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On this page
  • Import Necessary Libraries
  • # Reading all the Files:
  • Reading Order Report:
  • Reading Company Invoice
  • Reading SKU Master:
  • Reading Courier Rates:
  • Reading Pincode Zones:
  • Renaming all the columns as x as client x and cc as courier company

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  1. Projects
  2. Data Analytics Project

Solution

PreviousCourier Analytics ChallengeNextSkytrax Airline Review Analysis Pipeline

Last updated 1 year ago

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Import Necessary Libraries

import pandas as pd

# Reading all the Files:

Reading Order Report:

CX_order_report = pd.read_excel("COURIER DATA/Company X - Order Report.xlsx")
CX_order_report.head()

Reading Company Invoice

CC_invoice = pd.read_excel(r"COURIER DATA/Courier Company - Invoice.xlsx")
CC_invoice.head()

Reading SKU Master:

CX_SKU_Master = pd.read_excel(r"COURIER DATA/Company X - SKU Master.xlsx")
CX_SKU_Master.head()

Reading Courier Rates:

CC_Rates = pd.read_excel(r"COURIER DATA/Courier Company - Rates.xlsx")
CC_Rates.head()

Reading Pincode Zones:

CX_Pincode_Zones = pd.read_excel(r"COURIER DATA\Company X - Pincode Zones.xlsx")
CX_Pincode_Zones.head()
CX_Pincode_Zones

# renaming all the columns as x as client x and cc as courier company

Renaming all the columns as x as client x and cc as courier company

CX_Pincode_Zones.rename(columns = {'Zone':'zone_X'}, inplace = True)
CX_Pincode_Zones