{"id":18551954,"url":"https://github.com/bepb/kaggle_titanic","last_synced_at":"2025-04-09T22:31:47.103Z","repository":{"id":109797683,"uuid":"585268730","full_name":"BEPb/kaggle_titanic","owner":"BEPb","description":null,"archived":false,"fork":false,"pushed_at":"2023-05-17T06:10:47.000Z","size":4621,"stargazers_count":36,"open_issues_count":0,"forks_count":3,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-03-24T13:04:29.517Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/BEPb.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,"publiccode":null,"codemeta":null}},"created_at":"2023-01-04T18:38:58.000Z","updated_at":"2025-03-15T13:57:10.000Z","dependencies_parsed_at":null,"dependency_job_id":"88d05e6b-1532-42fb-bc3d-be3ec407ab0a","html_url":"https://github.com/BEPb/kaggle_titanic","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BEPb%2Fkaggle_titanic","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BEPb%2Fkaggle_titanic/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BEPb%2Fkaggle_titanic/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BEPb%2Fkaggle_titanic/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/BEPb","download_url":"https://codeload.github.com/BEPb/kaggle_titanic/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248123659,"owners_count":21051509,"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":"2024-11-06T21:11:16.833Z","updated_at":"2025-04-09T22:31:47.091Z","avatar_url":"https://github.com/BEPb.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n\n\n\u003cimg src=\"./art/logo.png\" alt=\"Bot logo\" width=\"300\" height=\"156.5\"\u003e\n\n# kaggle titanic\n\n\u003c/div\u003e\n\n## How it works?\n\nIt's very simple: here are the solutions for the [titanic competition ](https://www.kaggle.com/competitions/titanic)\n\n## Order of preparation and work\n\n1. Clone the repository or download the archive from github or using the following commands on the command line\n    ```command line\n    $cmd\n    $ git clone https://github.com/BEPb/kaggle_titanic\n    $ cd kaggle_titanic\n    ```\n\n2. Create a Python virtual environment.\n3. Install all necessary packages for our code to work using the following command:\n\n     ```\n     pip install -r requirements.txt\n     ```\n4. file list\n- data - directory with data files\n- data/titanic.zip - archive of the initial tabular data of the competition (3 files)\n- data/gender_submission.csv - one of the original data files\n- data/test.csv - one of the original data files\n- data/train.csv - one of the original data files\n- notebooks - directory with jupiter notebooks\n- notebooks/eda_and_analysis - directory with notebooks food and data analysis\n- notebooks/eda_and_analysis/titanic_universal_eda.ipynb - universal food notebook\n- notebooks/eda_and_analysis/titanic_eda.ipynb - food notebook\n- notebooks/solutions - directory with notebook solutions\n- python_code - directory with python code solutions\n\n\n5. Well, as a result of the training, I wrote a console application that, based on the model, predicts whether the \npassenger whose data you enter in the fields will survive or not. \n   - python_code/Titanic_gui.py\n\nprediction for my data, let's say I'm traveling first class with my family:\n\u003cimg src=\"./art/gui.png\" alt=\"Gui logo\" width=\"600\" height=\"600\"\u003e\n\n\nprediction for data from a set:\n\n\u003cimg src=\"./art/gui2.png\" alt=\"Gui logo\" width=\"600\" height=\"600\"\u003e","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbepb%2Fkaggle_titanic","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbepb%2Fkaggle_titanic","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbepb%2Fkaggle_titanic/lists"}