Exercise

Exploring and transforming shelf life data

Understanding the distribution of different variables in our data is a key aspect of any data work including experimental analysis. The food_preservation dataset captures various food preservation methods and their impact on nutrient retention and shelf life. A crucial aspect of this data involves the shelf life of preserved foods, which can vary significantly across different preservation methods and food types.

The food_preservation DataFrame, from scipy.stats import boxcox, pandas as pd, numpy as np, seaborn as sns, and matplotlib.pyplot as plt have been loaded for you.

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Visualize the original distribution of the 'ShelfLife' column.

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Instructions 1/3

Exercise