"""

Beer Analysis - Using Jupyter Code Cells

Accompanying article on https://pbpython.com/notebook-alternative.html

"""

# %%

import pandas as pd

import seaborn as sns

import plotly.express as px

# %%

# Load in the Craft Beer analysis

df_beers = pd.read_csv(

'https://github.com/nickhould/craft-beers-dataset/blob/master/data/processed/beers.csv?raw=True',

index_col=0)

df_breweries = pd.read_csv(

'https://github.com/nickhould/craft-beers-dataset/blob/master/data/processed/breweries.csv?raw=True',

index_col=0)

# %%

sns.set_style('whitegrid')

# %%

df_beers.head()

# %%

df_breweries.head()

# %%

df_beers.info()

# %%

df_breweries.info()

# %%

all_beer = pd.merge(df_beers,

df_breweries,

how='left',

left_on="brewery_id",

right_on="id",

suffixes=('_beer', '_brewery'))

# %%

all_beer.head()

# %%

# Useful to check for null values

empty_data = all_beer.isna().sum()

# %%

all_beer.info()

# %%

all_beer['ounces'].plot(kind='hist', title='Beer Size')

# %%

all_beer['IPA'] = all_beer['style'].str.contains('IPA', case=False)

# %%

all_beer['IPA'].value_counts()

# %%

all_beer_types = all_beer['style'].value_counts()

# %%

sns.catplot(data=all_beer, x='IPA', y='ibu', kind='box')

# %%

sns.catplot(data=all_beer, x='IPA', y='ibu', kind='swarm')

# %%

fig = px.scatter(all_beer, x="abv", y="ibu")

fig.show()

# %%

fig = px.scatter(all_beer,

x="abv",

y="ibu",

color='state',

hover_name='name_beer',

hover_data=['name_brewery'])

fig.show()

# %%

# Do some analysis on MN beers

mn_beer = all_beer[all_beer['state'].str.contains('MN')].copy()

# %%

all_beer['state'].value_counts()

# %%

all_beer.describe()

# %%

# Any relationship betwee alcohol volume and IBU?

fig = px.scatter(mn_beer,

x="abv",

y="ibu",

hover_name='name_beer',

hover_data=['name_brewery'])

fig.show()

# %%