Time-based indexing is a very powerful method of the pandas library when it comes to time series data. Having time-based indexing allows using a formatted string to select data. See the following code, for example:

df_power.loc['2015-10-02']

The output of the preceding code is given here:

Consumption 1391.05
Wind 81.229
Solar 160.641
Wind+Solar 241.87
Year 2015
Month 10
Weekday Name Friday
Name: 2015-10-02 00:00:00, dtype: object

Note that we used the pandas dataframe loc accessor. In the preceding example, we used a date as a string to select a row. We can use all sorts of techniques to access rows just as we can do with a normal dataframe index.