import numpy as np

a=np.arange(1,11,2)
print("Values in a:",a)
print("Total values in a:",a.size)

print("Mean val is:",np.mean(a))
print("Variance is:",np.var(a))
print("Standard Deviation is:",np.std(a))

print("Minimum val in a:",np.min(a))
print("25% val is:",np.percentile(a,25))
print("50% val is:",np.percentile(a,50))
print("Median is:",np.median(a))
print("75% val is:",np.percentile(a,75))
print("Maximim val is:",np.max(a))

print("Sum of all values:",np.sum(a))
print("Product of all values:",np.prod(a))
print("Cummulative sum of values:",np.cumsum(a))
print("Return index of minimum val:",np.argmin(a))
print("Return index of maximum val:",np.argmax(a))
print("Return True if any val in a is >5 else False:",np.any(a>5))
print("Return True if all val in a is >5 else False:",np.all(a>5))

#Example
import numpy as np
import pandas as pd
data = pd.read_csv(r"D:\DataSets\primeminister_heights.csv")
heights = np.array(data['Height'])
print(heights)

print("Minimum height:    ", heights.min())
print("Average height:    ", heights.mean())
print("Maximum height:    ", heights.max())

print("25th percentile:   ", np.percentile(heights, 25))
print("Median:            ", np.median(heights))
print("75th percentile:   ", np.percentile(heights, 75))