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I have two DataFrames, table_of_concepts_df (the left one) and jobs_score_table_of_context_df (the right one) of the same dtype int64 as you can see in images. enter image description here

enter image description here

But, after merging them, the type of columns from the right DataFrame changes to float64: merged_df = table_of_concepts_df.merge(jobs_score_table_of_context_df, how="left", left_index=True, right_index=True) merged_df.dropna(inplace=True). enter image description here I haven't found any explanation in the pandas documentation relative to this weird behavior. Could someone can give me explanation on why ? Thanks.

Guy NANA
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  • i think its because after merging, theres NULL value in that columns (that changed to float). because int dtype cant contain null value – biyazelnut Mar 29 '23 at 08:47

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