Now we will look at how you can diversify and improve the presentation of your graphs. This will improve the perception of the graph and can also be useful when creating presentations and other documents with data analysis.

Let's start by adding headings to the graph:

plt.figure(figsize=(11, 9))
dataset.plot()
plt.title("HH spot price")  
plt.show()

You can also change the style of the time series chart. If you want the graph to be not a solid line but consist of dots, then change the value of the linestyle argument to "dotted":

plt.figure(figsize=(11, 9))
dataset.plot(linestyle="dotted")
plt.title("HH spot price")  
plt.show()

And finally, let's figure out how to change the chart's color scheme. You have a huge selection of colormaps, a complete list of which is on the official matplotlib website.

To change the color palette, you just need to change the value of the colormap argument to the name of the palette you are interested in:

plt.figure(figsize=(11, 9))
dataset.plot(label="dataset", colormap="cool")
plt.ylabel("Price")
plt.xlabel("Date")
plt.legend()