quantile() 函数

最新推荐文章于 2024-06-27 08:00:00 发布

原创最新推荐文章于 2024-06-27 08:00:00 发布 · 2.6w 阅读

9 ·

CC 4.0 BY-SA版权

文章标签：

#Python #quantile() #interpolation

随记专栏收录该内容

3 篇文章

订阅专栏

本文介绍了Python中的quantile()函数，用于计算指定的分位数。重点讲解了参数q、axis和interpolation的含义，以及四分位数的概念，包括Q1、Q2（中位数）和Q3，并提到了四分位距IQR的重要性。此外，还解释了不同插值方法对分位数计算的影响。

Series. quantile ( q=0.5, interpolation='linear' )

Parameters:

Parameters:	q : float or array-like, default 0.5 (50% quantile) 0 <= q <= 1, the quantile(s) to compute interpolation : {‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’} New in version 0.18.0. This optional parameter specifies the interpolation method to use, when the desired quantile lies between two data points i and j: linear: i + (j - i) * fraction, where fraction is the fractional part of the index surrounded by i and j. lower: i. higher: j. nearest: i or j whichever is nearest. midpoint: (i + j) / 2.
Returns:	quantile : float or Series if `q` is an array, a Series will be returned where the index is `q` and the values are the quantiles.

q : float or array-like, default 0.5 (50% quantile)

0 <= q <= 1, the quantile(s) to compute

interpolation : {‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’}

New in version 0.18.0.

This optional parameter specifies the interpolation method to use, when the desired quantile lies between two data points i and j:

linear: i + (j - i) * fraction, where fraction is the fractional part of the index surrounded by i and j.
lower: i.
higher: j.
nearest: i or j whichever is nearest.
midpoint: (i + j) / 2.

Returns:

quantile : float or Series

if q is an array, a Series will be returned where the index is q and the values are the quantiles.

- q : float or array-like, default 0.5 (50% quantile 即中位数-第2四分位数)
0 <= q <= 1, the quantile(s) to compute

- axis : {0, 1, ‘index’, ‘columns’} (default 0)
0 or ‘index’ for row-wise, 1 or ‘columns’ for column-wise

- interpolation（插值方法） : {‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’}

当选中的分为点位于两个数数据点 i and j 之间时:
linear: i + (j - i) * fraction, fraction由计算得到的pos的小数部分（可以通过下面一个例子来理解这个fraction）；
lower: i.
higher: j.
nearest: i or j whichever is nearest.

midpoint: (i + j) / 2.

统计学上的四分为函数

原则上q是可以取0到1之间的任意值的。但是有一个四分位数是q分位数中较为有名的。

所谓四分位数；即把数值由小到大排列并分成四等份，处于三个分割点位置的数值就是四分位数。

第1四分位数 (Q1)，又称“较小四分位数”，等于该样本中所有数值由小到大排列后第25%的数字。
第2四分位数 (Q2)，又称“中位数”，等于该样本中所有数值由小到大排列后第50%的数字。
第3四分位数 (Q3)，又称“较大四分位数”，等于该样本中所有数值由小到大排列后第75%的数字。

第3四分位数与第1四分位数的差距又称四分位距（InterQuartile Range,IQR）

当q=0.25 0.5 0.75 时，就是在计算四分位数。

Return value at the given quantile, a la numpy.percentile

DataFrame. quantile ( q=0.5, axis=0, numeric_only=True )

Parameters:

Parameters:	q : float or array-like, default 0.5 (50% quantile) 0 <= q <= 1, the quantile(s) to compute axis : {0, 1, ‘index’, ‘columns’} (default 0) 0 or ‘index’ for row-wise, 1 or ‘columns’ for column-wise
Returns:	quantiles : Series or DataFrame If `q` is an array, a DataFrame will be returned where the index is `q`, the columns are the columns of self, and the values are the quantiles. If `q` is a float, a Series will be returned where the index is the columns of self and the values are the quantiles.

q : float or array-like, default 0.5 (50% quantile)

0 <= q <= 1, the quantile(s) to compute

axis : {0, 1, ‘index’, ‘columns’} (default 0)

0 or ‘index’ for row-wise, 1 or ‘columns’ for column-wise

Returns:

quantiles : Series or DataFrame

If q is an array, a DataFrame will be returned where the index is q, the columns are the columns of self, and the values are the quantiles. If q is a float, a Series will be returned where the index is the columns of self and the values are the quantiles.

Return values at the given quantile over requested axis, a la numpy.percentile.