大 pandas 如何计算偏斜 [英] How does pandas calculate skew
问题描述
我正在计算一个 coskew 矩阵,并想用 skew
方法中内置的 Pandas 仔细检查我的计算.我无法协调熊猫如何执行计算.
I'm calculating a coskew matrix and wanted to double check my calculation with pandas built in skew
method. I could not reconcile how pandas performing the calculation.
将我的系列定义为:
import pandas as pd
series = pd.Series(
{0: -0.051917457635120283,
1: -0.070071606515280632,
2: -0.11204865874074735,
3: -0.14679988245503134,
4: -0.088062467095565145,
5: 0.17579741198527793,
6: -0.10765856028420773,
7: -0.11971470229167547,
8: -0.15169210769159247,
9: -0.038616800990881606,
10: 0.16988162977411481,
11: 0.092999418364443032}
)
我比较了以下计算,并希望它们相同.
I compared the following calculations and expected them to be the same.
series.skew()
1.1119637586658944
我
(((series - series.mean()) / series.std(ddof=0)) ** 3).mean()
0.967840223081231
我 - 拿 2
这明显不同.我认为可能是 Fisher-Pearson 系数.所以我做到了:
n = len(series)
skew = series.sub(series.mean()).div(series.std(ddof=0)).apply(lambda x: x ** 3).mean()
skew * (n * (n - 1)) ** 0.5 / (n - 1)
1.0108761442417222
还有很多.
pandas 如何计算偏斜?
How does pandas calculate skew?
推荐答案
我发现了 scipy.stats.skew
与参数 bias=False
返回相等的输出,所以我认为在 pandasskew
默认为 bias=False
:
I found scipy.stats.skew
with parameter bias=False
return equal output, so I think in pandas skew
is bias=False
by default:
偏差:布尔
如果为 False,则根据统计偏差对计算进行校正.
If False, then the calculations are corrected for statistical bias.
import pandas as pd
import scipy.stats.stats as stats
series = pd.Series(
{0: -0.051917457635120283,
1: -0.070071606515280632,
2: -0.11204865874074735,
3: -0.14679988245503134,
4: -0.088062467095565145,
5: 0.17579741198527793,
6: -0.10765856028420773,
7: -0.11971470229167547,
8: -0.15169210769159247,
9: -0.038616800990881606,
10: 0.16988162977411481,
11: 0.092999418364443032}
)
print (series.skew())
1.11196375867
print (stats.skew(series, bias=False))
1.1119637586658944
不确定 100%,但我想我在 代码
Not sure for 100%, but I think I find it in code
编辑(piRSquared)
EDIT (piRSquared)
来自 scipy
歪斜
代码
if not bias:
can_correct = (n > 2) & (m2 > 0)
if can_correct.any():
m2 = np.extract(can_correct, m2)
m3 = np.extract(can_correct, m3)
nval = ma.sqrt((n-1.0)*n)/(n-2.0)*m3/m2**1.5
np.place(vals, can_correct, nval)
return vals
调整是 (n * (n - 1)) ** 0.5/(n - 2)
而不是 (n * (n - 1)) ** 0.5/(n - 1)
这篇关于大 pandas 如何计算偏斜的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!