Training activity information
Details
Retrieve data from a REST application programming interfaces (API) and manipulate to create dataframes in both python 3 (pandas) and R
Type
Developmental training activity (DTA)
Evidence requirements
Evidence the activity has been undertaken by the trainee​.
Reflection on the activity at one or more time points after the event including learning from the activity and/or areas of the trainees practice for development.
An action plan to implement learning and/or to address skills or knowledge gaps identified.
Considerations
- REST APIs
- Data provenance
- Quantitative data normalisation e.g., log transformation
- Cleaning and tidying data
- Transforming/reshaping a dataframe
Reflective practice guidance
The guidance below is provided to support reflection at different time points, providing you with questions to aid you to reflect for this training activity. They are provided for guidance and should not be considered as a mandatory checklist. Trainees should not be expected to provide answers to each of the guidance questions listed.
Before action
- What knowledge of REST APIs, data structures (dataframes), Python (pandas), and R do you need before starting?
- What specific skills in data retrieval and manipulation using APIs and creating dataframes do you hope to gain? What aspects of this task are new to you?
- Will you review documentation for the API you will be using, or practice creating dataframes in pandas and R? Have you discussed this activity with your training officer? What challenges do you foresee in accessing or manipulating the data? How do you feel about working with APIs and these programming languages?
In action
- What steps are you taking to retrieve the data from the API? How are you choosing which Python/R libraries or functions to use for data manipulation and dataframe creation? Are you encountering any issues with the API connection or data format?
- Are you successfully retrieving the data? Are you able to create the dataframes as expected? Are there any errors or warnings occurring during the process? What adjustments are you making to your code as you go?
- If you encounter difficulties with one language (Python or R), are you considering alternative approaches in the other? Are you looking up documentation or examples to overcome challenges?
On action
- Summarise the process of retrieving data from the API. What were the key steps involved in manipulating the data to create dataframes in Python (pandas) and R?
- What skills in using REST APIs did you develop or improve? What new techniques or approaches did you learn for data manipulation using pandas and R dataframes? Were there any unexpected challenges encountered during data retrieval or manipulation? What did you learn from these challenges? How did your actions during the activity (your ‘reflect-in-action’) influence the final dataframes you created? How does the ability to retrieve and manipulate data in this way relate to the requirements for post-programme practice in Clinical Bioinformatics?
- What areas for continued development in API interaction or dataframe manipulation have been identified? How can you apply the techniques learned in this activity to future data analysis tasks? What specific actions or ‘next steps’ will you take to further develop your skills in this area? What support or resources might you need to further develop your abilities in API data retrieval and dataframe creation?
Beyond action
- Have you since had to retrieve data from APIs in other contexts? How did your experience with this training activity inform your approach?
- How often do you now use pandas and R for data manipulation? Has the efficiency of your data handling improved since this activity?
- In future projects, how might your ability to retrieve and structure data programmatically contribute to more complex analyses?
Relevant learning outcomes
| # | Outcome |
|---|---|
| # 1 |
Outcome
Arrange and store data for programmatic analysis. |