I have a DataFrame named df as
Order Number Status 1 1668 Undelivered 2 19771 Undelivered 3 100032108 Undelivered 4 2229 Delivered 5 00056 Undelivered I would like to convert the Status column to boolean (True when Status is Delivered and False when Status is Undelivered) but if Status is neither 'Undelivered' neither 'Delivered' it should be considered as NotANumber or something like that.
I would like to use a dict
d = { 'Delivered': True, 'Undelivered': False } so I could easily add other string which could be either considered as True or False.
You can just use map:
In [7]: df = pd.DataFrame({'Status':['Delivered', 'Delivered', 'Undelivered', 'SomethingElse']}) In [8]: df Out[8]: Status 0 Delivered 1 Delivered 2 Undelivered 3 SomethingElse In [9]: d = {'Delivered': True, 'Undelivered': False} In [10]: df['Status'].map(d) Out[10]: 0 True 1 True 2 False 3 NaN Name: Status, dtype: object
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