% 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: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}, }