#todays task
#Learn how to use python t do basket analysis (association rule mining)

pip install --upgrade jupyter_client

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pip install mlxtend

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import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from mlxtend.preprocessing import TransactionEncoder
from mlxtend.frequent_patterns import apriori, association_rules

df= pd.read_csv('grocery_data.csv')
df.head()

#top 5 items sold
top5= df['itemDescription'].value_counts().head(5)
top5

plt.figure(figsize=(7,3))
sns.barplot(x=top5.index, y=top5.values, palette='viridis', hue= top5.index)
plt.title('Top 5 items sold')
plt.xlabel('Items')
plt.show()

# data preprocessing: turn the items into transactions
basket= df.groupby('customer_ID')['itemDescription'].apply(list)
basket_df=basket.reset_index()
basket_df.head()

te= TransactionEncoder()
onehot = te.fit_transform(basket_df['itemDescription'])
new_df= pd.DataFrame(onehot, columns=te.columns_, index= basket_df['customer_ID'])
new_df.head()

# Apriori
freq = apriori(new_df, min_support=0.1, use_colnames=True)
freq

rules= association_rules(freq, metric='confidence', min_threshold=0.2)
rules
#consequents is what item is most likely to be bought in association with the antecedents
#anything with a lift higher than 1.0 is likely to happen

#rank by strongest to weakest
rules= rules[rules['lift']>1.1].sort_values(by='confidence', ascending=False)
rules.head(10)[['antecedents', 'consequents', 'support', 'confidence', 'lift']]

	customer_ID	itemDescription
0	1808	tropical fruit
1	2552	whole milk
2	2300	pip fruit
3	1187	other vegetables
4	3037	whole milk

	count
itemDescription
whole milk	2502
other vegetables	1898
rolls/buns	1716
soda	1514
yogurt	1334

	customer_ID	itemDescription
0	1000	[soda, canned beer, sausage, sausage, whole mi...
1	1001	[frankfurter, frankfurter, beef, sausage, whol...
2	1002	[tropical fruit, butter milk, butter, frozen v...
3	1003	[sausage, root vegetables, rolls/buns, deterge...
4	1004	[other vegetables, pip fruit, root vegetables,...

	support	itemsets
0	0.119548	(beef)
1	0.158799	(bottled beer)
2	0.213699	(bottled water)
3	0.135967	(brown bread)
4	0.126475	(butter)
5	0.165213	(canned beer)
6	0.100564	(chicken)
7	0.185480	(citrus fruit)
8	0.114931	(coffee)
9	0.120831	(curd)
10	0.133145	(domestic eggs)
11	0.137506	(frankfurter)
12	0.102617	(frozen vegetables)
13	0.124936	(fruit/vegetable juice)
14	0.116983	(margarine)
15	0.139815	(newspapers)
16	0.376603	(other vegetables)
17	0.177527	(pastry)
18	0.170600	(pip fruit)
19	0.132376	(pork)
20	0.349666	(rolls/buns)
21	0.230631	(root vegetables)
22	0.206003	(sausage)
23	0.168291	(shopping bags)
24	0.313494	(soda)
25	0.233710	(tropical fruit)
26	0.154695	(whipped/sour cream)
27	0.458184	(whole milk)
28	0.282966	(yogurt)
29	0.112365	(bottled water, whole milk)
30	0.146742	(other vegetables, rolls/buns)
31	0.124166	(other vegetables, soda)
32	0.191380	(other vegetables, whole milk)
33	0.120318	(other vegetables, yogurt)
34	0.119805	(rolls/buns, soda)
35	0.178553	(rolls/buns, whole milk)
36	0.111339	(yogurt, rolls/buns)
37	0.113135	(root vegetables, whole milk)
38	0.106978	(sausage, whole milk)
39	0.151103	(soda, whole milk)
40	0.116470	(tropical fruit, whole milk)
41	0.150590	(yogurt, whole milk)

	antecedents	consequents	antecedent support	consequent support	support	confidence	lift	representativity	leverage	conviction	zhangs_metric	jaccard	certainty	kulczynski
0	(bottled water)	(whole milk)	0.213699	0.458184	0.112365	0.525810	1.147597	1.0	0.014452	1.142615	0.163569	0.200825	0.124815	0.385526
1	(whole milk)	(bottled water)	0.458184	0.213699	0.112365	0.245241	1.147597	1.0	0.014452	1.041790	0.237376	0.200825	0.040114	0.385526
2	(other vegetables)	(rolls/buns)	0.376603	0.349666	0.146742	0.389646	1.114335	1.0	0.015056	1.065502	0.164589	0.253209	0.061475	0.404654
3	(rolls/buns)	(other vegetables)	0.349666	0.376603	0.146742	0.419663	1.114335	1.0	0.015056	1.074197	0.157772	0.253209	0.069072	0.404654
4	(other vegetables)	(soda)	0.376603	0.313494	0.124166	0.329700	1.051695	1.0	0.006103	1.024178	0.078849	0.219402	0.023607	0.362886
5	(soda)	(other vegetables)	0.313494	0.376603	0.124166	0.396072	1.051695	1.0	0.006103	1.032237	0.071601	0.219402	0.031230	0.362886
6	(other vegetables)	(whole milk)	0.376603	0.458184	0.191380	0.508174	1.109106	1.0	0.018827	1.101643	0.157802	0.297448	0.092265	0.462934
7	(whole milk)	(other vegetables)	0.458184	0.376603	0.191380	0.417693	1.109106	1.0	0.018827	1.070564	0.181562	0.297448	0.065913	0.462934
8	(other vegetables)	(yogurt)	0.376603	0.282966	0.120318	0.319482	1.129050	1.0	0.013752	1.053660	0.183350	0.223121	0.050927	0.372343
9	(yogurt)	(other vegetables)	0.282966	0.376603	0.120318	0.425204	1.129050	1.0	0.013752	1.084553	0.159406	0.223121	0.077961	0.372343
10	(rolls/buns)	(soda)	0.349666	0.313494	0.119805	0.342627	1.092928	1.0	0.010187	1.044316	0.130743	0.220491	0.042436	0.362393
11	(soda)	(rolls/buns)	0.313494	0.349666	0.119805	0.382160	1.092928	1.0	0.010187	1.052593	0.123855	0.220491	0.049965	0.362393
12	(rolls/buns)	(whole milk)	0.349666	0.458184	0.178553	0.510638	1.114484	1.0	0.018342	1.107190	0.157955	0.283734	0.096813	0.450168
13	(whole milk)	(rolls/buns)	0.458184	0.349666	0.178553	0.389698	1.114484	1.0	0.018342	1.065592	0.189591	0.283734	0.061555	0.450168
14	(yogurt)	(rolls/buns)	0.282966	0.349666	0.111339	0.393472	1.125279	1.0	0.012396	1.072224	0.155267	0.213583	0.067359	0.355944
15	(rolls/buns)	(yogurt)	0.349666	0.282966	0.111339	0.318415	1.125279	1.0	0.012396	1.052011	0.171191	0.213583	0.049439	0.355944
16	(root vegetables)	(whole milk)	0.230631	0.458184	0.113135	0.490545	1.070630	1.0	0.007464	1.063522	0.085746	0.196524	0.059728	0.368733
17	(whole milk)	(root vegetables)	0.458184	0.230631	0.113135	0.246920	1.070630	1.0	0.007464	1.021630	0.121758	0.196524	0.021172	0.368733
18	(sausage)	(whole milk)	0.206003	0.458184	0.106978	0.519303	1.133394	1.0	0.012591	1.127146	0.148230	0.191989	0.112804	0.376393
19	(whole milk)	(sausage)	0.458184	0.206003	0.106978	0.233483	1.133394	1.0	0.012591	1.035850	0.217222	0.191989	0.034609	0.376393
20	(soda)	(whole milk)	0.313494	0.458184	0.151103	0.481997	1.051973	1.0	0.007465	1.045971	0.071966	0.243489	0.043950	0.405892
21	(whole milk)	(soda)	0.458184	0.313494	0.151103	0.329787	1.051973	1.0	0.007465	1.024310	0.091184	0.243489	0.023733	0.405892
22	(tropical fruit)	(whole milk)	0.233710	0.458184	0.116470	0.498353	1.087672	1.0	0.009388	1.080076	0.105189	0.202407	0.074139	0.376276
23	(whole milk)	(tropical fruit)	0.458184	0.233710	0.116470	0.254199	1.087672	1.0	0.009388	1.027473	0.148768	0.202407	0.026739	0.376276
24	(yogurt)	(whole milk)	0.282966	0.458184	0.150590	0.532185	1.161510	1.0	0.020940	1.158185	0.193926	0.254996	0.136580	0.430426
25	(whole milk)	(yogurt)	0.458184	0.282966	0.150590	0.328667	1.161510	1.0	0.020940	1.068076	0.256640	0.254996	0.063737	0.430426

	Instant food products	UHT-milk	abrasive cleaner	artif. sweetener	baby cosmetics	bags	baking powder	bathroom cleaner	beef	berries	beverages	bottled beer	bottled water	brandy	brown bread	butter	butter milk	cake bar	candles	candy	canned beer	canned fish	canned fruit	canned vegetables	cat food	cereals	chewing gum	chicken	chocolate	chocolate marshmallow	citrus fruit	cleaner	cling film/bags	cocoa drinks	coffee	condensed milk	cooking chocolate	cookware	cream	cream cheese	...	salt	salty snack	sauces	sausage	seasonal products	semi-finished bread	shopping bags	skin care	sliced cheese	snack products	soap	soda	soft cheese	softener	soups	sparkling wine	specialty bar	specialty cheese	specialty chocolate	specialty fat	specialty vegetables	spices	spread cheese	sugar	sweet spreads	syrup	tea	tidbits	toilet cleaner	tropical fruit	turkey	vinegar	waffles	whipped/sour cream	whisky	white bread	white wine	whole milk	yogurt	zwieback
customer_ID
1000	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	True	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	...	False	True	False	True	False	True	False	False	False	False	False	True	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	True	True	False
1001	False	False	False	False	False	False	False	False	True	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	...	False	False	False	True	False	False	False	False	False	False	False	True	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	True	False	True	False	True	False	False
1002	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	True	True	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	...	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	True	False	False	False	False	True	False	False	False	False	False	True	False	False	False	False	False	False	False	True	False	False
1003	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	...	False	False	False	True	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False
1004	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	True	False	False	False	False	False	False	False	True	False	False	False	True	False	False	False	False	False	False	False	...	False	False	False	False	False	False	True	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	False	True	False	False	False	False	False	False	False	True	False	False