python 方差分析

来源：互联网发布：apache flink demo 编辑：程序博客网时间：2024/04/28 01:19

pwd

‘d:\\python\\exerise-df\\df-data-analysis’

from scipy import statsimport pandas as pdimport numpy as npfrom statsmodels.formula.api import olsfrom statsmodels.stats.anova import anova_lmfrom statsmodels.stats.multicomp import pairwise_tukeyhsdimport matplotlib.pyplot as plt

单因素方差分析

dat = pd.read_csv("one-way.csv")

dat.head()

Variety rep y 0 A b1 15.3 1 B b1 18.0 2 C b1 16.6 3 D b1 16.4 4 E b1 13.7

model = ols('y ~ Variety',dat).fit()

anovat = anova_lm(model)

print(anovat)

            df     sum_sq    mean_sq          F        PR(>F)Variety    5.0  52.378333  10.475667  40.334118  3.662157e-09Residual  18.0   4.675000   0.259722        NaN           NaN

二因素方差分析

dat = pd.read_csv("anova.csv")dat.head()

loc cul y 0 Ann BH93 4.460 1 Ari BH93 4.417 2 Aug BH93 4.669 3 Cas BH93 4.732 4 Del BH93 4.390

formula = 'y~ loc + cul'anova_results = anova_lm(ols(formula,dat).fit())print(anova_results)

             df      sum_sq    mean_sq          F        PR(>F)loc        17.0   22.671174   1.333598   9.087496  2.327448e-15cul         8.0  114.536224  14.317028  97.560054  1.611882e-52Residual  136.0   19.958126   0.146751        NaN           NaN

阅读全文

0 0