To demonstrate the plotting functionality, we plot the energy price changes on May 16, 2020. For this, we construct a subframe of the data from that day:
solar_all.loc['2020-05-16'].plot(y='SEK')
You can see that we indexed here with the full day. This is a short form of slicing:
solar_all.loc['2020-05-16 00:00':'2020-05-16 23:59']
The resulting plot, Figure 10.1, shows the hourly variation of electricity prices in Swedish crowns on a typical day of the year.
Figure 10.1: Plotting one column of a dataframe; the hourly price in Swedish crowns (SEK) per kWh on May 16, 2020
pandas' plot command is built upon plot from the module matplotlib.pyplot, which we met in Chapter 6, Plotting.
It accepts the same parameters, for example, linestyle or marker.
The data for the x axis is taken from the dataframe index if not otherwise specified. Alternatively, you can plot one dataframe column versus another.
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