python multiple conditions in dataframe column values
df.loc[(df['Salary_in_1000']>=100) & (df['Age']< 60) & (df['FT_Team'].str.startswith('S')),['Name','FT_Team']]python multiple conditions in dataframe column values
df.loc[(df['Salary_in_1000']>=100) & (df['Age']< 60) & (df['FT_Team'].str.startswith('S')),['Name','FT_Team']]pandas create a new column based on condition of two columns
conditions = [
df['gender'].eq('male') & df['pet1'].eq(df['pet2']),
df['gender'].eq('female') & df['pet1'].isin(['cat', 'dog'])
]
choices = [5,5]
df['points'] = np.select(conditions, choices, default=0)
print(df)
gender pet1 pet2 points
0 male dog dog 5
1 male cat cat 5
2 male dog cat 0
3 female cat squirrel 5
4 female dog dog 5
5 female squirrel cat 0
6 squirrel dog cat 0dataframe isin multiple columns
pd.merge(df2, df1, how='inner')
# col1 col2
# 0 pizza boy
# 1 pizza girls
# 2 ice cream boyCopyright © 2021 Codeinu
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