{"id":21901518,"url":"https://github.com/deva-246/dataanalysis-on-realtime-swiggydata-using-sql","last_synced_at":"2025-03-22T06:17:40.652Z","repository":{"id":199930818,"uuid":"704112830","full_name":"deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL","owner":"deva-246","description":"Using SQL to manipulate and clean the data, analyzing to discover trends and patterns, dig insights in an understandable format.","archived":false,"fork":false,"pushed_at":"2023-10-13T14:36:05.000Z","size":48,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-27T06:43:53.615Z","etag":null,"topics":["data-science","dataanalysis","datainsight","mysqlserver"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/deva-246.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2023-10-12T15:02:19.000Z","updated_at":"2023-10-24T15:33:29.000Z","dependencies_parsed_at":"2023-10-14T14:11:14.231Z","dependency_job_id":null,"html_url":"https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL","commit_stats":null,"previous_names":["deva-246/dataanalysis-on-realtime-swiggydata-using-sql"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deva-246%2FDataAnalysis-on-Realtime-Swiggydata-using-SQL","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deva-246%2FDataAnalysis-on-Realtime-Swiggydata-using-SQL/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deva-246%2FDataAnalysis-on-Realtime-Swiggydata-using-SQL/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deva-246%2FDataAnalysis-on-Realtime-Swiggydata-using-SQL/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/deva-246","download_url":"https://codeload.github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244913332,"owners_count":20530818,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-science","dataanalysis","datainsight","mysqlserver"],"created_at":"2024-11-28T15:14:00.733Z","updated_at":"2025-03-22T06:17:40.627Z","avatar_url":"https://github.com/deva-246.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# DataAnalysis-on-Realtime-Swiggydata-using-SQL\nUsing SQL to manipulate and clean the data, analyzing to discover trends and patterns, dig insights in an understandable format.\n\n## Datasets\n**The fields present in Items dataset are,**\n            \n            1. id\n            \n            2. Order_id\n            \n            3. Name\n            \n            4. Is_veg/not\n\n**The fields present in Orders dataset are,**\n            \n            1. id\n            \n            2. order_id\n            \n            3. order_Total\n            \n            4. restaurent name\n            \n            5. order_time\n            \n            6. rain_mode\n            \n            7. on_time\n\n\n## Business Queries and solutions\n### 1. Count of unique number of orders that are placed ?\n\n   ![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/9bfec0ac-9970-4719-8314-166057b0e2b6)\n   \n   **95 unique orders** are placed according to this dataset.\n\n   \n   \n\n### 2. At what modes of rain were orders placed?\n\n   ![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/0192b30f-7201-4c39-ba72-2484f4c87ec8)\n\n   There are 3 modes namely -**Heavy,moderate,drizzle** with 0,2 and 5 as it's respective identifiers from the dataset.\n\n   \n   \n\n### 3.  What are the uniqiue restaurent names from the overall orders that have been placed?\n\n   ![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/f290ab7c-7a34-48b9-9345-321b54263034)\n\n   There are **49** unique restaurents name present in the order history in the given dataset.\n\n   \n   \n\n### 4.  Which Restaurent holds most of the orders ?\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/68b8cc0d-8b06-4f95-a608-2d278e46eb83)\n    \n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/e4b61785-5daf-4261-a905-cd880b58fdc0)\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/377aba1b-8f0a-43b6-8dd6-61ceb4b9dfd1)\n    \n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/5e8a17f7-f73e-4437-bfcb-68f3379d41bc)\n    \n\n**The Bowl company** is the restaurent which holds the highest number of orders according to the swiggy customers present in the dataset. from the above results we can also categorize the restaurents as **most favourite , favourite and least favourite** by which required recommendations can be activated by the company to attract its customer to place an order. \n\n### 5. List out the orders count in the form of Month and Year combination?\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/07a340db-af98-4a2b-b1ed-370f302695cc)\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/3ae3ecd2-5df7-40d0-8e0a-53bfd2b67cb0)\n\nFrom the above result, **2021, October** holds the highest number of Orders.\n\n### 6. What is the revenue earned by swiggy on each month ?\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/7d15f49e-9eca-4312-a6d1-a182a6ee8205)\n\nFrom the above results we can conclude that **October** month has generated the highest revenue and **March** month has generated least revenue, considering this more discounts and offers can be included during the least revenue months to bosst up the sales.\n\n### 7. What is the average order value ?\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/e61fa810-dd50-4af1-b213-cd38ccaf4194)\n\n### 8. Revenue based difference ?\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/b88832df-f7b2-4b7c-aecf-0bb03b1c4b97)\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/7219a3d9-c8da-42a9-bf8d-fdbafbf44a89)\n\n### 9. What is the count of unique food items that are ordered?\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/346ed1bb-bd47-49c6-abb0-846db72a123b)\n\nThere are **164** unique items.\n\n### 10. which is the most ordered item?\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/904183ae-65df-450f-9a2b-cff0286ab5ce)\n\n**Classic Mac \u0026 cheese** is the most ordered item.\n\n### 11. Details about veg and non-veg items ?]\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/1d20611a-59bf-4150-8f90-55e9010491af)\n\nA. There are **180** **veg** items\n\nB. There are **12** **non veg** items\n\nC. There is **1** undefined category item\n\n            \n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/1c9b902b-6a2d-4b74-8a3c-5aa2e52240b2)\n\nHere the undeifined category can be considered as **Desserts**.\n\n### 12. Mention the items and it's total count which includes chicken in it.\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/c45d0dcc-21f6-42c1-b5ce-ea6140ca8ec0)\n\nThere are **10** chicken based dishes present in our dataset.\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/864e7061-b8c3-452d-914b-b899b4452d8f)\n\n### 13. Details about paratha based dishes ?\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/0a48bd2a-4031-40ef-8afb-6398f46be423)\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/216046de-3882-4319-9dbb-f442a9377ed1)\n\nThere are **4** paratha items present in the dataset.\n\n### 14. What is the average items per order?\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/fd0c8100-6aca-4b62-8f2e-a711da86ddfc)\n\n**2** items are atleast placed in any order according to the given dataset.\n\n### 15. What are the frequently bought combos and what is it's count?\n\n            Corn \u0026 Cheddar Quesadilla \u0026 Garlic Bread With Cheese\n            Corn \u0026 Peas Sub ( 15 cm, 6 Inch ) \u0026 Paneer Tikka Sub ( 15 cm, 6 Inch )\n            Corn \u0026 Peas Sub (15 cms, 6 Inch) \u0026 Paneer Tikka Sub (15 cms, 6 Inch)\n            Corn \u0026 Peas Sub (15 cms, 6 Inch) \u0026 Paneer Tikka Sub (15 cms, 6 Inch)\n            Crunchy Chicken \u0026 Paneer \u0026 corn Pasta\n            Daily Special Side Dish (Portion) \u0026 Phulka Chapati\n            Desi Dal Tadka with Jeera Rice \u0026 Nawabi Paneer Lababdar with Matar Pulao\n            Desi Dal Tadka with Jeera Rice \u0026 Triple Ripple Death by Chocolate\n            Dragon Chicken \u0026 Gobi Manchurian (Dry)\n            Dragon Chicken \u0026 Paneer Fried Rice\n            Farmhouse \u0026 Golden Corn\n            Fries (R) \u0026 Mcflurry Oreo Small\n            Fries (R) \u0026 McSpicy Paneer Burger\n            Fries (R) \u0026 New Chocolate Chip Muffin\n            Fries (R) \u0026 Snack box\n            Garlic  Naan \u0026 Gobi Masala\n            Garlic  Naan \u0026 Paneer Pulao\n            Garlic  Naan \u0026 Strawberry Milk Shake\n            Ghee Paneer Masal Dosa \u0026 Kadai Paneer\n            Ghee Paneer Masal Dosa \u0026 Masala Kulcha\n            Ghee Paneer Masal Dosa \u0026 Phulka\n            Ghee Paneer Masal Dosa \u0026 Sambar Idli\n            Ghee Paneer Masal Dosa \u0026 Seven Taste Uttapam\n            Gobi Manchurian \u0026 Paneer Biryani\n            Gobi Manchurian \u0026 Paneer Pulao\n            Gobi Manchurian \u0026 Paneer Pulao with Kadhi\n            Gobi Manchurian \u0026 Phulka\n            Gobi Manchurian (Dry) \u0026 Paneer Fried Rice\n            Gobi Manchurian Dry \u0026 Paratha Kuruma\n            Gobi Masala \u0026 Paneer Pulao\n            Gobi Masala \u0026 Strawberry Milk Shake\n            Golden Corn \u0026 Paneer \u0026 Onion\n            Good ol' Rajma Chawal \u0026 Paneer Butter Masala with Mattar Pulao\n            Good ol' Rajma Chawal \u0026 Peri Peri Chicken with Egg Corn Rice\n            Hazelnut (Baby) \u0026 Strawberry (Baby)\n            Hazelnut Brownie \u0026 Jumbo Paneer Chole Wrap\n            Hazelnut Brownie \u0026 Paneer Signature Rice Bowl (Mini)\n            Hazelnut Brownie \u0026 Rajma Masala Rice Bowl (Mini)\n            Hazelnut Brownie \u0026 Super Saver Paneer Rice Bowl Meal\n            Idli (2 Pcs) \u0026 Poori Masala\n            Jumbo Paneer Chole Wrap \u0026 Paneer Signature Rice Bowl (Mini)\n            Jumbo Paneer Chole Wrap \u0026 Rajma Masala Rice Bowl (Mini)\n            Kadai Paneer \u0026 Masala Kulcha\n            Kadai Paneer \u0026 Phulka\n            Kadai Paneer \u0026 Sambar Idli\n            Kadai Paneer \u0026 Seven Taste Uttapam\n            Maggi Italiano \u0026 Mexican Fries (Chef Suggested)\n            Mango Mastani \u0026 Pomegranate Juices\n            Masala Kulcha \u0026 Mixed Vegetable Raita\n            Masala Kulcha \u0026 Onion Aloo Mixed Paratha\n            Masala Kulcha \u0026 Phulka\n            Masala Kulcha \u0026 Sambar Idli\n            Masala Kulcha \u0026 Seven Taste Uttapam\n            MASALA PURI \u0026 SEV PURI\n            Mattar Paneer \u0026 Punjabi Chaach Di-Bottle (Butter Milk)\n            Mattar Paneer \u0026 Tawa Ghee Phulka\n            McEgg Meal ( R )  \u0026 Mexican McAlooTikki Burger          \n            Mcflurry Oreo Small \u0026 McSpicy Paneer Burger\n            Mcflurry Oreo Small \u0026 New Chocolate Chip Muffin\n            Mcflurry Oreo Small \u0026 Snack box\n            McSpicy Paneer Burger \u0026 New Chocolate Chip Muffin\n            McSpicy Paneer Burger \u0026 Snack box\n            Mixed Veg Raita \u0026 Peas Pulao \n            Mixed Vegetable Raita \u0026 Onion Aloo Mixed Paratha\n            Naan \u0026 Paneer Tikka Masala\n            Naan \u0026 Roti\n            Nawabi Paneer Lababdar Parotta Bowl \u0026 Paneer 65 with Chilli Garlic Fried Rice\n            Nawabi Paneer Lababdar Parotta Bowl \u0026 Sprite Can (300 ml)\n            Nawabi Paneer Lababdar Parotta Bowl \u0026 Triple Ripple Death by Chocolate\n            Nawabi Paneer Lababdar with Matar Pulao \u0026 Triple Ripple Death by Chocolate\n            New Chocolate Chip Muffin \u0026 Snack box\n            Oreo Brownie \u0026 Trio of Chocolate Jar\n            Oreo Cream and Fudge \u0026 Swiss Chocolate Ice cream\n            Palak Paneer Bread Kulcha Lunchbox \u0026 Palak Paneer Jumbo Lunchbox\n            Palak Paneer Bread Kulcha Lunchbox \u0026 Red Velvet Lava Cake\n            Palak Paneer Jumbo Lunchbox \u0026 Red Velvet Lava Cake\n            Paneer 65 with Chilli Garlic Fried Rice \u0026 Sprite Can (300 ml)\n            Paneer 65 with Chilli Garlic Fried Rice \u0026 Triple Ripple Death by Chocolate\n            Paneer Butter Masala with Mattar Pulao \u0026 Peri Peri Chicken with Egg Corn Rice\n            Paneer Pulao \u0026 Phulka\n            Paneer Pulao \u0026 Strawberry Milk Shake\n            Paneer Signature Rice Bowl (Mini) \u0026 Rajma Masala Rice Bowl (Mini)\n            Paneer Tikka Masala \u0026 Roti\n            Penne Arrabiata Pasta La Vista \u0026 Pind Di Daal Makhani with Jeera Rice\n            Phulka \u0026 Sambar Idli\n            Phulka \u0026 Seven Taste Uttapam\n            Poori Masala \u0026 Uttapam\n            Punjabi Chaach Di-Bottle (Butter Milk) \u0026 Tawa Ghee Phulka\n            Rasmalai \u0026 Veg Pulao with Raita\n            Sambar Idli \u0026 Seven Taste Uttapam\n            Schezwan Paneer Frankie \u0026 Tawa Paneer Frankie\n            Sprite Can (300 ml) \u0026 Triple Ripple Death by Chocolate\n\n![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/b8180518-8303-4060-83fd-7a3b868a986a)\n\nThere are **171** item combos present in the dataset.\n\n\n\n\n\n\n\n\n\n\n\n\n            \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n   \n\n   \n   \n\n\n            \n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeva-246%2Fdataanalysis-on-realtime-swiggydata-using-sql","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdeva-246%2Fdataanalysis-on-realtime-swiggydata-using-sql","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeva-246%2Fdataanalysis-on-realtime-swiggydata-using-sql/lists"}