{"id":20303341,"url":"https://github.com/vbhvsingh0/matplotlib__egs","last_synced_at":"2026-05-28T13:31:22.016Z","repository":{"id":247679756,"uuid":"826548000","full_name":"vbhvsingh0/Matplotlib__egs","owner":"vbhvsingh0","description":"The codes here are examples of Matplotlib","archived":false,"fork":false,"pushed_at":"2024-07-10T00:25:47.000Z","size":4067,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-04T06:45:23.579Z","etag":null,"topics":["data-analysis","matplotlib-pyplot","numpy-library","pandas-python","python3"],"latest_commit_sha":null,"homepage":"","language":"Python","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/vbhvsingh0.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":"2024-07-09T23:27:19.000Z","updated_at":"2024-07-10T15:27:58.000Z","dependencies_parsed_at":"2024-07-10T03:34:20.310Z","dependency_job_id":null,"html_url":"https://github.com/vbhvsingh0/Matplotlib__egs","commit_stats":null,"previous_names":["vbhvsingh0/matplotlib__egs"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/vbhvsingh0/Matplotlib__egs","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vbhvsingh0%2FMatplotlib__egs","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vbhvsingh0%2FMatplotlib__egs/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vbhvsingh0%2FMatplotlib__egs/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vbhvsingh0%2FMatplotlib__egs/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/vbhvsingh0","download_url":"https://codeload.github.com/vbhvsingh0/Matplotlib__egs/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vbhvsingh0%2FMatplotlib__egs/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33611248,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-05-28T02:00:06.440Z","response_time":99,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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-analysis","matplotlib-pyplot","numpy-library","pandas-python","python3"],"created_at":"2024-11-14T16:36:49.810Z","updated_at":"2026-05-28T13:31:21.998Z","avatar_url":"https://github.com/vbhvsingh0.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Matplotlib__egs\nThe codes here are the examples of using Matplotlib\n\nNote: This codes here were a part of the Coursera course, \"Applied Plotting, Charting and data representation in Python\" offered by University of Michigan.\n\nThere are three codes here:\n\n1) Plotting weather pattern\n\nThe data for this assignment comes from a subset of The National Centers for Environmental Information (NCEI) Global Historical Climatology Network daily (GHCNd) (GHCN-Daily). The GHCN-Daily is comprised of daily climate records from thousands of land surface stations across the globe - it's a wonderfully large dataset to play with! In particular,  use data from the Ann Arbor Michigan location (my home!). and this is stored in the file: fb441e62df2d58994928907a91895ec62c2c42e6cd075c2700843b89.csv\n\nEach row in this datafile corresponds to a single observation from a weather station, and has the following variables:\n\n    id : station identification code\n    date : date in YYYY-MM-DD format (e.g. 2012-01-24 = January 24, 2012)\n    element : indicator of element type\n        TMAX : Maximum temperature (tenths of degrees C)\n        TMIN : Minimum temperature (tenths of degrees C)\n    value : data value for element (tenths of degrees C)\n\nFollowing steps were followed in order to plot the data:\n\n    * Read the documentation and familiarize yourself with the dataset, then write a python notebook which plots line graphs of the record high and record low temperatures by day of the year over the period 2005-2014. The area between the record high and record low temperatures for each day should be shaded.\n    * Overlay a scatter of the 2015 data for any points (highs and lows) for which the ten year record (2005-2014) record high or record low was broken in 2015. (Based on the graph, do you think extreme weather is getting more frequent in 2015?)\n    (Leap years were removed)\n \nOutput: weather_pattern.png\n\n\n2) Average of mean of some quantity vs years\n\nThe code here plots the mean of the quantity (here produced with random number generator but example can be average voting turnover in a country) as bar charts for the years 1992,1993,1994,1995. The standard deviation of the means were also calculated and displayed with error bars on the bar chart.\n\nHere is the twist: Depending upon the y-value chosen from the bar chart (interactively), the color of the bars will change displaying the confidence level of whether the y-value will be involved in the data of each year or not. This confidence level was calculated using Monte Carlo.\n\nOutput snipped is saved as meansvsyear_int.png\n\n3) Creating an animation of changing 4 random number distributions with changing sample-size. Animation function was used and the results are provided in hists_animation.gif.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvbhvsingh0%2Fmatplotlib__egs","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvbhvsingh0%2Fmatplotlib__egs","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvbhvsingh0%2Fmatplotlib__egs/lists"}