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
import pandas as pd
df.head( 10 )
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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 ])
df = 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 ])
df = 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:

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Last Updated :
29 Jul, 2021
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