将对象(字符串)转换为 Int32 时出错:TypeError:对象无法转换为 IntegerDtype [英] Error converting object (string) to Int32: TypeError: object cannot be converted to an IntegerDtype

问题描述

我在尝试将 Pandas 中的对象(字符串)列转换为 Int32 时遇到以下错误，Int32 是允许 NA 值的整数类型.

df.column = df.column.astype('Int32')

<块引用>

TypeError: 对象无法转换为 IntegerDtype

我使用的是熊猫版本:0.25.3

解决方案

It's known bug, as defined 此处.

解决方法是先将列转换为 float，然后再转换为 Int32.

确保在进行转换之前从空格中去除您的列:

df.column = df.column.str.strip()

比做转换:

df.column = df.column.astype('float') # 先转为浮点型，再转为 intdf.column = df.column.astype('Int32')

或更简单:

 df.column = df.column.astype('float').astype('Int32') # 或 Int64

I get following error while trying to convert object (string) column in Pandas to Int32 which is integer type that allows for NA values.

df.column = df.column.astype('Int32')

TypeError: object cannot be converted to an IntegerDtype

I'm using pandas version: 0.25.3

解决方案

It's known bug, as explained here.

Workaround is to convert column first to float and than to Int32.

Make sure you strip your column from whitespaces before you do conversion:

df.column = df.column.str.strip()

Than do conversion:

df.column = df.column.astype('float')  # first convert to float before int
df.column = df.column.astype('Int32')

or simpler:

 df.column = df.column.astype('float').astype('Int32') # or Int64

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