CODEWITHSUNDEEP
pythonexcelpandasmergeconcatenation
raptorzee
raptorzee

Reputation: 167

How to merge multiple sheets and rename column names with the names of the sheet names?

I have the following data. It is all in one excel file.

    Sheet name: may2019
    Productivity Count                          
 Date : 01-Apr-2020 00:00 to 30-Apr-2020 23:59                          
 Date Type: Finalized Date Modality: All     
    Name    MR  DX  CT  US  MG  BMD TOTAL
    Svetlana    29  275 101 126 5   5   541
    Kate    32  652 67  171 1   0   923
    Andrew  0   452 0   259 1   0   712
    Tom     50  461 61  104 4   0   680
    Maya    0   353 0   406 0   0   759
    Ben     0   1009    0   143 0   0   1152
    Justin  0   2   9   0   1   9   21
    Total   111 3204    238 1209    12  14  4788

    Sheet Name: June 2020
Productivity Count                              
 Date : 01-Jun-2019 00:00 to 30-Jun-2019 23:59                              
 Date Type: Finalized Date Modality: All

NAme US DX  CT  MR  MG  BMD TOTAL
Svetlana    4   0   17  6   0   4   31
Kate    158 526 64  48  1   0   797
Andrew  154 230 0   0   0   0   384
Tom     1   0   19  20  2   8   50
Maya    260 467 0   0   1   1   729
Ben     169 530 59  40  3   0   801
Justin  125 164 0   0   4   0   293
Alvin   0   1   0   0   0   0   1
Total   871 1918    159 114 11  13  3086

I want to merge all the sheets into on sheet, drop the first 3 rows of all the sheets and and this is the output I am looking for

Sl.No   Name US_jun2019 DX_jun2019  CT_jun2019  MR_jun2019  MG_jun2019  BMD_jun2019 TOTAL_jun2019   MR_may2019  DX_may2019  CT_may2019  US_may2019  MG_may2019  BMD_may2019 TOTAL_may2019
1   Svetlana    4   0   17  6   0   4   31  29  275 101 126 5   5   541
2   Kate    158 526 64  48  1   0   797 32  652 67  171 1   0   923
3   Andrew  154 230 0   0   0   0   384 0   353 0   406 0   0   759
4   Tom     1   0   19  20  2   8   50  0   2   9   0   1   9   21
5   Maya    260 467 0   0   1   1   729 0   1009    0   143 0   0   1152
6   Ben     169 530 59  40  3   0   801 50  461 61  104 4   0   680
7   Justin  125 164 0   0   4   0   293 0   452 0   259 1   0   712
8   Alvin   0   1   0   0   0   0   1   #N/A    #N/A    #N/A    #N/A    #N/A    #N/A    #N/A

I tried the following code but the output is not the one i am looking for.

df=pd.concat(df,sort=False)
df= df.drop(df.index[[0,1]])
df=df.rename(columns=df.iloc[0])
df= df.drop(df.index[[0]])
df=df.drop(['Sl.No'], axis = 1)

print(df)

Upvotes: 1

Views: 751

Answers (1)

Safwan Samsudeen
Safwan Samsudeen

Reputation: 1707

First, read both Excel sheets.

>>> df1 = pd.read_excel('path/to/excel/file.xlsx', sheet_name="may2019")
>>> df2 = pd.read_excel('path/to/excel/file.xlsx', sheet_name="jun2019")

Drop the first three rows.

>>> df1.drop(index=range(3), inplace=True)
>>> df2.drop(index=range(3), inplace=True)

Rename columns to the first row, and drop the first row

>>> df1.rename(columns=dict(zip(df1.columns, df1.iloc[0])), inplace=True)
>>> df1.drop(index=[0], inplace=True)
>>> df2.rename(columns=dict(zip(df2.columns, df2.iloc[0])), inplace=True)
>>> df2.drop(index=[0], inplace=True)

Add suffixes to the columns.

>>> df1.rename(columns=lambda col_name: col_name + '_may2019', inplace=True)
>>> df2.rename(columns=lambda col_name: col_name + '_jun2019', inplace=True)

Remove the duplicate name column in the second DF.

>>> df2.drop(columns=['Name'], inplace=True)

Concatenate both the dataframes

>>> df = pd.concat([df1, df2], axis=1, inplace=True)

All the code in one place:

import pandas as pd

df1 = pd.read_excel('path/to/excel/file.xlsx', sheet_name="may2019")
df2 = pd.read_excel('path/to/excel/file.xlsx', sheet_name="jun2019")

df1.drop(index=range(3), inplace=True)
df2.drop(index=range(3), inplace=True)

df1.rename(columns=dict(zip(df1.columns, df1.iloc[0])), inplace=True)
df1.drop(index=[0], inplace=True)
df2.rename(columns=dict(zip(df2.columns, df2.iloc[0])), inplace=True)
df2.drop(index=[0], inplace=True)

df1.rename(columns=lambda col_name: col_name + '_may2019', inplace=True)
df2.rename(columns=lambda col_name: col_name + '_jun2019', inplace=True)

df2.drop(columns=['Name'], inplace=True)

df = pd.concat([df2, df1], axis=1, inplace=True)

print(df)

Upvotes: 1

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