lambda <args> : <return Value> if <condition> else ( <return value> if <condition> else <return value>)
lambda x: x*10 if x<2 else (x**2 if x<4 else x+10)df['new column name'] = df['column name'].apply(lambda x: 'value if condition is met' if x condition else 'value if condition is not met')
lambda <arguments> : <Return Value if condition is True> if <condition> else <Return Value if condition is False>
lambda x : True if (x > 10 and x < 20) else False# Think of the lambda function as defining a REALLY small function without
# a name.
# EXAMPLE #
lis = [2, 4, 6, 8]
output = lambda [parameter] : return True if [parameter] in lis else return False
print(output[4])