{"id":2874,"date":"2021-08-26T09:30:56","date_gmt":"2021-08-26T04:00:56","guid":{"rendered":"https:\/\/python-programs.com\/?p=2874"},"modified":"2021-11-22T18:45:23","modified_gmt":"2021-11-22T13:15:23","slug":"append-add-row-to-dataframe-in-pandas","status":"publish","type":"post","link":"https:\/\/python-programs.com\/append-add-row-to-dataframe-in-pandas\/","title":{"rendered":"Append\/Add Row to Dataframe in Pandas – dataframe.append() | How to Insert Rows to Pandas Dataframe?"},"content":{"rendered":"
Worried about how to append or add rows to a dataframe in Pandas? Then, this tutorial will guide you completely on how to append rows to a dataframe in Pandas Python using the function dataframe.append() We have listed the various methods for appending rows to a dataframe. In this tutorial, we will discuss how to append or add rows to the dataframe in Pandas. Before going to the main concept let us discuss some basic concepts about pandas and Dataframes.<\/p>\n
Pandas is a package in python that is used to analyze data in a very easy way. The reason why pandas are so famous is that it is very easy to use. But we can not directly use the pandas’ package in our program. To use this package first we have to import it.<\/p>\n
Dataframe is a 2D data structure that store or represent the data in the 2D form or simply say in tabular form. The tabular form consists of rows, columns, and actual data. By using pandas we can manipulate the data as we want i.e we can see as many columns as we want or as many rows as we want. We can group the data or filter the data.<\/p>\n
Let us understand both dataframe and pandas with an easy example<\/p>\n
import pandas as pd\r\nd={\"Name\":[\"Mayank\",\"Raj\",\"Rahul\",\"Samar\"],\r\n \"Marks\":[90,88,97,78]\r\n }\r\ndf=pd.DataFrame(d)\r\nprint(df)<\/pre>\nOutput<\/p>\n
Name Marks\r\n0 Mayank 90\r\n1 Raj 88\r\n2 Rahul 97\r\n3 Samar 78<\/pre>\nHere we see that first, we import our pandas package then we create a dictionary, and out of this dictionary, we create our dataframe. When we see our dataframe we see that it consists of rows and columns and data. There are many ways to create a dataframe like importing excel or CSV files or through a dictionary but this is not the main concern of this article.<\/p>\n
Before understanding the concept of appending rows to a dataframe first we have to know a little bit about the append() method.<\/p>\n
<\/a>append() method<\/h3>\n
append() method is used to append rows of other dataframe at the end of the original or given dataframe. It returns a new dataframe object. If some columns are not presented in the original dataframe but presented in a new dataframe then-new column will also be added in the dataframe and data of that column will become
NAN.<\/code>
\nSyntax: DataFrame.<\/span>append<\/span>(<\/span>other, ignore_index=<\/span>False<\/span>, verify_integrity=<\/span>False<\/span>, sort=<\/span>None<\/span>)<\/span><\/p>\n<\/a>Ways on Pandas append row to Dataframe<\/h2>\n
Method 1- <\/a>How to Add dictionary as a row to dataframe<\/h3>\n
In this method, we see how we can append dictionaries as rows in pandas dataframe. It is a pretty simple way. We have to pass a dictionary in the append() method and our work is done. That dictionary is passed as an argument to
other<\/code> the parameter in the append method. Let us see this with an example.<\/p>\n
<\/p>\n
d={\"Name\":[\"Mayank\",\"Raj\",\"Rahul\",\"Samar\"],\r\n \"Marks\":[90,88,97,78]\r\n }\r\ndf=pd.DataFrame(d)\r\nprint(df)\r\nprint(\"---------------\")\r\nnew_d={\"Name\":\"Gaurav\",\r\n \"Marks\":76}\r\nnew_df=df.append(new_d,ignore_index=True)\r\nprint(new_df)<\/pre>\nOutput:<\/strong><\/p>\n
\n\n\n\n