This is a little trick I used to append new rows to a Pandas DataFrame. This method is similar to appending a new item to a list.
Create an empty DataFrame
df = pd.DataFrame(columns=['A','B']) df
Add rows by dynamically by leveraging loc[] and len()
The .loc[] method allows you to return a row by identifying the index value. The len() makes this operation dynamic because it will always produce a value 1 greater than the highest index. Because the index doesn’t exist in the DataFrame, Pandas creates a new row. Lastly, pass in the new values as a list to create the new row. Note that the length of your list should be the same as the number of columns in the DataFrame.
df.loc[len(df)] = [1,2] df
Adding another row is as simple as specifying the values for the next row with a list.
df.loc[len(df)] = [3,4] df
By passing in one value for the index, Pandas will set that value for the entire row.
df.loc[len(df)] = 'hello' df
Final Thoughts
Check out more Python tricks in this Colab Notebook or in my recent Python Posts.
Thanks for reading!