i have a dataframe that looks like this:
SP_removed
Date Removed
Date Ticker Security
0 January 7, 2021 TIF Tiffany & Co.
1 December 21, 2020 AIV Apartment Investment & Management
2 October 12, 2020 NBL Noble Energy
3 October 9, 2020 NaN NaN
4 October 7, 2020 ETFC E*TRADE Financial
... ... ... ...
258 December 5, 2000 OI Owens-Illinois
259 December 5, 2000 GRA W.R. Grace
260 December 5, 2000 CCK Crown Holdings
261 July 27, 2000 RAD RiteAid
262 December 7, 1999 LDW Laidlaw
263 rows × 3 columns
I want to delete the first header (Date and Removed), but everything i've tried so far didn't work.
Thanks!
Try to use droplevel()
to get rid of the first row column names:
df.columns = df.columns.droplevel()
Example
import pandas as pd
import numpy as np
header = pd.MultiIndex.from_product([['location1','location2'],
['S1','S2','S3']],
names=['loc','S'])
df = pd.DataFrame(np.random.randn(5, 6),
index=['a','b','c','d','e'],
columns=header)
df.columns = df.columns.droplevel()
df