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machine-learning pandas python time-series arima

其他 - 在ARIMA时间序列建模py中提取列表中的p值以进行Adfuller测试(平稳性测试)

发布于 2020-03-31 23:36:30

df

 Col1   Col2   Col3
  12     10     3
   3      5     2
  100    12     10

等等.....

为时间序列中的ARIMA建模编写adfuller测试的代码。(将为数据帧df的所有列计算p值)

import statsmodels.tsa.stattools as tsa
adf_results = {}
for col in df.columns.values:  
    adf_results[col] = tsa.adfuller(df[col])

使用此代码,我得到以下格式的输出:(当我键入adf_result时输出)

 [IN] adf_result
 [OUT]
  {'Col1': (-4.236149193618492,
  0.0005719678593039654,  #This is the second value for this column/p value
  0,
  37,
  {'1%': -3.6209175221605827,
   '5%': -2.9435394610388332,
   '10%': -2.6104002410518627},
  138.66116123406837),
 'Col2': (-3.707023043984407,
  0.004015446231411924,  #This is the second value for this column/p value
  0,
  37,
  {'1%': -3.6209175221605827,
   '5%': -2.9435394610388332,
   '10%': -2.6104002410518627},
  144.6019873130419),
 'Col3': (1.8083888603589304,
  0.9983655107052215,   #This is the second value for this column/p value
  0,
  37,
  {'1%': -3.6209175221605827,
   '5%': -2.9435394610388332,
   '10%': -2.6104002410518627},
  -74.4384052778039)}

等等。

在这个问题中,第二个值/ p值是

    0.0005719678593039654, 0.004015446231411924 and 0.9983655107052215 for the 3 columns taken.

我需要一个列表中第二个值> 0.05的列和另一列表中p值<0.05的列

因此,一个列表将是col1和col2(第二个值/ p值<0.05),另一个列表将是col3(第二个值/ p值<0.05)

查看更多

提问者
Shailaja Gupta Kapoor
被浏览
58
Zaraki Kenpachi 2020-01-31 20:01
import pandas as pd
from io import StringIO


data = StringIO("""
Col1 Col2 Col3
12 10 3
3 5 2
100 12 10
13 4 1
""")

# load data into data frame
df = pd.read_csv(data, sep=' ')

import statsmodels.tsa.stattools as tsa
adf_results = {}
for col in df.columns.values:
    adf_results[col] = tsa.adfuller(df[col])

# loop over dictionary data
columns_big = []
columns_small = []
for key, value in adf_results.items():
    if value[1] > 0.05:
        columns_big.append(key)
    else:
        columns_small.append(key)

输出:

columns_big = ['Col1', 'Col3']
columns_small = ['Col2']

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