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‎docs/source/index.rst

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:maxdepth: 2
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:caption: Tutorials
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tutorial/installation
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tutorial/ex0_install
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tutorial/ex1_plot
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tutorial/ex2_plot_intraday
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‎docs/source/tutorial.rst

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.. toctree::
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:maxdepth: 2
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tutorial/installation
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tutorial/ex0_install
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tutorial/ex1_plot
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tutorial/ex2_plot_intraday

‎docs/source/tutorial/installation.rst renamed to ‎docs/source/tutorial/ex0_install.rst

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@@ -91,8 +91,8 @@ Create a file named ``config.ini`` and structure it as follows:
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.. code-block:: ini
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[Credentials]
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email = 'your-email@example.com'
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api_key = 'your-secret-api-key'
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email = your-email@example.com
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api_key = your-secret-api-key
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**Read Config File, Login, and Access Data**
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# Read credentials from config file
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config = configparser.ConfigParser()
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config.read('config.ini')
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email = config['Credentials']['email']
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api_key = config['Credentials']['api_key']
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email = config.get("Credentials","email")
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api_key = config.get("Credentials","api_key")
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# Login and access data
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mdb.login(email, api_key)

‎docs/source/tutorial/ex2_plot_intraday.rst

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Plotting Intraday Stock Prices
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##############################
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In this guide, we will walk you through the steps to retrieve
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financial data using MoabDB and how to create a basic
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chart using the `matplotlib` library.
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.. image:: https://img.shields.io/pypi/v/moabdb.svg
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:target: https://pypi.python.org/pypi/moabdb
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:alt: PyPI Version
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Continuing with the theme of price plotting, this guide will walk
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you through how to plot intraday stock prices using MoabDB and `matplotlib`.
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.. Prerequisites
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.. =============
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Prerequisites
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=============
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.. - For advanced plotting, ensure you've set up and authenticated with MoabDB as described in the Quick Start guide.
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.. The advanced plotting will assume you have a ``config.ini`` file in your working directory with the following structure:
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- For advanced plotting, ensure you've set up and authenticated with MoabDB as described in the Quick Start guide.
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- The advanced plotting will assume you have a ``config.ini`` file in your working directory with the following structure:
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.. .. code-block:: ini
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.. code-block:: ini
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.. [Credentials]
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.. email = 'your-email@example.com'
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.. api_key = 'your-secret-api-key'
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[Credentials]
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email = your-email@example.com
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api_key = your-secret-api-key
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.. - You will need `matplotlib` installed. If you haven't already, you can install it with:
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- You will need `matplotlib` installed. If you haven't already, you can install it with:
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.. .. code-block:: bash
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.. code-block:: bash
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.. pip install matplotlib
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pip install matplotlib
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.. Plotting Single Stock with Daily-Level Data
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.. ===========================================
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Plotting Single Stock with Daily-Level Data
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===========================================
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.. First, let's retrieve some financial data. For this example, we'll fetch historical closing prices for a given stock (e.g., `AAPL`):
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First, let's retrieve some financial data. For this example, we'll fetch historical closing prices for a given stock (e.g., `AAPL`):
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.. Import MoabDB and fetch data
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.. ----------------------------
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Import MoabDB and fetch data
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----------------------------
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.. .. code-block:: python
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.. code-block:: python
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.. import moabdb as mdb
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.. import matplotlib.pyplot as plt
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import configparser
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import moabdb as mdb
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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.. # Constants defined here for flexibility
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.. TIC = 'MSFT'
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.. SAMPLE = '5y'
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# Constants defined here for flexibility
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TIC = 'MSFT'
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SAMPLE = '1d'
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DAY_START = '9:30'
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DAY_END = '16:00'
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.. # Load and Check Data
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.. data_df = mdb.get_equity(tickers=TIC, sample=SAMPLE)
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.. print(data_df.head())
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# Reading in credentials from config.ini file
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# Read credentials from config file
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config = configparser.ConfigParser()
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config.read('config.ini')
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email = config.get("Credentials", "email")
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api_key = config.get("Credentials", "api_key")
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mdb.login(email, api_key)
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.. Visualizing Data with Matplotlib
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.. --------------------------------
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Plot 1 day of intraday data
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---------------------------
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.. With our data in hand, we can now plot it:
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**Simple plot**
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.. .. code-block:: python
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With our data in hand, we can now plot it:
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.. import moabdb as mdb
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.. import matplotlib.pyplot as plt
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.. code-block:: python
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.. # Constants defined here for flexibility
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.. TIC = 'MSFT'
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.. SAMPLE = '5y'
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import configparser
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import moabdb as mdb
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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.. # Load and Check Data
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.. data_df = mdb.get_equity(tickers=TIC, sample=SAMPLE)
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.. print(data_df.head())
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# Constants defined here for flexibility
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TIC = 'MSFT'
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SAMPLE = '1d'
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DAY_START = '9:30'
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DAY_END = '16:00'
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.. # Creating the plot
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.. x = data_df.index
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.. y = data_df['Close']
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# Reading in credentials from config.ini file
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# Read credentials from config file
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config = configparser.ConfigParser()
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config.read('config.ini')
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email = config.get("Credentials", "email")
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api_key = config.get("Credentials", "api_key")
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mdb.login(email, api_key)
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# Load and get price data
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data_df = mdb.get_equity(tickers=TIC, sample=SAMPLE, intraday=True)
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price_df = data_df['Close'].between_time(DAY_START, DAY_END)
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# Plot
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price_df.plot()
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plt.show()
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**Customization with Matplotlib**
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The simple plot leaves a lot to be desired. Let's customize it with `matplotlib`:
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.. code-block:: python
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import configparser
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import moabdb as mdb
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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# Constants defined here for flexibility
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TIC = 'MSFT'
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SAMPLE = '1d'
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DAY_START = '9:30'
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DAY_END = '16:00'
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# Reading in credentials from config.ini file
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# Read credentials from config file
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config = configparser.ConfigParser()
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config.read('config.ini')
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email = config.get("Credentials", "email")
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api_key = config.get("Credentials", "api_key")
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mdb.login(email, api_key)
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# Load and get price data
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data_df = mdb.get_equity(tickers=TIC, sample=SAMPLE, intraday=True)
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price_df = data_df['Close'].between_time(DAY_START, DAY_END)
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# Plot Data Values
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x = price_df.index
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y = price_df.values
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# Plot
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fig, ax = plt.subplots(figsize=(8,4))
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ax.plot(x, y, label=TIC, color='blue')
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ax.set_xlabel('Date')
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ax.set_ylabel('Closing Price (in $)')
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ax.xaxis.set_major_formatter(
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mdates.ConciseDateFormatter(ax.xaxis.get_major_locator()))
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fig.autofmt_xdate()
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plt.legend()
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plt.show()
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.. fig, ax = plt.subplots(figsize=(6,4))
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.. ax.plot(x, y, label=TIC, color='blue')
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.. ax.set_xlabel('Date')
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.. ax.set_ylabel('Closing Price (in $)')
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.. plt.legend()
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.. plt.show()
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