The PDE (Pdf Data Extractor) allows the extraction of 
    information and tables optionally based on search words from 
    PDF (Portable Document Format) files and enables the visualization 
    of the results, both by providing a convenient user-interface.

Data sets for the Panel Data Econometrics with R <doi:10.1002/9781119504641> book.

Cluster analysis via nonparametric density 
   estimation is performed. Operationally, the kernel method is used throughout to estimate
   the density. Diagnostics methods for evaluating the quality of the clustering 
   are available. The package includes also a routine to estimate the 
   probability density function obtained by the kernel method, given a set of
   data with arbitrary dimensions.

Farmer, J., D. Jacobs (2108) <DOI:10.1371/journal.pone.0196937>. A multivariate nonparametric density estimator based on the maximum-entropy method.  Accurately predicts a probability density function (PDF) for random data using a novel iterative scoring function to determine the best fit without overfitting to the sample.

Download economic and financial time series from public sources, 
  including the St Louis Fed's FRED system, Yahoo Finance, the US Bureau of Labor Statistics, 
  the US Energy Information Administration, the World Bank, Eurostat, the European Central Bank,
  the Bank of England, the UK's Office of National Statistics, Deutsche Bundesbank, and INSEE.

Provides an interface to 'PDFMiner' <https://github.com/pdfminer/pdfminer.six> 
    a 'Python' package for extracting information from 'PDF'-files. 
    'PDFMiner' has the goal to get all information available in a 'PDF'-file, 
    position of the characters, font type, font size and informations about lines. 
    Which makes it the perfect starting point for extracting tables from 'PDF'-files.
    More information can be found in the package 'README'-file.

Includes functions for keyword search of pdf files. There is
    also a wrapper that includes searching of all files within a single
    directory.