The Code Interpreter tool lets mentorAI run Python code in-chat and display the resulting graphs, charts, tables, and other visualizations instantly. It’s ideal for math, statistics, data analysis, and any scenario where seeing the data makes concepts clearer—such as integrals, functions, distributions, or real-world datasets—directly alongside the explanation.
Student
Ask mentorAI to plot functions, integrals, histograms, bar charts, scatterplots, and more. Visuals appear directly below the AI’s response.
mentorAI safely runs Python code behind the scenes, enabling calculations, filtering, aggregation, and visualization without leaving the chat.
Before executing, mentorAI restates your request (e.g., “Plot the integral of x² from 1 to 100”) so you can confirm it understood correctly.
After rendering a visualization, mentorAI explains what you’re seeing—highlighting trends, key values, comparisons, or anomalies.
Upload spreadsheets or datasets (CSV, Excel, etc.) and ask mentorAI to:
- Analyze the data
- Generate charts
- Summarize patterns
- Extract specific records
When datasets contain sensitive information, mentorAI follows privacy guardrails—automatically anonymizing or omitting restricted fields when generating outputs.
For certain requests, mentorAI can generate CSV outputs you can download and review outside the platform.
In the mentor sidebar, confirm Code Interpreter is toggled On.
Type a prompt in the chat, such as:
”Plot the integral of x² from 1 to 100.”
The AI echoes your request to confirm understanding, for example:
“Sure — plotting ∫ x² dx from 1 to 100.”
mentorAI runs the code and displays the visualization directly in the chat.
Beneath the output, mentorAI explains what the graph or table represents and why it matters.
You can ask follow-up prompts such as:
”Add gridlines.”
”Zoom into x = 1 to 10.”
”Overlay y = x³ for comparison.”
mentorAI updates the visualization accordingly.
Use the file upload option to provide a dataset, such as a spreadsheet containing incident reports, lab results, or survey data.
For example:
“Show me a graph of the campuses with the most incidents reported.“
mentorAI will:
- Analyze the uploaded data
- Aggregate values as needed
- Render a chart (e.g., bar graph)
- Explain what the chart shows
Sensitive fields are anonymized automatically if required.
You can also request specific subsets of the data, for example:
”Show me all records involving hydrochloric acid.”
In this case, mentorAI may:
- Provide a short executive summary
- Generate a CSV file containing only the relevant records
- Include a download link so you can open the data externally
Plot definite or indefinite integrals, derivatives, and Riemann sums to see area under curves and slope behavior.
Compare multiple functions (e.g., y = sin x vs. y = cos x) on the same axes to study amplitude, period, and phase shifts.
Upload datasets and generate histograms, box plots, bar charts, or scatterplots to analyze distributions and correlations.
Graph experimental data (e.g., projectile motion or lab incident frequency) and fit trend lines or models to validate hypotheses.
Explore real institutional or research datasets—summarizing trends, identifying outliers, and extracting specific records.
Replicate textbook graphs or lab figures to verify understanding or test “what-if” scenarios.
With Code Interpreter enabled, you can move seamlessly from raw data or abstract equations to clear visuals, summaries, and downloadable results—all inside mentorAI.