How to Split Comma-Separated Values into Multiple Rows in Pandas DataFrames?

Splitting Cell into Multiple Rows in Pandas DataFrames

When dealing with comma-separated values in pandas dataframes, converting them into their own rows can be necessary for further analysis. Here's how to achieve this:

For Pandas >= 0.25:

This method simplifies the process:

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

   order_id order_date package package_code
0         1  20/5/2018      p1         #111
1         1  20/5/2018      p2         #222
2         1  20/5/2018      p3         #333
3         3  22/5/2018      p4         #444
4         7  23/5/2018      p5         #555
5         7  23/5/2018      p6         #666</code>

For Pandas

For earlier Pandas versions, a different approach is necessary:

<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()
)

  order_date  order_id package package_code
0  20/5/2018         1      p1         #111
1  20/5/2018         1      p2         #222
2  20/5/2018         1      p3         #333
3  22/5/2018         3      p4         #444
4  23/5/2018         7      p5         #555
5  23/5/2018         7      p6         #666</code>

Details:

Both methods involve several steps:

• Set non-splitting columns as the index.
• Split values on commas using str.split.
• Stack the split values into rows.
• Unstack to move the split values into separate columns.
• Reset the final index.

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