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picture1_Python Pdf 186002 | Dv Excel Python Cl Fs 2021 Eng


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File: Python Pdf 186002 | Dv Excel Python Cl Fs 2021 Eng
data visualization excel versus python when to use which approach university library bern science library dr michael horn coffee bit e s spring 2021 this lecture content excel and python ...

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    Data Visualization: Excel versus Python
    When to use which approach ?
    University Library Bern, Science Library
    Dr. Michael Horn, Coffee & Bit(e)s, Spring 2021
       This Lecture
       Content
                     Excel and Python tools in a nutshell
                     data visualization: data size and data complexity
                     data visualization: chart/ plot types
                     conclusion
       2
       Excel and Python tools in a nutshell
       Excel / Python tools (jupyter, pandas, matplotlib)
   Excel:                                                 Python tools:
          o   Microsoft product                                   o open source: non-proprietary, transparent
          o   desktop application                                 o Python: 
          o   intuitive handling                                        −  programming (scripting) language
          o   multifunctional:                                          −  easy to learn, very powerful and flexible
                −   spreadsheets for data handling                o jupyter notebook:
                −   allows complex data analysis                        −  browser-based application
                −   allows data visualization                           −  integrates code, code output and documentation
                −   …                                             o pandas and matplotlib
          o   has some relevant limitations in                          −  python libraries (pandas: data processing, 
              comparison to python tools                                   matplotlib: data visualization)
                                                                        −  fast, powerful, flexible, easy to use, very robust
       3
       Data size and data complexity
       Small and simple data sets
     Typical scenario:
     o manual data acquisition
     o rapid data visualization
     Some pros and cons:
     (+) very intuitive
     (+) quickly ready for use
     (-) requires intermediate 
       steps (average, stddev)
       4
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