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Introduction to Data Visualization,Matplotlib.pdf

The document provides an overview of data visualization in Python, primarily focusing on the matplotlib library, its usage, and various types of plots including bar, pie, and step plots. It includes multiple code examples illustrating how to implement these plots for different scenarios and customization options. Key aspects such as importing libraries, plotting data, and saving figures are also discussed.

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Sanjivani Rural Education Society's Sanjivani College of Engineering, Kopargaon 423603. -Department of Strucutral Engineering- By Mr. Sumit S. Kolapkar (Assistant Professor) Mail Id- kolapkarsumitst@sanjivani.org.in
Ø Why data visualization in Python- • Is a quick and easy way to convey the concepts in a universal manner. Ø What is data visualization- • Is a graphical way of representing information and data. Ø Types of data visualization in Python- • Plotting Libraries- • Matplotlib- • Pandas Visualization- • Seaborn- • ggplot- • Plotly-
Ø What is Matplotlib- • Is a plotting library for Python and it is numerical mathematical extension of Numpy • Is 2D and 3D plotting Python library • It was introduced by John Hunter in the year 2002 Ø Matplotlib graphs-
Ø Importing Matplotlib in Python- • import matplotlib.pyplot as plt OR • from matplotlib import pyplot as plt Example- import matplotlib.pyplot as plt x=[1,2,3,4,5] y=[6,7,8,9,10] plt.plot(x,y) plt.show () Example- import matplotlib.pyplot as plt x=[1,2,3,4,5] y=[6,7,8,9,10] plt.bar(x,y) plt.show ()
Ø Importing Matplotlib in Python- Example- import matplotlib.pyplot as plt x=[1,2,3,4,5] y=[6,7,8,9,10] Z=['b','g','r','black','pink'] plt.bar(x,y,color=Z) plt.show () Base Color-
Ø Importing Matplotlib in Python-
Ø Matplotlib Bar Plot- • import matplotlib.pyplot as plt x = ['Python','C','C++', 'Java'] y = [90,65,82,85] plt.bar(x,y) plt.show ()
Ø Matplotlib Bar Plot- • import matplotlib.pyplot as plt x=[ ] y=[ ] z=[ ] plt.bar(x,y, width=0.4, color=“y”, align= “edge” (or center), edgecolor=“r”, linewidth=10, linestyle=“:”, alpha=0.4, label=“Popularity”) plt.bar(x,z, width=0.4, color=“g”, align=edge, edgecolor=“r”, linewidth=10, linestyle=“:”, alpha=0.4, label=“Popularity1”)...for multiple bar graphs plt.legend() plt.show( ) plt.xlabel (“languages”, fontsize=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note- To apply the label we must apply for legend.
Ø Matplotlib Bar Plot- • import matplotlib.pyplot as plt x=[ ] y=[ ] z=[ ] plt.bar(x,y, width=0.4, color=“y”,label=“Popularity”) plt.bar(x,z, width=0.4, color=“g”, label=“Popularity1”)...for multiple bar graphs.....overlapped plt.legend() plt.show( ) plt.xlabel (“languages”, fontsize=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note- To apply the label we must apply for legend.
Ø Matplotlib Bar Plot- Side by Side Graph • import matplotlib.pyplot as plt • import numpy as np x=[ “python”, “c”, “c++”, “java”] y=[80,70,60,82 ] z=[ 20,30,40,50] p = [0,1,2,3].....indexing of x OR p = np.arange(len(x))...by importing numpy also we can create an array of indexing width = 0.4 plt.bar(p,y, width, color=“y”,label=“Popularity”)....x replaced with ‘p’ plt.bar(p,z, width, color=“g”, label=“Popularity1”)....x replaced with ‘p’ plt.legend() plt.show( ) plt.xlabel (“languages”, fontsize=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note- To apply the label we must apply for legend. gives number at x-axis and is over lapped
Ø Matplotlib Bar Plot- Side by Side Graph • import matplotlib.pyplot as plt • import numpy as np x=[ “python”, “c”, “c++”, “java”] y=[80,70,60,82 ] z=[ 20,30,40,50] width = 0.4 p = np.arange(len(x)) p1=[ j+width for j in p]...will create another graph of same width on side plt.bar(p,y, width, color=“y”,label=“Popularity”)....x replaced with ‘p’ plt.bar(p1,z, width, color=“g”, label=“Popularity1”)....x replaced with ‘p’ plt.legend() plt.show( ) plt.xlabel (“languages”, fontsize=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note- To apply the label we must apply for legend. gives number at x-axis
Ø Matplotlib Bar Plot- Side by Side Graph • import matplotlib.pyplot as plt • import numpy as np x=[ “python”, “c”, “c++”, “java”] y=[80,70,60,82 ] z=[ 20,30,40,50] width = 0.4 p = np.arange(len(x)) p1=[ j+width for j in p]...will create another graph of same width on side plt.bar(p,y, width, color=“y”,label=“Popularity”)....x replaced with ‘p’ plt.bar(p1,z, width, color=“g”, label=“Popularity1”)....x replaced with ‘p’ plt.xticks(p+width,x)......to show name at x-axisand at right hand side plt.legend() plt.show( ) plt.xlabel (“languages”, fontsize=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note- To apply the label we must apply for legend. gives name at RHS
Ø Matplotlib Bar Plot- Side by Side Graph • import matplotlib.pyplot as plt • import numpy as np x=[ “python”, “c”, “c++”, “java”] y=[80,70,60,82 ] z=[ 20,30,40,50] width = 0.4 p = np.arange(len(x)) p1=[ j+width for j in p]...will create another graph of same width on side plt.bar(p,y, width, color=“y”,label=“Popularity”)....x replaced with ‘p’ plt.bar(p1,z, width, color=“g”, label=“Popularity1”)....x replaced with ‘p’ plt.xticks(p+width/2,x,rotation=10)......to show name at x-axis and at center plt.legend() plt.show( ) plt.xlabel (“languages”, fontsize=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note- To apply the label we must apply for legend. gives name in rotation
Ø Matplotlib Bar Plot- Horizontal Graph • import matplotlib.pyplot as plt • import numpy as np • x=['Python','C','C++', 'Java'] • y=[90,65,82,85] • z=[23,52,29,20] • width = 0.8 • p=np.arange(len(x)) • p1=[j+width for j in p] • plt.barh(p,y, width, color='r') • plt.bar(p1,z, width, color='k') • plt.xticks(p+width/2,x,rotation=50) • plt.show ()
Ø Matplotlib Step Plot- • import matplotlib.pyplot as plt x=[ ] y=[ ] plt.step(x,y,marker= “o”, color= “r”, ms=10, mfc= “g”) plt.legend() plt.grid() plt.show( ) plt.xlabel (“languages”, font size=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note-To align the bars on the right edge pass a negative width and align='edge'
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • plt.pie(x) • plt.show () • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • plt.pie(x,labels=y) • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z) • plt.show () • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • var1=["r","c","g","orange"] • plt.pie(x,labels=y,explode=z,colors=var1) • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • var1=["r","c","g","orange"] • plt.pie(x,labels=y,explode=z,colors=var1,autopct="%0. 1f%%")
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • var1=["r","c","g","orange"] • plt.pie(x,labels=y,explode=z,colors=var1,autopct="%0. 3f%%")
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",shad ow=True) • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",radiu s=1.5) • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",label distance=1.3) • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",start angle=90) • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",textp rops={"fontsize":15}) • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",textp rops={"fontsize":15},counterclock=False) • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",shad ow=True,textprops={"fontsize":15},wedgeprops={"line width":5}) • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",shad ow=True,textprops={"fontsize":15},wedgeprops={"line width":5,"edgecolor":"c"}) • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",shad ow=True,textprops={"fontsize":15},wedgeprops={"line width":5},rotatelabels=True) • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",radiu s=0.9,shadow=True,textprops={"fontsize":15},wedgep rops={"linewidth":5},rotatelabels=True) • plt.title("Computers and Structures") • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",radiu s=0.9,shadow=True,textprops={"fontsize":15},wedgep rops={"linewidth":5},rotatelabels=True) • plt.title("Computers and Structures") • plt.legend(loc=1).....loc=1 to 10 • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • x1=[40,30,20,10] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,radius=1.5) • plt.pie(x1,radius=1) • plt.show ()
Ø Matplotlib Pie Plot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • x1=[40,30,20,10] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,radius=1.5) • plt.pie([1],colors="w",radius=1) • plt.show ()
Ø Matplotlib Save Figure- • import matplotlib.pyplot as plt x=[ ] y=[ ] plt.plot(x,y) plt.savefig(“fname”, dpi=1000, facecolor= “g”, transparent=True) plt.savefig(fname.pdf)......save in format as per requirement plt.show( ) Ex- import matplotlib.pyplot as plt x=[1,2,3,4,5] y=[90,65,82,85,80] plt.plot(x,y) plt.savefig("line") plt.show() Note- File gets saved in a folder location
Ø Matplotlib Work With Axes- • import matplotlib.pyplot as plt • x=[1,2,3,4,5] • y=[3,2,1,3,4] • plt.plot(x,y) • plt.xticks(x) • plt.yticks(x) • plt.show ()
Ø Matplotlib Work With Axes- • import matplotlib.pyplot as plt • x=[1,2,3,4,5] • y=[3,2,1,3,4] • plt.plot(x,y) • plt.xticks(x,labels=["Python","Java","C","C++","HTML"]) • plt.yticks(x) • plt.show ()
Ø Matplotlib Work With Axes- • import matplotlib.pyplot as plt • x=[1,2,3,4,5] • y=[3,2,1,3,4] • plt.plot(x,y) • plt.xlim(0,10) • plt.show ()
Ø Matplotlib Work With Axes- • import matplotlib.pyplot as plt • x=[1,2,3,4,5] • y=[3,2,1,3,4] • plt.plot(x,y) • plt.axis([0,10,0,7]) • plt.show ()
Ø Text in Matplotlib- text- Add text at an arbitrary location of the axes. annotate- Add an annotation with an optional arrow at an arbitrary location of the axes xlabel- Add a label to the axes’s along x-axis ylabel- Add a label to the axes’s along y-axis title- Add a title to the axes
Ø Text in Matplotlib- Ex- import matplotlib.pyplot as plt x=[1,2,3,4,5] y=[3,2,1,3,4] plt.plot(x,y) plt.text(2,3,"java",style="italic",bbox={"facecolor":"c"}) plt.annotate("python",xy=(2,1),xytext=(4,4),arrowprops=dict(facec olor="green")) plt.legend(["up"],loc=9,facecolor="red",edgecolor="c",framealpha =0.5,shadow=True) plt.show () text position on x and y axis
THANK YOU....

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Introduction to Data Visualization,Matplotlib.pdf

  • 1.
    Sanjivani Rural EducationSociety's Sanjivani College of Engineering, Kopargaon 423603. -Department of Strucutral Engineering- By Mr. Sumit S. Kolapkar (Assistant Professor) Mail Id- kolapkarsumitst@sanjivani.org.in
  • 2.
    Ø Why datavisualization in Python- • Is a quick and easy way to convey the concepts in a universal manner. Ø What is data visualization- • Is a graphical way of representing information and data. Ø Types of data visualization in Python- • Plotting Libraries- • Matplotlib- • Pandas Visualization- • Seaborn- • ggplot- • Plotly-
  • 3.
    Ø What isMatplotlib- • Is a plotting library for Python and it is numerical mathematical extension of Numpy • Is 2D and 3D plotting Python library • It was introduced by John Hunter in the year 2002 Ø Matplotlib graphs-
  • 4.
    Ø Importing Matplotlibin Python- • import matplotlib.pyplot as plt OR • from matplotlib import pyplot as plt Example- import matplotlib.pyplot as plt x=[1,2,3,4,5] y=[6,7,8,9,10] plt.plot(x,y) plt.show () Example- import matplotlib.pyplot as plt x=[1,2,3,4,5] y=[6,7,8,9,10] plt.bar(x,y) plt.show ()
  • 5.
    Ø Importing Matplotlibin Python- Example- import matplotlib.pyplot as plt x=[1,2,3,4,5] y=[6,7,8,9,10] Z=['b','g','r','black','pink'] plt.bar(x,y,color=Z) plt.show () Base Color-
  • 6.
  • 7.
    Ø Matplotlib BarPlot- • import matplotlib.pyplot as plt x = ['Python','C','C++', 'Java'] y = [90,65,82,85] plt.bar(x,y) plt.show ()
  • 8.
    Ø Matplotlib BarPlot- • import matplotlib.pyplot as plt x=[ ] y=[ ] z=[ ] plt.bar(x,y, width=0.4, color=“y”, align= “edge” (or center), edgecolor=“r”, linewidth=10, linestyle=“:”, alpha=0.4, label=“Popularity”) plt.bar(x,z, width=0.4, color=“g”, align=edge, edgecolor=“r”, linewidth=10, linestyle=“:”, alpha=0.4, label=“Popularity1”)...for multiple bar graphs plt.legend() plt.show( ) plt.xlabel (“languages”, fontsize=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note- To apply the label we must apply for legend.
  • 9.
    Ø Matplotlib BarPlot- • import matplotlib.pyplot as plt x=[ ] y=[ ] z=[ ] plt.bar(x,y, width=0.4, color=“y”,label=“Popularity”) plt.bar(x,z, width=0.4, color=“g”, label=“Popularity1”)...for multiple bar graphs.....overlapped plt.legend() plt.show( ) plt.xlabel (“languages”, fontsize=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note- To apply the label we must apply for legend.
  • 10.
    Ø Matplotlib BarPlot- Side by Side Graph • import matplotlib.pyplot as plt • import numpy as np x=[ “python”, “c”, “c++”, “java”] y=[80,70,60,82 ] z=[ 20,30,40,50] p = [0,1,2,3].....indexing of x OR p = np.arange(len(x))...by importing numpy also we can create an array of indexing width = 0.4 plt.bar(p,y, width, color=“y”,label=“Popularity”)....x replaced with ‘p’ plt.bar(p,z, width, color=“g”, label=“Popularity1”)....x replaced with ‘p’ plt.legend() plt.show( ) plt.xlabel (“languages”, fontsize=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note- To apply the label we must apply for legend. gives number at x-axis and is over lapped
  • 11.
    Ø Matplotlib BarPlot- Side by Side Graph • import matplotlib.pyplot as plt • import numpy as np x=[ “python”, “c”, “c++”, “java”] y=[80,70,60,82 ] z=[ 20,30,40,50] width = 0.4 p = np.arange(len(x)) p1=[ j+width for j in p]...will create another graph of same width on side plt.bar(p,y, width, color=“y”,label=“Popularity”)....x replaced with ‘p’ plt.bar(p1,z, width, color=“g”, label=“Popularity1”)....x replaced with ‘p’ plt.legend() plt.show( ) plt.xlabel (“languages”, fontsize=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note- To apply the label we must apply for legend. gives number at x-axis
  • 12.
    Ø Matplotlib BarPlot- Side by Side Graph • import matplotlib.pyplot as plt • import numpy as np x=[ “python”, “c”, “c++”, “java”] y=[80,70,60,82 ] z=[ 20,30,40,50] width = 0.4 p = np.arange(len(x)) p1=[ j+width for j in p]...will create another graph of same width on side plt.bar(p,y, width, color=“y”,label=“Popularity”)....x replaced with ‘p’ plt.bar(p1,z, width, color=“g”, label=“Popularity1”)....x replaced with ‘p’ plt.xticks(p+width,x)......to show name at x-axisand at right hand side plt.legend() plt.show( ) plt.xlabel (“languages”, fontsize=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note- To apply the label we must apply for legend. gives name at RHS
  • 13.
    Ø Matplotlib BarPlot- Side by Side Graph • import matplotlib.pyplot as plt • import numpy as np x=[ “python”, “c”, “c++”, “java”] y=[80,70,60,82 ] z=[ 20,30,40,50] width = 0.4 p = np.arange(len(x)) p1=[ j+width for j in p]...will create another graph of same width on side plt.bar(p,y, width, color=“y”,label=“Popularity”)....x replaced with ‘p’ plt.bar(p1,z, width, color=“g”, label=“Popularity1”)....x replaced with ‘p’ plt.xticks(p+width/2,x,rotation=10)......to show name at x-axis and at center plt.legend() plt.show( ) plt.xlabel (“languages”, fontsize=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note- To apply the label we must apply for legend. gives name in rotation
  • 14.
    Ø Matplotlib BarPlot- Horizontal Graph • import matplotlib.pyplot as plt • import numpy as np • x=['Python','C','C++', 'Java'] • y=[90,65,82,85] • z=[23,52,29,20] • width = 0.8 • p=np.arange(len(x)) • p1=[j+width for j in p] • plt.barh(p,y, width, color='r') • plt.bar(p1,z, width, color='k') • plt.xticks(p+width/2,x,rotation=50) • plt.show ()
  • 15.
    Ø Matplotlib StepPlot- • import matplotlib.pyplot as plt x=[ ] y=[ ] plt.step(x,y,marker= “o”, color= “r”, ms=10, mfc= “g”) plt.legend() plt.grid() plt.show( ) plt.xlabel (“languages”, font size=10) plt.ylabel(“No.” ”, font size=10) plt.title(“Graph1” ”, font size=10) Note-To align the bars on the right edge pass a negative width and align='edge'
  • 16.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • plt.pie(x) • plt.show () • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • plt.pie(x,labels=y) • plt.show ()
  • 17.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z) • plt.show () • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • var1=["r","c","g","orange"] • plt.pie(x,labels=y,explode=z,colors=var1) • plt.show ()
  • 18.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • var1=["r","c","g","orange"] • plt.pie(x,labels=y,explode=z,colors=var1,autopct="%0. 1f%%")
  • 19.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • var1=["r","c","g","orange"] • plt.pie(x,labels=y,explode=z,colors=var1,autopct="%0. 3f%%")
  • 20.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",shad ow=True) • plt.show ()
  • 21.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",radiu s=1.5) • plt.show ()
  • 22.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",label distance=1.3) • plt.show ()
  • 23.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",start angle=90) • plt.show ()
  • 24.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",textp rops={"fontsize":15}) • plt.show ()
  • 25.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",textp rops={"fontsize":15},counterclock=False) • plt.show ()
  • 26.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",shad ow=True,textprops={"fontsize":15},wedgeprops={"line width":5}) • plt.show ()
  • 27.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",shad ow=True,textprops={"fontsize":15},wedgeprops={"line width":5,"edgecolor":"c"}) • plt.show ()
  • 28.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",shad ow=True,textprops={"fontsize":15},wedgeprops={"line width":5},rotatelabels=True) • plt.show ()
  • 29.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",radiu s=0.9,shadow=True,textprops={"fontsize":15},wedgep rops={"linewidth":5},rotatelabels=True) • plt.title("Computers and Structures") • plt.show ()
  • 30.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,explode=z,autopct="%0.3f%%",radiu s=0.9,shadow=True,textprops={"fontsize":15},wedgep rops={"linewidth":5},rotatelabels=True) • plt.title("Computers and Structures") • plt.legend(loc=1).....loc=1 to 10 • plt.show ()
  • 31.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • x1=[40,30,20,10] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,radius=1.5) • plt.pie(x1,radius=1) • plt.show ()
  • 32.
    Ø Matplotlib PiePlot- • import matplotlib.pyplot as plt • x=[1,2,3,4] • x1=[40,30,20,10] • y=["C","C++","Java","Python"] • z=[0.4,0.0,0.0,0.0] • plt.pie(x,labels=y,radius=1.5) • plt.pie([1],colors="w",radius=1) • plt.show ()
  • 33.
    Ø Matplotlib SaveFigure- • import matplotlib.pyplot as plt x=[ ] y=[ ] plt.plot(x,y) plt.savefig(“fname”, dpi=1000, facecolor= “g”, transparent=True) plt.savefig(fname.pdf)......save in format as per requirement plt.show( ) Ex- import matplotlib.pyplot as plt x=[1,2,3,4,5] y=[90,65,82,85,80] plt.plot(x,y) plt.savefig("line") plt.show() Note- File gets saved in a folder location
  • 34.
    Ø Matplotlib WorkWith Axes- • import matplotlib.pyplot as plt • x=[1,2,3,4,5] • y=[3,2,1,3,4] • plt.plot(x,y) • plt.xticks(x) • plt.yticks(x) • plt.show ()
  • 35.
    Ø Matplotlib WorkWith Axes- • import matplotlib.pyplot as plt • x=[1,2,3,4,5] • y=[3,2,1,3,4] • plt.plot(x,y) • plt.xticks(x,labels=["Python","Java","C","C++","HTML"]) • plt.yticks(x) • plt.show ()
  • 36.
    Ø Matplotlib WorkWith Axes- • import matplotlib.pyplot as plt • x=[1,2,3,4,5] • y=[3,2,1,3,4] • plt.plot(x,y) • plt.xlim(0,10) • plt.show ()
  • 37.
    Ø Matplotlib WorkWith Axes- • import matplotlib.pyplot as plt • x=[1,2,3,4,5] • y=[3,2,1,3,4] • plt.plot(x,y) • plt.axis([0,10,0,7]) • plt.show ()
  • 38.
    Ø Text inMatplotlib- text- Add text at an arbitrary location of the axes. annotate- Add an annotation with an optional arrow at an arbitrary location of the axes xlabel- Add a label to the axes’s along x-axis ylabel- Add a label to the axes’s along y-axis title- Add a title to the axes
  • 39.
    Ø Text inMatplotlib- Ex- import matplotlib.pyplot as plt x=[1,2,3,4,5] y=[3,2,1,3,4] plt.plot(x,y) plt.text(2,3,"java",style="italic",bbox={"facecolor":"c"}) plt.annotate("python",xy=(2,1),xytext=(4,4),arrowprops=dict(facec olor="green")) plt.legend(["up"],loc=9,facecolor="red",edgecolor="c",framealpha =0.5,shadow=True) plt.show () text position on x and y axis
  • 40.