1. Raw data

 2. Original column change

Listing and original listing identical Is modification

import pandas as pd
import numpy as np
df = pd.read_excel('test.xlsx')
df[' Gender '] = np.where(df[' Gender '] == 1,' male ',' Woman ')# amount to IF(F2=1,' male ',' Woman ')
df.to_excel('test02.xlsx',index=False)

 3. New column

Listing and original listing inequality Is new

import pandas as pd
import numpy as np
df = pd.read_excel('test.xlsx')
df[' Gender 2'] = np.where(df[' Gender '] == 1,' male ',' Woman ')# amount to IF(F2=1,' male ',' Woman ')
df.to_excel('test02.xlsx',index=False)

 4. Create a new column at the specified position

Ideas ： First new , List again

insert(loc, column, value, allow_duplicates=False)

Where is the ：

loc： Insert the index of the column . The first column is 0.
column： Give the new column a name .
value： Array of values for the new column .
allow_duplicates： Whether to allow new column names to match existing column names . The default is false .

import pandas as pd
import numpy as np
df = pd.read_excel('test.xlsx')
df.insert(1, ' Gender 2', "") # Location , listed , data
df[' Gender 2'] = np.where(df[' Gender '] == 1, ' male ', ' Woman ') # amount to IF(F2=1,' male ',' Woman ')
df.to_excel('test02.xlsx', index=False)

5. Advanced （if nesting ）

import pandas as pd
import numpy as np
df = pd.read_excel('test.xlsx')
# IF(F2=1,IF(B2>90,' yes ',' no '),' no ')
df[' Whether to go to the office '] = np.where(df[' Gender '] == 1, np.where(df[' mathematics '] > 90, ' yes ', ' no '), ' no ')
df.to_excel('test02.xlsx', index=False)