Convert Pandas column containing NaNs to dtype ‘int’

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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?

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We hope this article has helped you to resolve the problem. Apart from Convert Pandas column containing NaNs to dtype ‘int’, check other ast Python module-related topics.

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Chen Gonzalez

San Francisco | 2023-01-31

Maybe there are another answers? What Convert Pandas column containing NaNs to dtype ‘int’ exactly means?. I just hope that will not emerge anymore

Davies Richtgofen

Moscow | 2023-01-31

Maybe there are another answers? What Convert Pandas column containing NaNs to dtype ‘int’ exactly means?. Will use it in my bachelor thesis

Davies Richtgofen

Paris | 2023-01-31

Simply put and clear. Thank you for sharing. Convert Pandas column containing NaNs to dtype ‘int’ and other issues with time Python module was always my weak point 😁. Checked yesterday, it works!

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