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[Project] Advanced Pandas: Optimize speed and memory

We made a comparison of various Pandas functions for indexing, vectorization and filtering. We benchmarked and compared their performance. For example, we found out that using a vectorized function to transform data is 82000x faster than using a for-loop with iloc[]. Check out the blog post with more details on various Pandas optimizations here: https://medium.com/bigdatarepublic/advanced-pandas-optimize-speed-and-memory-a654b53be6c2

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.