Matplolib plotting resume in action

Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.

Resources

Useful Cheat Sheets

Official Matplotlib cheat sheets

%matplotlib inline
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd

Drawing Line Charts

A line chart is a set of points with coordinates (x, y) between which a line is drawn: the more points are used in the plot, the smoother the plot looks. Lest work a couple of examples in order to understand what Matplotlib can do for our project.

Simple Line Plot

plt.title('My First House Plot')
 plt.xlabel('Abscissae')
 plt.ylabel('Ordinate')
 plt.xlim([-1,2])
 plt.ylim([-1,3])
 plt.plot([0, 0, 1, 1, 0, 0.5, 1], [1, 0, 0, 1, 1, 2, 1]);

Data Frame Line Plot

sales = pd.read_csv('sales.csv')
 
 sales.plot(x='Month', y=['Product1', 'Product2'], title='Product 1 Monthly Sales', ylabel='Sales', xlabel='Months');

Multiple Line Plots applying styles

t = np.arange(0,5,0.2)
 plt.ylim(0,50)
 plt.title("Power of 2 and 3")
 plt.ylabel("Powers")
 plt.ylabel("values")
 plt.plot(t, t, 'r:', t, np.power(t,2), 'g-', t, np.power(t,3), 'b--');

t = np.arange(0,5,0.2)
 plt.ylim(0,50)
 plt.title("Power of 2 and 3")
 plt.ylabel("Powers")
 plt.xlabel("values")
 plt.plot(t, t, 'yh-')
 plt.plot(t, np.power(t,2), 'g-', linewidth=5)
 plt.plot(t, np.power(t,3), 'b--D');

Multiple Line Plots with Legend

t = np.arange(0,5,0.2)
 plt.ylim(0,50)
 plt.title("Speed in Time")
 plt.ylabel("Speed")
 plt.xlabel("Time")
 plt.grid(True)
 plt.plot([50,100,150,200], [2,3,7,10], 'b-*', linewidth=.8, label='Path 1')
 plt.plot([50,100,150,200], [2,7,9,10], 'g-+', linewidth=.8, label='Path 2')
 plt.legend(loc='upper left');

sales = pd.read_csv('sales.csv')
 sales.head()
 plt.style.use("seaborn-v0_8")
 plt.style.use("bmh")
 plt.style.use("Solarize_Light2")
 p = sales.plot(x='Month',
            y=['Product1', 'Product2'],  
            title='Sales per month', 
            ylabel='Sales', 
            xlabel='Months',
            )
 p.grid(True, which='both');

Drawing Bar Charts

The plt.bar function allows to plot vertical bar charts with one or more numerical series. To plot the bars, you just need to pass two arguments to the function: the first one is the positions of the x-axis on which the bars will be centered, and the second argument is the height of each bar.

Single Bar plot

plt.bar(range(sales.Month.count()), sales.Product1 , color = 'blue', width = .6);

Multiple Bar Plot

plt.title("My bar chart")
 plt.ylabel("Height")
 plt.xlabel("Number")
 plt.bar([1,3,5,7,9],[5,2,7,8,2], label='Example 1')
 plt.bar([2,4,6,8,10],[8,6,2,5,6], label='Example 2')
 plt.legend();

Stacked Bar Plots

plt.title("My bar chart")
 plt.ylabel("Height")
 plt.xlabel("Number")
 plt.bar([1,3,5,7,9],[5,2,7,8,2], label='Example 1')
 plt.bar([1,3,5,7,9],[8,6,2,5,6], bottom = [5,2,7,8,2], label='Example 2')
 plt.legend();

plt.bar(range(sales.Month.count()), sales.Product1 ,  width = .6, label = "Product1")
 plt.bar(range(sales.Month.count()), sales.Product2, bottom= sales.Product1 , width = .6, label = "Product2")
 plt.legend();

sales.plot.bar(x = 'Month', y=['Product1', 'Product2', 'Returns'], xticks=sales.index, stacked=True, rot=0);

Compared Bar Plot

barWidth = 0.4
 
 x1 = range(12)
 x2 = [r + barWidth for r in x1 ]
 
 
 sales12 = sales.head(12)
 
 plt.bar(x1, sales12.Product1, width = barWidth, label = "Product1")
 plt.bar(x2, sales12.Product2, width = barWidth, label = "Product2")
 plt.xticks([0,2,4,6,8,11], ['January', 'Mars', 'May', 'July', 'September', 'December'])
 plt.legend();

Jose Antonio Pio Gil

Discovering the Magic of Matplotlib: Resume with Examples