Data colouring Matplotlib bar charts

We have previously seen how to create a bar chart of the average daily temperatures by month:

We can style the bar chart by controlling the colour and outline of the bar. Here is an example:

Matplotlib allows us to set the colour of each bar individually. This chart sets the colour of each month depending on the season:

Here is the code to do that:

import matplotlib.pyplot as plt
import csv

with open("2009-temp-monthly.csv") as csv_file:
    csv_reader = csv.reader(csv_file, quoting=csv.QUOTE_NONNUMERIC)
    temperature = [x[0] for x in csv_reader]

month_names = ["J", "F", "M", "A", "M", "J",
               "J", "A", "S", "O", "N", "D"]

months = range(12)

plt.title("Monthly temperature 2009")
plt.xlabel("Month")
plt.ylabel("Temperature")
plt.xticks(months, month_names)

colors = ['c', 'c', 'c', 'g', 'g', 'g', 'y', 'y', 'y', 'm', 'm', 'm']

plt.bar(months, temperature, color=colors)
plt.show()

This code is available on github as barchart_monthly_temperatures_seasons.py.

This code is very similar to the previous code for plotting a simple bar chart. The difference is that we have created a list colors, containing 12 color strings (one for each month).

The first three colours are cyan, to represent winter (January, February, and March are predominantly winter). The next three are gree for spring, and so on.

We pass this list into the plt.bar method as the named parameter color. This tells Matplotlib to give each month bar its own colour fron the list. So the first three bars are cyan, the next three are green, etc.

Making the colours data dependent

So far we have used fixed colours for each month. This effect is mainly decorative, it doesn't tell us a great deal extra about the data.

In this graph we colour each bar according to the temperature value:

• Less than 7.5 degrees is cyan.
• Greater than or equal to 17.5 degrees is yellow.
• The temeperatures in between are green.

Here it is:

This is the code:

import matplotlib.pyplot as plt
import csv

with open("2009-temp-monthly.csv") as csv_file:
    csv_reader = csv.reader(csv_file, quoting=csv.QUOTE_NONNUMERIC)
    temperature = [x[0] for x in csv_reader]

month_names = ["J", "F", "M", "A", "M", "J",
               "J", "A", "S", "O", "N", "D"]

months = range(12)

plt.title("Monthly temperature 2009")
plt.xlabel("Month")
plt.ylabel("Temperature")
plt.xticks(months, month_names)

colors = ['c' if t < 7.5 else ('g' if t < 17.5 else 'y') for t in temperature]

plt.bar(months, temperature, color=colors)
plt.show()

This code is available on github as barchart_monthly_temperatures_coded.py.

The main work is done by this list comprhension:

colors = ['c' if t < 7.5 else ('g' if t < 17.5 else 'y') for t in temperature]

It loops over the list of 12 monthly temperatures, and sets the colors list to the correct colour based on the value of the temperature.

The code picks the colours dynamically, which means that if you run the same code with different data, the colouring would reflect the new data.