mirror of
https://github.com/OpenBB-finance/OpenBB.git
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a7c148026f
* bring dashboards and reports menus one step above * remove checkpoints * add notebooks again
256 lines
8.6 KiB
Plaintext
Vendored
256 lines
8.6 KiB
Plaintext
Vendored
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": true,
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"jupyter": {
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"outputs_hidden": true
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}
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},
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"outputs": [],
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"source": [
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"import io\n",
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt\n",
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"import requests\n",
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"from datetime import datetime, timedelta\n",
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"import ipywidgets as widgets\n",
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"from IPython.display import display\n",
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"\n",
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"%matplotlib widget"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 47,
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"metadata": {
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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},
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"class ShortDataDash:\n",
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" def __init__(self):\n",
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" self.df = pd.DataFrame()\n",
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" self.days_slider = widgets.IntSlider(\n",
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" value=5,\n",
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" min=5,\n",
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" max=252,\n",
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" step=1,\n",
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" description=\"Days Back\",\n",
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" style={\"description_width\": \"initial\"},\n",
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" )\n",
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" self.count_slider = widgets.IntSlider(\n",
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" value=10,\n",
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" min=1,\n",
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" max=25,\n",
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" step=1,\n",
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" description=\"Number to show.\",\n",
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" style={\"description_width\": \"initial\"},\n",
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" )\n",
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" self.output1 = widgets.Output()\n",
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" self.output2 = widgets.Output()\n",
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" self.load_button = widgets.Button(\n",
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" description=\"Load Data\", layout=widgets.Layout(width=\"200px\", height=\"40px\")\n",
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" )\n",
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" self.load_button.on_click(self.load_button_click)\n",
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" self.show_button = widgets.Button(\n",
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" description=\"Change Number Shown\", layout=self.load_button.layout\n",
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" )\n",
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" self.show_button.on_click(self.show_button_click)\n",
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"\n",
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" self.slider_box = widgets.HBox([self.days_slider, self.count_slider])\n",
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" self.button_box = widgets.VBox([self.load_button, self.show_button])\n",
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"\n",
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" self.stock_input = widgets.Text(\n",
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" value=\"GME\",\n",
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" placeholder=\"GME\",\n",
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" description=\"Ticker:\",\n",
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" )\n",
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" self.ticker_button = widgets.Button(description=\"Plot Ticker\")\n",
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" self.ticker_button.on_click(self.ticker_button_click)\n",
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"\n",
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" def show_button_click(self, b):\n",
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" self.output1.clear_output()\n",
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" with self.output1:\n",
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" self.update()\n",
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"\n",
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" def load_button_click(self, b):\n",
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" self.output1.clear_output()\n",
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" self.output2.clear_output()\n",
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" with self.output1:\n",
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" print(f\"Data Loading for {self.days_slider.value} days\")\n",
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" self.fetch_new_data()\n",
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" self.update()\n",
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"\n",
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" def ticker_button_click(self, b):\n",
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" self.output2.clear_output()\n",
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" with self.output2:\n",
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" self.ticker_plot()\n",
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"\n",
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" def fetch_new_data(self):\n",
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" self.df = pd.DataFrame()\n",
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" today = datetime.now().date()\n",
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" idx = 0\n",
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" len_df = 0\n",
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" while len_df < self.days_slider.value:\n",
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" date = today - timedelta(days=idx)\n",
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" r = requests.get(\n",
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" f\"https://cdn.finra.org/equity/regsho/daily/CNMSshvol{date.strftime('%Y%m%d')}.txt\"\n",
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" )\n",
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" if r.status_code == 200:\n",
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" self.df = pd.concat(\n",
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" [self.df, pd.read_csv(io.StringIO(r.text), sep=\"|\")], axis=0\n",
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" )\n",
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" len_df += 1\n",
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" idx += 1\n",
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" self.df = self.df[self.df.Date > 20100101]\n",
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" self.df.Date = self.df[\"Date\"].apply(\n",
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" lambda x: datetime.strptime(str(x), \"%Y%m%d\")\n",
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" )\n",
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"\n",
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" def update(self):\n",
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" if not self.df.empty:\n",
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" temp = (\n",
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" self.df.groupby(\"Symbol\")[[\"ShortVolume\", \"TotalVolume\"]]\n",
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" .agg(\"sum\")\n",
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" .sort_values(by=\"ShortVolume\", ascending=False)\n",
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" .head(self.count_slider.value)[::-1]\n",
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" )\n",
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" self.fig, self.ax = plt.subplots(figsize=(6, 6))\n",
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" self.ax.barh(temp.index, temp.TotalVolume, alpha=0.4, label=\"Total Volume\")\n",
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" self.ax.barh(temp.index, temp.ShortVolume, label=\"Short Volume\")\n",
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" self.ax.set_title(\n",
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" f\"Top {self.count_slider.value} Short Volume in Last {self.days_slider.value} Days\"\n",
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" )\n",
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" self.ax.legend()\n",
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" self.fig.tight_layout()\n",
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" plt.show()\n",
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"\n",
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" def ticker_plot(self):\n",
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" stock_data = self.df.copy().loc[\n",
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" self.df.Symbol == self.stock_input.value,\n",
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" [\"Date\", \"ShortVolume\", \"TotalVolume\"],\n",
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" ]\n",
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" self.fig2, self.ax2 = plt.subplots(figsize=(6, 6))\n",
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" self.ax2.plot(\n",
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" stock_data.Date, stock_data.TotalVolume, alpha=0.4, label=\"Total Volume\"\n",
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" )\n",
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" self.ax2.plot(stock_data.Date, stock_data.ShortVolume, label=\"Short Volume\")\n",
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" self.ax2.set_title(\n",
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" f\"Stock Volume and Short Volume for {self.stock_input.value.upper()}\"\n",
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" )\n",
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" self.ax2.legend()\n",
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" self.fig2.autofmt_xdate()\n",
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" self.fig2.tight_layout()\n",
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" plt.show()\n",
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"\n",
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" def build_app(self):\n",
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" title_html = \"\"\"\n",
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"<h2>Finra Short Data</h2>\n",
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"<p>This widget downloads the consolidated NMS short data from FINRA and aggregates the data by summing over the entire time period.</p>\n",
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"<p>Note that clicking the 'Load Data' button will reload all data. This can get time consuming, so if you pick a few hundred days, expect a few minutes for loading time.</p>\n",
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"\"\"\"\n",
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" middle_html = \"\"\"\n",
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"Here we allow the user to query for a single stock. This will work with the loaded data. Note that if you want to reload the data, this will once again take some time.\n",
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" \"\"\"\n",
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" return [\n",
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" widgets.HTML(\n",
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" title_html, layout=widgets.Layout(margin=\"0 0 3em 0\", max_width=\"800px\")\n",
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" ),\n",
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" self.slider_box,\n",
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" self.button_box,\n",
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" self.output1,\n",
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" widgets.HTML(\n",
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" middle_html,\n",
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" layout=widgets.Layout(margin=\"0 0 3em 0\", max_width=\"800px\"),\n",
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" ),\n",
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" self.stock_input,\n",
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" self.ticker_button,\n",
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" self.output2,\n",
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" ]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 48,
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"metadata": {
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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},
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"dash = ShortDataDash()\n",
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"app = widgets.VBox(\n",
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" dash.build_app(), layout=widgets.Layout(max_width=\"1024px\", margin=\"0 auto 0 auto\")\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 49,
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"metadata": {
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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},
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "dcda08c8d643465fb862d01341d71370",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"VBox(children=(HTML(value=\"\\n<h2>Finra Short Data</h2>\\n<p>This widget downloads the consolidated NMS short da…"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"display(app)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.12"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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