# 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.

```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.