DOC: update readme, move parts to docs

README.rst

@@ -1,10 +1,27 @@
-=======
-Fast F1
-=======
+======
+FastF1
+======
 
 FastF1 is a python package for accessing and analyzing Formula 1 results,
 schedules, timing data and telemetry.
 
+.. image:: docs/_static/readme.png
+    :target: docs/_static/readme.png
+
+
+Main Features
+=============
+
+- Access to F1 timing data, telemetry, sessions results and more
+- Full support for `Ergast <http://ergast.com/mrd/>`_ to access current and
+  historical F1 data
+- All data is provided in the form of extended Pandas DataFrames to make
+  working with the data easy while having powerful tools available
+- Adds custom functions to the Pandas objects specifically to make working
+  with F1 data quick and simple
+- Integration with Matplotlib to facilitate data visualization
+- Implements caching for all API requests to speed up your scripts
+
 
 Installation
 ============
@@ -16,8 +33,6 @@ It is recommended to install FastF1 using `pip`:
    pip install fastf1
 
 Note that Python 3.8 or higher is required.
-(The live timing client does not support Python 3.10, therefore full
-functionality is only available with Python 3.8 and 3.9)
 
 Alternatively, a wheel or a source distribution can be downloaded from Pypi.
 
@@ -28,97 +43,15 @@ You can also install using `conda`:
   conda install -c conda-forge fastf1
 
 
-Getting Started: Documentation and Examples
-===========================================
-
- - `Documentation <https://theoehrly.github.io/Fast-F1/>`_.
- - `Examples <https://theoehrly.github.io/Fast-F1/examples/index.html>`_.
- - `Changelog <https://theoehrly.github.io/Fast-F1/changelog.html>`_.
- - `Contributing <https://theoehrly.github.io/Fast-F1/contributing/index.html>`_.
-
-Furthermore, there are  some great articles and examples written by other
-people. They provide a nice overview about what you can do with FastF1 and
-might help you to get started.
-
-  - `Accessing Formula-1 Race's historical data using Python (medium.com) <https://pandeyparul.medium.com/accessing-formula-1-races-historical-data-using-python-b7c80e544f50>`_
-  - `Formula 1 Data Analysis Tutorial - 2021 Russian GP: "To Box, or Not to Box?" (medium.com) <https://medium.com/@jaspervhat/formula-1-data-analysis-tutorial-2021-russian-gp-to-box-or-not-to-box-da6399bd4a39>`_
-  - `How to Analyze Formula 1 Telemetry in 2022 - A Python Tutorial (medium.com) <https://medium.com/towards-formula-1-analysis/how-to-analyze-formula-1-telemetry-in-2022-a-python-tutorial-309ced4b8992>`_
-
-
-General Information
-===================
-
-Usage
------
-
-Creating a simple analysis is not very difficult, especially if you are already familiar
-with pandas and numpy.
-
-Suppose that we want to analyse the race pace of Leclerc compared to
-Hamilton for the Turkish GP 2020.
-
-.. code:: python
-
-    import fastf1
-    from fastf1 import plotting
-    from matplotlib import pyplot as plt
-
-    plotting.setup_mpl()
-
-    race = fastf1.get_session(2020, 'Turkish Grand Prix', 'R')
-    race.load()
-
-    lec = race.laps.pick_driver('LEC')
-    ham = race.laps.pick_driver('HAM')
-
-Once the session is loaded, and drivers are selected, you can plot the
-information.
-
-:code:`fastf1.plotting` provides some special axis formatting and data type conversion. This is required
-for generating a correct plot.
-
-It is not necessary to enable the usage of a cache but it is recommended. Simply provide
-the path to some empty folder on your system.
-
-.. code:: python
-
-    fig, ax = plt.subplots()
-    ax.plot(lec['LapNumber'], lec['LapTime'], color='red')
-    ax.plot(ham['LapNumber'], ham['LapTime'], color='cyan')
-    ax.set_title("LEC vs HAM")
-    ax.set_xlabel("Lap Number")
-    ax.set_ylabel("Lap Time")
-    plt.show()
-
-.. image:: docs/_static/readme.svg
-    :target: docs/_static/readme.svg
-
-
-Compatibility
--------------
-
-Timing data, car telemetry and position data is available for the 2018 and
-later seasons. Schedule information and session results are available for
-older seasons too.
-(limited to `Ergast web api <http://ergast.com/mrd/>`_).
-
-
-Data Sources
-------------
-
-FastF1 uses data from F1's live timing service.
-
-Data can be downloaded after a session. Alternatively, the actual live timing
-data can be recorded and the recording can be used as a data source.
+Documentation
+=============
 
-Usually it is not necessary to record the live timing data. But there have
-been server issues in the past which resulted in the data being unavailable
-for download. Therefore, you only need to record live timing data if you
-want to benefit from the extra redundancy.
+The official documentation can be found here:
+`https://theoehrly.github.io/Fast-F1/ <https://theoehrly.github.io/Fast-F1/>`_
 
 
 Notice
-------
+======
 
 FastF1 and this website are unofficial and are not associated in any way with
 the Formula 1 companies. F1, FORMULA ONE, FORMULA 1, FIA FORMULA ONE WORLD