Exegetic Analytics is a Data Science consultancy specialising in data acquisition and augmentation, data preparation, predictive analytics and machine learning. Our services are used by a range of industries from Education to Security, Food Delivery to Politics. Our consultants are based in Durban and Cape Town and we engage with clients all over the world. Our products and services are used by a multitude of industries including Aerospace, Education, Finance, Food and Transport.
Exegetic Analytics also offers training, with experienced and knowledgeable facilitators. Our courses focus on practical applications, working through examples and exercises based on real-world datasets.
All of our training packages include access to:
- our online development environment and
- detailed course material which participants will have continued access to even once the training has concluded.
For more information about what we do, you can refer to our website.
These are some of the companies who have benefitted from our trainning:
Take a look at our full list of courses to see what other training we have on offer.
If this proposal is of interest to you or you would like to hear more about what we do you can get in touch on firstname.lastname@example.org or +27 (0)73 805 7439.
2. Course Description
|Who should attend?||The course is aimed at students, academics and professionals who conduct data analysis using other tools like Excel. It’s assumed that participants already have some familiarity with Python.|
|Objectives||Python is a effective tool for working with data. Being able to lay out the steps in an analysis as a script means that the analysis is repeatable and can also be version controlled. One of the first steps in any analysis is the preparation of the data. The Numpy and Pandas packages have a wide range of functionality to aid in the data preparation process.|
|Outcomes||Participants will be able to utilize a core set of functions from Numpy and Pandas to process data.|
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3. Course Outline
This course covers two major packages:
- Numpy — data in arrays and
- Pandas — data in tables.
Almost all Data Analysis or Machine Learning projects will use either one or both of these packages for data manipulation.
- Array fundamentals
- Array creation
- Special arrays
- Data types
- Dimension and shape
- Indexing (slicing and dicing)
- Series and DataFrame objects
- Creating DataFrames
- From dictionaries and lists
- From a file (CSV, XLSX and JSON)
- Manipulating Data Frames
- Column types
- Column names
- Selecting columns
- Hierarchical index
- Filtering rows
- Inserting and manipulating columns
- Time Series data
- Data Layout
- Splitting compound columns
- Dealing with missing data
- Pivoting, Stacking and Joining
- Long versus wide data formats
- Types of joins
- Functional programming
- Mapping functions