PYTHON

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'})  

switch cases pandas

df['new_column'] = np.where(df['col2']<9, 'value1',
                   np.where(df['col2']<12, 'value2',
                   np.where(df['col2']<15, 'value3', 'value4')))

pandas columns case when equivalent

df['c'] = np.select(
[
    (df['a'].isnull() & (df['b'] == 0))
], 
[
    1
], 
default=0 )