#Pd drop duplicates download

itemid timestamp y y_lowerĤ3406 T16:00:00 27.61612174350883 4.7486855702091635ĭataset_bytes_array, dataset_metadata = download_object_directory_bytes(ĭataset_storage.bucket_name, prefix=f'/datasets',ĭataset_bytes_data = b''.join(dataset_bytes_array)Īfter obtaining the final bytes array, I create a Pandas dataframe in the following way: dataset_df = pd.read_csv(īytesIO(dataset_bytes_data), on_bad_lines='warn', keep_default_na=False, dtype=object, Method 1: Remove Duplicates in One Column and Keep Row with Max df.sortvalues('var2', ascendingFalse).dropduplicates('var1').sortindex() Method 2: Remove Duplicates in Multiple Columns and Keep Row with Max df.sortvalues('var3', ascendingFalse).dropduplicates( 'var1', 'var2'). We can use Pandas built-in method dropduplicates() to drop duplicate rows. Removing duplicates is a part of data cleaning.

Those csv's are all equals in format so I'm expecting always the same number of data. Pandas dropduplicates () Function Syntax dropduplicates ( self, subsetNone, keep 'first', inplace False ) subset: Subset takes a column or list of column label for identifying duplicate rows.

#Pd drop duplicates download

I have multiple csv in cloud which I have to download as bytes.