{"id":25176437,"url":"https://github.com/mamtapanda088/dataanalaysis-warmup-","last_synced_at":"2025-04-04T01:41:02.663Z","repository":{"id":253255398,"uuid":"842948087","full_name":"mamtapanda088/Dataanalaysis-warmup-","owner":"mamtapanda088","description":"Tasks: Create a DataFrame: Convert the dictionary into a pandas DataFrame. Top and Bottom Rows: Display the top 3 bottom ,3 rows of the DataFrame. Summary Statistics: Generate summary statistics for the dataset. Gender Count: Count the occurrences of each gender. Marks Analysis: Calculate the average, maxi, and min marks. Tools Used: Python ,pandas","archived":false,"fork":false,"pushed_at":"2024-08-15T13:14:14.000Z","size":6,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-09T13:17:08.370Z","etag":null,"topics":["data-analysis","data-science","jupyter-notebook","visualization"],"latest_commit_sha":null,"homepage":"https://github.com/mamtapanda088/Dataanalaysis-warmup-","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/mamtapanda088.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":"2024-08-15T13:03:53.000Z","updated_at":"2024-08-15T13:21:05.000Z","dependencies_parsed_at":"2024-08-15T15:08:28.832Z","dependency_job_id":"25fcc74e-e563-4131-a6c7-47e616eb17d9","html_url":"https://github.com/mamtapanda088/Dataanalaysis-warmup-","commit_stats":null,"previous_names":["mamtapanda088/dataanalaysis-warmup-"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mamtapanda088%2FDataanalaysis-warmup-","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mamtapanda088%2FDataanalaysis-warmup-/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mamtapanda088%2FDataanalaysis-warmup-/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mamtapanda088%2FDataanalaysis-warmup-/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mamtapanda088","download_url":"https://codeload.github.com/mamtapanda088/Dataanalaysis-warmup-/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247107820,"owners_count":20884795,"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-science","jupyter-notebook","visualization"],"created_at":"2025-02-09T13:17:10.244Z","updated_at":"2025-04-04T01:41:02.644Z","avatar_url":"https://github.com/mamtapanda088.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"Explanation:\nCreating the Dataset: The dictionary dict1 is defined with keys ‘Name’, ‘Marks’, and ‘Gender’.\nCreating a DataFrame: The pandas DataFrame is created from the dictionary.\nTop 3 Rows: The head(3) method is used to display the top 3 rows of the DataFrame.\nBottom 3 Rows: The tail(3) method is used to display the bottom 3 rows of the DataFrame.\nSummary Statistics: The describe(include='all') method provides summary statistics for all columns, including count, unique values, top values, frequency, mean, standard deviation, min, max, and quartiles.\nGender Count: The value_counts() method is used to count the occurrences of each gender.\nAverage Marks: The mean() method calculates the average marks.\nMaximum and Minimum Marks: The max() and min() methods find the highest and lowest marks, respectively.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmamtapanda088%2Fdataanalaysis-warmup-","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmamtapanda088%2Fdataanalaysis-warmup-","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmamtapanda088%2Fdataanalaysis-warmup-/lists"}