Removing top header from Dataframe

i would like to read table from following page :
Countries by GDP

i have tried pandas read_html command and got following result :

import requests

    from bs4 import BeautifulSoup
    import pandas as pd
    data =pd.DataFrame(pd.read_html("https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal)")[2])
    print(data.head())
  Country/Territory UN Region  ... United Nations[15]           
  Country/Territory UN Region  ...           Estimate       Year
0             World         —  ...           85328323       2020
1     United States  Americas  ...           20893746       2020
2             China      Asia  ...           14722801  [n 1]2020
3             Japan      Asia  ...            5057759       2020
4           Germany    Europe  ...            3846414       2020

question is : how can i remove first content?for instance we might iterate through all rows :

for index, row  in data.iterrows():
    print(index,row)

and create empty dataframe and all elements starting by index one(so remove first index and save rest of them in empty dataframe), but i am sure there exist more professional way(maybe we need little help from the regular expression? or BeautifulSoup? ) thanks in advance

Edited

with help of great person, i have solved this problem, but there is one additional issue, please look at table below :

Country/Territory UN Region   Estimate  ...       Year  Estimate       Year
0             World         —  101560901  ...       2021  85328323       2020
1     United States  Americas   25035164  ...       2021  20893746       2020
2             China      Asia   18321197  ...  [n 3]2021  14722801  [n 1]2020
3             Japan      Asia    4300621  ...       2021   5057759       2020
4           Germany    Europe    4031149  ...       2021   3846414       2020

you can see additional nonnecessary symbols [n 1] in front of same data, maybe because of NaN or something like this, can we just filter out such data? and leave rest of them?

Edited :
i have tried to create one common function and then apply to all Year column, here is very simple example : if we extract only first element :

result =data.loc[2,"Year"][0]

which is equal to : [n 1]2022

then of course i can split it :

print(result.split("]")[1])

now it is : 2022 based on this information i have created following function :

def  split_column(text):
   if  len(text)==4:
       return int(text)
   else:
       return int(text.split("]")[1])

logic is that if len(text)==4 means that we have string consist of only 4 digit(like a 2020) and therefore directly convert to number, else apply logic mentioned in the previous example , but when i run :

data['Year'] =data['Year'].apply(split_column,axis=1)

it gives me error :

AttributeError: 'Series' object has no attribute 'split'. Did you mean: 'plot'?

is not it strange? thanks in advance

Solved

finally it is solved with given code :

def  split_column(text):
   if  len(text)==4:
       return int(text)
   elif text=="—":
       return 0
   else:
       return int(text.split("]")[1])

here is complete code :

import requests
from bs4 import BeautifulSoup
import pandas as pd
wiki_link = "https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal)"
def  split_column(text):
   if  len(text)==4:
       return int(text)
   elif text=="—":
       return 0
   else:
       return int(text.split("]")[1])
data = pd.DataFrame(pd.read_html(wiki_link)[2]).droplevel(0, axis=1).loc[:, lambda x: ~x.columns.duplicated()]
data.dropna(inplace=True)
print(data['Year'].value_counts())
print(data['Year'])
# data['Year'] =data['Year'].map(split_column)
# for col in data.columns:
#     print(col)
#     # if col=='Year':
#     #     data[col] =data[col].map(split_column)
data['Year'] =data['Year'].map(split_column)
print(data.head())
# result =data.loc[2,"Year"][0]
# print(result.split("]")[1])
# print(result)
# print(data.head())
# print(data.columns)
# print(data['Year'].loc[2,:][0].split("]")[1])
# print(len(data['Year'].iloc[0,0]))