Answers for "how to place if else condition on column in pandas"

pandas if else new column

# Method 1:
df.loc[df['column name'] condition, 'new column name'] = 'value if condition is met'
#or
df.loc[df['set_of_numbers'] <= 4, 'equal_or_lower_than_4?'] = 'True' 

# Method 2:
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')
#or
df['name_match'] = df['First_name'].apply(lambda x: 'Match' if x == 'Bill' else 'Mismatch')

# or
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'

conditions in pandas dataframe

from pandas import DataFrame
  
names = {'First_name': ['Hanah', 'Ria', 'Jay', 'Bholu', 'Sachin']}
df = DataFrame(names, columns =['First_name'])
  
df['Status'] = df['First_name'].apply(lambda x: 'Found' if x == 'Ria' else 'Not Found')
  
print (df)