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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#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()) |
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