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Data Analysis at Warp Speed: Explore the World of Polars

Mlearning.ai

Goal The objective of this post is to demonstrate how Polars performance is much better than other open-source libraries in a variety of data analysis tasks, such as data cleaning, data wrangling, and data visualization. ? Contributions welcome ! ?Acknowledgments

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Discover Interoperability between Python, MATLAB and R Languages

Pickl AI

Step 2: Numerical Computation in MATLAB Once the data is cleaned, you can use MATLAB for heavy numerical computations. You can load the cleaned data and use MATLAB’s extensive mathematical functions for analysis. Load the cleaned data from the CSV file, and perform statistical tests or models like linear regression.

Python 52
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Top 15 Data Analytics Projects in 2023 for beginners to Experienced

Pickl AI

Here are some project ideas suitable for students interested in big data analytics with Python: 1. Kaggle datasets) and use Python’s Pandas library to perform data cleaning, data wrangling, and exploratory data analysis (EDA). Analyzing Large Datasets: Choose a large dataset from public sources (e.g.,