pandas select rows by condition on multiple columns code example

Example 1: select rows with multiple conditions pandas query

df.loc[(df['Salary_in_1000']>=100) & (df['Age']< 60) & (df['FT_Team'].str.startswith('S')),['Name','FT_Team']]

Example 2: how to slicing dataframe using two 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')]

Example 3: 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  900