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Exploratory Data Analysis

Explore how to perform exploratory data analysis to understand key data features and relationships in a business context. Learn to analyze price distributions and use pair plots to identify trends that inform effective linear regression modeling.

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Exploratory data analysis (EDA) is a key for any data-related project. A better understanding of data helps create practical and effective models.

Price distribution

Let's see how the price is distributed.

Python 3.8
# housing price (target) histogram 
plt.figure(figsize=(12, 6)) # setting fig size, we can leave this line for default
plt.hist(x=df['price'], bins=50) # we can change the bin number
plt.xlabel('price ($1000s)') # setting x label
plt.ylabel('count') # setting y label

If we look at the above histogram, most of the prices are in the 20s (x1,000s), and the average price is around ...