One common task in data analysis with Pandas is adding or inserting a new row to an existing DataFrame. Whether you need to add a single row or multiple rows, Pandas provides a lot of techniques for this.\u00a0 In this article, we will explore different techniques for adding rows to a Pandas DataFrame using Pandas.<\/p>\n\n\n\n
Let us start by exploring the various ways we can add a row to a DataFrame.<\/p>\n\n\n\n
There are various scenarios where adding rows becomes necessary, such as appending new records to an existing dataset or incorporating new observations into an analysis.<\/p>\n\n\n\n
We can add a single row to a DataFrame using the following methods:<\/p>\n\n\n\n
One way to add a single row to a DataFrame is by using the DataFrame.loc method. This method allows us to specify the position where the new row should be inserted.\u00a0<\/p>\n\n\n\n
To add a row at the end of the DataFrame, we can simply utilize the length of the index of the DataFrame to determine the position.<\/p>\n\n\n\n
Let us try an example:<\/p>\n\n\n\n
import pandas as pd\n\n# Create a DataFrame\ndf = pd.DataFrame({'Name':['Martha', 'Tim', 'Rob', 'Georgia'], 'Maths':[87, 91, 97, 95], 'Science':[83, 99, 84, 76] })\n\n# Display the DataFrame\nprint('Original DataFrame:\\n', df)\n\n# Add a new row\ndf.loc[len(df.index)] = ['Amy', 89, 93]\n\n# Display the New DataFrame\nprint('New DataFrame:\\n', df)<\/pre><\/div>\n\n\n\nOutput:<\/strong><\/p>\n\n\n\nOriginal DataFrame:\n Name Maths Science\n0 Martha 87 83\n1 Tim 91 99\n2 Rob 97 84\n3 Georgia 95 76\n\nNew DataFrame:\n Name Maths Science\n0 Martha 87 83\n1 Tim 91 99\n2 Rob 97 84\n3 Georgia 95 76\n4 Amy 89 93\n<\/code><\/pre>\n\n\n\n2) Using DataFrame.append<\/strong><\/h3>\n\n\n\nAnother method to add a single row to a DataFrame is by using the DataFrame.append function. This method allows us to append a new row as a dictionary or a Series.\u00a0<\/p>\n\n\n\n
We can set the ignore_index parameter to True, and it will automatically assign a new index to the appended row.<\/p>\n\n\n\n
Let us see an example:<\/p>\n\n\n\n
import pandas as pd\n\n# Create a DataFrame\ndf = pd.DataFrame({'Name':['Martha', 'Tim', 'Rob', 'Georgia'], 'Maths':[87, 91, 97, 95], 'Science':[83, 99, 84, 76] })\n\n# Display the DataFrame\nprint('Original DataFrame:\\n', df)\n\n# Create a new row as a dictionary\nnew_row = {'Name': 'Amy', 'Maths': 89, 'Science': 93}\n\n# Append the new row to the DataFrame\ndf = df.append(new_row, ignore_index=True)\n\n# Display the New DataFrame\nprint('New DataFrame:\\n', df)<\/pre><\/div>\n\n\n\nOutput<\/strong>:<\/p>\n\n\n\nOriginal DataFrame:\n Name Maths Science\n0 Martha 87 83\n1 Tim 91 99\n2 Rob 97 84\n3 Georgia 95 76\n\nNew DataFrame:\n Name Maths Science\n0 Martha 87 83\n1 Tim 91 99\n2 Rob 97 84\n3 Georgia 95 76\n4 Amy 89 93\n<\/code><\/pre>\n\n\n\nHow to Add Multiple Rows in a DataFrame?<\/strong><\/h2>\n\n\n\nWe can also add multiple rows to our DataFrame. The need to add multiple rows can arise when we want to merge two DataFrames.<\/p>\n\n\n\n