将包含NaN的Pandas列转换为dtype`int` [英] Convert Pandas column containing NaNs to dtype `int`
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问题描述
我将数据从.csv文件读取到Pandas数据框,如下所示.对于其中一列,即id
,我想将列类型指定为int
.问题在于id
系列的值缺少/为空.
I read data from a .csv file to a Pandas dataframe as below. For one of the columns, namely id
, I want to specify the column type as int
. The problem is the id
series has missing/empty values.
当我在读取.csv时尝试将id
列转换为整数时,我得到:
When I try to cast the id
column to integer while reading the .csv, I get:
df= pd.read_csv("data.csv", dtype={'id': int})
error: Integer column has NA values
或者,我尝试按如下所示转换列类型,但是这次我得到了:
Alternatively, I tried to convert the column type after reading as below, but this time I get:
df= pd.read_csv("data.csv")
df[['id']] = df[['id']].astype(int)
error: Cannot convert NA to integer
我该如何解决?
推荐答案
通常的解决方法是仅使用浮点数.
The usual workaround is to simply use floats.
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