Python for Data Analysis

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Course Description

This Python training course offers a short but intensive hands-on introduction to the use of Python and the most popular data analytics packages and how to apply this to pre-process, shape, model and visualize data.
This is a very hands on course where participants will spend the majority of their time importing data stored in various formats (csv, excel, json) stored in a variety of locations (files, web sites and databases).

 

Course Outline

DAY 1

Morning

Introduction to Anaconda Navigator
•    Cells & Cell Types, Checkpoints, Help
•    Magic commands
•    Downloading

Python for the Data Scientist
Basics
•    Maths expressions
•    Packages
•    Variables
•    Strings

Flow Control (if, if/else)
•    If
•    nested if
•    If-else
•    Doing nothing
•    Is a value in a set of values
•    Is a value in a range of values

Collections
•    Lists, Tuples, Sets, Dictionaries
•    Loops & Iteration –
     While, For, For loops in a Range, Unconditional Loops, For else loops
•    Comprehensions

Functions
•    User Defined Functions
•    Named parameters
•    Default Parameters

Afternoon

Introduction to Data Science
•    Shaping data

• Intro to Pandas

• Import data into a DataFrame

• Rows, Columns, Indexes

•    Modelling Data

• Intro to numpy

• Vector arithmetic

Visualizing Data

• Intro to Matplotlib

• Figures, Axes, Plotting Data

Use Case – Calculating & Displaying Moving averages and standard deviations

Introduction to Pandas
•    Rows & Columns, adding, removing
•    Filtering Data
•    Sorting Data & Sorting Indexes
•    Multi Indexes & Cross Sections

DAY 2

Morning
    Introduction to Data Visualization

•     Anatomy of a Figure, axes, plots and subplots
•     How to use matplotlib, seaborn, pandas and plotly

Time Series Analysis
•    Structure of a DateTimeIndex
•    Date ranges & Frequencies
•    Shifting Dates
•    Resampling Data - Up Sampling and Down Sampling
•    Rolling, Moving and Expanding windows
•    Aggregating by Time

Afternoon
Advanced Pandas
•    Merging Data
•    Joins
•    Grouping and Aggregating
•    Multi-part indexes
•    Cross Sections
•    Categorical Data
•    Pivot Tables
•    Formatting Data

Data Pre-processing
•    Missing Data
•    Data Transformation & Imputers
•    Cutting Data
•    Transforming Continuous Data to Categorical Data

 

DAY 3

Morning
Financial Calculations
•    Built in statistical Functions
•    Calculating Pay Offs
•    Normalized prices, log of returns, MACD
•    Correlation & Covariance
•    Measuring run Time Performance

Introduction to statsmodels
•    Statistical Distributions
•    OLS
•    Confidence intervals and p-values
•    Regression analysis

Afternoon
Scripting and Process Automation
•    The os package
•    The re package
•    Working with pdf documents

Scripting and Process Automation
•    Use python to create a powerpoint presentation
•    Using REST APIs

 

Learning Path

There are many Python training options you can consider. Here are some suggestions, though please don't hesitate to call us if you would like to discuss.

 

• Introduction to Python 3
• Automating with Python
• Big Data Analysis with Python
• Data Wrangling with Python
• Data Science Projects with Python
• Introduction to Python and PySpark Development
• Advanced Python Development

Ways to Attend

Currently this course is only available as a live online delviery.

Prior to covid-19 restrictions, we deliver this course either on or off-site in various regions around the world, and can customise your delivery to suit your exact business needs. Talk to us about how we can fine-tune a course to suit your team's current skillset and ultimate learning objectives.