End-to-End Survey Data Simulation and Analysis on TSSFL Technology Stack

[Eli]

Summary

• Generate Sample Pre- and Post-Intervention Survey Data using Python on the TSSFL Technology Stack
• Test and Analyze Survey Datasets with the Survey Insights Generator on TSSFL Technology Stack

Hi everyone,

I’d like to share a simple Python script that generates mock data for pre- and post-intervention surveys. This can be useful for anyone working on research, program evaluation, or simulations where realistic survey data is needed for testing or demonstration purposes.

Survey Setup

• Number of Respondents: 100
• Number of Questions: 16
• Response Options (Likert Scale):
  
  • Strongly Disagree
  • Disagree
  • Somewhat Agree
  • Agree
  • Strongly Agree

Each question is treated as a column, and each respondent occupies a row in the dataset.

Output

The script generates four files:

• pre_survey.xlsx
• post_survey.xlsx
• pre_survey.csv
• post_survey.csv

These files contain randomly generated responses simulating answers before and after an intervention.


Python Script

Code: [Select all] [Expand/Collapse]

1. import pandas as pd
2. import numpy as np
3.  
4. #Define parameters
5. num_questions = 16
6. num_respondents = 100
7. response_options = ["Strongly Disagree", "Disagree", "Somewhat Agree", "Agree", "Strongly Agree"]
8.  
9. # Generate column names for questions
10. question_columns = [f"Q{i+1}" for i in range(num_questions)]
11.  
12. # Generate random responses for pre and post surveys
13. pre_survey_data = pd.DataFrame({
14.     question: np.random.choice(response_options, size=num_respondents)
15.     for question in question_columns
16. })
17.  
18. post_survey_data = pd.DataFrame({
19.     question: np.random.choice(response_options, size=num_respondents)
20.     for question in question_columns
21. })
22.  
23. # Save to Excel and CSV files
24. pre_survey_data.to_excel("pre_survey.xlsx", index=False)
25. post_survey_data.to_excel("post_survey.xlsx", index=False)
26. pre_survey_data.to_csv("pre_survey.csv", index=False)
27. post_survey_data.to_csv("post_survey.csv", index=False)

Feel free to adapt the script to your specific use case - such as changing the number of respondents or using a custom set of questions.

You can generate the dataset by running the Python code at AI-Assisted Live Programming and Computing with Python, R, Sage, Octave, Maxima, Singular, Gap, GP, HTML & Macaulay2

And test the datasets with our app - Survey Insights Generator.

Let me know if you have any questions or suggestions!