As the number of fields is growing in each industry, in each Data sources. It is almost impossible to store all the variables in single Data table. So ideally we received Data tables in multiple files. In these situation, whenever
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As the number of fields is growing in each industry, in each Data sources. It is almost impossible to store all the variables in single Data table. So ideally we received Data tables in multiple files. In these situation, whenever
As the number of fields is growing in each industry, in each Data sources. It is almost impossible to store all the variables in single Data table. So ideally we received Data tables in multiple files. In these situation, whenever
As the number of fields is growing in each industry, in each Data sources. It is almost impossible to store all the variables in single Data table. So ideally we received Data tables in multiple files. In these situation, whenever
As the number of fields is growing in each industry, in each Data sources. It is almost impossible to store all the variables in single Data table. So ideally we received Data tables in multiple files. In these situation, whenever
As the number of fields is growing in each industry, in each Data sources. It is almost impossible to store all the variables in single Data table. So ideally we received Data tables in multiple files. In these situation, whenever
As the number of fields is growing in each industry, in each Data sources. It is almost impossible to store all the variables in single Data table. So ideally we received Data tables in multiple files. In these situation, whenever
As the number of fields is growing in each industry, in each Data sources. It is almost impossible to store all the variables in single Data table. So ideally we received Data tables in multiple files. In these situation, whenever
As the number of fields is growing in each industry, in each Data sources. It is almost impossible to store all the variables in single Data table. So ideally we received Data tables in multiple files. In these situation, whenever
Sometimes Dataframe does not contains header in the column names. Pyspark has union function that helps in stacking one Dataframe below the other. In case Dataframe does not contain header, then it is important to do basic checks before importing.