How do alt coin trends compare? If you're into crypto-currency you may wonder about this.
This question can be answered with Python. The way this works is by getting all the json data for each coin, then grabbing the years and finally plotting them into a plot.
Line Trend comparison
We wrap the code to get the price trend in a function.
Then call the functions to get the lists. As parameter you can define the currency.
#!/usr/bin/python3 prices = getCoin("litecoin") prices_btc = getCoin("bitcoin") prices_eth = getCoin("ethereum") prices_bcn = getCoin("binance-coin") prices_eos = getCoin("eos") This puts the prices in lists. You can then plot them all together with matplotlib.
#!/usr/bin/python3 plt.title('price from 2014') plt.ylabel('Price in USD') plt.xlabel('Years from 2014') plt.plot(x, prices, label='litecoin', color='gold') #plt.plot(x, prices_btc, label='bitcoin', color='silver') plt.plot(x, prices_eth, label='ethereum', color='silver') plt.plot(x, prices_bcn, label='binance-coin', color='green') plt.plot(x, prices_eos, label='eos', color='blue') plt.legend() 
This shows the biggest bull market is several years ago. Then there was a slight increase for some, but others like Ethereum had a dump time. This makes sense, because many early investors wanted to cash out.
We see binance coin increasing, binance is an exchange, so growth of their business likely sees their coin increase in value.
Bar plot trend
Can we get more insights with a different plot?
Lets try a stacked bar plot. Change the code from plot to bar.
#!/usr/bin/python3 plt.bar(x, prices_eth, label='ethereum', color='silver') plt.bar(x, prices_bcn, label='binance-coin', color='green') plt.bar(x, prices_eos, label='eos', color='blue') 
Here we see that Ethereum has gained many times compared to other coins. But that doesn't mean the increase for others has been small. Binance is in a bust trend. If you were to buy them in 2017, they would be $0.89 but now they are $21 (this is not financial advice).
If you want to play around with the code:
#!/usr/bin/python3 import time import os 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 def getCoin(coin): enddate = strftime("%Y%m%d", gmtime()) r = requests.get("https://coinmarketcap.com/currencies/" + coin + "/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] for i in range(0,len(prices)): prices[i] = float(prices[i]) while len(prices) < 6: prices = [0] + prices return prices prices = getCoin("litecoin") prices_btc = getCoin("bitcoin") prices_eth = getCoin("ethereum") prices_bcn = getCoin("binance-coin") prices_eos = getCoin("eos") x = list(range(0, len(prices))) plt.title('price from 2014') plt.ylabel('Price in USD') plt.xlabel('Years from 2014') plt.plot(x, prices, label='litecoin', color='gold') #plt.plot(x, prices_btc, label='bitcoin', color='silver') plt.plot(x, prices_eth, label='ethereum', color='silver') plt.plot(x, prices_bcn, label='binance-coin', color='green') plt.plot(x, prices_eos, label='eos', color='blue') plt.legend() os.system("rm -rf chart.png") time.sleep(1) plt.savefig('chart.png') Related links:
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