Bar Charts and Histograms with Matplotlib

In this tutorial, we cover bar charts and histograms with Matplotlib. First, let's cover a bar chart.

import matplotlib.pyplot as plt[1,3,5,7,9],[5,2,7,8,2], label="Example one")[2,4,6,8,10],[8,6,2,5,6], label="Example two", color='g')
plt.xlabel('bar number')
plt.ylabel('bar height')

plt.title('Epic Graph\nAnother Line! Whoa')

The creates the bar chart for us. If you do not explicitly choose a color, then, despite doing multiple plots, all bars will look the same. This gives us a change to cover a new Matplotlib customization option, however. You can use color to color just about any kind of plot, using colors like g for green, b for blue, r for red, and so on. You can also use hex color codes, like #191970

Next, we can cover histograms. Very much like a bar chart, histograms tend to show distribution by grouping segments together. Examples of this might be age groups, or scores on a test. Rather than showing every single age a group might be, maybe you just show people from 20-25, 25-30... and so on. Here's an example:

import matplotlib.pyplot as plt

population_ages = [22,55,62,45,21,22,34,42,42,4,99,102,110,120,121,122,130,111,115,112,80,75,65,54,44,43,42,48]

bins = [0,10,20,30,40,50,60,70,80,90,100,110,120,130]

plt.hist(population_ages, bins, histtype='bar', rwidth=0.8)

plt.title('Interesting Graph\nCheck it out')

The resulting graph is:

For plt.hist, you first put in all of the values, then you specify into what "bins" or containers you will place the data into. In our case, we are plotting a bunch of ages, and we want to display them in terms of increments of 10 years. We give the bars a width of 0.8, but you can choose something else if you want to make the bars thicker, or thinner.

The next tutorial:

  • Introduction to Matplotlib and basic line
  • Legends, Titles, and Labels with Matplotlib
  • Bar Charts and Histograms with Matplotlib
  • Scatter Plots with Matplotlib
  • Stack Plots with Matplotlib
  • Pie Charts with Matplotlib
  • Loading Data from Files for Matplotlib
  • Data from the Internet for Matplotlib
  • Converting date stamps for Matplotlib
  • Basic customization with Matplotlib
  • Unix Time with Matplotlib
  • Colors and Fills with Matplotlib
  • Spines and Horizontal Lines with Matplotlib
  • Candlestick OHLC graphs with Matplotlib
  • Styles with Matplotlib
  • Live Graphs with Matplotlib
  • Annotations and Text with Matplotlib
  • Annotating Last Price Stock Chart with Matplotlib
  • Subplots with Matplotlib
  • Implementing Subplots to our Chart with Matplotlib
  • More indicator data with Matplotlib
  • Custom fills, pruning, and cleaning with Matplotlib
  • Share X Axis, sharex, with Matplotlib
  • Multi Y Axis with twinx Matplotlib
  • Custom Legends with Matplotlib
  • Basemap Geographic Plotting with Matplotlib
  • Basemap Customization with Matplotlib
  • Plotting Coordinates in Basemap with Matplotlib
  • 3D graphs with Matplotlib
  • 3D Scatter Plot with Matplotlib
  • 3D Bar Chart with Matplotlib
  • Conclusion with Matplotlib