Metadata-Version: 2.1
Name: pandas-x
Version: 0.0.4
Summary: GPS/position calculation accessor for pandas DataFrames.
Home-page: https://github.com/aaron-schroeder/pandas-x
Author: Aaron Schroeder
Author-email: aaron@trailzealot.com
License: MIT
Project-URL: Documentation, https://pandas-x.readthedocs.io/en/v0.0.4/
Description: # pandas-x
        <!-- # pandas-distance -->
        <!-- # pandas-position -->
        <!-- # pandas-gps -->
        
        GPS/position calculation accessor for pandas DataFrames.
        
        ## Example Usage
        
        pandas-x provides the `.pos` DataFrame accessor:
        
        ```python
        >>> import pandas as pd
        >>> import pandas_x
        
        >>> df = pd.DataFrame.from_dict({
        ...   'lat': [40.0, 40.1, 40.3],
        ...   'lon': [-105.0, -105.0, -105.0]
        ... })
        
        >>> df['displacement'] = df.pos.ds_from_xy()
        >>> df['displacement']
        0        0.000000
        1    11119.492664
        2    22238.985329
        dtype: float64
        
        >>> df.pos.s_from_ds()
        0        0.000000
        1    11119.492664
        2    33358.477993
        dtype: float64
        ```
        
        ## Dependencies and Installation
        
        [Pandas](https://pandas.pydata.org/) and [NumPy](https://numpy.org/) are required.
        
        The package is available on [PyPi](https://pypi.org/project/pandas-x) and can be installed with `pip`:
        
        ```
        $ pip install pandas-x
        ```
        
        ## License 
        
        [![License](http://img.shields.io/:license-mit-blue.svg)](http://badges.mit-license.org)
        
        This project is licensed under the MIT License. See
        [LICENSE](https://github.com/aaron-schroeder/pandas-x/blob/master/LICENSE)
        file for details.
        
        ## Documentation
        
        The official documentation is hosted at readthedocs: https://pandas-x.readthedocs.io/en/stable/
        
        ## Current Activities
        
        - Implement an algorithm to smooth GPS position and speed data. 
          Most GPS-enabled activity trackers filter their speed and distance
          timeseries to remove measurement noise. I want to try and figure out
          how they do it, then replicate their techniques, and compare the
          smoothed position data.
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
