PDXtra

PDXtra is a data analysis library built on top of Pandas and geared toward time-series data analysis. The library offers subclasses of traditional Pandas Series and DataFrame objects which provide additional convenience methods for querying and manipulating data while retaining all of the functionality of the original Pandas API. Additionally, the library also provides TimeSeries and TimeSeriesDataFrame subclasses which are specifically designed to be used for time-series and financial data analysis.

What can the package do?

• Downcast entire dataframes. Choose whether to downcast integer columns, float columns, or both.
• Perform Excel-style x-lookup, and v-lookup.
• Qickly scan dataframes for column values based on index values, and optionally search using nearest-match.
• Compute the intersections of curves.
• Use inter-quartile range to eliminate outliers in data sets.
• Compute the linear regression of a series.
• Get true N-day moving averages.
• Temporarily set a dataframe index using a context manager.
• Compute common financial time-series metrics including: relative strength index, moving average convergence-divergence, and on-balance volume.

Note

This distribution has been developed and tested on a standalone Python build and could--under rare circumstances--exibit unexpected behavior on standard CPython. Although no differences between the execution of code in the standalone build and normal CPython have been found during the process of development, I nevertheless wish to provide fair warning.

Installation

python -m pip install pdxtra

Documentation

Up-to-date documentation can be found here: https://jammin93.github.io/pdxtra/

Usage

TimeSeries and TimeSeriesDataFrame are both subclasses of the Series and DataFrame objects, respectively, and they themselves are subclasses of the original Pandas DataFrame and Series objects. This means that all of the functionality of the Pandas API is inhereted by these subclasses.

Series Objects

Creation of Series and DataFrame objects follows the same syntax as traditional Pandas.

import pdxtra as pdx

series = pdx.Series([1, 2, 3, 4, 5])
time_series = pdx.TimeSeries([1, 2, 3, 4, 5])

DataFrame Objects

Creating TimeSeries and TimeSeriesDataFrame objects is no different from creating their vanilla counterparts.

import pdxtra as pdx

df = pdx.Dataframe({
    "a": ["a", "b", "c", "d", "e"],
    "b": [1, 2, 3, 4, 5],
})
ts_df = pdx.TimeSeriesDataFrame({
    "a": ["a", "b", "c", "d", "e"],
    "b": [1, 2, 3, 4, 5],
})

License

GNU General Public License