pandas 将具有数字和nan的对象转换为int或float [英] pandas convert objects with numbers and nans to ints or floats

问题描述

知道类似的案例已经被回答了好几次了，我还是无法使它生效。

with the knowledge that similar cases have been answered several times I couldn't make it work anyway.

样本数据：

10
5
20

5

6

在我弄清楚以下内容之后：

after i figured out that with:

df = df['column_name'].astype(str).astype(int)

如果输入数据中没有nans，它将起作用。

it would work if there wasn't nans in the input data.

error: invalid literal for int() with base 10: 'nan'

我也尝试过使用float，但同样会出现错误

Also I did try to use float instead but it gives an error as well

error: could not convert string to float

我想念什么？

输出可以是带有 null， nan，的任何内容，例如：

output can be anything with "null", "nan", "" for example:

10
5
20
null
5
null
6

推荐答案

您可以使用 to_numeric 和 errors ='coerce'对于列中的浮点数和整数使用 可空整数数据类型 （熊猫0.24 +）：

You can convert to numeric with to_numeric and errors='coerce' for floats in columns and for integers use nullable integer data type (pandas 0.24+):

df['column_name'] = pd.to_numeric(df['column_name'], errors='coerce').astype('Int64')
print (df)
   column_name
0           10
1            5
2           20
3          NaN
4            5
5          NaN
6            6

详细信息：

print (pd.to_numeric(df['column_name'], errors='coerce'))
0    10.0
1     5.0
2    20.0
3     NaN
4     5.0
5     NaN
6     6.0
Name: column_name, dtype: float64

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