  # Understanding the different Box Plot with visualization

NumPy | Python Methods and Functions

 ` import ` ` numpy as np ` ` import ` ` pandas as pd ` ` import ` ` matplotlib.pyplot as plt `

Data preparation

 ` spread ` ` = ` ` np.random.rand (` ` 50 ` `) ` ` * ` ` 100 ` ` center ` ` = ` ` np.ones (` ` 25 ) * 50 `` flier_high = np.random.rand ( 10 ) * 100 + 100 flier_low = np.random.rand ( 10 ) * - 100 data = np.concatenate ((spread, center, flier_high, flier_low), 0 )    print (data) `

Output:

` [35.94741387 98.49500418 37.2487085 93.19618571 6.34263359 49.10532713 53.86860981 58.59362227 36.96325746 62.27757508 65.44118887 73.79592156 95.15399991 79.94114982 16.64273792 88.35737021 14.84581489 91.61486239 16.03299406 73.12589808 0.76759854 8.63636833 33.25606049 46.05712779 81.60993207 43.94169286 95.0390852 2.96961334 8.79716665 38.21446718 12.15763603 61.18542821 70.93695599 48.90136391 54.6233727 77.27315695 14.63597135 68.22763576 52.23548596 14.34491407 55.53669512 93.63144771 15.66242535 72.47360029 67.82493039 0.34568417 0.46750944 63.39884046 70.39370656 83.42420235 50. 50. 50 . 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 134.61039367 133.42423423 132.77938791 157.75858139 105.99552891 159.1713425 190.9938417 118.33354777 142.13310114 113.5 4291724 -32.73427425 -34.92884623 -49.28116565 -15.24891626 -14.57460618 -9.48256045 -46.74250253 -36.3992666 -88.14980994 -64.49187441] `

Code # 1: Normal section of the box

` `

` plt.figure (figsize = ( 7 , 5 )) plt.boxplot (data)   plt.show () `

Output:

Code # 2: notch area

 ` plt.figure (figsize ` ` = ` ` (` ` 7 ` `, ` ` 5 ` `)) ` ` plt.boxplot (data, ` ` 1 ` `) `   ` plt.show () `

Output: