filter dataframe multiple conditions
# when you wrap conditions in parantheses, you give order
# you do those in brackets first before 'and'
# AND
movies[(movies.duration >= 200) & (movies.genre == 'Drama')]filter dataframe multiple conditions
# when you wrap conditions in parantheses, you give order
# you do those in brackets first before 'and'
# AND
movies[(movies.duration >= 200) & (movies.genre == 'Drama')]pandas select rows by multiple conditions
>>> df["A"][(df["B"] > 50) & (df["C"] == 900)]
2 5
3 8
Name: A, dtype: int64
>>> df.loc[(df["B"] > 50) & (df["C"] == 900), "A"]
2 5
3 8
Name: A, dtype: int64
>>> df.loc[(df["B"] > 50) & (df["C"] == 900), "A"].values
array([5, 8], dtype=int64)
>>> df.loc[(df["B"] > 50) & (df["C"] == 900), "A"] *= 1000
>>> df
A B C
0 9 40 300
1 9 70 700
2 5000 70 900
3 8000 80 900
4 7 50 900python 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']]Copyright © 2021 Codeinu
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