Classwork 12

Data Visualization with seaborn

Part 1

import pandas as pd
beer_mkt = pd.read_csv('https://bcdanl.github.io/data/beer_markets.csv')

Question 1

• Provide (1) seaborn code and (2) a simple comment to describe how the distribution of price_per_floz varies by brand.

Answer:

Question 2

• Provide (1) seaborn code and (2) a simple comment to describe how the relationship between log(price_per_floz) and log(beer_floz) varies by brand.
  • Below adds log(price_per_floz) and log(beer_floz) to the beer_mkt DataFrame using numpy’s log() function:

import numpy as np
beer_mkt['log_price_per_floz'] = np.log( beer_mkt['price_per_floz'] )
beer_mkt['log_beer_floz'] = np.log( beer_mkt['beer_floz'] )

Answer:

Part 2

stock = pd.read_csv('https://bcdanl.github.io/data/stock_2023_2025.csv')

Question 3

• Provide (1) seaborn code and (2) a simple comment to describe how the daily trend of Close varies by company.

Answer:

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