from pylab import * from datetime import datetime, timezone  mi, ma, gu, t = [], [], [], [] matplotlib.rcParams.update({'font.size': 16})  # CSV file from https://ccaf.io/cbeci/api/v1.4.0/download/data?price=0.05 f = open("export.csv") for num, l in enumerate(f.readlines()):     if num < 2: continue     x = l.split(",")     ts = int(x[0])     d = datetime.fromtimestamp(ts, timezone.utc)     t.append(d)     ma.append(float(x[5]))     mi.append(float(x[6]))     gu.append(float(x[7]))  figure(figsize = (9, 7)) fill_between(t, mi, ma, color = "#d8d8d8") plot(t, ma, label = "Upper bound" , lw = 3.5, c = "#1829af", alpha = .5) plot(t, mi, label = "Lower bound" , lw = 3.5, c = "#18af23", alpha = .5) plot(t, gu, label = "Estimate", lw = 5.5, c = "#af2318")  # Estimate is drawn last (so that it is not obscured by the other curves), # but it should come in _second_ place in the legend, so shuffle legend order accordingly: handles, labels = gca().get_legend_handles_labels() order = [0, 2, 1] legend([handles[idx] for idx in order], [labels[idx] for idx in order], loc = "upper left")  xlabel("Year") ylabel("[TWh]") title("Bitcoin annualized electricity consumption") axis([datetime(2016, 1, 1), datetime(2024, 1, 1), 0, 500]) grid() gca().tick_params(axis = "both", pad = 14) gca().set_position([.15, .15, .8, .75]) text(datetime(2024, 1, 1), -90, 'Source: University of Cambridge', va = 'bottom', ha = 'right' , size = 14) savefig("Bitcoin electricity consumption.svg")  show()