Introduction to Data Visualization with Matplotlib
Ariel Rokem
Data Scientist
fig, ax = plt.subplots() plot_timeseries(ax, climate_change.index, climate_change['co2'], 'blue', 'Time', 'CO2 (ppm)') ax2 = ax.twinx() plot_timeseries(ax2, climate_change.index, climate_change['relative_temp'], 'red', 'Time', 'Relative temperature (Celsius)')
ax2.annotate(">1 degree", xy=(pd.Timestamp("2015-10-06"), 1))
plt.show()
ax2.annotate(">1 degree",
xy=(pd.Timestamp('2015-10-06'), 1),
xytext=(pd.Timestamp('2008-10-06'), -0.2))
ax2.annotate(">1 degree",
xy=(pd.Timestamp('2015-10-06'), 1),
xytext=(pd.Timestamp('2008-10-06'), -0.2),
arrowprops={})
ax2.annotate(">1 degree",
xy=(pd.Timestamp('2015-10-06'), 1),
xytext=(pd.Timestamp('2008-10-06'), -0.2),
arrowprops={"arrowstyle":"->", "color":"gray"})
Introduction to Data Visualization with Matplotlib