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python 方差分析

程序员文章站 2024-01-19 15:31:40
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pwd
‘d:\\python\\exerise-df\\df-data-analysis’
from scipy import stats
import pandas as pd
import numpy as np
from statsmodels.formula.api import ols
from statsmodels.stats.anova import anova_lm
from statsmodels.stats.multicomp import pairwise_tukeyhsd
import 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-09
Residual  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-15
cul         8.0  114.536224  14.317028  97.560054  1.611882e-52
Residual  136.0   19.958126   0.146751        NaN           NaN
相关标签: python numpy