Pandas：无法更改列数据类型
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Pandas: unable to change column data type
提问by
I was following the advice hereto change the column data type of a pandas dataframe. However, it does not seem to work if I reference the columns by index numbers instead of column names. Is there a way to do this correctly?
我正在按照此处的建议更改Pandas数据框的列数据类型。但是，如果我通过索引号而不是列名来引用列，它似乎不起作用。有没有办法正确地做到这一点？
In [49]: df.iloc[:, 4:].astype(int)
Out[49]:
<class 'pandas.core.frame.DataFrame'>
Int64Index: 5074 entries, 0 to 5073
Data columns (total 3 columns):
5 5074 non-null values
6 5074 non-null values
7 5074 non-null values
dtypes: int64(3)
In [50]: df.iloc[:, 4:] = df.iloc[:, 4:].astype(int)
In [51]: df
Out[51]:
<class 'pandas.core.frame.DataFrame'>
Int64Index: 5074 entries, 0 to 5073
Data columns (total 7 columns):
1 5074 non-null values
2 5074 non-null values
3 5074 non-null values
4 5074 non-null values
5 5074 non-null values
6 5074 non-null values
7 5074 non-null values
dtypes: object(7)
In [52]:
采纳答案by Jeff
Do it like this
像这样做
In [49]: df = DataFrame([['1','2','3','.4',5,6.,'foo']],columns=list('ABCDEFG'))
In [50]: df
Out[50]:
A B C D E F G
0 1 2 3 .4 5 6 foo
In [51]: df.dtypes
Out[51]:
A object
B object
C object
D object
E int64
F float64
G object
dtype: object
Need to assign columns one-by-one
需要一一分配列
In [52]: for k, v in df.iloc[:,0:4].convert_objects(convert_numeric=True).iteritems():
df[k] = v
....:
In [53]: df.dtypes
Out[53]:
A int64
B int64
C int64
D float64
E int64
F float64
G object
dtype: object
Convert objects usually does the right thing, so easiest to do this
转换对象通常会做正确的事情，所以最容易做到这一点
In [54]: df = DataFrame([['1','2','3','.4',5,6.,'foo']],columns=list('ABCDEFG'))
In [55]: df.convert_objects(convert_numeric=True).dtypes
Out[55]:
A int64
B int64
C int64
D float64
E int64
F float64
G object
dtype: object
assigning via df.iloc[:,4:]with a series on the right-hand side copies the data changing type as needed, so I think this should work in theory, but I suspect that this is hitting a very obscure bug that prevents the object dtype from changing to a real(meaning int/float) dtype. Should probably raise for now.
df.iloc[:,4:]使用右侧的系列分配 via根据需要复制数据更改类型，所以我认为这在理论上应该有效，但我怀疑这是一个非常模糊的错误，阻止对象 dtype 更改为真实的（意思是 int/float) dtype。应该暂时加注。
Heres the issue to track this: https://github.com/pydata/pandas/issues/4312
这是跟踪此问题的问题：https: //github.com/pydata/pandas/issues/4312
