{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "### Imports" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/vnd.plotly.v1+html": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "import plotlyink\n", "import plotly\n", "plotly.offline.init_notebook_mode(connected=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Let's get some cryptocurrencies datas" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "base_polo_url = 'https://poloniex.com/public?command=returnChartData¤cyPair={}&start={}&end={}&period={}'\n", "start_date = pd.Timestamp('2018-01-01', tz='CET')\n", "end_date = pd.Timestamp('2018-02-01', tz='CET')\n", "period = 86400 # pull daily data (86,400 seconds per day)\n", "\n", "def get_crypto_data(poloniex_pair):\n", " '''Retrieve cryptocurrency data from poloniex'''\n", " json_url = base_polo_url.format(poloniex_pair, start_date.timestamp(), end_date.timestamp(), period)\n", " df = pd.read_json(json_url)\n", " return df.set_index('date')" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "altcoins = ['ETH','LTC','XRP','ETC','STR','DASH','SC','XMR','XEM']\n", "dfs = []\n", "for altcoin in altcoins:\n", " coinpair = 'BTC_{}'.format(altcoin)\n", " crypto_price_df = get_crypto_data(coinpair)[['weightedAverage']]\n", " dfs.append(crypto_price_df.rename(columns={'weightedAverage': coinpair}))\n", " \n", "df = pd.concat(dfs, axis=1)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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BTC_ETHBTC_LTCBTC_XRPBTC_ETCBTC_STRBTC_DASHBTC_SCBTC_XMRBTC_XEM
date
2018-01-010.0556750.0167230.0001450.0021940.0000330.0751740.0000020.0247880.000076
2018-01-020.0606320.0176490.0001470.0022580.0000370.0784090.0000020.0253840.000077
2018-01-030.0599440.0165700.0001710.0021210.0000510.0749160.0000020.0250830.000094
2018-01-040.0641910.0158640.0001990.0023340.0000530.0758190.0000030.0250950.000123
2018-01-050.0620740.0153310.0001650.0021040.0000410.0702310.0000030.0224400.000103
\n", "
" ], "text/plain": [ " BTC_ETH BTC_LTC BTC_XRP BTC_ETC BTC_STR BTC_DASH \\\n", "date \n", "2018-01-01 0.055675 0.016723 0.000145 0.002194 0.000033 0.075174 \n", "2018-01-02 0.060632 0.017649 0.000147 0.002258 0.000037 0.078409 \n", "2018-01-03 0.059944 0.016570 0.000171 0.002121 0.000051 0.074916 \n", "2018-01-04 0.064191 0.015864 0.000199 0.002334 0.000053 0.075819 \n", "2018-01-05 0.062074 0.015331 0.000165 0.002104 0.000041 0.070231 \n", "\n", " BTC_SC BTC_XMR BTC_XEM \n", "date \n", "2018-01-01 0.000002 0.024788 0.000076 \n", "2018-01-02 0.000002 0.025384 0.000077 \n", "2018-01-03 0.000002 0.025083 0.000094 \n", "2018-01-04 0.000003 0.025095 0.000123 \n", "2018-01-05 0.000003 0.022440 0.000103 " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Scatter plots" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { 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