guest ::
| Home > Publications database > Data Analysis and Plotting in Python with Pandas > print |
| 001 | 915941 | ||
| 005 | 20250822121514.0 | ||
| 024 | 7 | _ | |a 2128/33148 |2 Handle |
| 037 | _ | _ | |a FZJ-2022-05804 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Herten, Andreas |0 P:(DE-Juel1)145478 |b 0 |e Corresponding author |u fzj |
| 111 | 2 | _ | |a JSC as part of the training programme of Forschungszentrum Jülich |c online |d 2022-05-12 - 2022-05-12 |
| 245 | _ | _ | |a Data Analysis and Plotting in Python with Pandas |
| 260 | _ | _ | |c 2022 |
| 336 | 7 | _ | |a lecture |2 DRIVER |
| 336 | 7 | _ | |a Generic |0 31 |2 EndNote |
| 336 | 7 | _ | |a MISC |2 BibTeX |
| 336 | 7 | _ | |a Lecture |b lecture |m lecture |0 PUB:(DE-HGF)17 |s 1671626771_28423 |2 PUB:(DE-HGF) |x Other |
| 336 | 7 | _ | |a LECTURE_SPEECH |2 ORCID |
| 336 | 7 | _ | |a Text |2 DataCite |
| 520 | _ | _ | |a 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. |
| 536 | _ | _ | |a 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) |0 G:(DE-HGF)POF4-5112 |c POF4-511 |f POF IV |x 0 |
| 536 | _ | _ | |a ATML-X-DEV - ATML Accelerating Devices (ATML-X-DEV) |0 G:(DE-Juel-1)ATML-X-DEV |c ATML-X-DEV |x 1 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/915941/files/Introduction-to-Pandas--slides.pdf |y OpenAccess |
| 909 | C | O | |o oai:juser.fz-juelich.de:915941 |p openaire |p open_access |p VDB |p driver |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)145478 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action |1 G:(DE-HGF)POF4-510 |0 G:(DE-HGF)POF4-511 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Enabling Computational- & Data-Intensive Science and Engineering |9 G:(DE-HGF)POF4-5112 |x 0 |
| 914 | 1 | _ | |y 2022 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 980 | _ | _ | |a lecture |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | 1 | _ | |a FullTexts |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|