What is box cox transformation?
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# What is box cox transformation?

This recipe explains what is box cox transformation

## Recipe Objective

Transformation of any power-law or any non-linear distribution to normal distribution is generally carried on by Box-Cox Transformation. A Box cox transformation is defined as a way to transform non-normal dependent variables in our data to a normal shape.

So this recipe is a short example on what is box cox transformation. Let's get started.

## Step 1 - Import the library

``` import numpy as np from scipy.stats import boxcox import seaborn as sns import matplotlib.pyplot as plt ```

Let's pause and look at these imports. Numpy is general one. boxcox will help in normalizing dataset. sns and plt are used for plotting of dataset.

## Step 2 - Setup the Data

``` original_data = np.random.exponential(size = 1000) ```

We have set here an exponential function for normalization.

## Step 3 - Using boxcox

``` fitted_data, fitted_lambda = boxcox(original_data) ```

We have fitted our data usin boxcox into normal function and found the lamda used for the transformation.

## Step 4 - Plotting the pattern

``` fig, ax = plt.subplots(1, 2) sns.distplot(original_data, hist = False, kde = True, kde_kws = {'shade': True, 'linewidth': 2}, label = "Non-Normal", color ="green", ax = ax) sns.distplot(fitted_data, hist = False, kde = True, kde_kws = {'shade': True, 'linewidth': 2}, label = "Normal", color ="green", ax = ax) plt.legend(loc = "upper right") fig.set_figheight(5) fig.set_figwidth(10) ```

We have simply used sns class to plot for original as well as fitted dataset.

## Step 5 - Let's look at our dataset now

Once we run the above code snippet, we will see:

```Srcoll down the ipython file to visualize the results.
```

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