When programming market research surveys in Python, researchers without a background in coding can benefit from using AI tools like ChatGPT to troubleshoot, refine, and even create code. Whether you’re trying to fix an existing snippet or start a section of code from scratch, ChatGPT can provide step-by-step guidance to help you reach your desired outcome. This article explores how researchers can leverage ChatGPT to simplify Python programming tasks.
Why Use ChatGPT for Survey Programming?
For those new to Python, writing or debugging code can seem daunting. With ChatGPT, however, you can access a “programming assistant” that can clarify syntax, fix errors, and guide you through code updates. ChatGPT enables you to:
Diagnose Issues: Ask questions about existing code and receive detailed feedback on errors.
Write Code from Scratch: Generate new code to meet specific survey needs, like adding term points or defining custom logic.
Save Time: Reduce repetitive testing by asking ChatGPT for the optimal way to achieve specific functions.
Fixing Existing Code with ChatGPT
Scenario 1: Troubleshooting a Section of Existing Code
Let’s say you have a section of Python code for a survey question that isn’t working as expected. You want it to work in a specific way, but you aren’t sure how to update it. Here’s an example of how ChatGPT can help.
Example Code with an Issue
python
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# Code to terminate respondents who don’t select "Streaming services"
video_devices = s.multi_select_question(
question="Which of the following ways do you watch TV/video? Please select all that apply.",
options=[
"Streaming services",
"TV Apps",
"Cable Provider",
"Antenna",
"NextGen TV",
"Satellite Service",
],
randomize=True,
other_options=["None of the above"],
)
s.terminate_if("Streaming services" not in video_devices,
reason="Sorry, this survey is only for people who watch streaming services."
)
Here, you notice that most respondents are being terminated in the testing environment because simulated responses don’t often select “Streaming services.” To prevent this, you want “Streaming services” to be a default selection. By setting a response as a default, you ensure your reports with simulated data are accurate and usable for quality assurance and that all variables are captured for reporting in the platform.
Using ChatGPT for Help
You could ask ChatGPT:
"How do I modify this code to set 'Streaming services' as the default selection to prevent excessive terminations?"
ChatGPT may suggest an updated version of the code:
python
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video_devices = s.multi_select_question(
question="Which of the following ways do you watch TV/video? Please select all that apply.",
options=[
"Streaming services",
"TV Apps",
"Cable Provider",
"Antenna",
"NextGen TV",
"Satellite Service",
],
default=["Streaming services"],
randomize=True,
other_options=["None of the above"],
)
s.terminate_if("Streaming services" not in video_devices,
reason="Sorry, this survey is only for people who watch streaming services."
)
By adding the default selection, you simulate a more realistic distribution, which helps prevent excessive terminations and ensures that your survey logic functions as expected.
Writing New Code from Scratch with ChatGPT
Scenario 2: Adding Term Points to a Survey Question
Suppose you’re adding a term point from scratch that was missing in the survey word document. You’re not sure how to write the termination logic in Python and add it to the existing question structure.
Using ChatGPT for Help
You could ask:
"How do I write python code that terminates respondents who don’t select 'Streaming services' for this question about TV viewing habits? <insert question>"
ChatGPT may provide you with the following:
python
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# Define the multi-select question
video_devices = s.multi_select_question(
question="Which of the following ways do you watch TV/video? Please select all that apply.",
options=[
"Streaming services",
"TV Apps",
"Cable Provider",
"Antenna",
"NextGen TV",
"Satellite Service",
],
randomize=True,
other_options=["None of the above"],
)
# Add termination logic based on their selection
s.terminate_if("Streaming services" not in video_devices,
reason="This survey is only for people who watch streaming services."
)
This example shows how ChatGPT can guide you from start to finish when implementing specific logic in your survey. ChatGPT helps make complex functions—like adding term points or skips—more manageable, even for researchers with little Python experience.
Best Practices for Using ChatGPT in Survey Programming
Here are some tips to make the most out of using ChatGPT for your survey programming:
Be Specific: Clearly describe what you’re trying to achieve. Providing context helps ChatGPT generate more accurate and relevant code suggestions.
Ask Follow-Up Questions: If the initial response doesn’t fully solve your issue, ask follow-up questions for clarification or further code refinement.
Review, Test, and Iterate As Needed: Always test any code generated by ChatGPT to ensure it performs as expected, especially if it involves complex survey logic.
Conclusion
Using ChatGPT to assist with programming market research surveys in Python can save time and help you produce accurate, functional surveys. Whether you’re troubleshooting existing code or starting from scratch, ChatGPT can guide you through essential coding tasks, allowing you to focus on designing impactful surveys rather than getting stuck in technical details.