"""Fill missing values"""

import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

import os

def fill_missing_values(df_data):

    df_data.fillna(method='ffill', inplace=True)

    return df_data.fillna(method='bfill', inplace=True)

def symbol_to_path(symbol, base_dir="data"):

    """Return CSV file path given ticker symbol."""

    return os.path.join(base_dir, "{}.csv".format(str(symbol)))

def get_data(symbols, dates):

    """Read stock data (adjusted close) for given symbols from CSV files."""

    df_final = pd.DataFrame(index=dates)

    if "SPY" not in symbols:  # add SPY for reference, if absent

        symbols.insert(0, "SPY")

    for symbol in symbols:

        file_path = symbol_to_path(symbol)

        df_temp = pd.read_csv(file_path, parse_dates=True, index_col="Date",

            usecols=["Date", "Adj Close"], na_values=["nan"])

        df_temp = df_temp.rename(columns={"Adj Close": symbol})

        df_final = df_final.join(df_temp)

        if symbol == "SPY":  # drop dates SPY did not trade

            df_final = df_final.dropna(subset=["SPY"])

    return df_final

def plot_data(df_data):

    """Plot stock data with appropriate axis labels."""

    ax = df_data.plot(title="Stock Data", fontsize=2)

    ax.set_xlabel("Date")

    ax.set_ylabel("Price")

    plt.show()

def test_run():

    """Function called by Test Run."""

    # Read data

    symbol_list = ["JAVA", "FAKE1", "FAKE2"]  # list of symbols

    start_date = "2005-12-31"

    end_date = "2014-12-07"

    dates = pd.date_range(start_date, end_date)  # date range as index

    df_data = get_data(symbol_list, dates)  # get data for each symbol

    # Fill missing values

    fill_missing_values(df_data)

    # Plot

    plot_data(df_data)

if __name__ == "__main__":

    test_run()