PyCalendar/django-icalendar

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    RepositoryPull requestsIssuesCompleteRead
    PyCalendar/django-icalendar 17 / 17 8 / 8 100% 1 hour, 15 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.

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    Pull requests (17)
    5
    open
    11
    merged
    1
    closed unmerged
    Issues (8)
    6
    open
    2
    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%
    bot13measured2min1min1min5min
    bot13normal2min1min2min6min
    bot13exponential2min0min1min5min
    bot17Kaplan-Meier--1min-
    collaborator or higher2measured9h 31min7h 25min9h 31min16h 11min
    collaborator or higher2normal9h 31min5h 15min9h 31min21h 43min
    collaborator or higher2exponential9h 31min6h 44min6h 36min1d 4h
    collaborator or higher17Kaplan-Meier----
    external6measured1min0min1min2min
    external6normal1min0min1min2min
    external6exponential1min0min1min3min
    external17Kaplan-Meier----
    Issues: first response times
    classnfitaveragestd errormedian95%
    collaborator or higher1measured1d 21h-1d 21h1d 21h
    collaborator or higher1normal1d 21h-1d 21h-
    collaborator or higher1exponential1d 21h1d 21h1d 7h5d 15h
    collaborator or higher8Kaplan-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