400x times faster Pandas Data Frame Iteration
Image by Michal Jarmoluk from PixabayData processing is and data wrangling is important components of a data science model development pipeline. A data scientist spends 80% of their time preparing the dataset to make it fit for modeling. Sometimes performing data wrangling and explorations for a large-sized dataset becomes a tedious task, and one is only left to either…
Announcing google-cloud-bigquery Version 1.17.0: Query Results to DataFrame 31x Faster with Apache Arrow
Announcing google-cloud-bigquery Version 1.17.0: Query Results to DataFrame 31x Faster with Apache Arrow Tim Swast on July 29, 2019; updated September 25, 2019 Upgrade to the latest google-cloud-bigquery and google-cloud-bigquery-storage packages to download query results to a DataFrame 4.5 times faster compared to the same method with version 1.16.0. If you aren't using the BigQuery Storage API y
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Analyzing Python Pandas' memory leak and the fix
