运行 spicy.stats 数据框列中所有唯一值的 ANOVA 测试?

Run spicy.stats ANOVA test for all unique values in a data frames column?

我有一个包含许多城市及其相应温度的数据框:

               CurrentThermostatTemp
City                                
Cradley Heath                   20.0
Cradley Heath                   20.0
Cradley Heath                   18.0
Cradley Heath                   15.0
Cradley Heath                   19.0
...                              ...
Walsall                         16.0
Walsall                         22.0
Walsall                         20.0
Walsall                         20.0
Walsall                         20.0

[6249 rows x 1 columns]

唯一值是:

Index(['Cradley Heath', 'ROWLEY REGIS', 'Smethwick', 'Oldbury',
       'West Bromwich', 'Bradford', 'Bournemouth', 'Poole', 'Wareham',
       'Wimborne',
       ...
       'St. Helens', 'Altrincham', 'Runcorn', 'Widnes', 'St Helens',
       'Wakefield', 'Castleford', 'Pontefract', 'Walsall', 'Wednesbury'],
      dtype='object', name='City', length=137)

我的目标是进行单向方差分析测试,即

from scipy.stats import f_oneway

对于数据框中的所有唯一值。也一样

SciPy.stats.f_oneway("all unique values")

并接收输出:所有变量的单向方差分析检验给出 {} 和 p 值 {} 这是我尝试了很多次但不起作用的方法:

all = Tempvs.index.unique()
Tempvs.sort_index(inplace=True)
for n in range(len(all)):
    truncated = Tempvs.truncate(all[n], all[n])
    print(f_oneway(truncated))

IIUC 您想要一个方差分析测试,其中每个样本都包含独特元素 City 的值 Temp。如果是这种情况,你可以这样做

import numpy as np
import pandas as pd
import scipy.stats as sps

# I create a sample dataset
index = ['Cradley Heath', 'ROWLEY REGIS',
         'Smethwick', 'Oldbury',
         'West Bromwich', 'Bradford', 
         'Bournemouth', 'Poole', 'Wareham',
         'Wimborne','St. Helens', 'Altrincham', 
         'Runcorn', 'Widnes', 'St Helens',
         'Wakefield', 'Castleford', 'Pontefract', 
         'Walsall', 'Wednesbury']
np.random.seed(1)
df = pd.DataFrame({
    'City': np.random.choice(index, 500),
    'Temp': np.random.uniform(15, 25, 500)
})

# populate a list with all
# values of unique Cities
values = []
for city in df.City.unique():
    _df = df[df.City==city]
    values.append(_df.Temp.values)

# compute the ANOVA
# with starred *list
# as arguments
sps.f_oneway(*values)

在这种情况下,会给出

F_onewayResult(statistic=0.4513685152123563, pvalue=0.9788508507035195)

PS: do not use all as a variable, because it is a builtin python function, see https://docs.python.org/3/library/functions.html#all