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 # More advanced topics in Python
 
 ## Nice standard libraries
-* argsparse, datetime, fnmatch, glob, os, re, sys, subprocess
+* argsparse, datetime, fnmatch, re, sys, subprocess, pathlib
 
 ## Nice libraries for data analysis
 * [NumPy](https://numpy.org/)
 * [pandas](https://pandas.pydata.org/docs/)
 * [matplotlib](https://matplotlib.org/)
+* [iminuit](https://iminuit.readthedocs.io/en/stable/) for fitting
+* [resample](https://resample.readthedocs.io/en/stable/) for uncertainty estimation with the bootstrap and jackknife
+* [jacobi](https://hdembinski.github.io/jacobi/) for error propagation based on first derivatives
+* [numba-stats](https://github.com/HDembinski/numba-stats) fast implementations of statistical distributions to build statistical models
 
 ## Python and ROOT
 * pyROOT: Python interface for ROOT