Appending new rows to DataFrames

When performing data analysis, it is far more common to create new columns than new rows. This is because a new row of data usually represents a new observation, and as an analyst, it is typically not your job to continually capture new data. Data capture is usually left to other platforms like relational database management systems. Nevertheless, it is a necessary feature to know as it will crop up from time to time.

In this recipe, we will begin by appending rows to a small dataset with the .loc attribute and then transition to using the .append method.

How to do it…

1. Read in the names dataset, and output it:

   >>> import pandas as pd
   >>> import numpy as np
   >>> names = pd.read_csv('data/names.csv')
   >>> names
          Name  Age
   0  Cornelia   70
   1     Abbas   69
   2  Penelope    4
   3      Niko    2
   

2. Let's create a list that contains some new data and use the ...