Jupyter Notebook console

Import modules

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Load data

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Data at a glance

• describe: statisical properties
• info: data properties - structure and data types
• shape: rows and columns

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Numerical analysis and visualisation

brown red purple pink orange olive blue cyan green gray

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Categorical analysis and visualisation

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Correlation between columns

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Column wrangling

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Add and calculate a new column

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Modify existing column

conn = sqlite3.connect('data/sakila.db') df = pd.read_sql(''' SELECT rental.rental_id, rental.rental_date, rental.return_date, customer.last_name AS customer_lastname, store.store_id, city.city AS rental_store_city, film.title AS film_title, film.rental_duration AS film_rental_duration, film.rental_rate AS film_rental_rate, film.replacement_cost AS film_replacement_cost, film.rating AS film_rating FROM rental INNER JOIN customer ON rental.customer_id == customer.customer_id INNER JOIN inventory ON rental.inventory_id == inventory.inventory_id INNER JOIN store ON inventory.store_id == store.store_id INNER JOIN address ON store.address_id == address.address_id INNER JOIN city ON address.city_id == city.city_id INNER JOIN film ON inventory.film_id == film.film_id ; ''', conn, index_col='rental_id', parse_dates=['rental_date', 'return_date'])