Append an empty row in dataframe using pandas
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
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.