Pandas get_dummies 输出 dtype integer/bool 而不是 float
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Pandas get_dummies to output dtype integer/bool instead of float
提问by queise
I would like to know if could ask the get_dummies function in pandas to output the dummies dataframe with a dtype lighter than the default float64.
我想知道是否可以要求 pandas 中的 get_dummies 函数输出具有比默认 float64 更轻的 dtype 的虚拟数据帧。
So, for a sample dataframe with categorical columns:
因此，对于具有分类列的示例数据框：
In []: df = pd.DataFrame([(blue,wood),(blue,metal),(red,wood)],
columns=['C1','C2'])
In []: df
Out[]:
C1 C2
0 blue wood
1 blue metal
2 red wood
after getting the dummies, it looks like:
得到假人后，它看起来像：
In []: df = pd.get_dummies(df)
In []: df
Out[]:
C1_blue C1_red C2_metal C2_wood
0 1 0 0 1
1 1 0 1 0
2 0 1 0 1
which is perfectly fine. However, by default the 1's and 0's are float64:
这很好。但是，默认情况下 1 和 0 是 float64：
In []: df.dtypes
Out[]:
C1_blue float64
C1_red float64
C2_metal float64
C2_wood float64
dtype: object
I know I can change the dtype afterwards with astype:
我知道我可以在之后更改 dtype astype：
In []: df = pd.get_dummies(df).astype(np.int8)
But I don't want to have the dataframe with floats in memory, because I am dealing with a big dataframe (from a csv of about ~5Gb). I would like to have the dummies directly as integers.
但我不想让数据帧在内存中浮动，因为我正在处理一个大数据帧（来自大约 5Gb 的 csv）。我想将假人直接作为整数。
采纳答案by queise
The float issue is now solved. From pandas version 0.19, pd.get_dummies function returns dummy-encoded columns as small integers.
浮动问题现已解决。从 pandas 0.19 版开始，pd.get_dummies 函数将虚拟编码列作为小整数返回。
See: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#get-dummies-now-returns-integer-dtypes
请参阅：http: //pandas.pydata.org/pandas-docs/stable/whatsnew.html#get-dummies-now-returns-integer-dtypes
回答by Jeff
There is an open issue w.r.t. this, see here: https://github.com/pydata/pandas/issues/8725
这有一个未解决的问题，请参见此处：https: //github.com/pydata/pandas/issues/8725
