Quantitative comparisons: scatter plots

Introduction to Data Visualization with Matplotlib

Ariel Rokem

Data Scientist

Introducing scatter plots

fig, ax = plt.subplots()

ax.scatter(climate_change["co2"], climate_change["relative_temp"])

ax.set_xlabel("CO2 (ppm)")
ax.set_ylabel("Relative temperature (Celsius)")
plt.show()

Customizing scatter plots

eighties = climate_change["1980-01-01":"1989-12-31"]
nineties = climate_change["1990-01-01":"1999-12-31"]

fig, ax = plt.subplots()

ax.scatter(eighties["co2"], eighties["relative_temp"],
           color="red", label="eighties")

ax.scatter(nineties["co2"], nineties["relative_temp"],
           color="blue", label="nineties")

ax.legend()

ax.set_xlabel("CO2 (ppm)")
ax.set_ylabel("Relative temperature (Celsius)")

plt.show()

Encoding a comparison by color

Encoding a third variable by color

fig, ax = plt.subplots()

ax.scatter(climate_change["co2"], climate_change["relative_temp"],
           c=climate_change.index)

ax.set_xlabel("CO2 (ppm)")
ax.set_ylabel("Relative temperature (Celsius)")
plt.show()

Encoding time in color

Practice making your own scatter plots!

Introduction to Data Visualization with Matplotlib