PyCalendar/plann

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    PyCalendar/plann 32 / 32 54 / 54 100% 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.

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    Pull requests (32)
    0
    open
    28
    merged
    4
    closed unmerged
    Issues (54)
    29
    open
    25
    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%
    bot1measured1min-1min1min
    bot1normal1min-1min-
    bot1exponential1min1min0min2min
    bot32Kaplan-Meier----
    collaborator or higher5measured12h6h 32min2h 11min1d 5h
    collaborator or higher5normal12h5h 51min12h1d 9h
    collaborator or higher5exponential12h5h 22min8h 19min1d 11h
    collaborator or higher32Kaplan-Meier----
    Issues: first response times
    classnfitaveragestd errormedian95%
    collaborator or higher15measured4h 36min1h 36min2h 47min16h 2min
    collaborator or higher15normal4h 36min1h 33min4h 36min14h 28min
    collaborator or higher15exponential4h 36min1h 11min3h 11min13h 47min
    collaborator or higher54Kaplan-Meier----
    external2measured68d 10h9d 6h68d 10h76d 19h
    external2normal68d 10h6d 13h68d 10h83d 17h
    external2exponential68d 10h48d 9h47d 10h205d 1h
    external54Kaplan-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