Box Plot in Python using Matplotlib

Last Updated :12 Jul, 2025

ABox Plot (orWhisker plot) display the summary of a data set, including minimum, first quartile, median, third quartile and maximum. it consists of a box from the first quartile to the third quartile, with a vertical line at the median. the x-axis denotes the data to be plotted while the y-axis shows the frequency distribution. The matplotlib.pyplot module of matplotlib library provides boxplot() function with the help of which we can create box plots.

Syntax

matplotlib.pyplot.boxplot(data)

The data values given to the ax.boxplot() method can be a Numpy array or Python list or Tuple of arrays. Let us create the box plot by using numpy.random.normal() to create some random data, it takes mean, standard deviation, and the desired number of values as arguments.

Example:

Python

importmatplotlib.pyplotaspltimportnumpyasnpnp.random.seed(10)d=np.random.normal(100,20,200)fig=plt.figure(figsize=(10,7))plt.boxplot(d)plt.show()

Output:

The basic box plot that displays the distribution of the randomly generated data.

Customizing Box Plot

The matplotlib.pyplot.boxplot() provides endless customization possibilities to the box plot. some of the key customization parameters include:

The notch: True attribute creates the notch format to the box plot
patch_artist: True fills the boxplot with colors, we can set different colors to different boxes.
vert: 0 attribute creates horizontal box plot.
labels: specifies custom labels for the boxes.

Example 1: Multiple Datasets Box Plot

Python

importmatplotlib.pyplotaspltimportnumpyasnpnp.random.seed(10)d_1=np.random.normal(100,10,200)d_2=np.random.normal(90,20,200)d_3=np.random.normal(80,30,200)d_4=np.random.normal(70,40,200)d=[d_1,d_2,d_3,d_4]fig=plt.figure(figsize=(10,7))ax=fig.add_axes([0,0,1,1])bp=ax.boxplot(d)plt.show()

Output:

Example 2: Let's try to modify the above plot with some of the customizations:

We will customize the plot by adding a notch, filling the boxes with colors, and modifying the whisker and median styles.

Python

importmatplotlib.pyplotaspltimportnumpyasnpnp.random.seed(10)d_1=np.random.normal(100,10,200)d_2=np.random.normal(90,20,200)d_3=np.random.normal(80,30,200)d_4=np.random.normal(70,40,200)d=[d_1,d_2,d_3,d_4]fig=plt.figure(figsize=(10,7))ax=fig.add_subplot(111)bp=ax.boxplot(d,patch_artist=True,notch='True',vert=0)colors=['#0000FF','#00FF00','#FFFF00','#FF00FF']forpatch,colorinzip(bp['boxes'],colors):patch.set_facecolor(color)forwhiskerinbp['whiskers']:whisker.set(color='#8B008B',linewidth=1.5,linestyle=":")# changing color and linewidth offorcapinbp['caps']:cap.set(color='#8B008B',linewidth=2)formedianinbp['medians']:median.set(color='red',linewidth=3)# changing style of fliersforflierinbp['fliers']:flier.set(marker='D',color='#e7298a',alpha=0.5)ax.set_yticklabels(['d_1','d_2','d_3','d_4'])plt.title("Customized box plot")ax.get_xaxis().tick_bottom()ax.get_yaxis().tick_left()plt.show()