statsmodels で季節性のトレンドを見る - 日に日に分からんことが増えていく…

import warnings
import itertools
import numpy as np
import matplotlib.pyplot as plt
warnings.filterwarnings("ignore")
plt.style.use('fivethirtyeight')
import pandas as pd
import statsmodels.api as sm
import matplotlib
matplotlib.rcParams['axes.labelsize'] = 14
matplotlib.rcParams['xtick.labelsize'] = 12
matplotlib.rcParams['ytick.labelsize'] = 12
matplotlib.rcParams['text.color'] = 'k'

df = pd.read_excel("Superstore.xls")
furniture = df.loc[df['Category'] == 'Furniture']

furniture = furniture.set_index('Order Date')
y = furniture['Sales'].resample('MS').mean()

y.plot(figsize=(15, 6))
plt.show()


# 周期確認 additive: 足し算

import matplotlib as mpl

with mpl.rc_context():
    mpl.rc("figure", figsize=(18,8))
    decomposition = sm.tsa.seasonal_decompose(y, model='additive', freq=12)
    decomposition.plot()
    plt.show()