Right way to reverse pandas.DataFrame?

Question

Here is my code:

import pandas as pd

data = pd.DataFrame({\'Odd\':[1,3,5,6,7,9], \'Even\':[0,2,4,6,8,10]})

for i in reversed(data):
    print(data[\'Odd\']         


        

Answer 1

This works:

    for i,r in data[::-1].iterrows():
        print(r['Odd'], r['Even'])

Answer 2

You can reverse the rows in an even simpler way:

df[::-1]

Answer 3

data.reindex(index=data.index[::-1])

or simply:

data.iloc[::-1]

will reverse your data frame, if you want to have a for loop which goes from down to up you may do:

for idx in reversed(data.index):
    print(idx, data.loc[idx, 'Even'], data.loc[idx, 'Odd'])

or

for idx in reversed(data.index):
    print(idx, data.Even[idx], data.Odd[idx])

You are getting an error because reversed first calls data.__len__() which returns 6. Then it tries to call data[j - 1] for j in range(6, 0, -1), and the first call would be data[5]; but in pandas dataframe data[5] means column 5, and there is no column 5 so it will throw an exception. ( see docs )

Answer 4

The right way to do this is:

data = data.sort_index(ascending=False)

This approach has the benefits of (1) being a single line, (2) not requiring a utility function, and most importantly (3) not actually changing any of the data in the dataframe.

Answer 5

None of the existing answers resets the index after reversing the dataframe.

For this, do the following:

 data[::-1].reset_index()

Here's a utility function that also removes the old index column, as per @Tim's comment:

def reset_my_index(df):
  res = df[::-1].reset_index(drop=True)
  return(res)

Simply pass your dataframe into the function

Answer 6

The simplest solution might be

data = data[::-1]