make a condition statement on column pandas
df['color'] = ['red' if x == 'Z' else 'green' for x in df['Set']]make a condition statement on column pandas
df['color'] = ['red' if x == 'Z' else 'green' for x in df['Set']]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'})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
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