Python Matplotlib Tutorial | Matplotlib Tutorial | Python Tutorial | Python Training | Edureka

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Python Matplotlib

Agenda
➢ Why Data Visualization?
➢ What Is Data Visualization?
➢ What Is Matplotlib?
➢ Types Of Plots
➢ Getting Started

Why Data Visualization?

Human brain can process information easily when it is in pictorial or graphical form

Data visualization allows us to quickly interpret the data and adjust different variables to see their effect

What Is Data Visualization?

What Is Data Visualization?
Data visualization is the presentation of data in a pictorial or graphical format.
Visualize
Analyse
Document
Insight
Transform
Data set
Finding
Insights In
Data

What Is Matplotlib?

What is Matplolib?
Matplotlib is a Python package used for 2D graphics

Types Of Plots

Types of Plots
Bar graph Histograms Scatter Plot
Pie Plot Hexagonal Bin Plot Area Plot

Getting Started

Getting Started
Here's some basic code to generate one of the most simple graph.
from matplotlib import pyplot as plt
#Plotting to our canvas
plt.plot([1,2,3],[4,5,1])
#Showing what we plotted
plt.show()

Getting Started
Lets add title and labels to our graph
x = [5,8,10]
y = [12,16,6]
plt.plot(x,y)
plt.title('Info')
plt.ylabel('Y axis')
plt.xlabel('X axis')
plt.show()
Title
Labels

Adding Style To Our Graph
from matplotlib import style
style.use('ggplot')
x = [5,8,10]
y = [12,16,6]
x2 = [6,9,11]
y2 = [6,15,7]
plt.plot(x,y,'g',label='line one', linewidth=5)
plt.plot(x2,y2,'c',label='line two',linewidth=5)
plt.title('Epic Info')
plt.ylabel('Y axis')
plt.xlabel('X axis')
plt.legend()
plt.grid(True,color='k')
plt.show()

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

Histogram
population_ages =
[22,55,62,45,21,22,34,42,42,4,99,102,110,120,121,122,130,111,115,112,80,75,6
5,54,44,43,42,48]
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.xlabel('x')
plt.ylabel('y')
plt.title('Histogram')
plt.legend()
plt.show()

Scatter Plot
x = [1,2,3,4,5,6,7,8]
y = [5,2,4,2,1,4,5,2]
plt.scatter(x,y, label='skitscat', color='k)
plt.xlabel('x')
plt.ylabel('y')
plt.title('Scatter Plot')
plt.legend()
plt.show()

Stack Plot
days = [1,2,3,4,5]
sleeping = [7,8,6,11,7]
eating = [2,3,4,3,2]
working = [7,8,7,2,2]
playing = [8,5,7,8,13]
plt.plot([],[],color='m', label='Sleeping', linewidth=5)
plt.plot([],[],color='c', label='Eating', linewidth=5)
plt.plot([],[],color='r', label='Working', linewidth=5)
plt.plot([],[],color='k', label='Playing', linewidth=5)
plt.stackplot(days, sleeping,eating,working,playing, colors=['m','c','r','k'])
plt.xlabel('x')
plt.ylabel('y')
plt.title('Stck Plot')
plt.legend()
plt.show()

Pie Chart
slices = [7,2,2,13]
activities = ['sleeping','eating','working','playing']
cols = ['c','m','r','b']
plt.pie(slices,
labels=activities,
colors=cols,
startangle=90,
shadow= True,
explode=(0,0.1,0,0),
autopct='%1.1f%%')
plt.title('Pie Plot')
plt.show()

Working With Multiple Plots
import numpy as np
def f(t):
return np.exp(-t) * np.cos(2*np.pi*t)
t1 = np.arange(0.0, 5.0, 0.1)
t2 = np.arange(0.0, 5.0, 0.02)
plt.subplot(211)
plt.plot(t1, f(t1), 'bo', t2, f(t2))
plt.subplot(212)
plt.plot(t2, np.cos(2*np.pi*t2))
plt.show()

Session In A Minute
Why Data Visualization? What Is Data Visualization?
Types Of Plots Getting Started
What Is Matplotlib?
Working With Multiple Plots

Thank You …
Questions/Queries/Feedback

Python Matplotlib Tutorial | Matplotlib Tutorial | Python Tutorial | Python Training | Edureka

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