PyCalendar/django-icalendar

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    PyCalendar/django-icalendar 17 / 17 8 / 8 100% 12 hours, 5 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 (10)
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    6
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    Issues (0)
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    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.

    What the statistics mean
    classnfitaveragestd errormedian95%
    bot10measured1min0min1min1min
    bot10normal1min0min1min1min
    bot10exponential1min0min1min3min
    bot10Kaplan-Meier--1min1min
    collaborator or higher1measured2h 6min-2h 6min2h 6min
    collaborator or higher1normal2h 6min-2h 6min-
    collaborator or higher1exponential2h 6min2h 6min1h 27min6h 18min
    collaborator or higher10Kaplan-Meier----

    n counts the items with a response of the class. Kaplan-Meier counts all items, so its n is the same for every class: the items without a response of the class count as waiting, until they were closed or until now. How to read the response times

    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), model = measured, normal, exponential or kaplan-meier (optional), label = the text of the left side (optional).

    badge preview