Python for Data Analytics

For data analytics tasks to affect business decisions they must be driven by a business question. This section will formally outline how to move an analytics project through key phases of development from business question to business solution. Delegates will be able:

to describe and understand the general analytics process.

to describe and understand the different types of analytics can be used to derive data driven solutions to business

to apply that knowledge to their business context

This section will cover the basics of writing R programs. Topics covered will include:

What is Python?

Using Anaconda

Writing Python programs

Expressions and objects

Functions and arguments

Basic Python programming conventions

This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include:

Vectors

Arrays and matrices

Factors

Lists

Data frames

Loading .csv files into Python

This section will look at loading data from other sources into Python. Topics covered will include:

Loading .csv files into a pandas data frame

Connecting to and loading data from a database into a panda data frame

This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include:

Filtering data

Deriving new fields

Aggregating data

Joining data sources

Connecting to external data sources

This section will explain how Python can be used to perform basic descriptive. Topics covered will include:

Summary statistics

Grouped summary statistics

Using descriptive analytics to assess data quality

Using descriptive analytics to created business report

Using descriptive analytics to conduct exploratory analysis

This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include:

Significance tests

Correlation

Linear regressions

Using statistical output to create better business decisions.

This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include:

Creating different chart types such as bar charts, box plots, histograms and line plots

Formatting charts

This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.