case statement in pandas
# If the row value in column 'is_blue' is 1
# Change the row value to 'Yes'
# otherwise change it to 'No'
df['is_blue'] = df['is_blue'].apply(lambda x: 'Yes' if (x == 1) else 'No')
# or you can use np.where
df['is_blue'] = np.where(df['is_blue'] == 1, 'Yes', 'No')
# You can also use mapping to accomplish the same result
# Warning: Mapping only works once on the same column creates NaN's otherwise
df['is_blue'] = df['is_blue'].map({0: 'No', 1: 'Yes'})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'pandas columns case when equivalent
df['c'] = np.select(
[
(df['a'].isnull() & (df['b'] == 0))
],
[
1
],
default=0 )Copyright © 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
