将包含字符串的 pandas 系列转换为布尔值 [英] Convert Pandas series containing string to boolean
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问题描述
我有一个名为df
的数据框,
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
我想将Status
列转换为布尔值(状态为Delivered时为True
,状态为Undelivered时为False
)
但是如果状态既不是未交付"也不是已交付",则应将其视为NotANumber
或类似的内容.
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.
我想使用字典
d = {
'Delivered': True,
'Undelivered': False
}
所以我可以轻松添加其他字符串,可以将其视为True
或False
.
so I could easily add other string which could be either considered as True
or False
.
推荐答案
您可以只使用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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