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Pandas
pandas.pydata.org › docs › reference › api › pandas.Series.quantile.html
pandas.Series.quantile — pandas 3.0.6 documentation
Calculate the rolling quantile. ... Returns the q-th percentile(s) of the array elements. ... >>> s = pd.Series([1, 2, 3, 4]) >>> s.quantile(0.5) 2.5 >>> s.quantile([0.25, 0.5, 0.75]) 0.25 1.75 0.50 2.50 0.75 3.25 dtype: float64
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Pandas
pandas.pydata.org › pandas-docs › stable › reference › api › pandas.Series.quantile.html
pandas.Series.quantile — pandas 3.0.5 documentation
Calculate the rolling quantile. ... Returns the q-th percentile(s) of the array elements. ... >>> s = pd.Series([1, 2, 3, 4]) >>> s.quantile(0.5) 2.5 >>> s.quantile([0.25, 0.5, 0.75]) 0.25 1.75 0.50 2.50 0.75 3.25 dtype: float64
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Pandas
pandas.pydata.org › pandas-docs › version › 0.23 › generated › pandas.Series.quantile.html
pandas.Series.quantile — pandas 0.23.1 documentation
Extending Pandas · Release Notes · Enter search terms or a module, class or function name. Series.quantile(q=0.5, interpolation='linear')[source]¶ · Return value at the given quantile, a la numpy.percentile. See also · pandas.core.window.Rolling.quantile ·
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GeeksforGeeks
geeksforgeeks.org › pandas › python-pandas-series-quantile
Python | Pandas Series.quantile() - GeeksforGeeks
November 25, 2022 - The object supports both integer- ... the index. Pandas Series.quantile() function return value at the given quantile for the underlying data in the given Series object....
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Spark By {Examples}
sparkbyexamples.com › home › pandas › pandas series.quantile() function
Pandas Series.quantile() Function - Spark By {Examples}
March 27, 2024 - In Pandas, the Series.quantile() function is used to compute the quantiles of a Series. Quantiles are statistical values that divide the data into four
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Pandas
pandas.pydata.org › pandas-docs › version › 0.17 › generated › pandas.Series.quantile.html
pandas.Series.quantile — pandas 0.17.1 documentation
Return value at the given quantile, a la numpy.percentile. ... >>> s = Series([1, 2, 3, 4]) >>> s.quantile(.5) 2.5 >>> s.quantile([.25, .5, .75]) 0.25 1.75 0.50 2.50 0.75 3.25 dtype: float64
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Pandas
pandas.pydata.org › pandas-docs › version › 0.22 › generated › pandas.Series.quantile.html
pandas.Series.quantile — pandas 0.22.0 documentation
Return value at the given quantile, a la numpy.percentile. ... >>> s = Series([1, 2, 3, 4]) >>> s.quantile(.5) 2.5 >>> s.quantile([.25, .5, .75]) 0.25 1.75 0.50 2.50 0.75 3.25 dtype: float64
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Pandas
pandas.pydata.org › pandas-docs › version › 2.0 › reference › api › pandas.Series.quantile.html
pandas.Series.quantile — pandas 2.0.3 documentation
Calculate the rolling quantile. ... Returns the q-th percentile(s) of the array elements. ... >>> s = pd.Series([1, 2, 3, 4]) >>> s.quantile(.5) 2.5 >>> s.quantile([.25, .5, .75]) 0.25 1.75 0.50 2.50 0.75 3.25 dtype: float64
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Pandas
pandas.pydata.org › pandas-docs › version › 0.17.0 › generated › pandas.Series.quantile.html
pandas.Series.quantile — pandas 0.17.0 documentation
Return value at the given quantile, a la numpy.percentile. ... >>> s = Series([1, 2, 3, 4]) >>> s.quantile(.5) 2.5 >>> s.quantile([.25, .5, .75]) 0.25 1.75 0.50 2.50 0.75 3.25 dtype: float64
Find elsewhere
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Pandas
pandas.pydata.org › pandas-docs › version › 1.5 › reference › api › pandas.Series.quantile.html
pandas.Series.quantile — pandas 1.5.2 documentation
Calculate the rolling quantile. ... Returns the q-th percentile(s) of the array elements. ... >>> s = pd.Series([1, 2, 3, 4]) >>> s.quantile(.5) 2.5 >>> s.quantile([.25, .5, .75]) 0.25 1.75 0.50 2.50 0.75 3.25 dtype: float64
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Pandas
pandas.pydata.org › pandas-docs › version › 0.7.0 › generated › pandas.Series.quantile.html
pandas.Series.quantile — pandas 0.7.0 documentation
Series.quantile(q=0.5)¶ · Return value at the given quantile, a la scoreatpercentile in scipy.stats · previous | next | modules | modules | index Show Source · © Copyright 2008-2011, the pandas development team.
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Note.nkmk.me
note.nkmk.me › home › python › pandas
pandas: Find the quantile with quantile() | note.nkmk.me
January 19, 2024 - When calling quantile() on a Series, the median is returned as a scalar value.
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Pandas
pandas.pydata.org › pandas-docs › version › 2.2.1 › reference › api › pandas.Series.quantile.html
pandas.Series.quantile — pandas 2.2.1 documentation
Calculate the rolling quantile. ... Returns the q-th percentile(s) of the array elements. ... >>> s = pd.Series([1, 2, 3, 4]) >>> s.quantile(.5) 2.5 >>> s.quantile([.25, .5, .75]) 0.25 1.75 0.50 2.50 0.75 3.25 dtype: float64
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w3resource
w3resource.com › pandas › series › series-quantile.php
Pandas Series: quantile() function - w3resource
May 11, 2026 - Pandas Series - quantile() function: The quantile() function is used to return value at the given quantile.
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pandas
pandas.pydata.org › pandas-docs › dev › reference › api › pandas.Series.quantile.html
pandas.Series.quantile — pandas 3.1.0.dev0+1159.gd7b577e035 documentation
This method computes the value below which a given fraction of the data falls. When multiple quantiles are requested, a Series indexed by the quantile values is returned.
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Apache
spark.apache.org › docs › latest › api › python › reference › pyspark.pandas › api › pyspark.pandas.Series.quantile.html
pyspark.pandas.Series.quantile — PySpark 4.1.2 documentation
Unlike pandas’, the quantile in pandas-on-Spark is an approximated quantile based upon approximate percentile computation because computing quantile across a large dataset is extremely expensive. ... Default accuracy of approximation. Larger value means better accuracy.
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Pandas
pandas.pydata.org › pandas-docs › version › 0.8.0 › generated › pandas.Series.quantile.html
pandas.Series.quantile — pandas 0.8.0 documentation
Series.quantile(q=0.5)¶ · Return value at the given quantile, a la scoreatpercentile in scipy.stats · previous | next | modules | modules | index Show Source · © Copyright 2008-2012, the pandas development team.
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W3cubDocs
docs.w3cub.com › pandas~0.25 › reference › api › pandas.series.quantile
Series.quantile() - Pandas 0.25 - W3cubDocs
/pandas 0.25 · Series.quantile(self, q=0.5, interpolation='linear') [source] Return value at the given quantile. See also · core.window.Rolling.quantile · numpy.percentile · >>> s = pd.Series([1, 2, 3, 4]) >>> s.quantile(.5) 2.5 >>> s.quantile([.25, .5, .75]) 0.25 1.75 0.50 2.50 0.75 3.25 dtype: float64 ·