temperature_anomaly_and_CO2

rescale = lambda y: (y - np.min(y)) / (np.max(y) - np.min(y))

fig, ax1 = plt.subplots()

x = df_temp.index.tolist()
y = df_temp["mean"].values.tolist()

ax1.bar(x, y, color = my_cmap(rescale(y)), width = 0.8)
ax1.set_ylabel("Temperature anomaly \n relative to 1951-80 mean (°C)", color = "red")
ax1.tick_params(axis='y', color='red', labelcolor='red')
ax1.grid(False)

#Add twin axes
ax2 = ax1.twinx()
ax2.plot(co2_annual, color = "black", marker = "o", markersize = 4)
ax2.set_ylabel("CO$_2$ (ppm)")
ax2.grid(False)

ax2.tick_params(axis='y')

for pos in ["top"]:
    ax1.spines[pos].set_visible(False)
    ax2.spines[pos].set_visible(False)

plt.grid()
plt.title("Global temperature anomaly and atmospheric CO$_2$ emissions concentration\n (1959-2021)",
         pad = 20)

plt.savefig("../output/co2 emissions and temperature anomalies bar plot.jpeg",
           dpi = 300)

plt.show()