{"id":21557275,"url":"https://github.com/kernel-loophole/data-analysis-with-pandas","last_synced_at":"2026-04-30T20:34:22.547Z","repository":{"id":58442213,"uuid":"476370647","full_name":"kernel-loophole/data-analysis-with-pandas","owner":"kernel-loophole","description":"pandas","archived":false,"fork":false,"pushed_at":"2023-02-15T20:37:41.000Z","size":14426,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-07T12:40:54.504Z","etag":null,"topics":["data-science","dataset","numpy","pandas","python"],"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/kernel-loophole.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":"2022-03-31T15:38:45.000Z","updated_at":"2023-07-19T00:19:14.000Z","dependencies_parsed_at":"2024-11-24T10:00:20.075Z","dependency_job_id":null,"html_url":"https://github.com/kernel-loophole/data-analysis-with-pandas","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/kernel-loophole/data-analysis-with-pandas","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kernel-loophole%2Fdata-analysis-with-pandas","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kernel-loophole%2Fdata-analysis-with-pandas/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kernel-loophole%2Fdata-analysis-with-pandas/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kernel-loophole%2Fdata-analysis-with-pandas/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/kernel-loophole","download_url":"https://codeload.github.com/kernel-loophole/data-analysis-with-pandas/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kernel-loophole%2Fdata-analysis-with-pandas/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32476682,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-30T13:12:12.517Z","status":"ssl_error","status_checked_at":"2026-04-30T13:12:06.837Z","response_time":57,"last_error":"SSL_read: 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-science","dataset","numpy","pandas","python"],"created_at":"2024-11-24T08:11:49.555Z","updated_at":"2026-04-30T20:34:22.531Z","avatar_url":"https://github.com/kernel-loophole.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# pandas\npandas\n# Create DataFrame and series \n# make it simple\n```python\n\nimport pandas as pd\ndata_frame=pd.DataFrame({\n        \"Name\":[\"ali\",\"zain\",\"junaid\"],\n        \"age\":[20,15,15],\n        \"sex\":[\"male\",\"male\",\"male\"]\n    })\n\n```\n# Load csv or Excel file\n```python\ndef read_from_csv(filename):\n    with open (filename) as f:\n        dataset=pd.read_csv(f)\n#     print(dataset.head(20))\n#     print(dataset.dtypes)\n    return dataset\ndataset=read_from_csv(\"cities.csv\")\ndataset \n```\n# Locks\n```python\nstudent_data.loc[student_data[\"First name\"].str.len().idxmax(),\"First name\"]\n```\n# Modin for parallel computing \n# Modin uses Ray or Dask to provide an effortless way to speed up your pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Modin provides seamless integration and compatibility with existing pandas code. Even using the DataFrame constructor is identical.\n```python\nimport modin.pandas as pd\nimport numpy as np\ndata_frame=pd.read_csv(\"Airbnb_Open_Data.csv\")\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkernel-loophole%2Fdata-analysis-with-pandas","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkernel-loophole%2Fdata-analysis-with-pandas","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkernel-loophole%2Fdata-analysis-with-pandas/lists"}