Python 如何在 Pandas DataFrame 中将 True/False 映射到 1/0？
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How can I map True/False to 1/0 in a Pandas DataFrame?
提问by Simon Righley
I have a column in python pandas DataFrame that has boolean True/False values, but for further calculations I need 1/0 representation. Is there a quick pandas/numpy way to do that?
我在 python pandas DataFrame 有一列具有布尔值 True/False 值，但为了进一步计算，我需要 1/0 表示。有没有一种快速的 Pandas/numpy 方法来做到这一点？
采纳答案by User
A succinct way to convert a single column of boolean values to a column of integers 1 or 0:
将单列布尔值转换为一列整数 1 或 0 的简洁方法：
df["somecolumn"] = df["somecolumn"].astype(int)
回答by Gareth Latty
Trueis 1in Python, and likewise Falseis 0*:
True是1在Python，同样False是0*：
>>> True == 1
True
>>> False == 0
True
You should be able to perform any operations you want on them by just treating them as though they were numbers, as they arenumbers:
您应该能够通过将它们视为数字来执行您想要的任何操作，因为它们是数字：
>>> issubclass(bool, int)
True
>>> True * 5
5
So to answer your question, no work necessary - you already have what you are looking for.
因此，要回答您的问题，无需任何工作-您已经拥有了想要的东西。
* Note I use isas an English word, not the Python keyword is- Truewill not be the same object as any random 1.
* 注意我使用is作为英文单词，而不是 Python 关键字is-True不会与任何 random 相同的对象1。
回答by Jeff
You also can do this directly on Frames
您也可以直接在 Frames 上执行此操作
In [104]: df = DataFrame(dict(A = True, B = False),index=range(3))
In [105]: df
Out[105]:
A B
0 True False
1 True False
2 True False
In [106]: df.dtypes
Out[106]:
A bool
B bool
dtype: object
In [107]: df.astype(int)
Out[107]:
A B
0 1 0
1 1 0
2 1 0
In [108]: df.astype(int).dtypes
Out[108]:
A int64
B int64
dtype: object
回答by shubhamgoel27
Just multiply your Dataframe by 1 (int)
只需将您的 Dataframe 乘以 1 (int)
[1]: data = pd.DataFrame([[True, False, True], [False, False, True]])
[2]: print data
0 1 2
0 True False True
1 False False True
[3]: print data*1
0 1 2
0 1 0 1
1 0 0 1
回答by Bruno Benevides
You can use a transformation for your data frame:
您可以对数据框使用转换：
df = pd.DataFrame(my_data condition)
transforming True/False in 1/0
在 1/0 中转换 True/False
df = df*1
回答by jezrael
Use Series.viewfor convert boolean to integers:
使用Series.view的转换布尔为整数：
df["somecolumn"] = df["somecolumn"].view('i1')
