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Read dataframe with datatype

Read dataframe with datatype

I have a dataset with a column 'Serial Number' with data type string, Text (see attached)

When I read it in a notebook 


mydataset = dataiku.Dataset(dataset_name)
df_f3 = mydataset.get_dataframe()
df_f3['Serial Number'].dtypes


 I get dtype('int64')

 And it's too late to convert it to string, because the original values have leading 0's which are lost when the values are read as integers.

How can I force it to read the column as a string? I tried 



df_f3 = mydataset.get_dataframe(infer_with_pandas=False)



but this failed for an unrelated reason, in a different column

 ValueError: Integer column has NA values in column 47

I'm using DSS Version 9.0.7

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1 Reply

Hi @davidmakovoz ,

If you want to keep the original values leading zero you should indeed use

df_f3 = mydataset.get_dataframe(infer_with_pandas=False) 

In your case is failing because most likely there are empty cells in the other column and pandas is not able to deal with empty integers, it converts to double and uses NaN for empty value.

You should check if there are empty values in the other column and replace the empty values with an integer like 0.

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