Python Data Analysis Course
Python for data analysis
In this course, we cover Python packages that are commonly used for data analysis. These packages include handling CSV files, importing data, Numpy (‘Numerical Python'), SciPy (used for scientific and technical computing ) and Pandas (data analysis library) . You would learn to code and execute simple data analysis programs in Python. Learn to use powerful extensions available in Python. You would learn to manipulate large and varied datasets by getting hands-on, practical experience working on real-life data problems on anonymized data sets. You would gain working knowledge of a few of the most commonly used Python modules, used by data scientists.
Python Coding Basics
Who Should attend?
The course is useful for professionals who anyone who use data as part of their work and who need to draw analysis from the data. It is best to already have an understanding of programming.
What are 'modules' and how can they be useful for data analysis tasks
Reading and writing CSV files in to a Python program: The CSV module
Identifying and fixing errors in datasets.
Python data analysis with Python Pandas:
Dataframes, Indexing, Iteration, Functions, Group by and aggregation, merge/join. Comparison with SQL.
Python data analysis with The Python NumPy Module:
Working with arrays, array manipulation, string, math, arithmetic and statistical functions.
Introduction and overview of SciPy.
The basics of plotting data graphs using Python MatPlotLib.
What is included in this Python Data Analysis Course:
Python Data Course Certificate on completion (assessment based)
Python Data Course notes
Practical Python Data Course exercises, Python Data Course Homework / Python Data Course Revision work
Bring your own laptop, or make arrangements beforehand to use ours
Tea, coffees, but no lunch
After the course, 1 free, online session forquestions or revision on the Python Data Course.
Max group size on this Python Data Course is 4.