pandas stack columns to rows

pandas is a powerful data manipulation library for python. one common task in data analysis is transforming wide-format data (columns) into long-format data (rows). the stack function in pandas can be used for this purpose. this tutorial will guide you through the process of stacking columns to rows using pandas.
make sure you have the pandas library installed. you can install it using the following command:
let's start with a simple example dataset in a dataframe:
this will create a dataframe with columns 'id', 'name', 'math_score', and 'english_score'.
to stack columns to rows, we can use the set_index and stack functions. here's the code:
explanation:
the resulting dataframe, stacked_df, will have columns 'id', 'name', 'subject', and 'score'. the 'subject' column contains the original column names ('math_score' and 'english_score'), and the 'score' column contains the corresponding values.
in this tutorial, we've learned how to use pandas to stack columns to rows using the stack function. this technique is helpful when dealing with datasets in wide format and needing to reshape them into long format for analysis or visualization.
feel free to adapt this example to your specific use case and explore additional features provided by pandas for data manipulation.
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