% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@MISC{Herten:915941,
author = {Herten, Andreas},
title = {{D}ata {A}nalysis and {P}lotting in {P}ython with {P}andas},
reportid = {FZJ-2022-05804},
year = {2022},
abstract = {Pandas solves the full stack of data analysis in Python;
reading-in of data, mangling and manipulation, analysis, and
visualization (and much more, actually). It builds up on
established Python packages and can be used interchangeably
with them (like Numpy, matplotlib); it fits perfectly into
the Jupyter Notebooks workflow of modern-day data
analysis.This course will introduce Pandas with simple
examples in hands-on exercises, highlighting the
capabilities of the software package on the way with
increasing complexity.},
month = {May},
date = {2022-05-12},
organization = {JSC as part of the training programme
of Forschungszentrum Jülich, online,
12 May 2022 - 12 May 2022},
subtyp = {Other},
cin = {JSC},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
and Research Groups (POF4-511) / ATML-X-DEV - ATML
Accelerating Devices (ATML-X-DEV)},
pid = {G:(DE-HGF)POF4-5112 / G:(DE-Juel-1)ATML-X-DEV},
typ = {PUB:(DE-HGF)17},
url = {https://juser.fz-juelich.de/record/915941},
}