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@MISC{Herten:1019180,
      author       = {Herten, Andreas},
      title        = {{D}ata {A}nalysis and {P}lotting in {P}ython with {P}andas},
      reportid     = {FZJ-2023-05226},
      year         = {2023},
      note         = {Material can also be found at
                      https://herten1.pages.jsc.fz-juelich.de/jsc-pandas-introduction/},
      abstract     = {Pandas solves the full stack of data analysis in Python;
                      reading-in of data, mangling and manipulation, analysis, and
                      visualisation (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 introduces Pandas with simple examples in
                      hands-on exercises, highlighting the capabilities of the
                      software package on the way with increasing complexity.},
      month         = {Sep},
      date          = {2023-09-04},
      organization  = {JSC - as part of the Training
                       Programme of Forschungszentrum Jülich,
                       online (Germany), 4 Sep 2023 - 4 Sep
                       2023},
      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},
      doi          = {10.34734/FZJ-2023-05226},
      url          = {https://juser.fz-juelich.de/record/1019180},
}