Convert Pandas column containing NaNs to dtype `int`

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.

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

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

How can I tackle this?

Answer

The lack of NaN rep in integer columns is a pandas “gotcha”.

The usual workaround is to simply use floats.

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