Here are some question-style titles based on the information provided: Clear and Concise: * How to Split Comma-Separated Values into Multiple Rows in a Pandas DataFrame? * Splitting Columns with Com

Split Cells into Multiple Rows in pandas DataFrame

Question:

How can I split comma-separated [package and package_code] columns into multiple rows in a pandas DataFrame, creating a new row for each package with its corresponding order details?

Answer:

Method 1: (pandas >= 0.25)

<code class="python">df.set_index(['order_id', 'order_date']) \
    .apply(lambda x: x.str.split(',').explode()) \
    .reset_index() </code>

Method 2: (pandas <= 0.24)

<code class="python">(df.set_index(['order_date', 'order_id'])
   .stack()
   .str.split(',', expand=True)
   .stack()
   .unstack(-2)
   .reset_index(-1, drop=True)
   .reset_index()
)</code>

Details:

1. Set the columns that should not be split as the index.
2. Use stack() to flatten the rows.
3. Use str.split() with expand=True to split the values on the comma and expand them into columns.
4. Stack the resulting DataFrame again to flatten the rows.
5. Use unstack(-2) to create new columns from the second last level of the index.
6. Use reset_index(-1, drop=True) to remove the superfluous last level of the index.
7. Reset the index to return it to the original order.

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