### Install Stockdex Python Package

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

Instructions to install the Stockdex Python package using pip. The `-U` flag ensures the package is updated to the latest version, and `--no-cache-dir` prevents caching issues during installation.

```bash
pip install stockdex -U --no-cache-dir
```

--------------------------------

### Python Project Dependencies List

Source: https://github.com/ahnazary/stockdex/blob/main/requirements_sphinx.txt

This snippet details the Python packages and their exact versions necessary for the project. These dependencies are crucial for reproducing the project's environment and ensuring all required libraries are installed correctly.

```Python
sphinx-rtd-theme==1.2.2
sphinxcontrib-applehelp==1.0.4
sphinxcontrib-devhelp==1.0.2
sphinxcontrib-htmlhelp==2.0.1
sphinxcontrib-jquery==4.1
sphinxcontrib-jsmath==1.0.1
sphinxcontrib-qthelp==1.0.3
sphinxcontrib-serializinghtml==1.1.5
myst-parser==2.0.0
plotly>=5.24.1
dash>=2.18.0
numpy==1.25.1
```

--------------------------------

### Retrieve Raw Financial Data from Yahoo Finance, Digrin, and Macrotrends

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

Examples of retrieving various types of raw financial data for a given stock ticker using the `Ticker` object. This includes price data from Yahoo Finance API, historical dividends from Digrin, income statements from Macrotrends, and summary information from the Yahoo Finance website. It also shows how to plot financial data using Plotly.

```python
from stockdex import Ticker
from datetime import datetime

ticker = Ticker(ticker="AAPL")

# Price data (use range and dataGranularity to make range and granularity more specific) from Yahoo Finance API
price = ticker.yahoo_api_price(range='1y', dataGranularity='1d')

# plot financial data using Plotly
ticker = Ticker(ticker="MSFT")
ticker.plot_yahoo_api_financials(group_by="field")

# Complete historical data of the stock in certain categories from digrin website
dividend = ticker.digrin_dividend

# Financial data from macrotrends website
income_statement = ticker.macrotrends_income_statement

# Summary including general financial information from Yahoo Finance website
summary = ticker.yahoo_web_summary
```

--------------------------------

### Retrieve Raw Historical and Non-Historical Data from Digrin

Source: https://github.com/ahnazary/stockdex/blob/main/USAGE.md

This snippet shows how to access various historical and non-historical stock data points from the Digrin website using the `stockdex.Ticker` object. Unlike Yahoo Finance, Digrin provides more extensive historical data. Examples include dividend history, payout ratios, stock splits, price data, assets vs. liabilities, free cash flow, net income, cash and debt, shares outstanding, expenses, cost of revenue, and upcoming estimated earnings.

```python
from stockdex import Ticker

ticker = Ticker(ticker="AAPL")

# Complete historical data of the stock in certain categories
dividend = ticker.digrin_dividend
payout_ratio = ticker.digrin_payout_ratio
stock_splits = ticker.digrin_stock_splits
price = ticker.digrin_price

# Non-historical data
assets_vs_liabilities = ticker.digrin_assets_vs_liabilities
free_cash_flow = ticker.digrin_free_cash_flow
net_income = ticker.digrin_net_income
cash_and_debt = ticker.digrin_cash_and_debt
shares_outstanding = ticker.digrin_shares_outstanding
expenses = ticker.digrin_expenses
cost_of_revenue = ticker.digrin_cost_of_revenue
upcoming_estimated_earnings = ticker.digrin_upcoming_estimated_earnings

# Dividend data
dividend = ticker.digrin_dividend
dgr3 = ticker.digrin_dgr3
dgr5 = ticker.digrin_dgr5
dgr10 = ticker.digrin_dgr10
```

--------------------------------

### Plot Financial Data from Yahoo Finance API

Source: https://github.com/ahnazary/stockdex/blob/main/USAGE.md

This snippet illustrates how to use `stockdex` functions to plot financial data retrieved from the Yahoo Finance API. These functions leverage the `plotly` library to generate interactive visualizations. Examples include plotting financials, income statements, cash flow, and balance sheets. The `group_by` and `freq` parameters allow for customization of the plot's aggregation and frequency.

```python

from stockdex import Ticker

ticker = Ticker(ticker="MSFT")

ticker.plot_yahoo_api_financials(group_by="field")
ticker.plot_yahoo_api_income_statement(group_by="timeframe")
ticker.plot_yahoo_api_cash_flow(freq="quarterly")
ticker.plot_yahoo_api_balance_sheet(freq="quarterly")
```

--------------------------------

### Retrieve Raw Financial Data from Yahoo Finance API

Source: https://github.com/ahnazary/stockdex/blob/main/USAGE.md

This snippet demonstrates how to use the `stockdex.Ticker` object to fetch various raw financial data points from the Yahoo Finance API. Data is returned as pandas DataFrames. Examples include price data, current trading periods, income statements, cash flow, balance sheets, and general financials. Parameters like `range`, `dataGranularity`, `frequency`, `format`, `period1`, and `period2` can be used to fine-tune the data retrieval.

```python
from stockdex import Ticker
from datetime import datetime

ticker = Ticker(ticker="AAPL")

# Price data (use range and dataGranularity to make range and granularity more specific)
price = ticker.yahoo_api_price(range='1y', dataGranularity='1d')

# Current trading period of the stock (pre-market, regular, post-market trading periods)
current_trading_period = ticker.yahoo_api_current_trading_period

# Fundamental data (use frequency, format, period1 and period2 to fine-tune the returned data)
income_statement = ticker.yahoo_api_income_statement(frequency='quarterly')
cash_flow = ticker.yahoo_api_cash_flow(format='raw')
balance_sheet = ticker.yahoo_api_balance_sheet(period1=datetime(2020, 1, 1))
financials = ticker.yahoo_api_financials(period1=datetime(2022, 1, 1), period2=datetime.today())
```

--------------------------------

### API Documentation for stockdex.justetf_interface Module

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the `stockdex.justetf_interface` module, including all public and undocumented members, and inheritance hierarchy. This module is designed for interacting with the JustETF data source.

```APIDOC
stockdex.justetf_interface module
----------------------------------

.. automodule:: stockdex.justetf_interface
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### API Documentation for stockdex.config Module

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the `stockdex.config` module, including all public and undocumented members, and inheritance hierarchy. This module likely handles configuration settings for the stockdex library.

```APIDOC
stockdex.config module
----------------------

.. automodule:: stockdex.config
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### API Documentation for stockdex.lib Module

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the `stockdex.lib` module, including all public and undocumented members, and inheritance hierarchy. This module likely contains general utility functions and helper classes for the stockdex library.

```APIDOC
stockdex.lib module
-------------------

.. automodule:: stockdex.lib
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### API Documentation for stockdex Main Package

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the main `stockdex` package, including all public and undocumented members, and inheritance hierarchy. This entry documents the top-level components and functionalities of the stockdex library.

```APIDOC
Module contents
---------------

.. automodule:: stockdex
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### API Documentation for stockdex.digrin_interface Module

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the `stockdex.digrin_interface` module, including all public and undocumented members, and inheritance hierarchy. This module is expected to facilitate interaction with the Digrin data source.

```APIDOC
stockdex.digrin_interface module
---------------------------------

.. automodule:: stockdex.digrin_interface
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### API Documentation for stockdex.nasdaq_interface Module

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the `stockdex.nasdaq_interface` module, including all public and undocumented members, and inheritance hierarchy. This module facilitates interaction with the Nasdaq data source.

```APIDOC
stockdex.nasdaq_interface module
---------------------------------

.. automodule:: stockdex.nasdaq_interface
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### API Documentation for stockdex.yahoo_api_interface Module

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the `stockdex.yahoo_api_interface` module, including all public and undocumented members, and inheritance hierarchy. This module is designed for interacting with Yahoo's financial API.

```APIDOC
stockdex.yahoo_api_interface module
-------------------------------------

.. automodule:: stockdex.yahoo_api_interface
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### Plotting Stock Data from Digrin with Plotly

Source: https://github.com/ahnazary/stockdex/blob/main/USAGE.md

Demonstrates how to plot various financial metrics (shares outstanding, price, dividend, assets vs. liabilities, free cash flow, cash and debt, net income, expenses, cost of revenue) extracted from Digrin using the `stockdex` library and `plotly`. Each function call opens a plot in the default browser.

```python
from stockdex import Ticker

ticker = Ticker(ticker="ASML")

ticker.plot_digrin_shares_outstanding()
ticker.plot_digrin_price()
ticker.plot_digrin_dividend()
ticker.plot_digrin_assets_vs_liabilities()
ticker.plot_digrin_free_cash_flow()
ticker.plot_digrin_cash_and_debt()
ticker.plot_digrin_net_income()
ticker.plot_digrin_expenses()
ticker.plot_digrin_cost_of_revenue()
```

--------------------------------

### API Documentation for stockdex.macrotrends_interface Module

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the `stockdex.macrotrends_interface` module, including all public and undocumented members, and inheritance hierarchy. This module is intended for interacting with the Macrotrends data source.

```APIDOC
stockdex.macrotrends_interface module
--------------------------------------

.. automodule:: stockdex.macrotrends_interface
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### API Documentation for stockdex.exceptions Module

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the `stockdex.exceptions` module, including all public and undocumented members, and inheritance hierarchy. This module defines custom exception classes used throughout the stockdex library.

```APIDOC
stockdex.exceptions module
--------------------------

.. automodule:: stockdex.exceptions
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### API Documentation for stockdex.selenium_interface Module

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the `stockdex.selenium_interface` module, including all public and undocumented members, and inheritance hierarchy. This module likely integrates Selenium for web scraping or automation tasks.

```APIDOC
stockdex.selenium_interface module
-----------------------------------

.. automodule:: stockdex.selenium_interface
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### API Documentation for stockdex.ticker_base Module

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the `stockdex.ticker_base` module, including all public and undocumented members, and inheritance hierarchy. This module likely contains the base class or foundational elements for ticker-related operations.

```APIDOC
stockdex.ticker_base module
----------------------------

.. automodule:: stockdex.ticker_base
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### Initialize Stockdex Ticker Object for Stock Data

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

Demonstrates how to create a `Ticker` object in Stockdex, which serves as the primary entry point for accessing financial data. The ticker symbol of the desired stock is passed as an argument during initialization.

```python
from stockdex import Ticker

ticker = Ticker(ticker="AAPL")
```

--------------------------------

### API Documentation for stockdex.yahoo_web_interface Module

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the `stockdex.yahoo_web_interface` module, including all public and undocumented members, and inheritance hierarchy. This module likely handles web scraping or direct web interaction with Yahoo Finance.

```APIDOC
stockdex.yahoo_web_interface module
-------------------------------------

.. automodule:: stockdex.yahoo_web_interface
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### Retrieving EU ETF Data from justETF by ISIN

Source: https://github.com/ahnazary/stockdex/blob/main/USAGE.md

Explains how to retrieve specific data for EU ETFs from the justETF website. It requires passing the `isin` (International Securities Identification Number) and setting `security_type` to 'etf' when initializing the `Ticker` object. Data includes general info, WKN, description, basic ETF data, and holdings by company, country, and sector.

```python
from stockdex import Ticker

etf = Ticker(isin="IE00B4L5Y983", security_type="etf")

etf_general_info = etf.justetf_general_info
etf_wkn = etf.justetf_wkn
etf_description = etf.justetf_description

# Basic data about the ETF
etf_basics = etf.justetf_basics

# Holdings of the ETF by company, country and sector
etf_holdings_companies = etf.justetf_holdings_companies
etf_holdings_countries = etf.justetf_holdings_countries
etf_holdings_sectors = etf.justetf_holdings_sectors
```

--------------------------------

### Creating a Multi-Plot Financial Dashboard with Stockdex and Dash

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

This Python code snippet illustrates how to generate a dashboard displaying various financial metrics for a given stock (e.g., MSFT) using `stockdex` and `dash`. It fetches data from Digrin, creates individual `plotly` figures by calling `ticker.plot_digrin_*` methods with `show_plot=False` to prevent immediate display, and then consolidates these figures into a single web application using `plot_multiple_categories`. The dashboard will be accessible at `http://127.0.0.1:8050/`.

```Python
from stockdex.ticker import Ticker
from stockdex.lib import plot_multiple_categories

# choose the stock
ticker = Ticker(ticker="MSFT")

# Here you will choose arbitrary figures to plot. In this example we will plot data extracted from digrin website
# IMPORTANT: make sure to set show_plot=False in each function to return the plotly figure object instead of showing the plot. Not setting this parameter will show the plots in separate tabs.
figures = [
    ticker.plot_digrin_shares_outstanding(show_plot=False),
    ticker.plot_digrin_price(show_plot=False),
    ticker.plot_digrin_dividend(show_plot=False),
    ticker.plot_digrin_assets_vs_liabilities(show_plot=False),
    ticker.plot_digrin_free_cash_flow(show_plot=False),
    ticker.plot_digrin_net_income(show_plot=False),
    ticker.plot_digrin_cash_and_debt(show_plot=False),
    ticker.plot_digrin_expenses(show_plot=False),
    ticker.plot_digrin_cost_of_revenue(show_plot=False)
]

# main functions that will create the dash app
plot_multiple_categories(ticker=ticker.ticker, figures=figures)
```

--------------------------------

### API Documentation for stockdex.sankey_charts Module

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the `stockdex.sankey_charts` module, including all public and undocumented members, and inheritance hierarchy. This module likely contains functionalities for generating Sankey charts.

```APIDOC
stockdex.sankey_charts module
------------------------------

.. automodule:: stockdex.sankey_charts
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### Retrieving Raw Financial Data from Macrotrends as Pandas DataFrame

Source: https://github.com/ahnazary/stockdex/blob/main/USAGE.md

Shows how to extract various financial data points (income statement, balance sheet, cash flow, key financial ratios, and different margin types) from the Macrotrends website using `stockdex`. The data is returned as pandas DataFrames for further analysis.

```python
from stockdex import Ticker

ticker = Ticker(ticker="AAPL")

# Financial data
income_statement = ticker.macrotrends_income_statement
balance_sheet = ticker.macrotrends_balance_sheet
cash_flow = ticker.macrotrends_cash_flow
key_financial_ratios = ticker.macrotrends_key_financial_ratios

# Margins
gross_margin = ticker.macrotrends_gross_margin
operating_margin = ticker.macrotrends_operating_margin
ebitda_margin = ticker.macrotrends_ebitda_margin
pre_tax_margin = ticker.macrotrends_pre_tax_margin
net_margin = ticker.macrotrends_net_margin
```

--------------------------------

### Python Project Dependency List

Source: https://github.com/ahnazary/stockdex/blob/main/requirements.txt

This snippet provides a comprehensive list of Python packages and their specific versions required to run the 'stockdex' project. These dependencies are typically managed via a `requirements.txt` file and are crucial for setting up the project's virtual environment.

```Python
beautifulsoup4==4.12.3
numpy
pandas>=2.2.3
plotly>=5.24.1
Requests==2.32.3
selenium==4.25.0
plotly>=5.24.1
dash>=2.18.0
```

--------------------------------

### Stockdex Python Package Requirements

Source: https://github.com/ahnazary/stockdex/blob/main/requirements_tests.txt

This snippet details the Python packages and their exact versions necessary to run the 'stockdex' project. It includes libraries for generating documentation (sphinx, myst-parser), handling data (pandas, numpy), performing web scraping (beautifulsoup4, requests, selenium), unit testing (pytest), and creating interactive dashboards (plotly, dash).

```Python
sphinx-rtd-theme==1.2.2
sphinxcontrib-applehelp==1.0.4
sphinxcontrib-devhelp==1.0.2
sphinxcontrib-htmlhelp==2.0.1
sphinxcontrib-jquery==4.1
sphinxcontrib-jsmath==1.0.1
sphinxcontrib-qthelp==1.0.3
sphinxcontrib-serializinghtml==1.1.5
myst-parser==2.0.0
pandas==2.0.3
beautifulsoup4==4.12.2
pytest >=8.0.0
requests==2.31.0
selenium==4.18.1
numpy==1.25.1
plotly==5.24.1
dash>=2.18.0
```

--------------------------------

### Create a Multi-Plot Financial Dashboard with Stockdex and Dash

Source: https://github.com/ahnazary/stockdex/blob/main/USAGE.md

This Python snippet illustrates how to generate an interactive dashboard containing multiple financial plots using the `stockdex` library and the `dash` framework. It fetches various financial metrics (e.g., shares outstanding, price, dividend, assets vs. liabilities, free cash flow, net income, cash and debt, expenses, cost of revenue) for a specified ticker (e.g., MSFT) from the Digrin website. Each individual plot function must be called with `show_plot=False` to return a Plotly figure object, which is then passed to `plot_multiple_categories` to construct the Dash application, accessible at `http://127.0.0.1:8050/` by default.

```python
from stockdex.ticker import Ticker
from stockdex.lib import plot_multiple_categories

# choose the stock
ticker = Ticker(ticker="MSFT")

# Here you will choose arbitrary figures to plot. In this example we will plot data extracted from digrin website
# IMPORTANT: make sure to set show_plot=False in each function to return the plotly figure object instead of showing the plot. Not setting this parameter will show the plots in separate tabs.
figures = [
    ticker.plot_digrin_shares_outstanding(show_plot=False),
    ticker.plot_digrin_price(show_plot=False),
    ticker.plot_digrin_dividend(show_plot=False),
    ticker.plot_digrin_assets_vs_liabilities(show_plot=False),
    ticker.plot_digrin_free_cash_flow(show_plot=False),
    ticker.plot_digrin_net_income(show_plot=False),
    ticker.plot_digrin_cash_and_debt(show_plot=False),
    ticker.plot_digrin_expenses(show_plot=False),
    ticker.plot_digrin_cost_of_revenue(show_plot=False)
]

# main functions that will create the dash app
plot_multiple_categories(ticker=ticker.ticker, figures=figures)
```

--------------------------------

### API Documentation for stockdex.ticker Module

Source: https://github.com/ahnazary/stockdex/blob/main/docs/stockdex.rst

Provides API reference for the `stockdex.ticker` module, including all public and undocumented members, and inheritance hierarchy. This module likely defines the core Ticker class or related functionalities.

```APIDOC
stockdex.ticker module
----------------------

.. automodule:: stockdex.ticker
   :members:
   :undoc-members:
   :show-inheritance:
```

--------------------------------

### Retrieving Various Stock Data from Yahoo Finance

Source: https://github.com/ahnazary/stockdex/blob/main/USAGE.md

Illustrates how to fetch a wide range of stock-related data from Yahoo Finance, including summary, financial statements, analyst estimates, options data (calls/puts), company profile, shareholder information, and various statistics. Data is accessed via `stockdex` attributes.

```python
from stockdex import Ticker

ticker = Ticker(ticker="AAPL")

# Summary including general financial information
summary = ticker.yahoo_web_summary

# Financial data as it is seen in the yahoo finance website
income_stmt = ticker.yahoo_web_income_stmt
balance_sheet = ticker.yahoo_web_balance_sheet
cash_flow = ticker.yahoo_web_cashflow

# Analysts and estimates
analysis = ticker.yahoo_web_analysis

# Data about options
calls = ticker.yahoo_web_calls
puts = ticker.yahoo_web_puts

# Profile data 
key_executives = ticker.yahoo_web_key_executives
description = ticker.yahoo_web_description
corporate_governance = ticker.yahoo_web_corporate_governance

# Data about shareholders
major_holders = ticker.yahoo_web_major_holders
top_institutional_holders = ticker.yahoo_web_top_institutional_holders
top_mutual_fund_holders = ticker.yahoo_web_top_mutual_fund_holders

# Statistics
valuation_measures = ticker.yahoo_web_valuation_measures
financial_highlights = ticker.yahoo_web_financial_highlights
trading_information = ticker.yahoo_web_trading_information
```

--------------------------------

### Plotting Financial Data from Macrotrends with Plotly

Source: https://github.com/ahnazary/stockdex/blob/main/USAGE.md

Demonstrates how to plot financial statements (income statement, balance sheet, cash flow) extracted from Macrotrends using the `stockdex` library and `plotly`. Each function call opens a plot in the default browser for visual inspection.

```python
from stockdex import Ticker

ticker = Ticker(ticker="GOOGL")

ticker.plot_macrotrends_income_statement()
ticker.plot_macrotrends_balance_sheet()
ticker.plot_macrotrends_cash_flow()
```

--------------------------------

### Plotting Historical Stock Price from Digrin as Line Chart

Source: https://github.com/ahnazary/stockdex/blob/main/USAGE.md

Illustrates how to plot the historical price data from Digrin as a line chart for stocks with many data points, such as 'CAT'. This function visualizes both real and adjusted prices, automatically switching from bar to line chart for dense data.

```python
from stockdex import Ticker

ticker = Ticker(ticker="CAT")

ticker.plot_digrin_price()
```

--------------------------------

### Retrieving EU ETF Data from justETF using ISIN

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

This Python snippet shows how to retrieve detailed information for EU ETFs from the justETF website using `stockdex`. It requires passing the ETF's ISIN and setting `security_type` to 'etf'. The code fetches general info, WKN, description, price data, basic ETF details, and holdings by company, country, and sector.

```python
from stockdex import Ticker

etf = Ticker(isin="IE00B4L5Y983", security_type="etf")

etf_general_info = etf.justetf_general_info
etf_wkn = etf.justetf_wkn
etf_description = etf.justetf_description

# Price data and chabges
etf_price = etf.justetf_price

# Basic data about the ETF
etf_basics = etf.justetf_basics

# Holdings of the ETF by company, country and sector
etf_holdings_companies = etf.justetf_holdings_companies
etf_holdings_countries = etf.justetf_holdings_countries
etf_holdings_sectors = etf.justetf_holdings_sectors
```

--------------------------------

### Plotting Financial Data from Digrin with Plotly

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

This Python code demonstrates how to use the `stockdex` library to extract and plot various financial data points from the Digrin website using `plotly`. It covers shares outstanding, price, dividend, assets vs. liabilities, free cash flow, cash and debt, net income, expenses, and cost of revenue. Each function call opens a new browser tab with the generated plot.

```python
from stockdex import Ticker

ticker = Ticker(ticker="ASML")

ticker.plot_digrin_shares_outstanding()
ticker.plot_digrin_price()
ticker.plot_digrin_dividend()
ticker.plot_digrin_assets_vs_liabilities()
ticker.plot_digrin_free_cash_flow()
ticker.plot_digrin_cash_and_debt()
ticker.plot_digrin_net_income()
ticker.plot_digrin_expenses()
ticker.plot_digrin_cost_of_revenue()
```

--------------------------------

### Retrieve EU ETF General Information from justETF

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

Shows how to retrieve general information for EU ETFs using Stockdex. The `Ticker` object is initialized with the ETF's International Securities Identification Number (ISIN) and the `security_type` parameter set to 'etf'. Users should be aware of justETF's strict rate limiting.

```python
from stockdex import Ticker

etf = Ticker(isin="IE00B4L5Y983", security_type="etf")

etf_general_info = etf.justetf_general_info
```

--------------------------------

### Generate Sankey Charts for Cash Flow Visualization

Source: https://github.com/ahnazary/stockdex/blob/main/USAGE.md

This snippet demonstrates how to create a Sankey chart using the `plot_sankey_chart` function in `stockdex`. Sankey charts are used to visualize the flow of cash within a company, based on data extracted from the Yahoo Finance API. The generated chart is interactive, allowing users to hover over categories to see specific cash amounts.

```python
from stockdex import Ticker

ticker = Ticker(ticker="AAPL")

ticker.plot_sankey_chart()
```

--------------------------------

### Generate Sankey Chart for Cash Flow Visualization

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

This snippet demonstrates how to create a Sankey chart using the `plot_sankey_chart` function. This chart visualizes the flow of cash based on data extracted from the Yahoo Finance API, typically representing the income statement. Hovering over the chart provides detailed amounts for each category.

```python
from stockdex import Ticker

ticker = Ticker(ticker="AAPL")

ticker.plot_sankey_chart()
```

--------------------------------

### Retrieving Comprehensive Financial Data from Yahoo Finance

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

This Python code demonstrates how to use `stockdex` to extract a wide range of financial information from Yahoo Finance. It covers summary data, detailed financial statements (income, balance, cash flow), analyst estimates, options data (calls, puts), company profile details (executives, description, governance), shareholder information, and various financial statistics.

```python
from stockdex import Ticker

ticker = Ticker(ticker="AAPL")

# Summary including general financial information
summary = ticker.yahoo_web_summary

# Financial data as it is seen in the yahoo finance website
income_stmt = ticker.yahoo_web_income_stmt
balance_sheet = ticker.yahoo_web_balance_sheet
cash_flow = ticker.yahoo_web_cashflow

# Analysts and estimates
analysis = ticker.yahoo_web_analysis

# Data about options
calls = ticker.yahoo_web_calls
puts = ticker.yahoo_web_puts

# Profile data 
key_executives = ticker.yahoo_web_key_executives
description = ticker.yahoo_web_description
corporate_governance = ticker.yahoo_web_corporate_governance

# Data about shareholders
major_holders = ticker.yahoo_web_major_holders
top_institutional_holders = ticker.yahoo_web_top_institutional_holders
top_mutual_fund_holders = ticker.yahoo_web_top_mutual_fund_holders

# Statistics
valuation_measures = ticker.yahoo_web_valuation_measures
financial_highlights = ticker.yahoo_web_financial_highlights
trading_information = ticker.yahoo_web_trading_information
```

--------------------------------

### Retrieving Raw Financial Data from Macrotrends as Pandas DataFrames

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

This Python code demonstrates how to fetch various raw financial datasets from the Macrotrends website using `stockdex`. The data, including income statements, balance sheets, cash flow, key financial ratios, and different margin types (gross, operating, EBITDA, pre-tax, net), is returned as pandas DataFrames for further analysis.

```python
from stockdex import Ticker

ticker = Ticker(ticker="AAPL")

# Financial data
income_statement = ticker.macrotrends_income_statement
balance_sheet = ticker.macrotrends_balance_sheet
cash_flow = ticker.macrotrends_cash_flow
key_financial_ratios = ticker.macrotrends_key_financial_ratios

# Margins
gross_margin = ticker.macrotrends_gross_margin
operating_margin = ticker.macrotrends_operating_margin
ebitda_margin = ticker.macrotrends_ebitda_margin
pre_tax_margin = ticker.macrotrends_pre_tax_margin
net_margin = ticker.macrotrends_net_margin
```

--------------------------------

### Retrieve Raw Financial Data from Yahoo Finance API

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

This snippet demonstrates how to use the `stockdex` package to fetch various raw financial data points from the Yahoo Finance API for a given ticker. It covers price data, current trading periods, and fundamental data like income statements, cash flow, balance sheets, and general financials, returning them as pandas DataFrames. Parameters like `range`, `dataGranularity`, `frequency`, `format`, `period1`, and `period2` can be used to refine the data.

```python
from stockdex import Ticker
from datetime import datetime

ticker = Ticker(ticker="AAPL")

# Price data (use range and dataGranularity to make range and granularity more specific)
price = ticker.yahoo_api_price(range='1y', dataGranularity='1d')

# Current trading period of the stock (pre-market, regular, post-market trading periods)
current_trading_period = ticker.yahoo_api_current_trading_period

# Fundamental data (use frequency, format, period1 and period2 to fine-tune the returned data)
income_statement = ticker.yahoo_api_income_statement(frequency='quarterly')
cash_flow = ticker.yahoo_api_cash_flow(format='raw')
balance_sheet = ticker.yahoo_api_balance_sheet(period1=datetime(2020, 1, 1))
financials = ticker.yahoo_api_financials(period1=datetime(2022, 1, 1), period2=datetime.today())
```

--------------------------------

### Plotting Historical Price Data from Digrin as a Line Chart

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

This Python snippet shows how to plot historical price data from the Digrin website using `stockdex`. For datasets with many points, the `plot_digrin_price()` function automatically generates a line chart instead of a bar chart, illustrating real and adjusted prices.

```python
from stockdex import Ticker

ticker = Ticker(ticker="CAT")

ticker.plot_digrin_price()
```

--------------------------------

### Retrieve Raw Historical Data from Digrin Website

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

This snippet shows how to access comprehensive historical and non-historical stock data from the Digrin website, which often provides more extensive historical coverage than Yahoo Finance. It retrieves various data points such as dividends, payout ratios, stock splits, prices, assets vs. liabilities, free cash flow, net income, cash and debt, shares outstanding, expenses, cost of revenue, and upcoming estimated earnings, all returned as pandas DataFrames.

```python
from stockdex import Ticker

ticker = Ticker(ticker="AAPL")

# Complete historical data of the stock in certain categories
dividend = ticker.digrin_dividend
payout_ratio = ticker.digrin_payout_ratio
stock_splits = ticker.digrin_stock_splits
price = ticker.digrin_price

# Non-historical data
assets_vs_liabilities = ticker.digrin_assets_vs_liabilities
free_cash_flow = ticker.digrin_free_cash_flow
net_income = ticker.digrin_net_income
cash_and_debt = ticker.digrin_cash_and_debt
shares_outstanding = ticker.digrin_shares_outstanding
expenses = ticker.digrin_expenses
cost_of_revenue = ticker.digrin_cost_of_revenue
upcoming_estimated_earnings = ticker.digrin_upcoming_estimated_earnings

# Dividend data
dividend = ticker.digrin_dividend
dgr3 = ticker.digrin_dgr3
dgr5 = ticker.digrin_dgr5
dgr10 = ticker.digrin_dgr10
```

--------------------------------

### Plot Financial Data from Yahoo Finance API using Plotly

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

This snippet illustrates how to visualize financial data obtained from the Yahoo Finance API using `plotly`. Functions prefixed with `plot_yahoo_api_` generate interactive plots for financials, income statements, cash flow, and balance sheets. The `group_by` and `freq` parameters allow for customization of the plot's aggregation and frequency. By default, these functions open a new browser tab with the plot, but setting `show_plot=False` returns the Plotly figure object for custom handling.

```python
from stockdex import Ticker

ticker = Ticker(ticker="MSFT")

ticker.plot_yahoo_api_financials(group_by="field")
ticker.plot_yahoo_api_income_statement(group_by="timeframe")
ticker.plot_yahoo_api_cash_flow(freq="quarterly")
ticker.plot_yahoo_api_balance_sheet(freq="quarterly")
```

--------------------------------

### Plotting Financial Data from Macrotrends with Plotly

Source: https://github.com/ahnazary/stockdex/blob/main/README.md

This Python snippet illustrates how to plot key financial statements (income statement, balance sheet, cash flow) extracted from the Macrotrends website using `stockdex` and `plotly`. Each function call generates a plot that opens in a new browser tab.

```python
from stockdex import Ticker

ticker = Ticker(ticker="GOOGL")

ticker.plot_macrotrends_income_statement()
ticker.plot_macrotrends_balance_sheet()
ticker.plot_macrotrends_cash_flow()
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.