If you are a long term trading, you are not interested in the day-to-day rates. You can get the historic price of bitcoin by year.
I pick Python because that's my go to language for quick scripts.
Collect data
You can get the JSON formatted data and parse it into a Python list. In the code below we use the requests module to do that.
We are only interested in the same day in each year, everything else is noise.I picked the day September 10. The data itself starts from 2014, you can't go further back than that, because they don't have that data.
#!/usr/bin/python3 import json import requests from bs4 import BeautifulSoup import csv import sys from time import sleep from time import gmtime, strftime import matplotlib.pyplot as plt import seaborn as sns enddate = strftime("%Y%m%d", gmtime()) r = requests.get("https://coinmarketcap.com/currencies/bitcoin/historical-data/?start=20140101&end={0}".format(enddate)) data = r.text soup = BeautifulSoup(data, "html.parser") table = soup.find('table', attrs={ "class" : "table"}) prices = [] for row in table.find_all('tr'): addPrice = False tag = row.findAll('td') for val in tag: value = val.text if "Sep 10" in value: print(value) addPrice = True if addPrice == True: prices.append( tag[3].text ) # flip list, months are in reverse order prices = prices[::-1] print(prices) We flip the pricing data, because the months start returning in reverse order.
Sep 10, 2019 Sep 10, 2018 Sep 10, 2017 Sep 10, 2016 Sep 10, 2015 Sep 10, 2014 Create plot
Ok so now that you have the pricing data you can create the plot.
x = list(range(0, len(prices))) plt.title('Bitcoin price from 2014') plt.ylabel('Price in USD') plt.xlabel('Years from 2014') plt.bar(x, prices) plt.show() That gives us:
So is it a good investment? That's for you to decide, this is not financial advice.
Related links:
Top comments (0)