Pandas recalculate index after a concatenation

If your index is autogenerated and you don't want to keep it, you can use the ignore_index option. `

train_df = pd.concat(train_class_df_list, ignore_index=True)

This will autogenerate a new index for you, and my guess is that this is exactly what you are after.

After vertical concatenation, if you get an index of [0, n) followed by [0, m), all you need to do is call reset_index:

train_df.reset_index(drop=True)

(you can do this in place using inplace=True).

import pandas as pd

>>> pd.concat([
    pd.DataFrame({'a': [1, 2]}), 
    pd.DataFrame({'a': [1, 2]})]).reset_index(drop=True)
    a
0   1
1   2
2   1
3   2

This should work:

train_df.reset_index(inplace=True, drop=True) 

Set drop to True to avoid an additional column in your dataframe.