Plot stock market prices

%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.dates as mdates

def bytespdate2num(fmt, encoding="utf-8"):
    strconverter = mdates.strpdate2num(fmt)
    def bytesconverter(b):
        s = b.decode(encoding)
        return strconverter(s)
    return bytesconverter



def graph_data(name_of_file):
    date_data = []
    stock_data_interim = []
    file = open(name_of_file, "r")
    file_list = list(file)

    # date
    for element in file_list:
        if "        \"2020" in element:
            date_string = element[9:28]
            date_data.append(date_string)

    # stock prices/volumes
    for element in file_list:
        for x in ["1. open", "2. high", "4. close", "5. volume"]:
            if "\"" + x in element:
                end_of_line = element.rfind("\"")
                stock_data_interim.append(element[24:end_of_line])
        # separately coding "3. low", because it is somehow formatted differently in the text file
        for x in ["3. low"]:
            if "\"" + x in element:
                end_of_line = element.rfind("\"")
                stock_data_interim.append(element[23:end_of_line])

    # remove parantheses and spaces
    stock_data_output = []
    for element in stock_data_interim:
        if "\"" or " " in element:
            new_string = element.replace("\"", "").replace(" ", "")
            stock_data_output.append(new_string)
        else:
            stock_data_output.append(element)


    file.close()

    date, closep, highp, loewp, openp, volume = np.loadtxt(stock_data_output,
                                                          delimiter=",",
                                                          unpack=True,
                                                          converters={0: bytespdate2num("%Y-%m-%d")})



plt.plot_date(date, closep)

plt.xlabel("Date")
plt.ylabel("Price")
plt.title("Interesting Graph\nCheck it out!")
plt.legend()
plt.show()


graph_data("Boring stock market price.txt")