Right way to reindex a dataframe?

Question

I have a large dataset which I filtered by location. The end result is something like this:

   column 1  column 2
 0        a         1
 106      b         2
 178      c         3

I guessed that the index values are skipping all over the place since the all the columns with the same locations aren't consecutive. To reset the indices, I did df.reindex(index = np.arange(len(df))), and it worked... but broke everything else. The output is this:

   column 1  column 2
 0        a         1
 1      NAN       NAN
 12     NAN       NAN

I don't have any idea why this is happening, and how I can fix this. Thanks for any help provided!

`df.reset_index(drop=True)` – Corralien Jul 05 '21 at 19:45 — Corralien, Jul 05 '21 at 19:45

score 0 · Accepted Answer · answered Jul 05 '21 at 19:47

0

Use reset_index:

>>> df.reset_index(drop=True)
  column 1  column 2
0        a         1
1        b         2
2        c         3

answered Jul 05 '21 at 19:47

Corralien

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Right way to reindex a dataframe?

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