dataframe, set index from list

If you don’t want index name:

df = pd.DataFrame(tmp, columns=["First", "Second"], index=[i[0] for i in tmp])

Result:

  First Second
a     a     a1
b     b     b1

Change it to list before assigning it to index

df.index = list(df["First"])

set_axis

To set arbitrary values as the index, best practice is to use set_axis:

df = df.set_axis(['idx1', 'idx2'])

#       First  Second
# idx1      a      a1
# idx2      b      b1

set_index (list vs array)

It’s also possible to pass arbitrary values to set_index, but note the difference between passing a list vs array:

• list — set_index assigns these columns as the index:

  df.set_index(['First', 'First'])
  
  #              Second
  # First First        
  # a     a          a1
  # b     b          b1
  

• array (Series/Index/ndarray) — set_index assigns these values as the index:

  df = df.set_index(pd.Series(['First', 'First']))
  
  #        First  Second
  # First      a      a1
  # First      b      b1
  

  _{Note that passing arrays to set_index is very contentious among the devs and may even get deprecated.}

Why not just modify df.index directly?

Directly modifying attributes is fine and is used often, but using methods has its advantages:

• Methods provide better error checking, e.g.:

  df = df.set_axis(['idx1', 'idx2', 'idx3'])
  
  # ValueError: Length mismatch: Expected axis has 2 elements, new values have 3 elements
  

  df.index = ['idx1', 'idx2', 'idx3']
  
  # No error despite length mismatch
  

• Methods can be chained, e.g.:

  df.some_method().set_axis(['idx1', 'idx2']).another_method()
  

import pandas as pd
tmp = [['a', 'a1'], ['b',' b1']]
df = pd.DataFrame(tmp, columns=["First", "Second"]).set_axis([tmp[0][0],tmp[1][0]])
df