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| author | Raymond Hettinger <rhettinger@users.noreply.github.com> | 2019-02-21 23:06:29 (GMT) |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2019-02-21 23:06:29 (GMT) |
| commit | 47d9987247bcc45983a6d51fd1ae46d5d356d0f8 (patch) | |
| tree | 16b7e88590f9a28ff47e8a0e041510c4a2d86756 /Doc/library | |
| parent | f36f89257b30e0bf88e8aaff6da14a9a96f57b9e (diff) | |
| download | cpython-47d9987247bcc45983a6d51fd1ae46d5d356d0f8.zip cpython-47d9987247bcc45983a6d51fd1ae46d5d356d0f8.tar.gz cpython-47d9987247bcc45983a6d51fd1ae46d5d356d0f8.tar.bz2 | |
bpo-35904: Add statistics.fmean() (GH-11892)
Diffstat (limited to 'Doc/library')
| -rw-r--r-- | Doc/library/random.rst | 4 | ||||
| -rw-r--r-- | Doc/library/statistics.rst | 18 |
2 files changed, 20 insertions, 2 deletions
diff --git a/Doc/library/random.rst b/Doc/library/random.rst index 7d051e1..79a7bdd 100644 --- a/Doc/library/random.rst +++ b/Doc/library/random.rst @@ -404,7 +404,7 @@ with replacement to estimate a confidence interval for the mean of a sample of size five:: # http://statistics.about.com/od/Applications/a/Example-Of-Bootstrapping.htm - from statistics import mean + from statistics import fmean as mean from random import choices data = 1, 2, 4, 4, 10 @@ -419,7 +419,7 @@ to determine the statistical significance or `p-value between the effects of a drug versus a placebo:: # Example from "Statistics is Easy" by Dennis Shasha and Manda Wilson - from statistics import mean + from statistics import fmean as mean from random import shuffle drug = [54, 73, 53, 70, 73, 68, 52, 65, 65] diff --git a/Doc/library/statistics.rst b/Doc/library/statistics.rst index 26bb592..20a2c1c 100644 --- a/Doc/library/statistics.rst +++ b/Doc/library/statistics.rst @@ -39,6 +39,7 @@ or sample. ======================= ============================================= :func:`mean` Arithmetic mean ("average") of data. +:func:`fmean` Fast, floating point arithmetic mean. :func:`harmonic_mean` Harmonic mean of data. :func:`median` Median (middle value) of data. :func:`median_low` Low median of data. @@ -111,6 +112,23 @@ However, for reading convenience, most of the examples show sorted sequences. ``mean(data)`` is equivalent to calculating the true population mean μ. +.. function:: fmean(data) + + Convert *data* to floats and compute the arithmetic mean. + + This runs faster than the :func:`mean` function and it always returns a + :class:`float`. The result is highly accurate but not as perfect as + :func:`mean`. If the input dataset is empty, raises a + :exc:`StatisticsError`. + + .. doctest:: + + >>> fmean([3.5, 4.0, 5.25]) + 4.25 + + .. versionadded:: 3.8 + + .. function:: harmonic_mean(data) Return the harmonic mean of *data*, a sequence or iterator of |