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OpenBB/examples/v3/volumeAtPrice.ipynb
Danglewood c047cfeddd docs/new-working-docs: New working docs branch (#5768) 
* move old example notebooks to v3 folder, update loadHistoricalPriceData and add findSymbols

* Create README.md

* Update README.md

* Update README.md

* Update README.md

* Vertical diagram instead

* important classes

* core dependencies

* folder structure

* devtools

* swap order

* fix github pages deploy issue

* development index

* delete expectations for developers

* devtools

* obbject stuff

* add

* installation

* hub sync

* idk if i committed already

* add usage page for financial statements

* add link to reference page

* syntax

* numbers

* nearly --> more than

* easier to read code blocks

* codespell

* removing mention to provider

* add 'orientation' for to_dict

* info card for output user preference

* put it in a code block

* correct user_settings.json example

* syntax corrections

* fix sentence

* get rid of floating point mathc

* get rid of other floating point math

* add companion example notebook for financial statements, and new section

* historical prices usage page

* codespell

* add commitment of traders section to usage

* add a note

* codespell

* get rid of equals sign

* Cleanup docs. with @the-praxs

* install

* obbject extend

* spell

* HeadTitle thingies

* Update obbject_extensions.md

* Update obbject_extensions.md

* typo

* Update architectural_considerations.md

* point to the TET pattern

* optional vs required

* reviewing the  patterns. removed the --pre flag under the assumption this will be the final docs for the release cc @deeleeramone

* add a walkthrough

* spelling

* Add more in the introduction

* validator examples

* update Copper-to-Gold notebook example for V4

* Update README.md

* QA Caveats w @the-praxs

* info on class outputs

* merge add data sources and add data points

* disclaimer on cookiecutter

* add missing import to example

* slight syntax change

* missing code block

* missing import

* update intrinio example syntax

* intrinio syntax update

* urls

* core and provider merged

* example syntax

* grammar

* Update API banner link

* quick-fix-docs cc @minhhoang1023

* Update pip install command for v3

* remove --pre note block

* update landing image

---------

Co-authored-by: Henrique Joaquim <h.joaquim@campus.fct.unl.pt>
Co-authored-by: Luqman <luqazino@gmail.com>
Co-authored-by: James Maslek <jmaslek11@gmail.com>
Co-authored-by: Igor Radovanovic <74266147+IgorWounds@users.noreply.github.com>
Co-authored-by: montezdesousa <79287829+montezdesousa@users.noreply.github.com>
Co-authored-by: Theodore Aptekarev <aptekarev@gmail.com>
Co-authored-by: Pratyush Shukla <ps4534@nyu.edu>
2023-12-01 01:09:25 +00:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "d724df06",
"metadata": {},
"source": [
"# Building a Volume at Price Chart\n",
"\n",
"Volume-at-price is a chart used by technical analysts as a visual gauge to where the trading levels are concentrated, relative to price and volume. In short, it is the sum of volume at different price levels. This notebook utilizes individual components of the OpenBB SDK and combines them to build a new view."
]
},
{
"cell_type": "code",
"execution_count": 67,
"id": "bb37c115-58e5-446d-9eab-047d2f650721",
"metadata": {},
"outputs": [],
"source": [
"# Import statements\n",
"\n",
"from datetime import datetime, timedelta\n",
"from typing import Optional, Union\n",
"from openbb_terminal.sdk import openbb\n",
"import pandas as pd\n",
"from plotly import graph_objects as go\n",
"from plotly.subplots import make_subplots\n",
"from openbb_terminal import OpenBBFigure\n",
"from openbb_terminal.common.technical_analysis import ta_helpers\n",
"from openbb_terminal.common.technical_analysis.overlap_model import sma, vwap\n",
"from openbb_terminal.rich_config import console\n"
]
},
{
"cell_type": "markdown",
"id": "8b045af0",
"metadata": {},
"source": [
"Let's look at the pieces we want to put together.\n",
"\n",
"- Price\n",
"- Volume\n",
"- VWAP\n",
"- SMA"
]
},
{
"cell_type": "code",
"execution_count": 71,
"id": "88a7f4be",
"metadata": {},
"outputs": [
{
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Open</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Close</th>\n",
" <th>Adj Close</th>\n",
" <th>Volume</th>\n",
" </tr>\n",
" <tr>\n",
" <th>date</th>\n",
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" <tbody>\n",
" <tr>\n",
" <th>2023-08-23 09:30:00</th>\n",
" <td>364.859985</td>\n",
" <td>364.859985</td>\n",
" <td>364.850006</td>\n",
" <td>364.850006</td>\n",
" <td>364.850006</td>\n",
" <td>1978013</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-23 09:31:00</th>\n",
" <td>364.859985</td>\n",
" <td>365.269989</td>\n",
" <td>364.730011</td>\n",
" <td>365.130005</td>\n",
" <td>365.130005</td>\n",
" <td>197931</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-23 09:32:00</th>\n",
" <td>365.119995</td>\n",
" <td>365.265015</td>\n",
" <td>364.640015</td>\n",
" <td>364.709900</td>\n",
" <td>364.709900</td>\n",
" <td>156792</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-23 09:33:00</th>\n",
" <td>364.690002</td>\n",
" <td>365.156189</td>\n",
" <td>364.690002</td>\n",
" <td>364.959991</td>\n",
" <td>364.959991</td>\n",
" <td>133015</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-23 09:34:00</th>\n",
" <td>364.970001</td>\n",
" <td>365.149292</td>\n",
" <td>364.750000</td>\n",
" <td>364.880005</td>\n",
" <td>364.880005</td>\n",
" <td>203328</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Open High Low Close \\\n",
"date \n",
"2023-08-23 09:30:00 364.859985 364.859985 364.850006 364.850006 \n",
"2023-08-23 09:31:00 364.859985 365.269989 364.730011 365.130005 \n",
"2023-08-23 09:32:00 365.119995 365.265015 364.640015 364.709900 \n",
"2023-08-23 09:33:00 364.690002 365.156189 364.690002 364.959991 \n",
"2023-08-23 09:34:00 364.970001 365.149292 364.750000 364.880005 \n",
"\n",
" Adj Close Volume \n",
"date \n",
"2023-08-23 09:30:00 364.850006 1978013 \n",
"2023-08-23 09:31:00 365.130005 197931 \n",
"2023-08-23 09:32:00 364.709900 156792 \n",
"2023-08-23 09:33:00 364.959991 133015 \n",
"2023-08-23 09:34:00 364.880005 203328 "
]
},
"execution_count": 71,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Get the OHLC+V data\n",
"\n",
"ticker= \"QQQ\"\n",
"ohlc_data = openbb.stocks.load(ticker, start_date = datetime.now().date().strftime(\"%Y-%m-%d\"), interval=1, verbose=False)\n",
"ohlc_data.head(5)"
]
},
{
"cell_type": "markdown",
"id": "e1fd1f07",
"metadata": {},
"source": [
"Rounding the price levels - here to the nearest ten cents - will make the final chart easier display better."
]
},
{
"cell_type": "code",
"execution_count": 76,
"id": "10246983",
"metadata": {},
"outputs": [
{
"data": {
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"<div>\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Volume</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Close</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>364.6</th>\n",
" <td>418695.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>364.7</th>\n",
" <td>156792.0</td>\n",
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" <tr>\n",
" <th>364.8</th>\n",
" <td>647207.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>364.9</th>\n",
" <td>2341760.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>365.0</th>\n",
" <td>261823.0</td>\n",
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],
"text/plain": [
" Volume\n",
"Close \n",
"364.6 418695.0\n",
"364.7 156792.0\n",
"364.8 647207.0\n",
"364.9 2341760.0\n",
"365.0 261823.0"
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Separate volume and close into a new DataFrame and group by the price.\n",
"\n",
"_vap = pd.DataFrame(data = [(round(ohlc_data[\"Close\"], 1)),ohlc_data[\"Volume\"]]).transpose()\n",
"_vap_df = _vap.groupby(\"Close\").sum()[[\"Volume\"]]\n",
"_vap_df.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 77,
"id": "03938620",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>VWAP_D</th>\n",
" </tr>\n",
" <tr>\n",
" <th>date</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2023-08-23 09:30:00</th>\n",
" <td>364.853333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-23 09:31:00</th>\n",
" <td>364.870616</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-23 09:32:00</th>\n",
" <td>364.870685</td>\n",
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" <tr>\n",
" <th>2023-08-23 09:33:00</th>\n",
" <td>364.874176</td>\n",
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" <tr>\n",
" <th>2023-08-23 09:34:00</th>\n",
" <td>364.878156</td>\n",
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"text/plain": [
" VWAP_D\n",
"date \n",
"2023-08-23 09:30:00 364.853333\n",
"2023-08-23 09:31:00 364.870616\n",
"2023-08-23 09:32:00 364.870685\n",
"2023-08-23 09:33:00 364.874176\n",
"2023-08-23 09:34:00 364.878156"
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Get VWAP levels\n",
"\n",
"_vwap = vwap(ohlc_data)\n",
"_vwap.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 78,
"id": "e1321d33",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>SMA_10</th>\n",
" </tr>\n",
" <tr>\n",
" <th>date</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2023-08-23 14:49:00</th>\n",
" <td>369.148868</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-23 14:50:00</th>\n",
" <td>369.159866</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-23 14:51:00</th>\n",
" <td>369.165869</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-23 14:52:00</th>\n",
" <td>369.200879</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-23 14:53:00</th>\n",
" <td>369.228598</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" SMA_10\n",
"date \n",
"2023-08-23 14:49:00 369.148868\n",
"2023-08-23 14:50:00 369.159866\n",
"2023-08-23 14:51:00 369.165869\n",
"2023-08-23 14:52:00 369.200879\n",
"2023-08-23 14:53:00 369.228598"
]
},
"execution_count": 78,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Calculate the simple moving average.\n",
"\n",
"_sma_df = sma(data = ohlc_data[\"Close\"], length = 10)\n",
"_sma_df.tail(5)"
]
},
{
"cell_type": "markdown",
"id": "d87c0523",
"metadata": {},
"source": [
"## Parameterize the Components as a Function\n",
"\n",
"To combine these components, a function needs to be created that parameterizes the inputs.\n",
"\n",
"The two functions below represent the \"model\" and \"view\" components. As Terminal components, they would be added to `openbb_terminal/common/technical_analysis/volume_model.py` and `volume_view.py` respectively. \n",
"\n",
"At the SDK level, users can call on either one, but only the view will return a chart and provide an input for the simple moving average. As a Terminal as a function, the controller module would call the view function, `display_vap()`."
]
},
{
"cell_type": "code",
"execution_count": 84,
"id": "754d902f",
"metadata": {},
"outputs": [],
"source": [
"def vap(data: pd.DataFrame) -> pd.DataFrame:\n",
" \"\"\"Volume at Price.\n",
"\n",
" Parameters\n",
" ----------\n",
" data: pd.DataFrame\n",
" Dataframe of OHLC + Volume.\n",
"\n",
" Returns\n",
" -------\n",
" pd.DataFrame\n",
" Dataframe with technical indicator.\n",
" \"\"\"\n",
" close_col = ta_helpers.check_columns(data, high=False, low=False)\n",
" if close_col is None:\n",
" return pd.DataFrame()\n",
" if \"Volume\" not in data.columns:\n",
" console.print(\"[red]Volume column not found[/red]\\n\")\n",
" return pd.DataFrame()\n",
"\n",
" vap_df = pd.DataFrame(data=[(round(data[\"Close\"], 1)), data[\"Volume\"]]).transpose()\n",
"\n",
" return vap_df.groupby(\"Close\").sum()[[\"Volume\"]]\n",
"\n",
"def display_vap(\n",
" data: Optional[pd.DataFrame] = None,\n",
" symbol: str = \"\",\n",
" ma: Optional[int] = None,\n",
" export: str = \"\",\n",
" sheet_name: Optional[str] = None,\n",
" external_axes: bool = False,\n",
") -> Union[OpenBBFigure, None]:\n",
" \"\"\"Plots Volume-at-Price with an optional simple moving average.\n",
"\n",
" Parameters\n",
" ----------\n",
" data : pd.DataFrame\n",
" Dataframe of ohlc prices\n",
" symbol : str\n",
" Ticker\n",
" ma: int\n",
" Window for calculating the simple moving average.\n",
" sheet_name: str\n",
" Optionally specify the name of the sheet the data is exported to.\n",
" export: str\n",
" Format to export data as\n",
" external_axes : bool, optional\n",
" Whether to return the figure object or not, by default False\n",
" \"\"\"\n",
" if data is None or data.empty:\n",
" data = openbb.stocks.load(symbol, start_date=datetime.now().strftime(\"%Y-%m-%d\"), interval=1)\n",
" if data.empty:\n",
" return None\n",
" \n",
" if ma is None:\n",
" ma = 0\n",
" ma_df = pd.DataFrame()\n",
"\n",
" if \"vw\" in data.columns:\n",
" data[\"VWAP\"] = data[\"vw\"]\n",
" data[\"VWAP\"] = vwap(data)\n",
"\n",
" vap_df = vap(data)\n",
"\n",
" fig = make_subplots(\n",
" rows=1, cols=2, shared_xaxes=False, shared_yaxes=True, horizontal_spacing=0.001\n",
" )\n",
" fig.add_trace(\n",
" go.Bar(\n",
" x=vap_df.Volume.astype(int),\n",
" y=vap_df.index,\n",
" orientation=\"h\",\n",
" name=\"Volume at Price\",\n",
" opacity=0.25,\n",
" marker={\"color\": \"gray\"},\n",
" ),\n",
" row=1,\n",
" col=1,\n",
" )\n",
" fig.add_trace(\n",
" go.Scatter(x=data.index, y=data[\"VWAP\"], name=\"VWAP\", marker={\"color\": \"red\"}),\n",
" row=1,\n",
" col=2,\n",
" )\n",
" fig.add_trace(\n",
" go.Scatter(\n",
" x=data.index, y=data[\"Close\"], name=\"Close\", marker={\"color\": \"green\"}\n",
" ),\n",
" row=1,\n",
" col=2,\n",
" )\n",
" if ma != 0:\n",
" ma_df = sma(data[\"Close\"], ma).iloc[:, 0]\n",
" fig.add_trace(\n",
" go.Scatter(\n",
" x=ma_df.index,\n",
" y=ma_df,\n",
" name=f\"SMA {ma}\",\n",
" marker={\"color\": \"orange\"},\n",
" ),\n",
" row=1,\n",
" col=2,\n",
" )\n",
"\n",
" fig.update_layout(\n",
" yaxis2=dict(\n",
" zeroline=False,\n",
" showticklabels=False,\n",
" showgrid=False,\n",
" mirror=True,\n",
" showline=True,\n",
" ticklen=0,\n",
" ),\n",
" xaxis2=dict(\n",
" zeroline=False,\n",
" mirror=True,\n",
" showline=True,\n",
" ticks=\"outside\",\n",
" showgrid=False,\n",
" ticklen=0,\n",
" domain=[0, 0],\n",
" ),\n",
" xaxis1=dict(\n",
" zeroline=False,\n",
" showline=False,\n",
" showticklabels=False,\n",
" showgrid=False,\n",
" autorange=False,\n",
" mirror=False,\n",
" range=[0, max(vap_df.Volume)],\n",
" ticklen=0,\n",
" domain=[0, 0],\n",
" ),\n",
" yaxis1=dict(\n",
" zeroline=False,\n",
" showgrid=False,\n",
" showticklabels=True,\n",
" ticks=\"outside\",\n",
" mirror=True,\n",
" showline=False,\n",
" ticklen=0,\n",
" ),\n",
" plot_bgcolor=\"rgba(0,0,0,0)\",\n",
" title=f\"{symbol} - Volume at Price\",\n",
" title_y=1,\n",
" title_x=0.5,\n",
" legend=dict(\n",
" orientation=\"h\",\n",
" yanchor=\"top\",\n",
" y=1.115,\n",
" xanchor=\"right\",\n",
" x=1,\n",
" bgcolor=\"rgba(0,0,0,0)\"\n",
" ),\n",
" )\n",
" # Using the OpenBBFigure class will provide additional processing like removing the time periods between trading days.\n",
" ta = OpenBBFigure(fig)\n",
"\n",
" return ta.show()"
]
},
{
"cell_type": "markdown",
"id": "d18c378b",
"metadata": {},
"source": [
"The function will check if the `data` parameter is used, and will grab one-minute data from today if not. There is also an optional parameter to add a simple moving average line."
]
},
{
"cell_type": "code",
"execution_count": 80,
"id": "25a88e10",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading Intraday 1min data for QQQ with starting period 2023-08-23.\n",
"</pre>\n"
],
"text/plain": [
"Loading Intraday 1min data for QQQ with starting period 2023-08-23.\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
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"plotlyServerURL": "https://plot.ly",
"scrollZoom": true
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{
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"Alternatively, if the `data` parameter is fed a time series DataFrame, it can offer more flexibility. Now the `symbol` parameter is just a title. This mimics the behaviour of similar functions in the Terminal.\n",
"\n",
"To see the difference between outputs of the Plotly figure object and the OpenBBFigure object, modify the last two lines in the `display_vap` function. Comment out `ta=OpenBBFigure(fig)` and change `return ta.show()` to be `return fig.show()`. You will notice that the gap between trading days is removed when the `OpenBBFigure` object is used.\n",
"\n",
"Without OpenBBFigure:\n",
"\n",
"``` \n",
" # ta = OpenBBFigure(fig)\n",
"\n",
" return fig.show()\n",
" ```"
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading Intraday 15min data for QQQ with starting period 2023-08-22.\n",
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"Loading Intraday 15min data for QQQ with starting period 2023-08-22.\n"
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"source": [
"data = openbb.stocks.load(\"QQQ\", start_date=(datetime.now()-timedelta(days=1)).date().strftime(\"%Y-%m-%d\"), interval=15)\n",
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"With OpenBBFigure:\n",
"\n",
"``` \n",
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" return ta.show()\n",
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading Intraday 15min data for QQQ with starting period 2023-08-22.\n",
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},
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],
"source": [
"data = openbb.stocks.load(\"QQQ\", start_date=(datetime.now()-timedelta(days=1)).date().strftime(\"%Y-%m-%d\"), interval=15)\n",
"display_vap(data=data, symbol=\"QQQ - 15 Minute\")"
]
}
],
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},
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