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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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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
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
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!