Pandas Data Series: Compute the autocorrelations of a given numeric series
Pandas: Data Series Exercise-34 with Solution
Write a Pandas program to compute the autocorrelations of a given numeric series.
Autocorrelation, also known as serial correlation, is the correlation of a signal with a delayed copy of itself as a function of delay. Informally, it is the similarity between observations as a function of the time lag between them.
Sample Solution :
Python Code :
import pandas as pd import numpy as np num_series = pd.Series(np.arange(15) + np.random.normal(1, 10, 15)) print("Original series:") print(num_series) autocorrelations = [num_series.autocorr(i).round(2) for i in range(11)] print("\nAutocorrelations of the said series:") print(autocorrelations[1:])
Original series: 0 13.207262 1 4.098685 2 -1.435534 3 13.626760 4 -1.435962 5 28.823612 6 -3.299048 7 14.048354 8 6.991233 9 13.289209 10 23.032654 11 7.080452 12 -2.453857 13 -2.346193 14 17.873884 dtype: float64 Autocorrelations of the said series: [-0.38, 0.1, -0.43, 0.03, 0.35, -0.2, 0.04, -0.59, 0.34, 0.11]
Python Code Editor:
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