Matplotlib - bar,scatter and histogram plots

• Simple bar plot
• Another bar plot
• Scatter plot

Simple bar plot

import numpy as npimport matplotlib.pyplot as pltfig = plt.figure()ax = fig.add_subplot(111)## the dataN = 5menMeans = [18, 35, 30, 35, 27]menStd =   [2, 3, 4, 1, 2]womenMeans = [25, 32, 34, 20, 25]womenStd =   [3, 5, 2, 3, 3]## necessary variablesind = np.arange(N)                # the x locations for the groupswidth = 0.35                      # the width of the bars## the barsrects1 = ax.bar(ind, menMeans, width,                color='black',                yerr=menStd,                error_kw=dict(elinewidth=2,ecolor='red'))rects2 = ax.bar(ind+width, womenMeans, width,                    color='red',                    yerr=womenStd,                    error_kw=dict(elinewidth=2,ecolor='black'))# axes and labelsax.set_xlim(-width,len(ind)+width)ax.set_ylim(0,45)ax.set_ylabel('Scores')ax.set_title('Scores by group and gender')xTickMarks = ['Group'+str(i) for i in range(1,6)]ax.set_xticks(ind+width)xtickNames = ax.set_xticklabels(xTickMarks)plt.setp(xtickNames, rotation=45, fontsize=10)## add a legendax.legend( (rects1[0], rects2[0]), ('Men', 'Women') )plt.show()

(Source code, png, hires.png, pdf)

Another bar plot

from mpl_toolkits.mplot3d import Axes3Dimport matplotlib.pyplot as pltimport numpy as npfig = plt.figure()ax = fig.add_subplot(111,projection='3d')for c, z in zip(['r', 'g', 'b', 'y'], [30, 20, 10, 0]):    xs = np.arange(20)    ys = np.random.rand(20)    # You can provide either a single color or an array. To demonstrate this,    # the first bar of each set will be colored cyan.    cs = [c] * len(xs)    cs[0] = 'c'    ax.bar(xs, ys, zs=z, zdir='y', color=cs, alpha=0.8)ax.set_xlabel('X')ax.set_ylabel('Y')ax.set_zlabel('Z')plt.show()

(Source code, png, hires.png, pdf)

Scatter plot

#!/usr/bin/env pythonimport matplotlib.pyplot as pltimport numpy as npfig = plt.figure()ax1 = fig.add_subplot(121)## the dataN=1000x = np.random.randn(N)y = np.random.randn(N)## left panelax1.scatter(x,y,color='blue',s=5,edgecolor='none')ax1.set_aspect(1./ax1.get_data_ratio()) # make axes square## right panelax2 = fig.add_subplot(122)props = dict(alpha=0.5, edgecolors='none' )handles = []colors = ['blue', 'green', 'magenta', 'cyan']for color in colors:    x = np.random.randn(N)    y = np.random.randn(N)    s = np.random.randint(50,200)    handles.append(ax2.scatter(x, y, c=color, s=s, **props))ax2.set_ylim([-5,11])ax2.set_xlim([-5,11])ax2.legend(handles, colors)ax2.grid(True)ax2.set_aspect(1./ax2.get_data_ratio())plt.show()

(Source code, png, hires.png, pdf)

Histogram plot

Here is the matplotlib histogram demo

import numpy as npimport matplotlib.pyplot as pltfig = plt.figure()ax = fig.add_subplot(111)x = np.random.normal(0,1,1000)numBins = 50ax.hist(x,numBins,color='green',alpha=0.8)plt.show()

(Source code, png, hires.png, pdf)