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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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