# Math Operations for Data Analysis in Python

Data Analysis is the process of extracting valuable information for data.

In python, we have a number of tools to do that. We will first import the numpy library, this library has many build-in tools to do a lot of mathematical operations easily.

## Math involved

To show the math functions involved I have loaded a basic dataset, you can any dataset as per your convenience or get it from sklearn.datasets.

Load the datasets.

import numpy as np data = np.genfromtxt("0000000000002419_training_ccpp_x_y_train (1).csv", delimiter=",")

As you can see, its a simple dataset with just numerical values in an array form.

array([[ 8.58, 38.38, 1021.03, 84.37, 482.26], [ 21.79, 58.2 , 1017.21, 66.74, 446.94], [ 16.64, 48.92, 1011.55, 78.76, 452.56], ..., [ 29.8 , 69.34, 1009.36, 64.74, 437.65], [ 16.37, 54.3 , 1017.94, 63.63, 459.97], [ 30.11, 62.04, 1010.69, 47.96, 444.42]])

### SUM

To get the sum of the data

data.sum() 11588436.350000001

### MAX

T get the maximum value in the data

data.max() 1033.3

### MIN

To get the minimum value in the data

data.min() 1.81

### MEAN

To get the mean of the data

data.mean() 322.97760172798223

### STANDARD DEVIATION

To get the standard deviation of the data

data.std() 379.76319759971136

These are some of the functions used, there are many more.

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