mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-06-21 18:42:57 +08:00
d91c9b9c35
* update charting extension for plotly v6 and do some cleanup * pylint * formatting * plotly.html
167 lines
4.3 KiB
Markdown
Vendored
167 lines
4.3 KiB
Markdown
Vendored
---
|
|
title: Examples
|
|
sidebar_position: 1
|
|
description: This page provides examples of creating charts with the `openbb-charting` extension.
|
|
keywords:
|
|
- tutorial
|
|
- OpenBB Platform
|
|
- Python client
|
|
- Fast API
|
|
- getting started
|
|
- extensions
|
|
- charting
|
|
- view
|
|
- Plotly
|
|
- toolkits
|
|
- how-to
|
|
- generic
|
|
- figure
|
|
---
|
|
|
|
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
|
|
|
|
<HeadTitle title="Examples - OpenBB Charting - Extensions | OpenBB Platform Docs" />
|
|
|
|
## Overview
|
|
|
|
This page will walk through creating different charts using the `openbb-charting` extension.
|
|
The perspective for this content is from the Python Interface,
|
|
and the examples will assume that the OpenBB Platform is installed with all optional packages.
|
|
|
|
```python
|
|
from datetime import datetime, timedelta
|
|
from openbb import obb
|
|
```
|
|
|
|
## Cumulative Returns
|
|
|
|
The historical (equity) prices can be requested for multiple symbols.
|
|
The extension will attempt to handle variations accordingly.
|
|
By default, more than three symbols will draw the chart as cumulative returns from the beginning of the series.
|
|
|
|
### Default View
|
|
|
|
The tickers below are a collection of State Street Global Advisors SPDR funds, representing S&P 500 components.
|
|
The data is looking back five years.
|
|
|
|
```python
|
|
SPDRS = [
|
|
"SPY",
|
|
"XLE",
|
|
"XLB",
|
|
"XLI",
|
|
"XHB",
|
|
"XLP",
|
|
"XLY",
|
|
"XRT",
|
|
"XLF",
|
|
"XLV",
|
|
"XLK",
|
|
"XLC",
|
|
"XLU",
|
|
"XLRE",
|
|
]
|
|
start_date = (datetime.now() - timedelta(weeks=52*5)).date()
|
|
spdrs = obb.equity.price.historical(SPDRS, start_date=start_date, provider="yfinance", chart=True)
|
|
|
|
spdrs.show()
|
|
```
|
|
|
|
|
|
|
|
### Redraw as YTD
|
|
|
|
The `charting` attribute of the command output has methods for creating the chart again.
|
|
The `data` parameter allows modifications to the data before creating the figure.
|
|
In this example, the length of the data is trimmed to the beginning of the year.
|
|
|
|
```python
|
|
new_data = spdrs.to_df().loc[datetime(2024,12,29).date():]
|
|
spdrs.charting.to_chart(data=new_data, title="YTD")
|
|
```
|
|
|
|
:::note
|
|
This replaces the chart that was already created.
|
|
:::
|
|
|
|
|
|
|
|
## Price Performance Bar Chart
|
|
|
|
The `obb.equity.price.performance` endpoint will create a bar chart over intervals.
|
|
|
|
```python
|
|
price_performance = obb.equity.price.performance(SPDRS, chart=True)
|
|
price_performance.show()
|
|
```
|
|
|
|
|
|
|
|
### Create Bar Chart
|
|
|
|
This example uses the `create_bar_chart()` method, which does not replace the existing chart, in `price_performance.chart`.
|
|
It isolates the one-month performance and orients the layout as horizontal.
|
|
|
|
```python
|
|
new_data = price_performance.to_df().set_index("symbol").multiply(100).reset_index()
|
|
price_performance.charting.create_bar_chart(
|
|
data=new_data,
|
|
x="symbol",
|
|
y="one_month",
|
|
orientation="h",
|
|
title="One Month Price Performance",
|
|
xtitle="Percent (%)"
|
|
)
|
|
```
|
|
|
|
|
|
|
|
## Create Your Own
|
|
|
|
This example analyzes the share volume turnover of the S&P 500 Energy Sector constituents, year-to-date.
|
|
|
|
```python
|
|
symbols = [
|
|
'XOM',
|
|
'CVX',
|
|
'COP',
|
|
'WMB',
|
|
'EOG',
|
|
'KMI',
|
|
'OKE',
|
|
'MPC',
|
|
'PSX',
|
|
'SLB',
|
|
'VLO',
|
|
'BKR',
|
|
'HES',
|
|
'TRGP',
|
|
'EQT',
|
|
'OXY',
|
|
'TPL',
|
|
'FANG',
|
|
'EXE',
|
|
'DVN',
|
|
'HAL',
|
|
'CTRA',
|
|
'APA',
|
|
]
|
|
data = obb.equity.price.historical(symbols, start_date="2025-01-01", provider="yfinance")
|
|
create_bar_chart = data.charting.create_bar_chart
|
|
volume = data.to_df().groupby("symbol").sum()["volume"]
|
|
shares = obb.equity.profile(
|
|
symbols, provider="yfinance"
|
|
).to_df().set_index("symbol")["shares_float"]
|
|
df = volume.to_frame().join(shares)
|
|
df["Turnover"] = (df.volume/df.shares_float).round(4)
|
|
df = df.sort_values(by="Turnover", ascending=False).reset_index()
|
|
create_bar_chart(
|
|
data=df,
|
|
x="symbol",
|
|
y="Turnover",
|
|
title="S&P Energy Sector YTD Turnover Rate",
|
|
)
|
|
```
|
|
|
|
|