Add a row at top in pandas DataFrame Last Updated : 29 Jul, 2021 Summarize Suggest changes Share Like Article Like Report 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 module import pandas as pd # making data frame df = pd.read_csv("https://media.geeksforgeeks.org/wp-content/uploads/nba.csv") df.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 dataframes 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]) # Concatenate new_row with df 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: Advertise with us Next Article Python | Pandas str.join() to join string/list elements with passed delimiter S Shivam_k Follow Similar Reads Pandas Tutorial Pandas is an open-source software library designed for data manipulation and analysis. It provides data structures like series and DataFrames to easily clean, transform and analyze large datasets and integrates with other Python libraries, such as NumPy and Matplotlib. It offers functions for data t 6 min read IntroductionPandas IntroductionPandas is open-source Python library which is used for data manipulation and analysis. It consist of data structures and functions to perform efficient operations on data. 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