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Read Large Dataset Quickly - Feather vs Parquet vs Jay vs CSV #python #pandas #coding #programming
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We generally prefer CSV files to read data for Data science stuff. But While dealing with large datasets like millions of rows, CSV file format outperforms. It takes quite a long time to load the data. Some other file formats also exist that work well while dealing with large datasets.
Some Efficient File Format:-
Feather format - It is fast, lightweight, and uses binary file format for storing data. It takes 122 milliseconds to read One million rows.
Parquet format - Parquet is more efficient in terms of storage and performance. whereas data is stored in a row-oriented approach. And it takes 159 milliseconds to read 1 million row
Jay format - It also uses a binary format for storing data frames and because of that it is fast, lightweight, and easy-to-use. And it takes only 235 microseconds, which is the least of all.
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Some Efficient File Format:-
Feather format - It is fast, lightweight, and uses binary file format for storing data. It takes 122 milliseconds to read One million rows.
Parquet format - Parquet is more efficient in terms of storage and performance. whereas data is stored in a row-oriented approach. And it takes 159 milliseconds to read 1 million row
Jay format - It also uses a binary format for storing data frames and because of that it is fast, lightweight, and easy-to-use. And it takes only 235 microseconds, which is the least of all.
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Show your support by subscribing to my channel.
Thank you
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