Learn Python by Building Data Science Applications

Selection – by columns, indices, or both

Now, let's learn how to access and edit specific values in pandas data structures. We'll start with a toy example—here, I will generate a dataframe from a dictionary of lists:

import pandas as pddata = {'x':[1,2,3], 'y':['a', 'b', 'c'], 'z': [False, True, False]}df = pd.DataFrame(data)

Now, we can take a look at the data we just stored:

>>> df    x   y   z  0   1   a   False1   2   b   True2   3   c   False

As you can see, this frame has three rows and two columns. Let's see how it works:

1. First, let's start selecting columns. Any column can be selected using indexing via square brackets with the column name. As we're asking for one column, it will be returned as a pandas Series object:

>>> df['x'] 1 2 3Name: x, dtype: int ...