python pandas dataframe append list as row
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Title: How to Append a List as a Row to a Pandas DataFrame in Python
Introduction:
Pandas is a powerful data manipulation library in Python, and it provides a convenient data structure called DataFrame for handling structured data. In this tutorial, we will explore how to append a list as a row to a Pandas DataFrame.
Prerequisites:
Make sure you have Python and Pandas installed on your machine. You can install Pandas using the following command:
Step 1: Import Pandas
Start by importing the Pandas library in your Python script or Jupyter Notebook.
Step 2: Create a DataFrame
You can create an empty DataFrame or initialize it with existing data. For this tutorial, let's create a simple DataFrame.
Step 3: Define a List to Append
Create a list containing values that you want to append as a new row to the DataFrame.
Step 4: Append the List as a Row
Use the loc indexer to append the list as a new row to the DataFrame.
Here, len(df) returns the index for the new row, and the values from the new_row_data list are assigned to the respective columns.
Step 5: Display the Updated DataFrame
Print the DataFrame to verify that the new row has been successfully appended.
Complete Code Example:
Conclusion:
Appending a list as a row to a Pandas DataFrame is a straightforward process using the loc indexer. This allows you to dynamically expand your DataFrame with new data rows. Experiment with different data types and column configurations to suit your specific use case.
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