Pandas DataFrame is two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns).
Let’s see how can we can add a row at top in pandas DataFrame.
Observe this dataset first.
Python3
# importing pandas moduleimport pandas as pd # making data framedf.head(10) |
Code #1: Adding row at the top of given dataframe by concatenating the old dataframe with new one.
Python3
new_row = pd.DataFrame({'Name':'Geeks', 'Team':'Boston', 'Number':3, 'Position':'PG', 'Age':33, 'Height':'6-2', 'Weight':189, 'College':'MIT', 'Salary':99999}, index =[0])# simply concatenate both dataframesdf = pd.concat([new_row, df]).reset_index(drop = True)df.head(5) |
Output:
Code #2: Adding row at the top of given dataframe by concatenating the old dataframe with new one.
Python3
new_row = pd.DataFrame({'Name':'Geeks', 'Team':'Boston', 'Number':3, 'Position':'PG', 'Age':33, 'Height':'6-2', 'Weight':189, 'College':'MIT', 'Salary':99999}, index =[0])# Concatenate new_row with dfdf = pd.concat([new_row, df[:]]).reset_index(drop = True)df.head(5) |
Output:
Code #3: Adding row at the top of given dataframe by concatenating the old dataframe with new one using df.ix[] method.
Python3
new_row = pd.DataFrame({'Name':'Geeks', 'Team':'Boston', 'Number':3, 'Position':'PG', 'Age':33, 'Height':'6-2', 'Weight':189, 'College':'MIT', 'Salary':99999}, index =[0])df = pd.concat([new_row, df.ix[:]]).reset_index(drop = True)df.head(5) |
Output:
