7
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Ran 30 Mar 2019 12:02AM UTC

Files 108

Run time 5s

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Committed 29 Mar 2019 09:34PM UTC coverage: 91.453% (-0.004%) from 91.457%

Job # PYTHON=3.6 NUMPY=1.14.1 PANDAS=0.22.0 TEST='true' LINT='true' COVERAGE='true' PARALLEL='false' XTRATESTARGS= TEST_IMPORTS='true'

Build Type

push

travis-ci

Committed by

martindurant

Commit Message

correct quantile to handle unsorted quantiles (#4650)

* correct quantile to handle unsorted quantiles

Currently dask.dataframe.core.quantile(df, q) can silently give incorrect results when the list of quantiles, q, is not sorted. For instance quantile(dask.array.arange(100), [0.75, 0.50, 0.25]) gives incorrect results. This patch uses numpy's mergesort to ensure that the quantiles are sorted. Note that with the patch behavior still differs from that in pandas.DataFrame.quantile() where quantiles are calculated correctly while preserving order. While this patch does not duplicate the behavior of pandas because it does not preserve the order of the quantiles, it does at least avoids the silent errors.

* added tests for unsorted arg to quantile

* moved sorting of quantiles before index is created

* avoid modifying argument to quantile()

* leave q arg to quantiles alone if scalar

* eliminated trailing whitespace

* testing quantile added length 1 list and scalar case

Run Details

17270 of 18884 relevant lines covered (91.45%)

0.91 hits per line

Source Files on job 11123.7 (PYTHON=3.6 NUMPY=1.14.1 PANDAS=0.22.0 TEST='true' LINT='true' COVERAGE='true' PARALLEL='false' XTRATESTARGS= TEST_IMPORTS='true')

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Source Files on job 11123.7 (PYTHON=3.6 NUMPY=1.14.1 PANDAS=0.22.0 TEST='true' LINT='true' COVERAGE='true' PARALLEL='false' XTRATESTARGS= TEST_IMPORTS='true')

dask / dask / 11123 / 7 53% master: 53%

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Source Files on job 11123.7 (PYTHON=3.6 NUMPY=1.14.1 PANDAS=0.22.0 TEST='true' LINT='true' COVERAGE='true' PARALLEL='false' XTRATESTARGS= TEST_IMPORTS='true')

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