ChatGPT Prompts for Data Science

The ChatGPT model is a large language model trained by OpenAI that is capable of generating human-like text. By providing it with a prompt, it can generate responses that continue the conversation or expand on the given prompt.
In this repository, you will find prompts that can be used with ChatGPT for data science purposes. It is curated by Travis Tang.
To get started, simply use the prompts below as input for ChatGPT. Replace everything in [squarebrackets] with your own to achieve results specific to your use case.
You can also view the collated prompts (including screenshots of ChatGPT's response) as a PDF here
Adapted from the Awesome ChatGPT repo for Data Science.
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Table of Contents:
1. Write python
2. Explain code
3. Optimize code
4. Format code
5. Translate code from one language to another
6. Explain concepts
7. Suggest ideas
8. Troubleshoot problem
9. Write SQL
10. Write other Code
11. Misc
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WRITE PYTHON
1. Train Classification Model
> Prompt: I want you to act as a data scientist and code for me. I have a dataset of [describe dataset]. Please build a machine learning model that predicts [target variable].
2. Automatic Machine Learning
> Prompt: I want you to act as an automatic machine learning (AutoML) bot using TPOT for me. I am working on a model that predicts [...]. Please write Python code to find the best classification model with the highest AUC score on the test set.
3. Tune Hyperparameter
> Prompt: I want you to act as a data scientist and code for me. I have trained a [model name]. Please write the code to tune the hyperparameters.
4. Explore Data
> Prompt: I want you to act as a data scientist and code for me. I have a dataset of [describe dataset]. Please write code for data visualisation and exploration.
5. Generate Data
> Prompt: I want you to act as a fake data generator. I need a dataset that has x rows and y columns: [insert column names]
6. Write Regex
> Prompt: I want you to act as a coder. Please write me a regex in Python that [describe regex]
7. Train Time Series
> Prompt: I want you to act as a data scientist and code for me. I have a time series dataset [describe dataset]. Please build a machine learning model that predicts [target variable]. Please use [time range] as train and [time range] as validation.
8. Address Imbalance Data
> Prompt: I want you to act as a coder. I have trained a machine learning model on an imbalanced dataset. The predictor variable is the column [Insert column name]. In Python, how do I oversample and/or undersample my data?
9. Get Feature Importance
> Prompt: I want you to act as a data scientist and explain the model's results. I have trained a decision tree model and I would like to find the most important features. Please write the code.
10. Visualize Data with Matplotlib
> Prompt: I want you to act as a coder in Python. I have a dataset [name] with columns [name]. [Describe graph requirements]
11. Visualize Image Grid Matplotlib
> Prompt: I want you to act as a coder. I have a folder of images. [Describe how files are organised in directory] [Describe how you want images to be printed]
12. Explain Model with Lime
> Prompt: I want you to act as a data scientist and explain the model's results. I have trained a [library name] model and I would like to explain the output using LIME. Please write the code.
13. Explain Model with Shap
> Prompt: I want you to act as a data scientist and explain the model's results. I have trained a scikit-learn XGBoost model and I would like to explain the output using a series of plots with Shap. Please write the code.
14. Write Multithreaded Functions
> Prompt: I want you to act as a coder. Can you help me parallelize this code across threads in Python?
15. Compare Function Speed
> Prompt: I want you to act as a software developer. I would like to compare the efficiency of two algorithms that performs the same task in Python. Please write code that helps me run an experiment that can be repeated for 5 times. Please output the runtime and other summary statistics of the experiment. [Insert functions]