Python 更改熊猫数据框特定列的数据类型
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Change data type of a specific column of a pandas dataframe
提问by DougKruger
I want to sort a dataframe with many columns by a specific column, but first I need to change type from objectto int. How to change the data type of this specific column while keeping the original column positions?
我想按特定列对包含多列的数据框进行排序，但首先我需要将类型从 更改object为int。如何在保持原始列位置的同时更改此特定列的数据类型？
采纳答案by jezrael
You can use reindexby sorted column by sort_values, cast to intby astype:
您可以使用reindexby 排序列 by sort_values，转换为intby astype：
df = pd.DataFrame({'A':[1,2,3],
'B':[4,5,6],
'colname':['7','3','9'],
'D':[1,3,5],
'E':[5,3,6],
'F':[7,4,3]})
print (df)
A B D E F colname
0 1 4 1 5 7 7
1 2 5 3 3 4 3
2 3 6 5 6 3 9
print (df.colname.astype(int).sort_values())
1 3
0 7
2 9
Name: colname, dtype: int32
print (df.reindex(df.colname.astype(int).sort_values().index))
A B D E F colname
1 2 5 3 3 4 3
0 1 4 1 5 7 7
2 3 6 5 6 3 9
print (df.reindex(df.colname.astype(int).sort_values().index).reset_index(drop=True))
A B D E F colname
0 2 5 3 3 4 3
1 1 4 1 5 7 7
2 3 6 5 6 3 9
If first solution does not works because Noneor bad data use to_numeric:
如果第一个解决方案由于None或错误数据而不起作用，请使用to_numeric：
df = pd.DataFrame({'A':[1,2,3],
'B':[4,5,6],
'colname':['7','3','None'],
'D':[1,3,5],
'E':[5,3,6],
'F':[7,4,3]})
print (df)
A B D E F colname
0 1 4 1 5 7 7
1 2 5 3 3 4 3
2 3 6 5 6 3 None
print (pd.to_numeric(df.colname, errors='coerce').sort_values())
1 3.0
0 7.0
2 NaN
Name: colname, dtype: float64
回答by JimmyOnThePage
df['colname'] = df['colname'].astype(int)works when changing from floatvalues to intatleast.
df['colname'] = df['colname'].astype(int)从float值更改为int至少时有效。
回答by user19120
I have tried following:
我试过以下：
df['column']=df.column.astype('int64')
and it worked for me.
它对我有用。
回答by Kripalu Sar
To simply change one column, here is what you can do:
df.column_name.apply(int)
要简单地更改一列，您可以执行以下操作：
df.column_name.apply(int)
you can replace intwith the desired datatype you want e.g (np.int64), str, category.
您可以替换int为所需的数据类型，例如(np.int64), str, category。
For multiple datatype changes, I would recommend the following:
对于多个数据类型更改，我建议如下：
df = pd.read_csv(data, dtype={'Col_A': str,'Col_B':int64})
df = pd.read_csv(data, dtype={'Col_A': str,'Col_B':int64})
