import matplotlib.pyplot as plt import pandas as pd import numpy as np

menu = pd.read_csv('https://raw.githubusercontent.com/umsi-data-science/data/main/menu.csv') menu

plt.plot(menu['Category'], menu['Total Fat'], 'o') plt.xticks(rotation=100) plt.title('Calories to Total Fat') plt.xlabel('Category') plt.ylabel('Total Fat') plt.annotate("Don't eat this", xy=(2, 118), xytext=(4, 100), arrowprops=dict(facecolor='black', shrink=0.10), ) plt.show()

plt.scatter(menu["Calories"],menu["Saturated Fat"]) plt.show()

plt.hist(menu['Calories']) plt.show()

plt.hist(menu['Total Fat']) plt.title('Total Fat') plt.xlabel('Total Fat') plt.show()

f = menu['Calories'].plot(kind='hist') type(f)

categories = menu.groupby('Category').size()

categories.plot(kind='barh')

categories_sorted = categories.sort_values(ascending=True)

categories_sorted.plot(kind='barh')

menu['Sugary'] = np.where(menu['Sugars'] > 20, 1,0) menu

menu.groupby(["Category", "Sugary"]).size().unstack().plot(kind = "bar")

menu.groupby(["Category", "Sugary"]).size().unstack().plot(kind = "bar", stacked = True)

menu.groupby(['Category', 'Sugary']).size().groupby(by='Category').apply( lambda x: 100 * x / x.sum() ).unstack().plot(kind='bar', stacked=True)

menu['Fatty'] = np.where(menu['Total Fat (% Daily Value)'] > 75, 1,0) menu.groupby(['Category', 'Fatty']).size().groupby(by='Category').apply( lambda x: 100 * x / x.sum() ).unstack().plot(kind='bar', stacked=True)

categories.plot(kind='pie', title='Menu Categories')

categories.plot(kind='bar', title='Menu Categories')

f, (ax1, ax2) = plt.subplots(2) # if only 1 argument, we assume it's the number of rows ax1.hist(menu['Calories']) plt.show()

f, (ax1, ax2) = plt.subplots(2) ax1.hist(menu['Calories']) ax2.plot(menu['Calories'],menu['Total Fat'],'bo') plt.show()

f, ((ax1, ax2),(ax3,ax4)) = plt.subplots(2,2) ax1.hist(menu['Calories']) ax2.plot(menu['Calories'],menu['Total Fat'],'bo') plt.show()

f, ((ax1, ax2),(ax3,ax4)) = plt.subplots(2,2) ax1.hist(menu['Total Fat']) ax2.plot(menu['Calories'],menu['Total Fat'],'bo') ax3.plot(menu['Total Fat'],menu['Calories'],'bo') ax4.hist(menu['Calories']) plt.show()

f, (ax1, ax2) = plt.subplots(2) menu['Calories'].plot(ax=ax1, kind='hist') menu['Dietary Fiber'].plot(ax = ax2,kind='hist') plt.show()

f, ((ax1, ax2),(ax3,ax4)) = plt.subplots(2,2) menu['Calories'].plot(ax=ax1, kind='barh') menu['Total Fat'].plot(ax=ax2, kind='line') menu['Sodium'].plot(ax=ax3, kind='hist') menu['Saturated Fat'].plot(ax=ax4, kind='box')

menu.Calories.plot(kind='hist')

menu.Calories.plot.hist()

menu.plot(kind="scatter", x='Calories', y='Total Fat')

menu.plot.scatter(x='Calories', y='Total Fat')

plt.figure(figsize=(12,5)) groups = menu.groupby('Category') for name, group in groups: plt.plot(group['Calories'], group['Total Fat'], marker='.', linestyle='', markersize=12, label=name) plt.legend() plt.show()