Descriptive Statistics

Descriptive statistics are measures that summarize important features of data, often with a single number. Producing descriptive statistics is a common first step to take after cleaning and preparing a data set for analysis.

1. Data Frame

2. Sum

Returns the sum of the values for the requested axis. By default, axis is index (axis=0).

3.Mean

Returns the average value

4.Std

Returns the Bressel standard deviation of the numerical columns.

5. describe

The describe() function computes a summary of statistics pertaining to the DataFrame columns.

Array of Random Integer Values

An array of random integers can be generated using the randint() NumPy function.

This function takes three arguments, the lower end of the range, the upper end of the range, and the number of integer values to generate or the size of the array. Random integers will be drawn from a uniform distribution including the lower value and excluding the upper value, e.g. in the interval [lower, upper).

The example below demonstrates generating an array of random integers.

# generate random integer values

from numpy.random import seed

from numpy.random import randint

# seed random number generator

seed(1)

# generate some integers

values = randint(0, 10, 20)

print(values)

Running the example generates and prints an array of 20 random integer values between 0 and 10.

>>>[5 8 9 5 0 0 1 7 6 9 2 4 5 2 4 2 4 7 7 9]

Generating Random Numbers With NumPy

import numpy as np

Generate A Random Number From The Normal Distribution

np.random.normal()

0.5661104974399703

Generate Four Random Numbers From The Normal Distribution

np.random.normal(size=4)

array([-1.03175853, 1.2867365 , -0.23560103, -1.05225393])

Generate Four Random Numbers From The Uniform Distribution

np.random.uniform(size=4)

array([ 0.00193123, 0.51932356, 0.87656884, 0.33684494])

Generate Four Random Integers Between 1 and 100

np.random.randint(low=1, high=100, size=4)

array([96, 25, 94, 77])