{"id":49873833,"url":"https://github.com/yernaz-togizbayev/microsoft_store_data-analysis","last_synced_at":"2026-05-15T11:36:04.186Z","repository":{"id":320072096,"uuid":"1080700834","full_name":"yernaz-togizbayev/microsoft_store_data-analysis","owner":"yernaz-togizbayev","description":"Microsoft Store","archived":false,"fork":false,"pushed_at":"2026-02-26T10:20:10.000Z","size":1352,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-05-06T11:49:09.540Z","etag":null,"topics":["data","data-analysis","data-visualization","jupyter-notebook","python3"],"latest_commit_sha":null,"homepage":"https://jovian.com/yernaz-togizbayev/microsoft-store-project","language":"Jupyter Notebook","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/yernaz-togizbayev.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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-10-21T18:37:25.000Z","updated_at":"2026-03-09T12:16:43.000Z","dependencies_parsed_at":"2025-10-21T20:37:45.780Z","dependency_job_id":null,"html_url":"https://github.com/yernaz-togizbayev/microsoft_store_data-analysis","commit_stats":null,"previous_names":["yernaz-togizbayev/microsoft_store_data-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/yernaz-togizbayev/microsoft_store_data-analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yernaz-togizbayev%2Fmicrosoft_store_data-analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yernaz-togizbayev%2Fmicrosoft_store_data-analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yernaz-togizbayev%2Fmicrosoft_store_data-analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yernaz-togizbayev%2Fmicrosoft_store_data-analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/yernaz-togizbayev","download_url":"https://codeload.github.com/yernaz-togizbayev/microsoft_store_data-analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yernaz-togizbayev%2Fmicrosoft_store_data-analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33065702,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-15T11:35:32.926Z","status":"ssl_error","status_checked_at":"2026-05-15T11:35:31.362Z","response_time":103,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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","data-analysis","data-visualization","jupyter-notebook","python3"],"created_at":"2026-05-15T11:36:02.014Z","updated_at":"2026-05-15T11:36:04.180Z","avatar_url":"https://github.com/yernaz-togizbayev.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 📊 Microsoft Store Data Analysis\n\nThis project explores and analyzes a dataset of applications from the **Microsoft Windows Store**.  \nUsing Python and data analysis libraries, the project focuses on **data cleaning, exploratory analysis, visualization, and answering business-related questions**.\n\nThe dataset includes app categories, prices, ratings, number of downloads (people rated), and release dates.\n\n---\n\n## 🧠 Project Goals\n\n- Clean and preprocess raw dataset\n- Convert string-based prices to numeric values\n- Perform exploratory data analysis (EDA)\n- Visualize trends in downloads and pricing\n- Answer analytical questions about popularity and revenue patterns\n\n---\n\n## 📂 Files Included\n\nmicrosoft-store-project.ipynb   # Full Jupyter Notebook  \nmicrosoft_store_project.py      # Script version of the notebook  \nmsft.csv                        # Dataset (required to run the project)\n\n---\n\n## 🛠 Technologies Used\n\n- Python 3\n- pandas\n- numpy\n- matplotlib\n- seaborn\n- Jupyter Notebook\n\n---\n\n## 🔎 Data Preparation \u0026 Cleaning\n\nKey preprocessing steps:\n\n- Removed empty/NaN rows\n- Converted \"Free\" prices to 0\n- Converted price strings (INR) to numeric values (EUR conversion)\n- Renamed columns for easier access\n- Converted `Price` column to numeric type\n- Extracted:\n  - year\n  - month\n  - day\n  - weekday\n\n---\n\n## 📈 Exploratory Data Analysis\n\n### 📌 Most Popular Category\nBar chart analysis shows which category appears most frequently.\n\nResult: **Music** is the most frequent category in the dataset.\n\n---\n\n### 💰 Most Expensive Category\nPie chart of total category prices.\n\nResult: **Developer Tools** accounts for the highest total price share.\n\n---\n\n### 📆 Most Active Download Year\nLine plot analysis of downloads per year.\n\nResult: Downloads peaked in **2016**, followed by a decline.\n\n---\n\n### 📅 Most Active Download Day\nBar plot of downloads by weekday.\n\nResult: **Monday** has the highest download activity.\n\n---\n\n## ❓ Questions Answered\n\n### 1️⃣ Most Popular \u0026 Unpopular Apps\nSorted by:\n- Rating (primary)\n- Number of people rated (secondary)\n\n---\n\n### 2️⃣ Top 10 Most Expensive Apps\nIdentified using both:\n- `sort_values()`\n- `groupby()` + sorting\n\n---\n\n### 3️⃣ When Did the Most Downloads Occur?\nGrouped by:\n- Year\n- Month\n- Day\n- Weekday\n\nHighest single-day download: **30 January 2018**\n\n---\n\n### 4️⃣ Most Downloaded Category\nGrouped by category and summed total ratings.\n\nMusic category dominates downloads.\n\n---\n\n### 5️⃣ Total \u0026 Average Downloads\n\n- Total downloads: ~2.9 million\n- Average downloads per day: ~731\n\n---\n\n## 🚀 How to Run\n\n### Install dependencies:\n\n```bash\npip install pandas numpy matplotlib seaborn\n```\n\n### Run notebook:\n\n```bash\njupyter notebook microsoft-store-project.ipynb\n```\n\nor run script:\n\n```bash\npython microsoft_store_project.py\n```\n\n---\n\n## 🎯 Learning Outcomes\n\n- Data cleaning \u0026 preprocessing\n- Handling mixed-type columns\n- Exploratory Data Analysis (EDA)\n- Grouping \u0026 aggregation with pandas\n- Data visualization best practices\n- Business-oriented data questioning\n\n---\n\n## 📚 Acknowledgements\n\nThis project was completed as part of the online course \"Data Analysis with Python: Zero to Pandas\" by Jovian.\n\n- Dataset: Kaggle (Windows Store dataset)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyernaz-togizbayev%2Fmicrosoft_store_data-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fyernaz-togizbayev%2Fmicrosoft_store_data-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyernaz-togizbayev%2Fmicrosoft_store_data-analysis/lists"}