Convert Pandas series containing string to boolean

问题

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.

回答1:

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

回答2:

An example of replace method to replace values only in the specified column C2 and get result as DataFrame type.

import pandas as pd
df = pd.DataFrame({'C1':['X', 'Y', 'X', 'Y'], 'C2':['Y', 'Y', 'X', 'X']})

  C1 C2
0  X  Y
1  Y  Y
2  X  X
3  Y  X

df.replace({'C2': {'X': True, 'Y': False}})

  C1     C2
0  X  False
1  Y  False
2  X   True
3  Y   True