我们可以使用python为卡方测试生成列联表吗? [英] Can we generate contingency table for chisquare test using python?
问题描述
我正在使用 scipy.stats.chi2_contingency 方法来获取卡方统计数据.我们需要传递频率表,即列联表作为参数.但是我有一个特征向量,想自动生成频率表.我们有这样的功能吗?我目前正在这样做:
I am using scipy.stats.chi2_contingency method to get chi square statistics. We need to pass frequency table i.e. contingency table as parameter. But I have a feature vector and want to automatically generate the frequency table. Do we have any such function available? I am doing it like this currently:
def contigency_matrix_categorical(data_series,target_series,target_val,indicator_val):
observed_freq={}
for targets in target_val:
observed_freq[targets]={}
for indicators in indicator_val:
observed_freq[targets][indicators['val']]=data_series[((target_series==targets)&(data_series==indicators['val']))].count()
f_obs=[]
var1=0
var2=0
for i in observed_freq:
var1=var1+1
var2=0
for j in observed_freq[i]:
f_obs.append(observed_freq[i][j]+5)
var2=var2+1
arr=np.array(f_obs).reshape(var1,var2)
c,p,dof,expected=chi2_contingency(arr)
return {'score':c,'pval':p,'dof':dof}
其中数据系列和目标系列是列值,另外两个是指标名称.任何人都可以帮忙吗?谢谢
Where data series and target series are the columns values and the other two are the name of the indicator. Can anyone help? thanks
推荐答案
您可以使用 pandas.crosstab
从 DataFrame 生成列联表.来自文档:
You can use pandas.crosstab
to generate a contingency table from a DataFrame. From the documentation:
计算两个(或多个)因素的简单交叉表.默认情况下计算因子的频率表,除非传递值数组和聚合函数.
Compute a simple cross-tabulation of two (or more) factors. By default computes a frequency table of the factors unless an array of values and an aggregation function are passed.
下面是一个使用示例:
import numpy as np
import pandas as pd
from scipy.stats import chi2_contingency
# Some fake data.
n = 5 # Number of samples.
d = 3 # Dimensionality.
c = 2 # Number of categories.
data = np.random.randint(c, size=(n, d))
data = pd.DataFrame(data, columns=['CAT1', 'CAT2', 'CAT3'])
# Contingency table.
contingency = pd.crosstab(data['CAT1'], data['CAT2'])
# Chi-square test of independence.
c, p, dof, expected = chi2_contingency(contingency)
以下数据
表
生成以下contingency
表
然后,scipy.stats.chi2_contingency(contingency)
返回 (0.052, 0.819, 1, array([[1.6, 0.4],[2.4, 0.6]]))代码>.
这篇关于我们可以使用python为卡方测试生成列联表吗?的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!