Instacart Market Basket Analysis - Reorder Analysis

Posted on Sep 8, 2017


InstaCart market basket analysis was a Kaggle competition that was open early 2016 and was conducted by Instacart. Instacart, a grocery ordering and delivery app, aims to make it easy to fill refrigerator and pantry with personal favorites and staples when needed. After selecting products through the Instacart app, personal shoppers review the order and do the in-store shopping and delivery for customers.

Instacart uses transactional data to develop models that predict which products a user will buy again, try for the first time, or add to their cart next during a session. The objective for this competition was to use anonymized data on customer orders over time to predict which previously purchased products will be in a user’s next order.

Data was provided as separate datasets with specific entities such as orders, products, reorders, etc. The datasets had to be combined appropriately for data analysis and visualization as well as for modeling. Data provided had no missing or null values. The training and test set were combined in a single dataset and had to be separated into different datasets. The training set contained 131209 rows, the test set contained 75000 and a prior set containing reorders contained over 3 million records. Due to computing restrains, this dataset was reduced to 300K rows for modeling.

Exploratory Data Analysis (EDA)

  1. Number of products in each department

The following plot helps us understand how Instacart has stocked products by department. Based on the plot, the most number of products is available under the personal care department. Followed by snacks and pantry.

2. Number of products in each aisle

The following plot helps us understand how Instacart has stocked products by aisle. Based on the plot, the most number of products is available under the candy chocolates. Followed by ice cream and vitamin supplements. This contradicts with the number of products by department. However, let's analyze further.


















3.  Number of products based on department and aisles

The following  plots divides the number of products among aisles and department. The highest number of products in personal care is vitamin supplements which was also one of the highest number of products based on aisles. Similarly candy chocolates is the highest under the department Snacks. So now we find a relationship between the number of products in department and in aisles.





4. Number of reorders in training set and priorset

There is more reorders in the prior set which is quite obvious considering the numbers of rows in the prior set

5.  Reorder for each day in training set and prior set

The reorders in both dataset are quite same. The highest reorder happening on day 0 which we assume is a Sunday, followed by a Monday and then on a Saturday

Data Modeling

Using Apriori algorithm the following set of items were obtained that were a possibility of being reordered by itself or with other items. Due to constraints of computing and time, the entire analysis could not get further than this.  With more time and computing available, I would like to perform more algorithms and more analysis on the models obtained to ensure the model is close to accurate.

support itemsets
0 0.106786 [100 Calorie Per Bag Popcorn]
1 0.097220 [100% Raw Coconut Water]
2 0.086337 [100% Recycled Paper Towels]
3 0.175343 [100% Whole Wheat Bread]
4 0.133578 [2% Reduced Fat Milk]
5 0.061625 [Aged White Cheddar Baked Rice & Corn Puffs Gl...
6 0.052405 [All Natural Marinara Sauce]
7 0.055733 [Almonds & Sea Salt in Dark Chocolate]
8 0.192673 [Apple Honeycrisp Organic]
9 0.163386 [Asparagus]
10 0.078573 [Backyard Barbeque Potato Chips]
11 0.715444 [Bag of Organic Bananas]
12 0.082421 [Baked Aged White Cheddar Rice and Corn Puffs]
13 0.053965 [Baked Rice and Corn Puffs, Aged White Cheddar]
14 0.976986 [Banana]
15 0.095210 [Bartlett Pears]
16 0.059753 [Blackberries]
17 0.179052 [Blueberries]
18 0.050326 [Blueberry on the Bottom Nonfat Greek Yogurt]
19 0.066269 [Boneless Skinless Chicken Breasts]
20 0.099473 [Broccoli Crown]
21 0.076113 [Bunched Cilantro]
22 0.080757 [Cantaloupe]
23 0.131776 [Carrots]
24 0.057258 [Cereal]
25 0.078435 [Cherubs Heavenly Salad Tomatoes]
26 0.228338 [Chips Ahoy! Chewy Cookies]
27 0.055421 [Chips Ahoy!/Nutter Butter/Oreo Cookies]
28 0.145501 [Chocolate Chip Cookies]
29 0.227818 [Chocolate Sandwich Cookies]
... ... ...
257 0.060862 [Sweet Potato Tortilla Chips]
258 0.169382 [Swiss Rolls]
259 0.050083 [Tortilla Chips, Clasico, Jalapeno Lime]
260 0.063635 [Total 0% Greek Yogurt]
261 0.084119 [Total 2% All Natural Greek Strained Yogurt wi...
262 0.054970 [Total 2% All Natural Low Fat 2% Milkfat Greek...
263 0.070602 [Total 2% Greek Strained Yogurt with Cherry 5....
264 0.070012 [Total 2% Lowfat Greek Strained Yogurt With Bl...
265 0.073998 [Total 2% Lowfat Greek Strained Yogurt with Pe...
266 0.110634 [Total 2% with Strawberry Lowfat Greek Straine...
267 0.148621 [Uncured Genoa Salami]
268 0.068834 [Unsalted Butter]
269 0.130840 [Unsweetened Almondmilk]
270 0.092576 [Unsweetened Original Almond Breeze Almond Milk]
271 0.093546 [Unsweetened Vanilla Almond Milk]
272 0.066235 [Vanilla Almond Breeze Almond Milk]
273 0.092195 [Vanilla Animal Cookies]
274 0.358797 [Vanilla Sandwich Creme Cookies]
275 0.053133 [Vanilla Skyr Nonfat Yogurt]
276 0.240053 [Vegan Oatmeal Chocolate Chip Cookies]
277 0.058783 [Vegan Oatmeal Raisin Cookies]
278 0.084362 [Watermelon Chunks]
279 0.104222 [Whipped Cream Cheese]
280 0.203209 [White Chocolate Macadamia Nut Cookies]
281 0.058575 [White Chocolate Macadamia Nut Energy Bar]
282 0.128275 [Whole Milk]
283 0.455462 [Whole Wheat Cookies Dark Chocolate]
284 0.065957 [XL Emerald White Seedless Grapes]
285 0.129350 [Yellow Onions]
286 0.083634 [YoKids Squeezers Organic Low-Fat Yogurt, Stra...

287 rows × 2 columns

About Author


Annie George

Annie George has more than a decade of experience using mainframe technology and databases such as DB2 and SQLServer to achieve results for organizations in the private sectors. Annie completed her Bachelors in Civil Engineering but she found...
View all posts by Annie George >

Related Articles

Leave a Comment

No comments found.

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 airbnb Alex Baransky alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus API Application artist aws beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep Bundles California Cancer Research capstone Career Career Day citibike clustering Coding Course Demo Course Report D3.js data Data Analyst data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization Deep Learning Demo Day Discount dplyr employer networking feature engineering Finance Financial Data Science Flask gbm Get Hired ggplot2 googleVis Hadoop higgs boson Hiring hiring partner events Hiring Partners Industry Experts Instructor Blog Instructor Interview Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter lasso regression Lead Data Scienctist Lead Data Scientist leaflet linear regression Logistic Regression machine learning Maps matplotlib Medical Research Meet the team meetup Networking neural network Neural networks New Courses nlp NYC NYC Data Science nyc data science academy NYC Open Data NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time Portfolio Development prediction Prework Programming PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn Selenium sentiment analysis Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau team TensorFlow Testimonial tf-idf Top Data Science Bootcamp twitter visualization web scraping Weekend Course What to expect word cloud word2vec XGBoost yelp