Autocorrelation plots graph autocorrelations of time series data for different lags. Autocorrelation is the correlation of a time series with the same time series lagged. The autocorrelation_plot() pandas function in pandas.tools.plotting can draw an autocorrelation plot.
The following is the code from the autocorr_plot.py file in this book's code bundle:
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from pandas.tools.plotting import autocorrelation_plot
df = pd.read_csv('transcount.csv')
df = df.groupby('year').aggregate(np.mean)
gpu = pd.read_csv('gpu_transcount.csv')
gpu = gpu.groupby('year').aggregate(np.mean)
df = pd.merge(df, gpu, how='outer', left_index=True, right_index=True)
df = df.replace(np.nan, 0)
autocorrelation_plot(np.log(df['trans_count']))
plt.show()Draw an autocorrelation plot for the CPU transistor counts as follows:
autocorrelation_plot(np.log(df['trans_count']))
Refer to the following plot for the end result. As we can...