Hands-On Data Analysis with Pandas

Selection

With selection, we grab entire columns. Using our earthquake data, let's grab the mag column, which contains the magnitudes of the earthquakes:

>>> df.mag0       1.351       1.292       3.423       0.444       2.16        ... 9327    0.629328    1.009329    2.409330    1.109331    0.66Name: mag, Length: 9332, dtype: float64

In the preceding example, we selected the mag column as an attribute of the dataframe; however, we can also access it with a dictionary-like notation:

>>> df['mag']0       1.351       1.292       3.423       0.444       2.16        ... 9327    0.629328    1.009329    2.409330    1.109331    0.66Name: mag, Length: 9332, dtype: float64

We aren't limited to selecting one column at a time. By passing a list to the dictionary lookup, we can select many columns, giving us a DataFrame object that is a subset of our ...