Python for data analytics
During this training, we learn how we can analyse data using Python. In the last few years, the fields of data analytics and data science became of great importance throughout the professional world. At the same time, we notice a spectacular growth in the popularity of Python in this field: it is on its way to become the leading language in scientific and business data analysis. Python's general strengths as a multi-purpose programming language, combined with a number of specialised libraries, make it a very valuable tool for exploring, analysing, and visualising all sorts of data.
In this course we look at the possibilities of Python in the field of data analysis and visualisation, including popular libraries such as NumPy, Pandas and Matplotlib.
Schedule
No public sessions are currently scheduled. We will be pleased to set up an on-site course or to schedule an extra public session (in case of a sufficient number of candidates). Interested? Please let us know.
Intended for
This training is aimed at whoever wants to start practising data analysis: developers, data scientists, data architects, marketeers, and anyone who needs to manipulate, visualize, or summarize their corporate data.
Background
Basic Python knowledge is a prerequisite for this training, as well as some notions of statistics (see courses Python fundamentals and Statistics fundamentals).
Main topics
- Reading and writing data
- Text files, CSV
- Databases
- Microsoft Excel
- XML, HTML, JSON
- Data Wrangling and exploratory analysis
- Concatenating, merging and joining data
- Transforming data
- Pivoting
- Handling missing data
- Data aggregation and Grouping
- Regular Expressions (optional)
- Visualisation
- The Scientific Python ecosystem (SciPy)
- NumPy
- Pandas
- Matplotlib
- IPython and Jupyter Notebooks
- Other useful packages
Training method
Classroom training with demos and practical exercises.
Duration
3 days.
Course leader
Arnout Veugelen.
Reviews
4.4/5 (based on 41 evaluations; the most recent ones are shown below)
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It was very well presented, interesting,useful and fun!
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| (Nina Sender, ING - Laanderpoort, ) |
The course was really in-depth and explained well
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| (N.N., Euroclear, ) |
good, I feel myself more comfortable with Python after this course
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| (Anastasia, ) |
Very satisfied (8.5/10)
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| (N.N., European Securities and Markets Authority, ) |
Excellent. The material was very complete, user friendly and well organised. The teacher was very knowledgeable about the topic and make the training not only interactive and interesting but also entertaining
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| (Ana Maria Rivera Serrano, ) |
The course was well organised, the explanations clear and the supporting documuments were very helpful. I would recommend it
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| (Erica, ) |
Really appreciated the course level, the instructor has been really clear in his explanations
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| (William, ) |
Very good for our needs. Perhaps slightly too "Theoric" in the initial part for an "Economists" audience.
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| (Luigi, ) |
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Very good, good pace and structure of the course.
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| (N.N., European Securities and Markets Authority, ) |
Zeer positief, zie al uit naar een volgende cursus bij ABIS.
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| (Bieneke Berendsen, KPN, ) |
Erg goed, veel geleerd van de fundamenten van data analyse.
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| (N.N., ING - Laanderpoort, ) |
Good, maybe a little more exercises could be added.
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| (N.N., European Securities and Markets Authority, ) |
Also interesting
Enrollees for this training also took the following courses:
| SESSION INFO AND ENROLMENT |