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')]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')]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']]or condition in pandas
df1 = df[(df.a != -1) & (df.b != -1)]or condition in pandas
df2 = df[(df.a != -1) | (df.b != -1)]select rows with multiple conditions pandas query
df.query('Salary_in_1000 >= 100 & Age < 60 & FT_Team.str.startswith("S").values')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 900Copyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
