Matplotlib Pyplot Plt Python Pandas Data Visualization Plotting
This is some quick notes about graphing or plotting graphs with Matplotlib in Python. Credits to sentdex. You can check him out on Youtube.
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import matplotlib.pyplot as plt %matplotlib inline # simple syntax is matplotlib plots as plt.plot(x, y) plt.plot([1,2,3], [5,6,7]) plt.show() |
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# plotting with variables and basic labelling of our plot x = [1,2,3] y = [5,6,7] ##adding a legend to the plot #add another line vectors first x2 = [4,6,8] y2= [10,14,18] plt.plot(x, y, label='First Line') # you have to give the plots a label before you can call the legends on them plt.plot(x2, y2, label='Second Line') plt.xlabel('Plot number') plt.ylabel('Important var') plt.title('Plotting\nNice Graph') #\nGives you a sub title plt.legend() #call the legend plt.show() |
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#plotting barcharts and histograms x3 = [2,4,6,8,10] y3 = [3,5,7,9,11] #second set of bars x4 = [1,3,5,7,9] y4 = [2,6,6,12,4] #plot barchart plt.bar(x3, y3, label='Bar1', color='r') plt.bar(x4,y4, label='Bar2', color ='c') plt.xlabel('x3') plt.ylabel('y3') plt.title('Bar Chart') plt.legend() plt.show() |
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#plotting histogram. population_dist = [24,45,5,6,42,65,34,75,75,34,75,7,24,26,87,98,98,67,86, 65,63, 87,98,76,53,35] #ids = [x for x in range(len(population_dist))] for bar chart plotting #plot barchart #plt.bar(ids, population_dist, label='hist') #histogram works with bins so we will have to create bin 'containers' for our distribution bins = [10,20,30,40,50,60,70,80,90,100] plt.hist(population_dist, bins, histtype='bar', rwidth=0.5) plt.xlabel('x3') plt.ylabel('y3') plt.title('Histogram') plt.legend() plt.show() |
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## scatter plot. #basic skeletion x = [1,2,3,4,5,6,7,8,9] y = [4,5,8,3,6,9,5,4,8] plt.scatter(x,y, label='ScatterShow', color='c', marker='^' , s=60) # s = size of the marker plt.xlabel('x3') plt.ylabel('y3') plt.title('Scatter') plt.legend() plt.show() |
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#stacked plot days = [1, 2, 3, 4, 5] sleeping = [6,8,7,3,8] eating = [6,9,7,3,6] working = [9,8,5,7,8] #working around legends for stackplots plt.plot([],[], color='red', label='eating', linewidth=2) plt.plot([],[], color='blue', label='sleeping', linewidth=2) plt.plot([],[], color='yellow', label='working', linewidth=2) plt.stackplot(days, eating, sleeping, working, color=['red','blue','yellow']) plt.xlabel('x3') plt.ylabel('y3') plt.title('Stacked Plot') plt.legend() plt.show() |
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#pie charts days = [1, 2, 3, 4, 5] sleeping = [6,8,7,3,8] eating = [6,9,7,3,6] working = [9,8,5,7,8] slices = [2,4,6,8,1] colors = ['red','blue','green','brown','pink'] activities = ['sleeping','eating','working','dancing','travelling'] plt.pie(slices, labels=activities, colors=colors, startangle=90, shadow=True, explode=(0,0.1,0,0,0), autopct='%1.1f%%') |
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([<matplotlib.patches.Wedge at 0x814e588>, <matplotlib.patches.Wedge at 0x7fb7080>, <matplotlib.patches.Wedge at 0x96f9ba8>, <matplotlib.patches.Wedge at 0x82853c8>, <matplotlib.patches.Wedge at 0x785a080>], [<matplotlib.text.Text at 0x82ac4a8>, <matplotlib.text.Text at 0x96f9438>, <matplotlib.text.Text at 0x8026390>, <matplotlib.text.Text at 0x94ac400>, <matplotlib.text.Text at 0x785ada0>], [<matplotlib.text.Text at 0x7fb7fd0>, <matplotlib.text.Text at 0x96f97b8>, <matplotlib.text.Text at 0x8285f98>, <matplotlib.text.Text at 0x94aca58>, <matplotlib.text.Text at 0x65bf860>]) |
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#modifying the matplotlib #plotting barchart. x3 = [2,4,6,8,10] y3 = [3,5,7,9,11] #second set of bars x4 = [1,3,5,7,9] y4 = [2,6,6,12,4] fig = plt.figure(facecolor='#f0f0f0') #set facecolour or background colour which will be maintained once we save our graph ax1 = plt.subplot2grid((1,1),(0,0)) #tilt the xlabels for labels in ax1.xaxis.get_ticklabels(): labels.set_rotation(45) #plot barchart ax1.bar(x3, y3, label='Bar1', color='r') ax1.bar(x4,y4, label='Bar2', color ='c') ax1.grid(True) #add a grid plt.xlabel('x3') plt.ylabel('y3') plt.title('Bar Chart') plt.legend() #customise the legend leg = ax1.legend(loc=2,ncol=6, prop={'size':10}) leg.get_frame().set_alpha(0.4) ##define spacing around the ticks and labels plt.subplots_adjust(left = 0.09, bottom=0.20, right=0.94, top= 0.93, wspace = 0.2, hspace = 0) plt.show() #lets save the graph fig.savefig('matplotlib.png', facecolor=fig.get_facecolor()) |