Append an empty row in dataframe using pandas

Solution 1:

Add a new pandas.Series using pandas.DataFrame.append().

If you wish to specify the name (AKA the "index") of the new row, use:

df.append(pandas.Series(name='NameOfNewRow'))

If you don't wish to name the new row, use:

df.append(pandas.Series(), ignore_index=True)

where df is your pandas.DataFrame.

Solution 2:

You can add it by appending a Series to the dataframe as follows. I am assuming by blank you mean you want to add a row containing only "Nan". You can first create a Series object with Nan. Make sure you specify the columns while defining 'Series' object in the -Index parameter. The you can append it to the DF. Hope it helps!

from numpy import nan as Nan
import pandas as pd

>>> df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
...                     'B': ['B0', 'B1', 'B2', 'B3'],
...                     'C': ['C0', 'C1', 'C2', 'C3'],
...                     'D': ['D0', 'D1', 'D2', 'D3']},
...                     index=[0, 1, 2, 3])

>>> s2 = pd.Series([Nan,Nan,Nan,Nan], index=['A', 'B', 'C', 'D'])
>>> result = df1.append(s2)
>>> result
     A    B    C    D
0   A0   B0   C0   D0
1   A1   B1   C1   D1
2   A2   B2   C2   D2
3   A3   B3   C3   D3
4  NaN  NaN  NaN  NaN

Solution 3:

You can add a new series, and name it at the same time. The name will be the index of the new row, and all the values will automatically be NaN.

df.append(pd.Series(name='Afterthought'))