PyCalendar/calendaring

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    Data sources

    RepositoryPull requestsIssuesCompleteRead
    PyCalendar/calendaring 19 / 19 18 / 18 100% 1 hour, 13 minutes ago

    Download the data behind this page. The ODS spreadsheets also have the data each table was made from, and what the download is.

    How to check the numbers with scipy.

    Sources shown

    Pull requests (19)
    2
    open
    15
    merged
    2
    closed unmerged
    Issues (18)
    8
    open
    10
    closed

    Response times

    Time until the first response of each class of people (edit classes). The author's own comments do not count. Measured, normal and exponential use only the items that got a response; Kaplan-Meier counts the others, too, as waiting at least until they were closed or until now, and is "-" where less than half (or 95 %) got a response.

    Pull requests: first response times
    classnfitaveragestd errormedian95%
    collaborator or higher3measured1d 9h21h 30min23h 31min2d 21h
    collaborator or higher3normal1d 9h17h 34min1d 9h3d 11h
    collaborator or higher3exponential1d 9h19h 10min23h4d 3h
    collaborator or higher19Kaplan-Meier----
    Issues: first response times
    classnfitaveragestd errormedian95%
    collaborator or higher1measured1h 42min-1h 42min1h 42min
    collaborator or higher1normal1h 42min-1h 42min-
    collaborator or higher1exponential1h 42min1h 42min1h 11min5h 5min
    collaborator or higher18Kaplan-Meier----

    Badges

    Embed the response time in a README. The badge counts with the default classes of people. The badge shows what is in the database and never calls GitHub. Parameters: kind = pr or issue, percentile = 0-100, class = a class name (optional).

    badge preview