%load_ext watermark

%watermark -u -v -d -p matplotlib,numpy,scipy

%matplotlib inline

importnumpyasnpfrommatplotlibimportpyplotaspltfromscipy.statsimportt# Generating 15 random data points in the range 5-15 (inclusive)X=np.random.randint(5,15,15)# sample sizen=X.size# meanX_mean=np.mean(X)# standard deviationX_std=np.std(X)# standard errorX_se=X_std/np.sqrt(n)# alternatively:#    from scipy import stats#    stats.sem(X)# 95% Confidence Intervaldof=n-1# degrees of freedomalpha=1.0-0.95conf_interval=t.ppf(1-alpha/2.,dof)*X_std*np.sqrt(1.+1./n)fig=plt.gca()plt.errorbar(1,X_mean,yerr=X_std,fmt='-o')plt.errorbar(2,X_mean,yerr=X_se,fmt='-o')plt.errorbar(3,X_mean,yerr=conf_interval,fmt='-o')plt.xlim([0,4])plt.ylim(X_mean-conf_interval-2,X_mean+conf_interval+2)# axis formattingfig.axes.get_xaxis().set_visible(False)fig.spines["top"].set_visible(False)fig.spines["right"].set_visible(False)plt.tick_params(axis="both",which="both",bottom="off",top="off",labelbottom="on",left="on",right="off",labelleft="on")plt.legend(['Standard Deviation','Standard Error','Confidence Interval'],loc='upper left',numpoints=1,fancybox=True)plt.ylabel('random variable')plt.title('15 random values in the range 5-15')plt.show()

importmatplotlib.pyplotasplt# input datamean_values=[1,2,3]variance=[0.2,0.4,0.5]bar_labels=['bar 1','bar 2','bar 3']fig=plt.gca()# plot barsx_pos=list(range(len(bar_labels)))plt.bar(x_pos,mean_values,yerr=variance,align='center',alpha=0.5)# set height of the y-axismax_y=max(zip(mean_values,variance))# returns a tuple, here: (3, 5)plt.ylim([0,(max_y[0]+max_y[1])*1.1])# set axes labels and titleplt.ylabel('variable y')plt.xticks(x_pos,bar_labels)plt.title('Bar plot with error bars')# axis formattingfig.axes.get_xaxis().set_visible(False)fig.spines["top"].set_visible(False)fig.spines["right"].set_visible(False)plt.tick_params(axis="both",which="both",bottom="off",top="off",labelbottom="on",left="on",right="off",labelleft="on")plt.show()