President heights

Importa le librerie

import numpy as np
import pandas as pd

data=pd.read_csv("president_heights.csv")

print(data)


    order              name height(cm) 
 0      1 George Washington        189 
 1      2        John Adams        170 
 2      3  Thomas Jefferson        189 
 3      4     James Madison        163 
 4      5      James Monroe        183
..    ..                ...        ...
37     40     Ronald Reagan        185 
38     41 George H. W. Bush        188 
39     42      Bill Clinton        188 
40     43    George W. Bush        182 
41     44      Barack Obama        185

Estrai le altezze

heights=np.array(data["height(cm)"])
print(heights)

[189 170 189 163 183 171 185 168 173 183 173 173 175 178 183 193 178 173 
 174 183 183 168 170 178 182 180 183 178 182 188 175 179 183 193 182 183 
 177 185 188 188 182 185]

Informazioni statistiche

print("Altezza minima     :", heights.min())
print("Altezza media      :", heights.mean())
print("Altezza massima    :", heights.max())
print("Deviazione standard:", heights.std())

Altezza minima     : 163 
Altezza media      : 179.73809523809524 
Altezza massima    : 193 
Deviazione standard: 6.931843442745892

print("Primo quartile (25%):", np.percentile(heights, 25))
print("Mediana             :", np.median(heights)        )
print("Terzo quartile (75%):", np.percentile(heights, 75))

Primo quartile (25%): 174.25 
Mediana             : 182.0 
Terzo quartile (75%): 183.0

import matplotlib.pyplot as plt

plt.hist(heights) 
plt.title('Distribuzione delle altezze') 
plt.xlabel('Altezza (cm)') 
plt.ylabel('Numero');

plt.show()

import matplotlib.pyplot as plt
import seaborn           as snc

snc.set()

plt.hist(heights) 
plt.title('Distribuzione delle altezze') 
plt.xlabel('Altezza (cm)') 
plt.ylabel('Numero');

plt.show()

Vedi: https://jakevdp.github.io/PythonDataScienceHandbook/02.04-computation-on-arrays-aggregates.html