{"id":15097570,"url":"https://github.com/hit07/data_science","last_synced_at":"2025-03-27T16:20:16.940Z","repository":{"id":245382499,"uuid":"817635811","full_name":"Hit07/Data_Science","owner":"Hit07","description":"Data [ Exploration, Cleaning, Manipulation, Visualisation ]","archived":false,"fork":false,"pushed_at":"2024-07-03T06:41:21.000Z","size":16148,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-27T16:19:56.549Z","etag":null,"topics":["data-analysis","data-cleaning","data-exploration","data-manipulation","data-visualization","eda","jupyter-notebook","matplotlib","numpy","pandas-dataframe","scipy"],"latest_commit_sha":null,"homepage":"","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/Hit07.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}},"created_at":"2024-06-20T06:30:28.000Z","updated_at":"2024-07-24T16:14:14.000Z","dependencies_parsed_at":"2024-09-20T00:01:19.650Z","dependency_job_id":"2b2f492e-a2ce-463b-8823-f2133187bad5","html_url":"https://github.com/Hit07/Data_Science","commit_stats":{"total_commits":35,"total_committers":1,"mean_commits":35.0,"dds":0.0,"last_synced_commit":"a5ad21d86226904bad5e84bedc0aa0a3f9a851d0"},"previous_names":["hit07/data_exploration"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Hit07%2FData_Science","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Hit07%2FData_Science/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Hit07%2FData_Science/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Hit07%2FData_Science/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Hit07","download_url":"https://codeload.github.com/Hit07/Data_Science/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245878929,"owners_count":20687297,"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-analysis","data-cleaning","data-exploration","data-manipulation","data-visualization","eda","jupyter-notebook","matplotlib","numpy","pandas-dataframe","scipy"],"created_at":"2024-09-25T16:23:42.575Z","updated_at":"2025-03-27T16:20:16.918Z","avatar_url":"https://github.com/Hit07.png","language":"Jupyter Notebook","readme":"# Data Science Project\n\nThis project covers several data analysis and visualization tasks using Python.\n\n## 1. Google Play Store Apps \u0026 Reviews Analysis\n\n### Overview\nAnalyzing Google Play Store app data for insights into ratings, sizes, reviews, and revenue estimates.\n\n### Files:\n- `apps.csv`: Dataset with app details.\n- `play_store.ipynb`: Jupyter notebook for data analysis.\n\n### Skills Learned:\n- Data cleaning and preprocessing.\n- Exploratory data analysis (EDA) techniques.\n- Visualization using matplotlib and seaborn.\n\n## 2. Data Exploration\n\n### Overview\nExploring salaries by college major dataset.\n\n### Files:\n- `salaries_by_college_major.csv`: Dataset on salaries by major.\n- `Salaries.ipynb`: Notebook for data exploration.\n\n### Skills Learned:\n- Data manipulation and handling missing data.\n- Basic statistical analysis.\n- Pandas operations for data summarization.\n\n## 3. Data Visualization\n\n### Overview\nVisualizing programming language popularity trends.\n\n### Files:\n- `prog_lang.ipynb`: Jupyter notebook for visualization.\n- `QueryResults.csv`: Dataset with programming language data.\n\n### Skills Learned:\n- Plotting with matplotlib.\n- Creating informative charts and graphs.\n- Data interpretation and presentation.\n\n## 4. Google Trends Analysis\n\n### Overview\nAnalyzing trends related to Bitcoin, TESLA, and unemployment benefits.\n\n### Files:\n- Various CSV files for trend data.\n- `trends.ipynb`: Notebook for trend analysis.\n\n### Skills Learned:\n- Time series data analysis.\n- Correlation analysis between different trends.\n- Insightful visualization techniques.\n\n## 5. LEGO Data Analysis\n\n### Overview\nAnalyzing LEGO dataset to understand themes and sets.\n\n### Files:\n- Datasets (`colors.csv`, `sets.csv`, `themes.csv`).\n- `Lego.ipynb`: Notebook for LEGO data analysis.\n\n### Skills Learned:\n- Data aggregation and merging.\n- Visualizing hierarchical data structures.\n- Insights into product trends and categorization.\n\n## 6. Numpy \u0026 N-dimensional Array\n\n### Overview\nPractical usage of NumPy for array operations.\n\n### Files:\n- `Numpy.ipynb`: Notebook for NumPy operations.\n- Images for illustration (`img_1.png`, `yummy_macarons.jpg`).\n\n### Skills Learned:\n- Efficient computation with NumPy arrays.\n- Basic image manipulation with NumPy.\n- Broadcasting and vectorization techniques.\n\n# Conclusion\nThis repository showcases various data science skills including data cleaning, exploration, visualization, and specialized tools like NumPy for efficient computation. Each section provides practical insights and skills applicable to real-world data analysis projects.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhit07%2Fdata_science","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhit07%2Fdata_science","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhit07%2Fdata_science/lists"}