Jupyter OHLCV aggregator

OHLCV_aggregator .py

# coding: utf-8

# In[1]:


import datetime
import numpy as np
import pandas as pd
import requests
import talib
import matplotlib.pyplot as plt


# # Cryptocompare API Class
# **Simple class to return Cryptocompare market historical data sets**
#     

# In[2]:


class CryptoCompareAPI():

    historical_day_url = 'https://min-api.cryptocompare.com/data/histoday'
    historical_hour_url = 'https://min-api.cryptocompare.com/data/histohour'
    historical_minute_url = 'https://min-api.cryptocompare.com/data/histominute'
    
    def get_historical_day(self, pair_symbol, base_symbol,
        exchange='BitTrex', aggregate=1, limit=None, all_data=False):
        '''
        Method for returning open, high, low, close, 
        volumefrom and volumeto daily historical data

        ** Parameters**
        pair_symbol <str>: Currency pair, EG ETH
        base_symbol <str>: Base currency, Eg BTC
        exchange <str>: Target exchange, EG BitTrex
        aggregate <int>: Aggregation multipler, Eg 1 = 1day, 2 = 2days
        limit <int>: Limit the number of ohlcv records returned
        all_data <bool>: Get all data

        ** Example call **
        crypto_compare_api = CryptoCompareAPI()
        data = crypto_compare_api.get_historical_day('ETH', 'BTC', aggregate=2, limit=1)

        '''


        url='{}?fsym={}&tsym={}&e={}&aggregate={}'.format(
            self.historical_day_url, pair_symbol.upper(),
            base_symbol.upper(), exchange, aggregate)

        if all_data:
            url += '&allData=true'

        if limit:
            url += '&limit={}'.format(limit)

        r = requests.get(url)
        data = r.json()['Data']
        return data

    def get_historical_hour(self,  pair_symbol, base_symbol,
        exchange='BitTrex', aggregate=1, limit=None, all_data=False):
        '''
        Method for returning open, high, low, close, 
        volumefrom and volumeto hourly historical data

        ** Parameters**
        pair_symbol <str>: Currency pair, EG ETH
        base_symbol <str>: Base currency, Eg BTC
        exchange <str>: Target exchange, EG BitTrex
        aggregate <int>: Aggregation multipler, Eg 1 = 1day, 2 = 2days
        limit <int>: Limit the number of ohlcv records returned
        all_data <bool>: Get all data

        ** Example call **
        crypto_compare_api = CryptoCompareAPI()
        data = crypto_compare_api.get_historical_hour('ETH', 'BTC', aggregate=2, limit=1)

        '''

        url='{}?fsym={}&tsym={}&e={}&aggregate={}'.format(
            self.historical_hour_url, pair_symbol.upper(),
            base_symbol.upper(), exchange, aggregate)

        if all_data:
            url += '&allData=true'

        if limit:
            url += '&limit={}'.format(limit)

        r = requests.get(url)
        data = r.json()['Data']
        return data

    def get_historical_minute(self,  pair_symbol, base_symbol,
        exchange='BitTrex', aggregate=1, limit=None, all_data=False):
        '''
        Method for returning open, high, low, close, 
        volumefrom and volumeto minute historical data

        ** Parameters**
        pair_symbol <str>: Currency pair, EG ETH
        base_symbol <str>: Base currency, Eg BTC
        exchange <str>: Target exchange, EG BitTrex
        aggregate <int>: Aggregation multipler, Eg 1 = 1day, 2 = 2days
        limit <int>: Limit the number of ohlcv records returned
        all_data <bool>: Get all data

        ** Example call **
        crypto_compare_api = CryptoCompareAPI()
        data = crypto_compare_api.get_historical_minute('ETH', 'BTC', aggregate=2, limi

        '''

        url='{}?fsym={}&tsym={}&e={}&aggregate={}'.format(
            self.historical_minute_url, pair_symbol.upper(),
            base_symbol.upper(), exchange, aggregate)

        if all_data:
            url += '&allData=true'

        if limit:
            url += '&limit={}'.format(limit)

        r = requests.get(url)
        data = r.json()['Data']
        return data


# # Get historical hour and minute data
# 

# In[3]:


# Instantiate CryptoCompareAPI and return historical hour period
crypto_compare_api = CryptoCompareAPI()
hour_data = crypto_compare_api.get_historical_hour('ETH', 'BTC')
minute_data = crypto_compare_api.get_historical_minute('ETH', 'BTC')


# In[4]:


def return_ohclv_data_frame(data_set):
    '''
    Return a clean ohclv DataFrame
    '''
    df = pd.DataFrame(data_set) # Create dataFrame
    df['timestamp'] = [datetime.datetime.fromtimestamp(d) for d in df.time] # create timestamp
    # Return OHLCV specific columns
    df = df[['close', 'high', 'low', 'open', 'volumefrom', 'timestamp']].rename(columns={"volumefrom": "volume"})
    df = df.set_index('timestamp') #Set timestamp as index
    return df


# # Resample dataframe to show 2, 4, 6 hour periods
# 

# In[5]:


df_hour = return_ohclv_data_frame(hour_data)
df_2hour = df_hour.resample('2H').mean() # Two hour period
df_4hour = df_hour.resample('4H').mean() # Four hour period
df_6hour = df_hour.resample('6H').mean() # Six hour period


# In[6]:


df_6hour.head()


# # Resample dataframe to show 5, 15, 30 minute periods

# In[7]:


df_min = return_ohclv_data_frame(minute_data)
df_5min = df_min.resample('5T').mean() # Five minute period
df_15min = df_min.resample('15T').mean() # Fifteen minute period
df_30min = df_min.resample('30T').mean() # Thirty minute period


# In[8]:


df_5min.head()


# In[9]:


plt.plot(df_5min.index, df_5min.close)


# In[13]:


df_30min['close'].plot()
df_15min['close'].plot()
plt.gcf().autofmt_xdate()
plt.show()