I have read data frame of sensor data, using pandas read_fwf function. I need to find covariance matrix of read 928991 x 8 matrix. Eventually, I want to find eigen vectors and eigen values, using principal component analysis algorithm for this covariance matrix.
The answer of this question would be as follows
import pandas as pd
import numpy as np
from numpy.linalg import eig
df_sensor_data = pd.read_csv('HT_Sensor_dataset.dat', delim_whitespace=True)
del df_sensor_data['id']
del df_sensor_data['time']
del df_sensor_data['Temp.']
del df_sensor_data['Humidity']
df = df_sensor_data.notna().astype('float64')
covariance_matrix = df_sensor_data.cov()
print(covariance_matrix)
values, vectors = eig(covariance_matrix)
print(values)
print(vectors)