columns={48 0: 'route_group_num',49 1: 'route_group',50 2: 'pre_calib_board',51 3: 'route_count',52 4: 'route_target',53 5: 'post_calib_board'54 }, convert_numerics=True, #'int_columns': 'station_group',55 index_col='route_group_num'),56 '3.01': TableDef('3.01', end_table_tag='TOTAL', skip_rows=8,57 df_drop_top_rows=1, index_col='origin',58 rename_columns={'Unnamed: 0': 'origin'}),59 '3.02': TableDef('3.02', end_table_tag='TOTAL', skip_rows=8,60 df_drop_top_rows=1, index_col='origin',61 rename_columns={'Unnamed: 0': 'origin'}),62 '3.03': TableDef('3.03', end_table_tag='TOTAL', skip_rows=8,63 df_drop_top_rows=1, index_col='origin',64 rename_columns={'Unnamed: 0': 'origin'}),65 '4.01': TableDef('4.01', end_table_tag='Total', skip_rows=5,66 df_drop_top_rows=1,index_col='origin',67 rename_columns={'Idist': 'origin'}),68 69 '4.02': TableDef('4.02', end_table_tag='Total', skip_rows=5,70 df_drop_top_rows=1,index_col='origin',71 rename_columns={'Idist': 'origin'}),72 73 '4.04': TableDef('4.04', end_table_tag='Total', skip_rows=5,74 df_drop_top_rows=1,75 rename_columns={'Unnamed: 0': 'origin'}),76 '8.01': TableDef('8.01', end_table_tag='Total', skip_rows=5,77 df_drop_top_rows=1, index_col='origin',78 rename_columns={'Idist': 'origin'},79 convert_numerics=True80 ),81 # Stop Level Boardings82 '9.01': TableDef('9.01', end_table_tag='\x00', skip_rows=8,83 reset_header=True,84 rename_columns={85 0: 'stop_id', 1: 'station_name',86 2: 'exist_wlk', 3: 'exist_knr', 4: 'exist_pnr', 5: 'exist_xfr', 6: 'exist_all',87 7: 'nb_wlk', 8: 'nb_knr', 9: 'nb_pnr', 10: 'nb_xfr', 11: 'nb_all',88 12: 'bld_wlk', 13: 'bld_knr', 14: 'bld_pnr', 15: 'bld_xfr', 16: 'bld_all',89 },90 int_columns=['exist_wlk','exist_knr', 'exist_pnr', 'exist_xfr', 'exist_all',91 'nb_wlk', 'nb_knr', 'nb_pnr', 'nb_xfr', 'nb_all',92 'bld_wlk', 'bld_knr', 'bld_pnr', 'bld_xfr', 'bld_all']93 ),94 # Route Ridership95 '10.01': TableDef('10.01', end_table_tag=' Total', skip_rows=7,96 reset_header=True, widths=[25, 30] + [10] * 13, df_drop_top_rows=1,97 rename_columns={98 0: 'route_id', 1: 'route_name', 2: 'route_count',99 3: 'exist_wlk', 4: 'exist_knr', 5: 'exist_pnr', 6: 'exist_all',100 7: 'nb_wlk', 8: 'nb_knr', 9: 'nb_pnr', 10: 'nb_all',101 11: 'bld_wlk', 12: 'bld_knr', 13: 'bld_pnr', 14: 'bld_all',102 },103 int_columns=[104 'route_count',105 'exist_wlk', 'exist_knr', 'exist_pnr', 'exist_all',106 'nb_wlk', 'nb_knr', 'nb_pnr', 'nb_all',107 'bld_wlk', 'bld_knr', 'bld_pnr', 'bld_all',108 ]),109 #Existing - HBW - TRN - 0 Car110 '30.01': TableDef('30.01', end_table_tag='Total', skip_rows=5,111 df_drop_top_rows=1, index_col='origin',112 rename_columns={'Idist': 'origin'}, convert_numerics=True),113 114 #Existing - HBW - TRN - 1 Car115 '51.01': TableDef('51.01', end_table_tag='Total', skip_rows=5,116 df_drop_top_rows=1, index_col='origin',117 rename_columns={'Idist': 'origin'}, convert_numerics=True),118 119 #Existing - HBW - TRN - 2 Car120 '72.01': TableDef('72.01', end_table_tag='Total', skip_rows=5,121 df_drop_top_rows=1, index_col='origin',122 rename_columns={'Idist': 'origin'}, convert_numerics=True),123 124 #Existing - HBW - TRN - ALL125 '93.01': TableDef('93.01', end_table_tag='Total', skip_rows=5,126 df_drop_top_rows=1, index_col='origin',127 rename_columns={'Idist': 'origin'}, convert_numerics=True),128 #Existing - HBO - TRN - 0 Car129 '114.01': TableDef('114.01', end_table_tag='Total', skip_rows=5,130 df_drop_top_rows=1, index_col='origin',131 rename_columns={'Idist': 'origin'}, convert_numerics=True),132 #Existing - HBO - TRN - 1 Car133 '135.01': TableDef('135.01', end_table_tag='Total', skip_rows=5,134 df_drop_top_rows=1, index_col='origin',135 rename_columns={'Idist': 'origin'}, convert_numerics=True),136 137 #Existing - HBO - TRN - 2 Car138 '156.01': TableDef('156.01', end_table_tag='Total', skip_rows=5,139 df_drop_top_rows=1, index_col='origin',140 rename_columns={'Idist': 'origin'}, convert_numerics=True),141 #Existing - HBO - TRN - ALL142 '177.01': TableDef('177.01', end_table_tag='Total', skip_rows=5,143 df_drop_top_rows=1, index_col='origin',144 rename_columns={'Idist': 'origin'}, convert_numerics=True),145 #Existing - NHB - TRN - 0 Car146 '198.01': TableDef('198.01', end_table_tag='Total', skip_rows=5,147 df_drop_top_rows=1, index_col='origin',148 rename_columns={'Idist': 'origin'}, convert_numerics=True),149 150 #Existing - NHB - TRN - 1 Car151 '219.01': TableDef('219.01', end_table_tag='Total', skip_rows=5,152 df_drop_top_rows=1, index_col='origin',153 rename_columns={'Idist': 'origin'}, convert_numerics=True),154 155 #Existing - NHB - TRN - 2 Car156 '240.01': TableDef('240.01', end_table_tag='Total', skip_rows=5,157 df_drop_top_rows=1, index_col='origin',158 rename_columns={'Idist': 'origin'}, convert_numerics=True),159 160 #Existing - NHB - TRN - ALL161 '261.01': TableDef('261.01', end_table_tag='Total', skip_rows=5,162 df_drop_top_rows=1, index_col='origin',163 rename_columns={'Idist': 'origin'}, convert_numerics=True),164 #Existing - All Trips - TRN - 0 Car165 '282.01': TableDef('282.01', end_table_tag='Total', skip_rows=5,166 df_drop_top_rows=1, index_col='origin',167 rename_columns={'Idist': 'origin'}, convert_numerics=True),168 169 #Existing - All Trips - TRN - 1 Car170 '303.01': TableDef('303.01', end_table_tag='Total', skip_rows=5,171 df_drop_top_rows=1, index_col='origin',172 rename_columns={'Idist': 'origin'}, convert_numerics=True),173 174 #Existing - All Trips - TRN - 2 Car175 '324.01': TableDef('324.01', end_table_tag='Total', skip_rows=5,176 df_drop_top_rows=1, index_col='origin',177 rename_columns={'Idist': 'origin'}, convert_numerics=True),178 179 #Existing - All Trips - TRN - ALL180 '345.01': TableDef('345.01', end_table_tag='Total', skip_rows=5,181 df_drop_top_rows=1, index_col='origin',182 rename_columns={'Idist': 'origin'}, convert_numerics=True),183 # No Build - HBW - TRN - 0 Car184 '366.01': TableDef('366.01', end_table_tag='Total', skip_rows=5,185 df_drop_top_rows=1, index_col='origin',186 rename_columns={'Idist': 'origin'}, convert_numerics=True),187 188 # No Build - HBW - TRN - 1 Car189 '387.01': TableDef('387.01', end_table_tag='Total', skip_rows=5,190 df_drop_top_rows=1, index_col='origin',191 rename_columns={'Idist': 'origin'}, convert_numerics=True),192 193 # No Build - HBW - TRN - 2 Car194 '408.01': TableDef('408.01', end_table_tag='Total', skip_rows=5,195 df_drop_top_rows=1, index_col='origin',196 rename_columns={'Idist': 'origin'}, convert_numerics=True),197 # No Build - HBW - TRN - ALL198 '429.01': TableDef('429.01', end_table_tag='Total', skip_rows=5,199 df_drop_top_rows=1, index_col='origin',200 rename_columns={'Idist': 'origin'}, convert_numerics=True),201 # No Build - HBO - TRN - O Car202 '450.01': TableDef('450.01', end_table_tag='Total', skip_rows=5,203 df_drop_top_rows=1, index_col='origin',204 rename_columns={'Idist': 'origin'}, convert_numerics=True),205 206 # No Build - HBO - TRN - 1 Car207 '471.01': TableDef('471.01', end_table_tag='Total', skip_rows=5,208 df_drop_top_rows=1, index_col='origin',209 rename_columns={'Idist': 'origin'}, convert_numerics=True),210 211 # No Build - HBO - TRN - 2 Car212 '492.01': TableDef('492.01', end_table_tag='Total', skip_rows=5,213 df_drop_top_rows=1, index_col='origin',214 rename_columns={'Idist': 'origin'}, convert_numerics=True),215 216 # No Build - HBO - TRN - ALL217 '513.01': TableDef('513.01', end_table_tag='Total', skip_rows=5,218 df_drop_top_rows=1, index_col='origin',219 rename_columns={'Idist': 'origin'}, convert_numerics=True),220 # No Build - NHB - TRN - 0 Car221 '534.01': TableDef('534.01', end_table_tag='Total', skip_rows=5,222 df_drop_top_rows=1, index_col='origin',223 rename_columns={'Idist': 'origin'}, convert_numerics=True),224 # No Build - NHB - TRN - 1 Car225 '555.01': TableDef('555.01', end_table_tag='Total', skip_rows=5,226 df_drop_top_rows=1, index_col='origin',227 rename_columns={'Idist': 'origin'}, convert_numerics=True),228 # No Build - NHB - TRN - 2 Car229 '576.01': TableDef('576.01', end_table_tag='Total', skip_rows=5,230 df_drop_top_rows=1, index_col='origin',231 rename_columns={'Idist': 'origin'}, convert_numerics=True),232 233 # No Build - NHB - TRN - ALL234 '597.01': TableDef('597.01', end_table_tag='Total', skip_rows=5,235 df_drop_top_rows=1, index_col='origin',236 rename_columns={'Idist': 'origin'}, convert_numerics=True),237 # No Build - All Trips - TRN - 0 Car238 '618.01': TableDef('618.01', end_table_tag='Total', skip_rows=5,239 df_drop_top_rows=1, index_col='origin',240 rename_columns={'Idist': 'origin'}, convert_numerics=True),241 # No Build - All Trips - TRN - 1 Car242 '639.01': TableDef('639.01', end_table_tag='Total', skip_rows=5,243 df_drop_top_rows=1, index_col='origin',244 rename_columns={'Idist': 'origin'}, convert_numerics=True),245 # No Build - All Trips - TRN - 2 Car246 '660.01': TableDef('660.01', end_table_tag='Total', skip_rows=5,247 df_drop_top_rows=1, index_col='origin',248 rename_columns={'Idist': 'origin'}, convert_numerics=True),249 # No Build - All Trips - TRN - ALL250 '681.01': TableDef('681.01', end_table_tag='Total', skip_rows=5,251 df_drop_top_rows=1, index_col='origin',252 rename_columns={'Idist': 'origin'}, convert_numerics=True),253 # Build - HBW - TRN - 0 Car254 '702.01': TableDef('702.01', end_table_tag='Total', skip_rows=5,255 df_drop_top_rows=1, index_col='origin',256 rename_columns={'Idist': 'origin'}, convert_numerics=True),257 # Build - HBW - TRN - 1 Car258 '723.01': TableDef('723.01', end_table_tag='Total', skip_rows=5,259 df_drop_top_rows=1, index_col='origin',260 rename_columns={'Idist': 'origin'}, convert_numerics=True),261 # Build - HBW - TRN - 2 Car262 '744.01': TableDef('744.01', end_table_tag='Total', skip_rows=5,263 df_drop_top_rows=1, index_col='origin',264 rename_columns={'Idist': 'origin'}, convert_numerics=True),265 266 # Build - HBW - TRN - ALL267 '765.01': TableDef('765.01', end_table_tag='Total', skip_rows=5,268 df_drop_top_rows=1, index_col='origin',269 rename_columns={'Idist': 'origin'}, convert_numerics=True),270 # Build - HBO - TRN - 0 Car271 '786.01': TableDef('786.01', end_table_tag='Total', skip_rows=5,272 df_drop_top_rows=1, index_col='origin',273 rename_columns={'Idist': 'origin'}, convert_numerics=True),274 # Build - HBO - TRN - 1 Car275 '807.01': TableDef('807.01', end_table_tag='Total', skip_rows=5,276 df_drop_top_rows=1, index_col='origin',277 rename_columns={'Idist': 'origin'}, convert_numerics=True),278 # Build - HBO - TRN - 2 Car279 '828.01': TableDef('828.01', end_table_tag='Total', skip_rows=5,280 df_drop_top_rows=1, index_col='origin',281 rename_columns={'Idist': 'origin'}, convert_numerics=True),282 # Build - HBO - TRN - ALL283 '849.01': TableDef('849.01', end_table_tag='Total', skip_rows=5,284 df_drop_top_rows=1, index_col='origin',285 rename_columns={'Idist': 'origin'}, convert_numerics=True),286 # Build - NHB - TRN - 0 Car287 '870.01': TableDef('870.01', end_table_tag='Total', skip_rows=5,288 df_drop_top_rows=1, index_col='origin',289 rename_columns={'Idist': 'origin'}, convert_numerics=True),290 # Build - NHB - TRN - 1 Car291 '891.01': TableDef('891.01', end_table_tag='Total', skip_rows=5,292 df_drop_top_rows=1, index_col='origin',293 rename_columns={'Idist': 'origin'}, convert_numerics=True),294 # Build - NHB - TRN - 2 Car295 '912.01': TableDef('912.01', end_table_tag='Total', skip_rows=5,296 df_drop_top_rows=1, index_col='origin',297 rename_columns={'Idist': 'origin'}, convert_numerics=True),298 # Build - NHB - TRN - ALL299 '933.01': TableDef('933.01', end_table_tag='Total', skip_rows=5,300 df_drop_top_rows=1, index_col='origin',301 rename_columns={'Idist': 'origin'}, convert_numerics=True),302 # Build - All Trips - TRN - ALL303 '954.01': TableDef('954.01', end_table_tag='Total', skip_rows=5,304 df_drop_top_rows=1, index_col='origin',305 rename_columns={'Idist': 'origin'}, convert_numerics=True),306 # Build - All Trips - TRN - ALL307 '975.01': TableDef('975.01', end_table_tag='Total', skip_rows=5,308 df_drop_top_rows=1, index_col='origin',309 rename_columns={'Idist': 'origin'}, convert_numerics=True),310 # Build - All Trips - TRN - ALL311 '996.01': TableDef('996.01', end_table_tag='Total', skip_rows=5,312 df_drop_top_rows=1, index_col='origin',313 rename_columns={'Idist': 'origin'}, convert_numerics=True),314 # Build - All Trips - TRN - ALL315 '1017.01': TableDef('1017.01', end_table_tag='Total', skip_rows=5,316 df_drop_top_rows=1, index_col='origin',317 rename_columns={'Idist': 'origin'}, convert_numerics=True),318}319def parse_table(result_file_path, table_label):320 def replace_dash(x):321 return 0 if x == '-' else x322 table_def = _table_parameters[table_label]323 start_table_tag = 'Table{:>9s}\n'.format(table_def.table_id)324 end_table_tag = table_def.end_table_tag325 skip_rows = table_def.skip_rows326 found_table = False327 table = StringIO('')328 with open(result_file_path, 'r') as result_file:329 for line in result_file:330 if line.startswith(start_table_tag):331 found_table = True332 if found_table:333 if line.startswith(end_table_tag):334 found_table = False335 else:336 table.write(line)337 table.seek(0)338 df = pd.read_fwf(table, widths=table_def.widths, skiprows=skip_rows)339 if table_def.df_drop_top_rows is not None:340 df = df[table_def.df_drop_top_rows:]341 if table_def.df_drop_tail_rows is not None:342 df = df[:-table_def.df_drop_tail_rows]343 if table_def.reset_header:344 columns = df.columns345 df.columns = np.arange(len(columns))346 if table_def.rename_columns is not None:347 df = df.rename(columns=table_def.rename_columns)348 if table_def.int_columns is not None or table_def.convert_numerics:349 df = df.applymap(np.vectorize(replace_dash))350 if table_def.int_columns is not None:351 df[table_def.int_columns] = df[table_def.int_columns].astype(np.int64)352 if table_def.index_col is not None:353 df = df.set_index(table_def.index_col)354 if table_def.convert_numerics:355 df = df.apply(pd.to_numeric)356 return df.copy()357def summarize_access_modes(result_file_path, percentage=False):358 table_label = '9.01'359 tbl = parse_table(result_file_path, table_label)360 table_def = _table_parameters[table_label]361 362 if not percentage:363 return tbl[table_def.int_columns].sum()364 365 exist = tbl[['exist_wlk','exist_knr', 'exist_pnr', 'exist_xfr']].sum() / tbl[['exist_wlk','exist_knr', 'exist_pnr', 'exist_xfr']].sum().sum()366 nb = tbl[['nb_wlk', 'nb_knr', 'nb_pnr', 'nb_xfr']].sum() / tbl[['nb_wlk', 'nb_knr', 'nb_pnr', 'nb_xfr']].sum().sum()367 bld = tbl[['bld_wlk', 'bld_knr', 'bld_pnr', 'bld_xfr']].sum() / tbl[['bld_wlk', 'bld_knr', 'bld_pnr', 'bld_xfr']].sum().sum()368 369 exist.index = exist.index.str[-3:]370 nb.index = nb.index.str[-3:]371 bld.index = bld.index.str[-3:]372 373 return pd.concat([exist, nb, bld], axis=1, keys=['existing', 'nb', 'bld']).transpose()...

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headers_cleanup.py

Source:headers_cleanup.py Github

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1"""2Helper functions to cleanup the headers from the various data sources.3This helps make the final product more human readable.4"""5HEADERS_CHANGE = {6 'elections_2020': {7 'rename_columns': {8 'fips5': 'county_fips'9 },10 'drop_columns': {11 'fips_char', 'place', 'fname', 'lname', 'pab', 'incumbent', 'mpc'12 }13 },14 'census_2019': {15 'rename_columns': {16 'state': 'state_fips_part',17 'county': 'county_fips_part',18 'popestimate2019': 'county_population'19 },20 'drop_columns': {21 'sumlev', 'region', 'division', 'stname', 'ctyname', 'census2010pop',22 'estimatesbase2010', 'popestimate2010', 'popestimate2011',23 'popestimate2012', 'popestimate2013', 'popestimate2014',24 'popestimate2015', 'popestimate2016', 'popestimate2017',25 'popestimate2018', 'npopchg_2010', 'npopchg_2011', 'npopchg_2012',26 'npopchg_2013', 'npopchg_2014', 'npopchg_2015', 'npopchg_2016',27 'npopchg_2017', 'npopchg_2018', 'npopchg_2019', 'births2010',28 'births2011', 'births2012', 'births2013', 'births2014', 'births2015',29 'births2016', 'births2017', 'births2018', 'births2019', 'deaths2010',30 'deaths2011', 'deaths2012', 'deaths2013', 'deaths2014', 'deaths2015',31 'deaths2016', 'deaths2017', 'deaths2018', 'deaths2019', 'naturalinc2010',32 'naturalinc2011', 'naturalinc2012', 'naturalinc2013', 'naturalinc2014',33 'naturalinc2015', 'naturalinc2016', 'naturalinc2017', 'naturalinc2018',34 'naturalinc2019', 'internationalmig2010', 'internationalmig2011',35 'internationalmig2012', 'internationalmig2013', 'internationalmig2014',36 'internationalmig2015', 'internationalmig2016', 'internationalmig2017',37 'internationalmig2018', 'internationalmig2019', 'domesticmig2010',38 'domesticmig2011', 'domesticmig2012', 'domesticmig2013',39 'domesticmig2014', 'domesticmig2015', 'domesticmig2016',40 'domesticmig2017', 'domesticmig2018', 'domesticmig2019', 'netmig2010',41 'netmig2011', 'netmig2012', 'netmig2013', 'netmig2014', 'netmig2015',42 'netmig2016', 'netmig2017', 'netmig2018', 'netmig2019', 'residual2010',43 'residual2011', 'residual2012', 'residual2013', 'residual2014',44 'residual2015', 'residual2016', 'residual2017', 'residual2018',45 'residual2019', 'gqestimatesbase2010', 'gqestimates2010',46 'gqestimates2011', 'gqestimates2012', 'gqestimates2013',47 'gqestimates2014', 'gqestimates2015', 'gqestimates2016',48 'gqestimates2017', 'gqestimates2018', 'gqestimates2019', 'rbirth2011',49 'rbirth2012', 'rbirth2013', 'rbirth2014', 'rbirth2015', 'rbirth2016',50 'rbirth2017', 'rbirth2018', 'rbirth2019', 'rdeath2011', 'rdeath2012',51 'rdeath2013', 'rdeath2014', 'rdeath2015', 'rdeath2016', 'rdeath2017',52 'rdeath2018', 'rdeath2019', 'rnaturalinc2011', 'rnaturalinc2012',53 'rnaturalinc2013', 'rnaturalinc2014', 'rnaturalinc2015',54 'rnaturalinc2016', 'rnaturalinc2017', 'rnaturalinc2018',55 'rnaturalinc2019', 'rinternationalmig2011', 'rinternationalmig2012',56 'rinternationalmig2013', 'rinternationalmig2014', 'rinternationalmig2015',57 'rinternationalmig2016', 'rinternationalmig2017', 'rinternationalmig2018',58 'rinternationalmig2019', 'rdomesticmig2011', 'rdomesticmig2012',59 'rdomesticmig2013', 'rdomesticmig2014', 'rdomesticmig2015',60 'rdomesticmig2016', 'rdomesticmig2017', 'rdomesticmig2018',61 'rdomesticmig2019', 'rnetmig2011', 'rnetmig2012', 'rnetmig2013',62 'rnetmig2014', 'rnetmig2015', 'rnetmig2016', 'rnetmig2017', 'rnetmig2018',63 'rnetmig2019'64 }65 },66 'cdc': {67 'rename_columns': {68 'fips county code': 'county_fips',69 'deaths involving covid-19': 'county_covid19_deaths',70 'deaths from all causes': 'county_all_cause_deaths',71 },72 'drop_columns': [73 'date as of', 'start date', 'end date', 'state', 'county name',74 'urban rural code', 'footnote'75 ]76 },77 'zillow_city_codes': {78 'rename_columns': {79 'code': 'city_code'80 },81 'drop_columns': ['area']82 },83 'experian': {84 'rename_columns': {85 'city ': 'city',86 'vantagescore 3.0 credit score': 'credit score',87 'avg vantagescore 3.0': 'credit score',88 'average vantagescore 3.0 credit score': 'credit score',89 'avg. vantagescore 3.0': 'credit score',90 'weighted vantage score': 'credit score',91 'sum of adjusted credit score': 'credit score',92 ' average vantagescore 3.0 credit score': 'credit score',93 'vantage score': 'credit score',94 'county name': 'county',95 },96 'drop_columns': ['rank', 'population', 'unnamed: 5', 'unnamed: 4']97 },98 'fbi_2015': {99 'rename_columns': {100 'rape (revised definition)1': 'rape',101 'larceny- theft': 'larceny theft',102 'arson3': 'arson',103 },104 'drop_columns': ['rape (legacy definition)2'],105 },106 'fbi_2016': {107 'rename_columns': {108 'rape (revised definition)1': 'rape',109 'larceny- theft': 'larceny theft',110 'arson3': 'arson',111 },112 'drop_columns': ['rape (legacy definition)2'],113 },114 'fbi_2017': {115 'rename_columns': {116 'rape1': 'rape',117 'larceny- theft': 'larceny theft',118 'arson2': 'arson',119 },120 'drop_columns': [121 'unnamed: 13',122 'unnamed: 14',123 'unnamed: 15',124 'unnamed: 16',125 'unnamed: 17',126 'unnamed: 18',127 ]128 },129 'fbi_2018': {130 'rename_columns': {131 'rape1': 'rape',132 'larceny- theft': 'larceny theft',133 'arson2': 'arson',134 },135 'drop_columns': []136 },137 'fbi_2019': {138 'rename_columns': {139 'rape1': 'rape',140 'larceny- theft': 'larceny theft',141 'arson2': 'arson',142 },143 'drop_columns': []144 },145 'census_2010': {146 'rename_columns': {147 'area in square miles - land area': 'land area sqmi census_2010',148 'area in square miles - total area': 'total area sqmi census_2010',149 'area in square miles - water area': 'water area sqmi census_2010',150 'target geo id2': 'geoid'151 },152 'drop_columns': [153 'density per square mile of land area - housing units',154 'density per square mile of land area - population', 'geographic area',155 'geographic area.1', 'geography', 'housing units', 'id', 'id2',156 'population', 'target geo id'157 ]158 },159 'final_csv': {160 'rename_columns': {},161 'drop_columns': [162 'city_code', 'city_fbi_crime', 'city_walkscore', 'cityexperian_2017',163 'cityzillow', 'geography census_2010', 'geography.1', 'geography.2',164 'latitudezillow', 'longitudezillow', 'rape_legacy', 'reverse_address',165 'state_fbi_crime', 'state_fbi_crime', 'state_walkscore',166 'state_walkscore', 'stateexperian_2017', 'statezillow', 'target geo id2',167 'longitude_x', 'longitude_y', 'latitude_x', 'latitude_y',168 'reverse_address_x', 'reverse_address_y'169 ]170 }...

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