数据分析 - 在python进行方差分析时，残差的自由度总是为0.

做过很多尝试，将数据集中的0值去掉也不行。因为数据集2是可以正常出结果的，照着它的样子改动，把月份改成字母还是不行。

#coding:utf8
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


path = r"E:\python code\zuoye\2facter-avaon.csv"
df = pd.read_csv(path,header=None,names=['data','month','time'] ) 
formula = 'data~C(time) + C(month) + C(time):C(month)'
anova_results = anova_lm(ols(formula,df).fit())
print(anova_results)

运行结果是这样的

数据集1（是我想要分析的）

1,4574.82,Jan,8
2,32136.71,Jan,9
3,73890.49,Jan,10
4,61498.92,Jan,11
5,38142.71,Jan,12
6,45988.9,Jan,13
7,66276.1,Jan,14
8,82821.365,Jan,15
9,81560.06,Jan,16
10,78350.47,Jan,17
11,80930.74,Jan,18
12,95226.79,Jan,19
13,75982.9,Jan,20
14,14012.17,Jan,21
15,4574.82,Feb,8
16,32136.71,Feb,9
17,73890.49,Feb,10
18,61498.92,Feb,11
19,38142.71,Feb,12
20,45988.9,Feb,13
21,66276.1,Feb,14
22,82821.365,Feb,15
23,81560.06,Feb,16
24,78350.47,Feb,17
25,80930.74,Feb,18
26,95226.79,Feb,19
27,75982.9,Feb,20
28,14012.17,Feb,21

数据集2（从网上教程中下的，可以正常出结果）

    len    supp    dose
1    4.2    VC    0.5
2    11.5    VC    0.5
3    7.3    VC    0.5
4    5.8    VC    0.5
5    6.4    VC    0.5
6    10    VC    0.5
7    11.2    VC    0.5
8    11.2    VC    0.5
9    5.2    VC    0.5
10    7    VC    0.5
11    16.5    VC    1
12    16.5    VC    1
13    15.2    VC    1
14    17.3    VC    1
15    22.5    VC    1
16    17.3    VC    1
17    13.6    VC    1
18    14.5    VC    1
19    18.8    VC    1
20    15.5    VC    1
21    23.6    VC    2
22    18.5    VC    2
23    33.9    VC    2
24    25.5    VC    2
25    26.4    VC    2
26    32.5    VC    2
27    26.7    VC    2
28    21.5    VC    2
29    23.3    VC    2
30    29.5    VC    2
31    15.2    OJ    0.5
32    21.5    OJ    0.5
33    17.6    OJ    0.5
34    9.7    OJ    0.5
35    14.5    OJ    0.5
36    10    OJ    0.5
37    8.2    OJ    0.5
38    9.4    OJ    0.5
39    16.5    OJ    0.5
40    9.7    OJ    0.5
41    19.7    OJ    1
42    23.3    OJ    1
43    23.6    OJ    1
44    26.4    OJ    1
45    20    OJ    1
46    25.2    OJ    1
47    25.8    OJ    1
48    21.2    OJ    1
49    14.5    OJ    1
50    27.3    OJ    1
51    25.5    OJ    2
52    26.4    OJ    2
53    22.4    OJ    2
54    24.5    OJ    2
55    24.8    OJ    2
56    30.9    OJ    2
57    26.4    OJ    2
58    27.3    OJ    2
59    29.4    OJ    2
60    23    OJ    2

![clipboard.png](/img/bVLHoD)