Pandas if python

df['new column name'] = df['column name'].apply(lambda x: 'value if condition is met' if x condition else 'value if condition is not met')

Source: datatofish.com

Pandas if python

import pandas as pd

names = {'First_name': ['Jon','Bill','Maria','Emma']}
df = pd.DataFrame(names,columns=['First_name'])

df.loc[(df['First_name'] == 'Bill') | (df['First_name'] == 'Emma'), 'name_match'] = 'Match'  
df.loc[(df['First_name'] != 'Bill') & (df['First_name'] != 'Emma'), 'name_match'] = 'Mismatch'  

print (df)

Source: datatofish.com

Pandas if python

import pandas as pd

numbers = {'set_of_numbers': [1,2,3,4,5,6,7,8,9,10]}
df = pd.DataFrame(numbers,columns=['set_of_numbers'])

df['equal_or_lower_than_4?'] = df['set_of_numbers'].apply(lambda x: 'True' if x <= 4 else 'False')

print (df)

Source: datatofish.com

Pandas if python

import pandas as pd

numbers = {'set_of_numbers': [1,2,3,4,5,6,7,8,9,10,0,0]}
df = pd.DataFrame(numbers,columns=['set_of_numbers'])
print (df)

df.loc[df['set_of_numbers'] == 0, 'set_of_numbers'] = 999
df.loc[df['set_of_numbers'] == 5, 'set_of_numbers'] = 555

print (df)

Source: datatofish.com

Pandas if python

import pandas as pd

names = {'First_name': ['Jon','Bill','Maria','Emma']}
df = pd.DataFrame(names,columns=['First_name'])

df['name_match'] = df['First_name'].apply(lambda x: 'Match' if x == 'Bill' else 'Mismatch')

print (df)

Source: datatofish.com

Pandas if python

import pandas as pd

names = {'First_name': ['Jon','Bill','Maria','Emma']}
df = pd.DataFrame(names,columns=['First_name'])

df.loc[df['First_name'] == 'Bill', 'name_match'] = 'Match'  
df.loc[df['First_name'] != 'Bill', 'name_match'] = 'Mismatch'  
 
print (df)

Source: datatofish.com

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