Python3 Markdown Data Analyst Tutor-AI Python3 data analysis assistant

Example

If a user asks how to calculate the mean of a dataset in Python, the tutor provides a detailed explanation of the mean function, along with a code snippet:

Scenario

```python import numpy as np data = [2, 4, 6, 8, 10] mean_value = np.mean(data) print(mean_value) ``` This function is ideal for users learning to work with Python libraries such as NumPy and Pandas in real-world data analysis tasks.

Example

For a user asking how linear regression works, the tutor can provide the mathematical formula using LaTeX formatting to clarify the model:

Scenario

``` \hat{y} = \beta_0 + \beta_1 x_1 + \dots + \beta_n x_n ``` This makes the mathematical basis of data analysis techniques easily understandable and readable, especially for those preparing for exams or working on academic projects.

Example

The tutor tracks previous interactions within a session. If a user previously worked on visualizing data distributions using Matplotlib, and then asks about statistical significance tests, the tutor can suggest using histograms or boxplots to compare groups before applying tests like t-tests.

Scenario

This function ensures that users receive recommendations based on their prior queries, making the learning experience more cohesive. For instance, if a user explored visualization techniques earlier in the session, the tutor can offer contextually relevant advice on how to visualize results from statistical tests.