REVISION - GRADE XII - MATPLOTLIB

 PYPLOT ASSIGNMENT 

 #1

import matplotlib.pyplot as plt

a=[20,30,40,50]

b=[2,4,6,8]

plt.plot(a,b)

plt.show()

 

#2

def fnplot(list1):

              plt.plot(list1)

              plt.title("Marks Line Chart")

              plt.xlabel("Value")

              plt.ylabel("Frequency")

              plt.show()

   

list1=[50,50,50,65,65,75,75,80,80,90,90,90,90]

fnplot(list)

 

#3

plt.plot([1,2,3,4],[1,4,9,16])

plt.show()

 

 #4

plt.plot([1,2,8,4],[1,4,9,16])

plt.title("First Plot")

plt.xlabel(" X Label")

plt.ylabel("Y Label")

plt.show()

 

#5

plt.figure(figsize=(4,4))

plt.plot([1,2,3,4],[1,4,9,16])

plt.title("First Plot")

plt.xlabel(" X Label")

plt.ylabel("Y Label")

plt.show()

 

#5

plt.plot([12,23,30,47])

plt.title("Second Plot")

plt.xlabel(" X Label")

plt.ylabel("Y Label")

plt.show()

 

#6

plt.subplot(1,2,1)  #the figure has 1 row, 2 columns, and this plot is the first plot.

plt.plot([1,2,3,4],[1,4,9,16],"go")

plt.title("First Plot")

plt.subplot(1,2,2)

plt.plot([1,2,3,4],[1,4,9,16],"r^")

plt.title("Second Plot")

plt.show()

HISTOGRAM

import numpy as np 

import matplotlib.pyplot as p1

a = np.array([22,87,5,43,56,73,55,54,11,20,51,5,79,31,27])

p1.hist(a, bins = [0,25,50,75,100],facecolor='y',edgecolor="red")

p1.title("histogram of result")

p1.xticks([0,25,50,75,100])

p1.xlabel('marks')

p1.ylabel('no. of students')

p1.show()

data_students=[1,11,21,31,41,51]

plt.hist(data_students,bins=[0,10,20,30,40,50,60],weights=[10,1,0,33,6,8],

         facecolor='y',edgecolor="red")

plt.title("Histogram for Students data")

plt.xlabel('Value')

plt.ylabel('Frequency')

#plt.savefig("student.png")

plt.show()

#EG: HISTOGRAM

import matplotlib.pyplot as plt

data_students=[5,15,25,35,45,55]

plt.hist(data_students,bins=[0,10,20,30,40,50,60],weights=[20,10,45,33,6,8],

         facecolor='y',edgecolor="red")

plt.title("Histogram for Students data")

plt.xlabel('Value')

plt.ylabel('Frequency')

plt.savefig("student.png")

plt.show()

#7

import matplotlib.pyplot as plt

import numpy as np

xpoints = np.array([0, 6])

ypoints = np.array([0, 250])

plt.plot(xpoints, ypoints)

plt.show()

 

#8

city=['del','mum','chandig','bang']

popu=[23456,5000,1876,1234]

plt.bar(city,popu)

plt.show()

'''

#9

import numpy as np

x=np.arange(1,5)

y=x**3

print(x)

print(y)

#plt.plot([1,2,3,4],[1,4,9,16],"go",x,y,'r^')

plt.title("First Plot")

plt.xlabel(" X Label")

plt.ylabel("Y Label")

plt.plot(x,y,'y')

plt.plot(x,y,"r^")

plt.show()

  

#10

plt.subplot(1,2,1)

plt.plot([1,2,3,4],[1,4,9,16],"bo")

plt.title("First Plot")

plt.subplot(1,2,2)

plt.plot([1,2,3,4],[1,8,9,20],"r^")

plt.title("Second Plot")

plt.show()

 

#11.

import matplotlib.pyplot as plt

import numpy as np

ypoints = np.array([3, 8, 1, 10])

plt.plot(ypoints, marker = 'o')

#or

plt.plot(ypoints, marker = '*')

plt.show()

 

#12.

import matplotlib.pyplot as plt

import numpy as np

ypoints = np.array([3, 8, 1, 10])

plt.plot(ypoints, linestyle = 'dotted')

plt.show()

#13.

Write a code to plot bar chart Olympics Top scores

import matplotlib.pyplot as p1

import numpy as np

countries=['CANADA','INDIA','SRILANKA','RUSSIA','GERMANY']

bronzes = np.array([40, 20, 25, 15, 5])

silvers = np.array([35, 27, 21, 18, 7])

golds = np.array([45, 22, 36, 15, 19])

ind = np.arange(len(countries))

p1.bar(ind, bronzes, width=0.8, label='bronzes', color='#CD853F')

p1.bar(ind, silvers, width=0.8, label='silvers', color='silver', bottom=bronzes)

p1.bar(ind, golds, width=0.8, label='golds', color='gold', bottom=silvers+bronzes)

p1.xticks(ind, countries)

p1.ylabel("Medals")

p1.xlabel("Countries")

p1.legend(loc="upper right")

p1.title("2012 Olympics Top Scorers")

p1.grid()

p1.show()

#14.Population comparison between India and Pakistan

matplotlib import pyplot as plt

year = [1960, 1970, 1980, 1990, 2000, 2010]

popul_pakistan = [44.91, 58.09, 78.07, 107.7, 138.5, 170.6]

popul_india = [449.48, 553.57, 696.783, 870.133, 1000.4, 1309.1]

 

plt.plot(year, popul_pakistan, color='green')

plt.plot(year, popul_india, color='orange')

plt.xlabel('Countries')

plt.ylabel('Population in million')

plt.title('India v/s Pakistan Population till 2010')

plt.show()

#15. Program to exhibit different line styles

import matplotlib.pyplot as plt

import numpy as np

y = np.arange(1, 3)

plt.plot(y, '--', y+1, '-.', y+2, ':')

plt.show()

#16. Program to plot a Bar chart on the basis of popularity of Programming Languages

import numpy as np

import matplotlib.pyplot as plt

objects = ('DotNet', 'C++', 'Java', 'Python', 'C', 'CGI/PERL')

y_pos = np.arange(len(objects))

performance = [8,10,9,20,4,1]

plt.bar(y_pos, performance, align='center')

plt.xticks(y_pos, objects,rotation=30) #set location and label

plt.ylabel('Usage')

plt.title('Programming language usage')

plt.show()

17.

x=[1,2,3,4,5]

y=[6,7,8,9,10]

p1.xlabel("DATA FROM A")

p1.ylabel("DATA FROM B")

p1.title("DATA ALL")

p1.bar(x,y)

p1.savefig("f:\pic1.pdf")

p1.show()

DATAFRAME

16.#Predict the output of the following code:

import pandas as pd 

d1 = {'rollno': [101,101,103,102,104], 'name': ['Pat', 'Sid', 'Tom', 'Kim', 'Ray'],

'physics': [90,40,50,90,65], 'chem': [75,80,60,85,60]} 

df = pd.DataFrame(d1) 

print (df) 

print(' ------- Basic aggregate functions min (), max (), sum () and mean()') 

print('minimum is:', df['physics'].min()) 

print('maximum is:',df['physics'].max()) 

print('sum is:',df['physics'].sum ()) 

print('average is:',df['physics'].mean())