import numpy as np
L = np.random.random(100)
sum(L)
np.sum(L)
big_array = np.random.random(1000000)
min(big_array),max(big_array)
np.min(big_array),np.max(big_array)
print(big_array.min(), big_array.max(), big_array.sum())
M = np.random.random((3,4))
print(M)
M.sum()
M.min(axis=0)
M.max(axis=1)
import pandas as pd
data = pd.read_csv('D:\president_heights.csv')
heights = np.array(data['height(cm)'])
print(heights)
print("Mean height: ", heights.mean())
print("Standard deviation:", heights.std())
print("Minimum height: ", heights.min())
print("Maximum height: ", heights.max())
print("25th percentile: ", np.percentile(heights, 25))
print("Median: ", np.median(heights))
print("75th percentile: ", np.percentile(heights, 75))
import matplotlib.pyplot as plt
import seaborn;seaborn.set()
plt.hist(heights)
plt.title('Height Distribution of US Presidents')
plt.xlabel('height (cm)')
plt.ylabel('number')