pandas lambda if else
df['equal_or_lower_than_4?'] = df['set_of_numbers'].apply(lambda x: 'True' if x <= 4 else 'False')pandas lambda if else
df['equal_or_lower_than_4?'] = df['set_of_numbers'].apply(lambda x: 'True' if x <= 4 else 'False')make a condition statement on column pandas
df['color'] = ['red' if x == 'Z' else 'green' for x in df['Set']]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')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)if condition dataframe python
df.loc[df['age1'] - df['age2'] > 0, 'diff'] = df['age1'] - df['age2']make a condition statement on column pandas
df.loc[df['column name'] condition, 'new column name'] = 'value if condition is met'Copyright © 2021 Codeinu
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