{"id":23910930,"url":"https://github.com/devoloper-1/iris-dataset","last_synced_at":"2026-02-28T02:16:37.597Z","repository":{"id":233018109,"uuid":"785752316","full_name":"DEVOLOPER-1/Iris-Dataset","owner":"DEVOLOPER-1","description":"Data Manipulation and Visualization","archived":false,"fork":false,"pushed_at":"2024-04-12T15:00:56.000Z","size":372,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-05T07:33:34.060Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"unlicense","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/DEVOLOPER-1.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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}},"created_at":"2024-04-12T14:48:14.000Z","updated_at":"2024-04-14T08:28:28.000Z","dependencies_parsed_at":"2024-04-13T00:07:56.114Z","dependency_job_id":"9fe869c5-bdf6-4a2b-8249-8354ff04296c","html_url":"https://github.com/DEVOLOPER-1/Iris-Dataset","commit_stats":null,"previous_names":["devoloper-1/iris-dataset"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DEVOLOPER-1%2FIris-Dataset","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DEVOLOPER-1%2FIris-Dataset/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DEVOLOPER-1%2FIris-Dataset/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DEVOLOPER-1%2FIris-Dataset/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/DEVOLOPER-1","download_url":"https://codeload.github.com/DEVOLOPER-1/Iris-Dataset/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240347981,"owners_count":19787237,"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":[],"created_at":"2025-01-05T07:29:49.418Z","updated_at":"2026-02-28T02:16:32.578Z","avatar_url":"https://github.com/DEVOLOPER-1.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Iris Dataset Manipulation and Visualization - README\n\nThis project provides tools for manipulating and visualizing the Iris flower dataset, a classic dataset used in machine learning and data science.\n\n**What's Included:**\n\n* Scripts for loading the Iris dataset from a CSV file.\n* Functions for data cleaning and exploration:\n    * Handling missing values (if applicable).\n    * Calculating descriptive statistics (mean, standard deviation, etc.).\n    * Exploring data distributions through visualizations.\n* Tools for data visualization:\n    * Creating scatter plots to visualize relationships between features (e.g., petal length vs. sepal length).\n    * Generating histograms or boxplots to examine distributions of each feature.\n    * Implementing dimensionality reduction techniques (e.g., Principal Component Analysis) for visualizing data in lower dimensions if needed.\n\n**Getting Started:**\n\n1. **Prerequisites:** Ensure you have the necessary libraries installed for your chosen programming language (e.g., pandas, matplotlib for Python).\n2. **Data:** Acquire the Iris dataset from a reliable source like UCI Machine Learning Repository ([https://archive.ics.uci.edu/dataset/53/iris](https://archive.ics.uci.edu/dataset/53/iris)). Place the CSV file in the project directory.\n3. **Run the Scripts:** Execute the provided scripts (e.g., Python script named `iris_analysis.py`) based on your specific implementation.\n\n**Expected Output:**\n\nThe scripts will generate various visualizations (plots, charts) that help you understand the structure and relationships within the Iris dataset. These visualizations can be used to:\n\n* Identify potential outliers or patterns in the data.\n* Compare and contrast different flower species based on their features.\n* Gain insights for further data analysis or machine learning tasks.\n\n**Further Exploration:**\n\n- Experiment with different data visualization techniques to see which ones best reveal insights from the dataset.\n- Try implementing dimensionality reduction techniques to visualize the data in lower dimensions.\n- Consider incorporating machine learning algorithms to classify iris flowers based on their features.\n\n**Disclaimer:**\n\nThis project provides a basic framework for manipulating and visualizing the Iris dataset. You might need to adapt the code and visualizations based on your specific goals and chosen programming language.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdevoloper-1%2Firis-dataset","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdevoloper-1%2Firis-dataset","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdevoloper-1%2Firis-dataset/lists"}