{"id":18551908,"url":"https://github.com/linsomniac/python-movingaverage","last_synced_at":"2025-04-09T22:31:42.109Z","repository":{"id":1379175,"uuid":"1332858","full_name":"linsomniac/python-movingaverage","owner":"linsomniac","description":"Function for computing a moving average of data.","archived":false,"fork":false,"pushed_at":"2011-02-16T03:53:47.000Z","size":94,"stargazers_count":20,"open_issues_count":0,"forks_count":7,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-04-02T23:09:01.244Z","etag":null,"topics":[],"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/linsomniac.png","metadata":{"files":{"readme":"README","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}},"created_at":"2011-02-05T22:41:52.000Z","updated_at":"2023-02-12T01:06:04.000Z","dependencies_parsed_at":"2022-07-29T11:19:40.224Z","dependency_job_id":null,"html_url":"https://github.com/linsomniac/python-movingaverage","commit_stats":null,"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linsomniac%2Fpython-movingaverage","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linsomniac%2Fpython-movingaverage/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linsomniac%2Fpython-movingaverage/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linsomniac%2Fpython-movingaverage/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/linsomniac","download_url":"https://codeload.github.com/linsomniac/python-movingaverage/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248123641,"owners_count":21051507,"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":"2024-11-06T21:11:01.551Z","updated_at":"2025-04-09T22:31:41.844Z","avatar_url":"https://github.com/linsomniac.png","language":"Python","readme":"Written by Sean Reifschneider  \u003cjafo@tummy.com\u003e\nReleased into the Public Domain\n2011-02-05\n\nModule to compute the moving average of a list.  For example:\n\n   from movingaverage import movingaverage\n   print list(movingaverage([1,2,3,4,5,6], 3))\n   \u003e\u003e\u003e [2,3,4,5]\n\nNOTE: Another option is the \"stats\" pacakge, which is currently (Feb 2011)\nin early development.  The author of that package says that it includes\nseveral moving average functions.  I haven't used it, because I didn't find\nout about it until after I wrote this.  For more information see:\nhttp://pypi.python.org/pypi/stats/\n\nmovingaverage(data, subset_size, data_is_list = None, avoid_fp_drift = True)\n\n   Return the moving averages of the data, with a window size of\n   `subset_size`.  `subset_size` must be an integer greater than 0 and\n   less than the length of the input data, or a ValueError will be raised.\n\n   `data_is_list` can be used to tune the algorithm for list or iteratable\n   as an input.  The default value, `None` will auto-detect this.\n   The algorithm used if `data` is a list is almost twice as fast as if\n   it is an iteratable.\n\n   `avoid_fp_drift`, if True (the default) sums every sub-set rather than\n   keeping a \"rolling sum\" (which may be subject to floating-point drift).\n   While more correct, it is also dramatically slower for subset sizes\n   much larger than 20.\n\n   NOTE: You really should consider setting `avoid_fp_drift = False` unless\n   you are dealing with very small numbers (say, far smaller than 0.00001)\n   or require extreme accuracy at the cost of execution time.  For\n   `subset_size` \u003c 20, the performance difference is very small.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flinsomniac%2Fpython-movingaverage","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flinsomniac%2Fpython-movingaverage","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flinsomniac%2Fpython-movingaverage/lists"}