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Converting Complex XML Files to Pandas DataFrame/CSV in Python

Data scientists often encounter a variety of data formats in their work. One such format is XML (eXtensible Markup Language), which is …

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Converting Pandas DataFrame to JSON Object Column: A Guide

Data scientists often encounter the need to convert a Pandas DataFrame to a JSON object column. This conversion is crucial when dealing …

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Converting PySpark DataFrame Column to List: A Guide

Data scientists often need to convert DataFrame columns to lists for various reasons, such as data manipulation, feature engineering, …

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Counting Rows in PySpark DataFrames: A Guide

Data science is a field that's constantly evolving, with new tools and techniques being introduced regularly. One such tool that has …

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Creating Custom Loss Functions in Keras/TensorFlow

In the world of machine learning, loss functions play a pivotal role. They measure the inconsistency between predicted and actual …

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Custom Loss Function in PyTorch: A Guide

As a data scientist or software engineer, you might have come across situations where the standard loss functions available in PyTorch …

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Downloading a CSV from a URL and Converting it to a DataFrame using Python Pandas

In this blog, we will learn about the potent role Python's Pandas library plays in data science, particularly in the manipulation and …

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Efficiently Appending to a DataFrame within a For Loop in Python

Data manipulation is a fundamental skill for any data scientist. One common task is appending to a DataFrame within a for loop. …

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