Problem scenario
You want to find the historic data for a given cryptocurrency using Python. You want to print out the low, high, open and close prices on a specific day. How do you get data for one specific date?
Solution
Prerequisite
This assumes you have installed pandas: pip install pandas
Procedures
Run this program:
"""
Usage instructions: Change the "2016-12-25" the value (assigned to "date_to_see") to the day you want to view.
Change "BTC" to the symbol of the cryptocurrency you want to examine.
You may or may note want to change "USD" or "Coinbase"
Written in March of 2021 by www.continualintegration.com
It was adapted from these postings:
https://towardsdatascience.com/cryptocurrency-analysis-with-python-buy-and-hold-c3b0bc164ffa
https://towardsdatascience.com/cryptocurrency-analysis-with-python-macd-452ceb251d7c?gi=12b983021ac2
"""
import pandas as pd
import requests
from datetime import datetime
from_symbol = 'BTC'
to_symbol = 'USD'
exchange = 'Coinbase' # "Bitstamp" and "Coinbase" are valid among others.
datetime_interval = 'day'
date_to_see="2016-12-25"
def get_filename(from_symbol, to_symbol, exchange, datetime_interval, download_date):
return '%s_%s_%s_%s_%s.csv' % (from_symbol, to_symbol, exchange, datetime_interval, download_date)
def download_data(from_symbol, to_symbol, exchange, datetime_interval):
supported_intervals = {'minute', 'hour', 'day'}
print('Downloading %s trading data for %s %s from %s' %
(datetime_interval, from_symbol, to_symbol, exchange))
base_url = 'https://min-api.cryptocompare.com/data/histo'
url = '%s%s' % (base_url, datetime_interval)
params = {'fsym': from_symbol, 'tsym': to_symbol,
'limit': 2000, 'aggregate': 1,
'e': exchange}
request = requests.get(url, params=params)
data = request.json()
return data
def convert_to_dataframe(data):
df = pd.json_normalize(data, ['Data'])
df['datetime'] = pd.to_datetime(df.time, unit='s')
df = df[['datetime', 'low', 'high', 'open',
'close', 'volumefrom', 'volumeto']]
return df
def filter_empty_datapoints(df):
indices = df[df.sum(axis=1) == 0].index
print('Filtering %d empty datapoints' % indices.shape[0])
df = df.drop(indices)
return df
def file_creator(from_symbol, to_symbol, exchange, datetime_interval):
data = download_data(from_symbol, to_symbol, exchange, datetime_interval)
df = convert_to_dataframe(data)
df = filter_empty_datapoints(df)
latest_date = datetime.now().date().isoformat()
filename = get_filename(from_symbol, to_symbol, exchange, datetime_interval, latest_date)
print('The oldest day in the range obtained for ' + from_symbol + ' was ' + str(df['datetime'].min()))
df.to_csv(filename, index=False)
def get_filename(from_symbol, to_symbol, exchange, datetime_interval, download_date):
return '%s_%s_%s_%s_%s.csv' % (from_symbol, to_symbol, exchange, datetime_interval, download_date)
def read_dataset(filename):
df = pd.read_csv(filename)
df.datetime = pd.to_datetime(df.datetime) # change to datetime
df = df.set_index('datetime')
df = df.sort_index() # sort by datetime
return df
file_creator(from_symbol, to_symbol, exchange, datetime_interval)
latest_date = datetime.now().date().isoformat()
df_btc = read_dataset(get_filename(from_symbol, to_symbol, exchange, datetime_interval, latest_date))
btc_date = open((get_filename(from_symbol, to_symbol, exchange, datetime_interval, latest_date)), 'r')
get_top = btc_date.read()[0:-1]
print("This prints out data for one cryptocurrency on one day. It downloads a file first.")
print(" ")
print("Here is data for " + from_symbol + " for " + date_to_see + ":")
print(get_top.split('\n')[0])
for line in get_top.split():
if line.split(",")[0] == date_to_see:
print(line)For aggregate data over a date range, see this posting.
If you sign up for Coinbase for the first time, you often can get up to $200 in free coins; it is ideal for Americans. For Europeans, the platform/company Iconomi.com can allow you to buy crypto or learn more.