外国為替レートと実質実効為替レートを調べてグラフ化してみた

'''
US Dollor Exchange Rate
'''
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import japanize_matplotlib
import matplotlib.dates as mdates

filename = 'WS_XRU_D_csv_row.csv'

#header = 'Reference area'
header = 'Title'

df = pd.read_csv(filename, header=7)
df = df.drop(index=[0,1,2,3,4,5,6])
df["date"] = mdates.date2num(df[header])
df = df.set_index("date")
df = df.drop(columns=[header])
df = df.astype(float) # TypeError: no numeric data to plot対策

print(len(df)) # データの件数
print(df.columns.values) # ヘッダー（項目名一覧）
print(df)

index = 0
titles = []
for column in df.columns.values.tolist():
    if index % 4 == 0:
        fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(18, 12))
        fig.suptitle("USドル為替レート")
        titles = []
        fig.tight_layout() # 余白調整

        ax = df[column].plot(ax=axes[0, 0])
    elif index % 4 == 1:
        ax = df[column].plot(ax=axes[0, 1])
    elif index % 4 == 2:
        ax = df[column].plot(ax=axes[1, 0])
    elif index % 4 == 3:
        ax = df[column].plot(ax=axes[1, 1])        
    
    arr = column.split(' - ')
    title = arr[0] + ' - ' + arr[1]
    country = title.replace('Exchange rates against USD ','').split(' - ')[0].strip()

    titles.append(country)
    ax.set_ylabel('')
    ax.set_xlabel(title)
    ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y")) 

    if index % 4 == 3:
        png_path = 'usder-{}.png'.format(int(index/4))
        t = 'USドル為替レート - {}'.format(', '.join(titles))
        print('### {}'.format(t))
        print('![{}]({})'.format(t, png_path))

        plt.savefig(png_path)
        plt.close('all')
    
    index = index + 1

'''
実質実効為替レート
The real effective exchange rate (REER)
'''
import pandas as pd
import matplotlib.pyplot as plt
import japanize_matplotlib
import matplotlib.dates as mdates

if __name__ == "__main__":

    filename = 'broad.xlsx'

    target_column = ['Euro area', 'China', 'Germany', 'Japan', 'Korea', 'United States', 'United Kingdom']

# https://ja.wikipedia.org/wiki/%E5%90%8D%E7%9B%AE%E3%81%A8%E5%AE%9F%E8%B3%AA_(%E7%B5%8C%E6%B8%88%E5%AD%A6)
# 名目: Nominal 実質: Real
    df = pd.read_excel(filename, header=3, sheet_name='Real')

    df = df.drop(index=[0])
    df["date"] = mdates.date2num(df["EER for:"])
    df = df.set_index("date")
    print(df)
    df = df.drop(columns=["EER for:"])
    df = df.astype(float) # TypeError: no numeric data to plot対策

    print(len(df)) # データの件数
    print(df.columns.values) # ヘッダー（項目名一覧）
    print(df)

    fig, axes = plt.subplots(figsize=(14, 10))
    fig.tight_layout() # 余白を少なく表示
    
    for column in target_column:
        ax = df[column].plot()
        # ax.set_ylabel(column)
        # ax.set_xlabel('')
        ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y")) 
        
    plt.legend(loc='lower left') # upper left
    # plt.legend() # 凡例
    plt.title('BIS effective exchange rate - Nominal, Broad Indices')
    #plt.show()
    plt.savefig('reer.png')
    plt.close('all')