overwriting data type in python wrapper for visualization

[hamed_digaleh]

Hi everyone,

I’ve problem in reading .csv in wrapper header file and it detect data type wrong. I originally imported moth_year column as text in data transform and here I do want to have “dataset” data from all column as text but it converts this column automatically to number format.  Do you have any idea how can I overwrite these autogenerate wrapper??

# Prolog - Auto Generated #

pandas.read_csv('input_df_79f27d2d-28f8-4512-9a2f-308cf041f073.csv')

what I tried till now:

• Turning off auto type detection in setting
• Changing data type via transform data -> Transform -> Data Type -> Text

Thanks and kind Regards

[amitchandak]

@hamed_digaleh , In Edit query mode , right click on table and open advance editor, You will see the column name with data types. You can change it(Data type) there.

Keep backup of file.

[hamed_digaleh]

I already changed data type power query editor, and the type of column in the model is text. but by running python visualize it redetect data type and it cause missdetection (in this case detect text column as number)

[Greg_Deckler]

@hamed_digaleh - Ah, I understand now. So, no. I have run into this with R visuals because it wipes out the duplicates, which is problematic if you are trying to generate a word cloud via R code! 😕

You will need to convert it back to a date within the Python code I imagine.

[hamed_digaleh]

@Greg_Deckler  yes, but it is easier to fix the problem in read_csv part if it could be overwritten to add data type as pre setting as str.

[Greg_Deckler]

@hamed_digaleh - So you have a source step where you import the data, why doesn't a subsequent step of transforming the column to text? Are you getting an error?

[hamed_digaleh]

In Source step data are read as text and in the write format (e.g. in this case MONTH_YEARS column as "02.2020"), but the problem rise when it tries to run the python wrapper and it conver these text in auto generate part to number (e.g. MONTH_YEARS reads as 22.02 which is wrong).