added matplotlib plotting examples

M/matplotlib_files/bar1.py

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+import matplotlib.pyplot as plt
+import numpy as np
+
+cities=['delhi','mumbai','bangalore','cuttack']
+population1=[2.5,3,4,1]
+population2=[2,3.7,3,6]
+population3=[1.4,2.8,2,1]
+x=np.arange(len(cities))
+plt.bar(x-0.3,population1,width=0.3)
+plt.bar(cities,population2,width=0.3)
+plt.bar(x+0.3,population3,width=0.3)
+plt.xlabel('cities')
+plt.xlabel('population')
+plt.title('multiple bargraph')
+plt.grid()
+plt.show()

M/matplotlib_files/bar2.py

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+import os
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+
+d1={'name':['omm','shakti','arya','satyakam'],'age':[13,14,14,15],'height':[170,172,168,174],'weight':[60,62,65,62]}
+df1=pd.DataFrame(d1)
+
+x = np.arange(len(df1['name']))
+width = 0.3
+
+# ensure output directory exists (inside the matplotlib_files folder)
+script_dir = os.path.dirname(os.path.abspath(__file__))
+graphs_dir = os.path.join(script_dir, 'graphs')
+os.makedirs(graphs_dir, exist_ok=True)
+
+plt.bar(x - width, df1['age'],  width=width, color='#e25625', label='age')
+plt.bar(x,           df1['height'], width=width, color='#100900', label='height')
+plt.bar(x + width, df1['weight'], width=width, color='#2596be', label='weight')
+
+# show names at the numeric x positions
+plt.xticks(x, df1['name'])
+
+plt.xlabel('studentName')
+plt.ylabel('studentData')
+plt.legend(loc='upper right') #to show the color code in graph
+plt.savefig(os.path.join(graphs_dir, 'fig_6.png'))
+plt.show()

M/matplotlib_files/hist1.py

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+import matplotlib.pyplot as plt
+import numpy as np
+
+x=np.linspace(1,20,300) # takes 300 values betwn 1-20
+plt.hist(x,bins=20)
+plt.show()

M/matplotlib_files/line1.py

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+import matplotlib.pyplot as plt
+import numpy as np
+
+x=[1,2,3,4,5]
+y=[1,2,3,4,5]
+plt.plot(x,y,'r*',linestyle='dotted',markersize=20,mec='k',mfc='g') #mec=markeredgecolor, mfc=markerfacecolor
+plt.xlabel('students')
+plt.ylabel('marks')
+plt.show()

M/matplotlib_files/pie1.py

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+import matplotlib.pyplot as plt
+
+popl = [1325, 338, 8]
+contri = ['India', 'USA', 'Sweden']
+clr = ['gold', 'pink', 'black']
+xpld = [0.3, 0.3, 0.3]
+plt.pie(popl, colors=clr, labels=contri,
+        shadow=True, explode=xpld, autopct='%4.1f%%')
+plt.title('population in millions')
+
+plt.show()

M/matplotlib_files/plt1.py

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+import matplotlib.pyplot as plt
+import numpy as np
+
+cities=['delhi','mumbai','bangalore','cuttack']
+population=[2.5,3,4,1]
+plt.bar(cities,population,width=0.3,color=['r','silver','gold','brown'])
+plt.plot(cities,population,'ro',linestyle='dashed')
+plt.xlabel('cities')
+plt.xlabel('population')
+plt.show()

M/matplotlib_files/sctr1.py

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+import matplotlib.pyplot as plt
+import numpy as np
+
+x=np.random.randint(0,100,size=(100,))
+y=np.random.randint(0,100,size=(100,))
+size=range(0,100)
+clr=['r','c','k','g']*25  #no of colors must be same as the size
+plt.scatter(x,y,s=size,c=clr)
+plt.show()