Please note: A number of learners have reported issues with the software and quizzes within this course. We will be carrying out a review and updating the material.Software and data make the world go round. Learn programming, to analyse and visualise open data, with this free course, Learn to code for data analysis. This course will teach you how to write your own computer programs, one line of code at a time. You'll learn how to access open data, clean and analyse it, and produce visualisations. You will also learn how to write up and share your analyses, privately or publicly. You'll code in Python, a widely used programming language across all disciplines. You will write up analyses and do coding exercises using the popular Jupyter Notebooks platform, which allows you to see immediately the result of running your code and helps you identify – and fix – any errors more easily. You will also look at real data from the World Health Organisation, the World Bank and other organisations. TranscriptEnrollingon the course will give you the opportunity to earn an Open University digitalbadge. Badges are not accredited by The Open University but they're a great wayto demonstrate your interest in the subject and commitment to your career, andto provide ofcontinuing professional development. Once you're signed in, you can manage your digital badges online from My OpenLearn. In addition you can download and print your OpenLearn Statement of Participation – which also displays your Open University badge.The Open University would really appreciate a few minutes of your time to tell us about yourself and your expectations for the course before you begin, in our optional start-of-course survey. Once you complete the course we would also value your feedback and suggestions for future improvement, in our optional end-of-course survey. Participation will be completely confidential and we will not pass on your details to others.This course is accredited by the CPD Standards Office. It can be used to provide evidence of continuing professional development and on successful completion of the course you will be awarded 24 CPD points. Evidence of your CPD achievement is provided on the free Statement of Participation awarded on completion.Anyone wishing to provide evidence of their enrolment on this course is able to do so by sharing their Activity Record on their OpenLearn Profile, which is available before completion of the course and earning of the Statement of Participation.
Overview
Syllabus
- Introduction and guidance
- Introduction and guidance
- What is a badged course?
- How to get a badge
- Acknowledgements
- Week1Week 1: Having a go at it Part 1
- Introduction
- 1 Install the software
- 1.1 Start with a question
- 1.2 Variables and assignments
- 1.3 The art of naming
- 1.4 Downloading the notebook and trying the first exercise
- 1.5 Expressions
- 1.6 Functions
- 1.7 Comments
- 1.8 Values have units
- 2 This week’s quiz
- 3 Summary
- Acknowledgements
- Week2Week 2: Having a go at it Part 2
- 1 Enter the pandas
- 1.1 This week’s data
- 1.2 Loading the data
- 1.3 Selecting a column
- 1.4 Calculations on a column
- 1.5 Sorting on a column
- 1.6 Calculations over columns
- 2 Writing up the analysis
- 2.1 Practice project
- 2.2 Sharing your project notebook
- 3 This week’s quiz
- 4 Summary
- 4.1 Week 1 and 2 glossary
- Acknowledgements
- Week3Week 3: Cleaning up our act Part 1
- Introduction
- 1 Weather data
- 1.1 What is a CSV file?
- 1.2 Dataframes and the ‘dot’ notation
- 1.3 Getting and displaying dataframe rows
- 1.4 Getting and displaying dataframe columns
- 1.5 Comparison operators
- 1.6 Bitwise operators
- 2 This week’s quiz
- 3 Summary
- Acknowledgements
- Week4Week 4: Cleaning up our act Part 2
- 1 Loading the weather data
- 1.1 Removing rogue spaces
- 1.2 Removing extra characters
- 1.3 Missing values
- 1.4 Changing the value types of columns
- 2 Every picture tells a story
- 2.1 Changing a dataframe’s index
- 2.2 The project
- 3 This week’s quiz
- 4 Summary
- 4.1 Week 4 glossary
- Acknowledgements
- Week5Week 5: Combine and transform data Part 1
- Introduction
- 1 Life expectancy project
- 1.1 Creating the data
- 1.2 Defining functions
- 1.3 What if...?
- 1.4 Applying functions
- 2 This week’s quiz
- 3 Summary
- Acknowledgements
- Week6Week 6: Combine and transform data Part 2
- 1 Joining left, right and centre
- 1.1 Constant variables
- 1.2 Getting real
- 1.3 Cleaning up
- 1.4 Joining and transforming
- 2 Correlation
- 2.1 Scatterplots
- 2.2 My project
- 3 This week’s quiz
- 4 Summary
- 4.1 Weeks 5 and 6 glossary
- Acknowledgements
- Week7Week 7: Further techniques Part 1
- Introduction
- 1 I spy with my little eye
- 1.1 Ways of grouping data
- 1.2 Data that describes the world of trade
- 1.3 Exploring the world of export data
- 1.4 Getting data from the Comtrade API
- 1.5 Practice getting data
- 2 This week’s quiz
- 3 Summary
- Acknowledgements
- Week8Week 8: Further techniques Part 2
- 1 The split-apply-combine pattern
- 1.1 Splitting a dataset by grouping
- 1.2 Looking at apply and combine operations
- 1.3 Summary operations
- 1.4 Filtering groups
- 2 Pivot tables
- 2.1 Pivot tables in pandas
- 2.2 Looking at the milk and cream trade
- 2.3 Your project
- 3 This week’s quiz
- 4 Summary
- 4.1 Week 7 and 8 glossary
- 4.2 What next?
- Tell us what you think
- Acknowledgements
