06 移動平均

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import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

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data = {
    "value": {
        "2013-01-01": 2878.8,
        ...
        "2021-12-01": 3012.3,
    }
}

data = pd.DataFrame(data)
data.index = pd.to_datetime(data.index)
data = data.rename(columns={"value": "Natural Gas Consumption(BCF)"})

plt.figure(figsize=(12, 6))
sns.lineplot(data=data)
plt.title("天然ガス消費量（BCF）")
plt.show()

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data_sma = data.copy()
rolling_obj = data_sma["Natural Gas Consumption(BCF)"].rolling(12)
data_sma["SMA(12)"] = rolling_obj.mean()
data_sma["RollingMax(12)"] = rolling_obj.max()
data_sma["RollingMin(12)"] = rolling_obj.min()

plt.figure(figsize=(12, 6))
sns.lineplot(data=data_sma[["Natural Gas Consumption(BCF)", "SMA(12)", "RollingMax(12)", "RollingMin(12)"]])
plt.title("SMA と上下バンド")
plt.show()

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weights = np.array([0, 1, 2, 3, 4, 5, 5, 4, 3, 2, 1, 0])

def get_wma(values, w=weights):
    return np.sum(w * values) / w.sum()

data_wma = data.copy()
data_wma["WMA(12, center=True)"] = (
    data_wma["Natural Gas Consumption(BCF)"]
    .rolling(12, center=True)
    .apply(get_wma, raw=True)
)
data_wma["WMA(12, center=False)"] = (
    data_wma["Natural Gas Consumption(BCF)"]
    .rolling(12, center=False)
    .apply(get_wma, raw=True)
)

plt.figure(figsize=(12, 6))
sns.lineplot(data=data_wma)
plt.title("加重移動平均（center True/False）")
plt.show()

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data_ema = data.copy()
data_ema["EMA(12)"] = (
    data_ema["Natural Gas Consumption(BCF)"].ewm(span=12, adjust=False).mean()
)

plt.figure(figsize=(12, 6))
sns.lineplot(data=data_ema)
plt.title("指数移動平均 (EMA)")
plt.show()