Number of file : 894 total file size : 22.2GB I have to do machine learning by reading many csv files. There is not enough memory to read at once.

First, I'm writing Spark df named calendar as a parquet file named cal. calendar.write.parquet("/user/vusal.babashov/dataset/cal", mode="overwrite") Then, I'm copying it from Hadoo...

Consider the following code import dask import dask.dataframe as dd import pandas as pd data_dict = {'data1':[1,2,3,4,5,6,7,8,9,10]} df_pd = pd.DataFrame(data_dict) df_dask = dd.from_pandas(df...

I am using read_csv() to read a long list of csv files and return two dataframes. I have managed to speed up this action by using dask. Unfortunately, I have not been able to return multiple variables...