from IPython.core.display import display, HTML
display(HTML("<style>.container { width:80% !important; }</style>"))

import pandas as pd
import pprint

pd.options.display.float_format = '{:20,.4f}'.format
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.width', 1000)
pd.set_option('display.colheader_justify', 'center')
pd.set_option('display.precision', 3)

# open file
x_rates = pd.read_csv("euro-daily-hist_1999_2020.csv")

# strip brackets and trailing space from country names
# replace remaining space with underscore
# lower case all column names
x_rates.columns = x_rates.columns.str.replace("[","").str.replace("]","")
x_rates.columns = x_rates.columns.str.rstrip()
x_rates.columns = x_rates.columns.str.replace(" ","_")
x_rates.columns = x_rates.columns.str.lower()

# rename columns
x_rates.rename(columns={"period\\unit:":"date",
                        "chinese_yuan_renminbi":"chinese_yuan",
                        "uk_pound_sterling":"uk_pound"}, inplace=True)

# convert datetime
x_rates["date"] = pd.to_datetime(x_rates["date"])

# resort and reindex
x_rates.sort_values("date", inplace=True)
x_rates.reset_index(drop=True, inplace=True)

# convert hyphens in currency columns to NaN
import numpy as np
x_rates = x_rates.replace("-", np.nan)

# convert exchange rate values to float
x_rates.iloc[:,1:] = x_rates.iloc[:,1:].astype(float)

mini = x_rates.iloc[:5000]
display(mini.head(2))
display(mini.tail(2))

display(br_vol)

# use string of currency to get index position and assign it to variable name
index = col_names.index("chinese_yuan")
print(index)
chinese_yuan = df_list[5]

# function to create df for each year in currency df
def split_years(df):
    return [df[df['year'] == y] for y in df['year'].unique()]

all_the_years = split_years(chinese_yuan)
# see if I can make split_years split and heads


# # determine annual volatility for euro to currency
# for frame in all_the_years:
#     year_name = frame.iat[0,4]
#     annual_volatility = frame["log_rate"].std()*253**.5 # volatility measured by standard deviation * 253 trading days per year
#     print("The Euro to Chinese yuan volatility for", year_name, "is" ,annual_volatility)

display(all_the_years[0])