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Python Basics for Data Analysis (English)

Website der Veranstaltung

Datum und Uhrzeit

27.09.2022, 09:00 - 30.09.2022, 12:15
Im Kalender speichern


Zoom (Online)
München, Deutschland


Course duration: 4 half days, each from 09:00 - 12:15 CET (Online-Live-Seminar)

Course language: English (we can switch to German if all participants are fluent in German)

The Python Basics course is intended for participants who want to learn basic Python skills as well as efficient handling of data preparation, data processing, and data analysis in Python. In addition, general "best practices" in Python will be taught, including, writing simple, readable, and modularly extensible code. All topics presented will be explained, demonstrated, and practiced in detail with the help of participant exercises under intensive instruction. The course covers the following topics:

Part 1: Introduction to Python

- Introduction to the basics of Python

- Installation and use of Python and useful Python modules

- Creating and working with virtual environments

- Explanation of the most important data types, operators, functions, and help pages

- Introduction to NumPy and Pandas

- Importing and exporting data

- Working with DataFrames and vectors (numeric, logical, character, factors), e.g. indexing, splitting, and transforming variables or data sets

- Calculating statistical ratios (e.g.: mean, quantiles, variance, etc.)

Part 2: Data Wrangling in Python

- Review of Python basics: built-in structures, NumPy, IPython, jupyter notebook, package management, jupytext

- Series and DataFrames: generation, meaning of line index, filtering, pointer vs. copy

- Importing and exporting data from text files and (unstructured) Excel spreadsheets, and accessing databases using Python

- Data cleansing: Handling missing values, editing strings, removing duplicates.

- Transforming data by vectorized operations like map or apply

- Merging different data sources and creating a "good" table structure of the data

- Grouping of data and aggregations: Split-Apply-Combine

- Time series and date-time objects

Prerequisites: none

For registrations 3 months before the course starts, you can get an additional 10% discount on top of the earlybird price using the following promotion code: GI


Essential Data Science Training GmbH

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