FBosler

PSEUDO_DATABASE = {
    'students': [{
        '_id': '1234',
        'name': 'John Doe',
        'age': 15
    },{
        '_id': '1235',
        'name': 'Jane Dane',
        'age': 14
    }],

FBosler

g = sns.FacetGrid(grouped_by_country_and_continent, col='Continent', col_wrap=3, height=4.5)
g = g.map(plt.hist, "Life Ladder",bins=np.arange(0,10,0.5))

FBosler

sns.set(
    font_scale=1.5,
    rc={'figure.figsize':(20,10)}
)

ax = sns.lineplot(
    x='Year', 
    y='Life Ladder', 
    hue='Continent',
    marker="o",  

FBosler

import pandas as pd
import numpy as np
import datetime
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline

FBosler

draw_heatmap(
    data=data, 
    outer_row='Timing of Meal',
    outer_col='Type of Meal',
    inner_row='Meal Price / Order Value',
    inner_col='Number Participants',
    values='Converted'
)

FBosler

# Aggregate the data a bit
orders_with_meals['Meal Price / Order Value'] = orders_with_meals['Meal Price']/orders_with_meals['Order Value']
orders_with_meals['Meal Price / Order Value'] = pd.qcut(
    orders_with_meals['Meal Price / Order Value']*-1,
    5,
    labels = ['Least Expensive','Less Expensive','Proportional','More Expensive','Most Expensive'][::-1]
)

orders_with_meals['Timing of Meal'] = pd.qcut(
    orders_with_meals['Days of meal before order'],

FBosler

def draw_heatmap(data,inner_row, inner_col, outer_row, outer_col, values):
    sns.set(font_scale=1)
    fg = sns.FacetGrid(
        data, 
        row=outer_row,
        col=outer_col, 
        margin_titles=True
    )

    position = left, bottom, width, height = 1.4, .2, .1, .6

FBosler

_ = orders_with_meals.groupby(['Days of meal before order']).agg(
    {'Converted': np.mean}
)
plot_bars(data=_,x_col='Days of meal before order',y_col='Converted')

FBosler

orders_with_meals['Type of Meal'].fillna('no meal',inplace=True)
_ = orders_with_meals.groupby('Type of Meal').agg({'Converted': np.mean})
plot_bars(_,x_col='Type of Meal',y_col='Converted')

FBosler

def plot_bars(data,x_col,y_col):
    data = data.reset_index()
    sns.set(
        font_scale=1.5,
        style="whitegrid",
        rc={'figure.figsize':(20,7)}
    )
    g = sns.barplot(x=x_col, y=y_col, data=data, color='royalblue')

    for p in g.patches: