Convert your categorical variable into dummy variables here and put your variable in numpy.array. For example:
data.csv:
age,size,color_head
4,50,black
9,100,blonde
12,120,brown
17,160,black
18,180,brown
Extract data:
import numpy as np
import pandas as pd
df = pd.read_csv('data.csv')
df:
Convert categorical variable color_head
into dummy variables:
df_dummies = pd.get_dummies(df['color_head'])
del df_dummies[df_dummies.columns[-1]]
df_new = pd.concat([df, df_dummies], axis=1)
del df_new['color_head']
df_new:
Put that in numpy array:
x = df_new.values
Compute the correlation:
correlation_matrix = np.corrcoef(x.T)
print(correlation_matrix)
Output:
array([[ 1. , 0.99574691, -0.23658011, -0.28975028],
[ 0.99574691, 1. , -0.30318496, -0.24026862],
[-0.23658011, -0.30318496, 1. , -0.40824829],
[-0.28975028, -0.24026862, -0.40824829, 1. ]])
See :
numpy.corrcoef
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