Add a row at top in pandas DataFrame

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.

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# importing pandas module 
import pandas as pd 
    
# making data frame 
  
df.head(10)

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Code #1: Adding row at the top of given datarame by concatenating the old dataframe with new one.

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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 dataframes
df = pd.concat([new_row, df]).reset_index(drop = True)
df.head(5)

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Output:

 
Code #2: Adding row at the top of given datarame by concatenating the old dataframe with new one.

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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 df 
df = pd.concat([new_row, df[:]]).reset_index(drop = True)
df.head(5)

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Output:

 
Code #3: Adding row at the top of given datarame by concatenating the old dataframe with new one using df.ix[] method.

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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)

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Output:



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