{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import requests\n", "import pandas as pd" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Let say\n", "\n", "Let say, TWTR.csv is my realtime data (follow [realtime-evolution-strategy.ipynb](realtime-evolution-strategy.ipynb)), remember, we trained using `Close`, and `Volume` data.\n", "\n", "So every request means new daily data.\n", "\n", "You can improve the code to bind historical data with your own database or any websocket streaming data. Imagination is your limit now." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
| \n", " | Date | \n", "Open | \n", "High | \n", "Low | \n", "Close | \n", "Adj Close | \n", "Volume | \n", "
|---|---|---|---|---|---|---|---|
| 0 | \n", "2018-05-23 | \n", "32.700001 | \n", "33.430000 | \n", "32.599998 | \n", "33.419998 | \n", "33.419998 | \n", "13407500 | \n", "
| 1 | \n", "2018-05-24 | \n", "33.439999 | \n", "33.759998 | \n", "33.119999 | \n", "33.520000 | \n", "33.520000 | \n", "14491900 | \n", "
| 2 | \n", "2018-05-25 | \n", "33.540001 | \n", "33.990002 | \n", "33.310001 | \n", "33.630001 | \n", "33.630001 | \n", "10424400 | \n", "
| 3 | \n", "2018-05-29 | \n", "33.419998 | \n", "34.830002 | \n", "33.349998 | \n", "34.040001 | \n", "34.040001 | \n", "22086700 | \n", "
| 4 | \n", "2018-05-30 | \n", "34.200001 | \n", "34.660000 | \n", "34.080002 | \n", "34.360001 | \n", "34.360001 | \n", "14588200 | \n", "