How to GroupBy and Convert Results to a Dictionary of Lists in Python?

GroupBy Results to a Dictionary of Lists

Suppose you have a dataset like the one provided in the question. By utilizing GroupBy in Python, you aim to organize the data by Column1 and generate a dictionary with lists as values. However, your current code presents challenges with the output displaying numerical indices instead of values.

To address this, a practical solution involves employing df.groupby('Column1')['Column3'].apply(list).to_dict(). This function will gather Column3 based on the groups defined by Column1, convert them into lists through apply(list), and return the result as a dictionary.

Alternatively, you can use a dictionary comprehension, as shown in {k: list(v) for k, v in df.groupby('Column1')['Column3']}. Here, the loop iterates over the groupby object, extracting the keys and values. The values are transformed into lists before being added to the dictionary.

Both methods will produce the desired dictionary of lists, where the keys represent the Column1 values, and the lists contain the corresponding Column3 values grouped by Column1.

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