{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\"Open" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# uncomment to install in colab\n", "# !pip install -e git+https://github.com/enzoampil/fastquant.git@master#egg=fastquant" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from fastquant import get_pse_data_cache, get_stock_data" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Symbol2GOAAA...WPIZHI
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dt
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2020-06-059.559.789.509.64626673.0NaNNaNNaNNaNNaN...0.3950.3950.3950.39515800.00.1490.1490.1470.14753180.0
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2020-06-099.559.809.559.801520175.0NaNNaNNaNNaNNaN...0.4000.4150.4000.415143350.00.1450.1480.1420.14784080.0
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openclose
dt
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" ], "text/plain": [ " open close\n", "dt \n", "2020-04-06 104.6 106.0\n", "2020-04-07 110.2 110.5\n", "2020-04-08 111.0 120.0\n", "2020-04-13 121.0 135.0\n", "2020-04-14 139.9 146.5" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#query within cache\n", "df = get_stock_data(phisix_symbol, \n", " start_date, \n", " end_date, \n", " source=\"phisix\", \n", " format=format\n", " )\n", "df.tail()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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close
dt
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2020-04-07110.5
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" ], "text/plain": [ " close\n", "dt \n", "2020-04-06 106.0\n", "2020-04-07 110.5\n", "2020-04-08 120.0\n", "2020-04-13 135.0\n", "2020-04-14 146.5" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#query within cache\n", "df = get_stock_data(phisix_symbol, \n", " start_date, \n", " end_date, \n", " source=\"phisix\", \n", " #format=format\n", " )\n", "df.tail()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[*********************100%***********************] 1 of 1 completed\n" ] }, { "data": { "text/html": [ "
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openclose
dt
2020-04-061133.0000001183.189941
2020-04-071217.0100101182.560059
2020-04-081203.0999761207.000000
2020-04-091218.1800541206.569946
2020-04-131201.5000001210.410034
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" ], "text/plain": [ " open close\n", "dt \n", "2020-04-06 1133.000000 1183.189941\n", "2020-04-07 1217.010010 1182.560059\n", "2020-04-08 1203.099976 1207.000000\n", "2020-04-09 1218.180054 1206.569946\n", "2020-04-13 1201.500000 1210.410034" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#query within cache\n", "df = get_stock_data(yahoo_symbol, \n", " start_date, \n", " end_date, \n", " source=\"yahoo\", \n", " format=format\n", " )\n", "df.tail()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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openclose
dt
2020-04-08111.0120.0
2020-04-13121.0135.0
2020-04-14139.9146.5
2020-04-15150.0148.6
2020-04-16147.0141.5
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" ], "text/plain": [ " open close\n", "dt \n", "2020-04-08 111.0 120.0\n", "2020-04-13 121.0 135.0\n", "2020-04-14 139.9 146.5\n", "2020-04-15 150.0 148.6\n", "2020-04-16 147.0 141.5" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#extend cache\n", "end_date = \"2020-04-16\"\n", "\n", "df = get_stock_data(phisix_symbol, \n", " start_date, \n", " end_date, \n", " source=\"phisix\", \n", " format=format\n", " )\n", "df.tail()" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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close
dt
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2020-04-14146.5
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" ], "text/plain": [ " close\n", "dt \n", "2020-04-08 120.0\n", "2020-04-13 135.0\n", "2020-04-14 146.5\n", "2020-04-15 148.6\n", "2020-04-16 141.5" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#extend cache\n", "end_date = \"2020-04-16\"\n", "\n", "df = get_stock_data(phisix_symbol, \n", " start_date, \n", " end_date, \n", " source=\"phisix\", \n", " #format=format\n", " )\n", "df.tail()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[*********************100%***********************] 1 of 1 completed\n" ] }, { "data": { "text/html": [ "
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openclose
dt
2020-04-081203.0999761207.000000
2020-04-091218.1800541206.569946
2020-04-131201.5000001210.410034
2020-04-141239.9699711265.229980
2020-04-151246.5100101257.300049
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" ], "text/plain": [ " open close\n", "dt \n", "2020-04-08 1203.099976 1207.000000\n", "2020-04-09 1218.180054 1206.569946\n", "2020-04-13 1201.500000 1210.410034\n", "2020-04-14 1239.969971 1265.229980\n", "2020-04-15 1246.510010 1257.300049" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#extend cache\n", "df = get_stock_data(yahoo_symbol, \n", " start_date, \n", " end_date, \n", " source=\"yahoo\", \n", " format=format\n", " )\n", "df.tail()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.2" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 4 }