Use case 01
The dataset contains one or more date or timestamp columns.
Data ScientistFeature EngineeringBeginnerSingle prompt
Date Feature Extraction AI Prompt
This prompt turns raw date and datetime columns into practical model-ready features. It is useful when temporal information exists but has not yet been decomposed into parts that models can learn from easily. It also encourages creation of interval features when multiple time columns exist.
Prompt text
Extract all useful features from the date and datetime columns in this dataset. For each date column, create: - year, month, day, day_of_week (0=Monday), day_of_year - quarter, week_of_year - is_weekend (boolean) - is_month_start, is_month_end (boolean) - is_quarter_start, is_quarter_end (boolean) - days_since_epoch (numeric, for ordinal encoding) - If the column is a datetime: hour, minute, part_of_day (morning/afternoon/evening/night) Also compute time-difference features if multiple date columns exist: - days_between_[col1]_and_[col2] for all meaningful pairs Return the feature creation code in pandas and a list of all new column names created.
When to use this prompt
Use case 02
You want fast, leakage-safe temporal feature extraction in pandas.
Use case 03
You need a complete list of standard calendar features without missing important ones.
Use case 04
You want reproducible feature code rather than only conceptual suggestions.
What the AI should return
Pandas code that creates all relevant date-derived columns, a clear list of every new feature generated, and notes on any pairwise time-difference features created from multiple date columns.
How to use this prompt
1
Open your data context
Load your dataset, notebook, or working environment so the AI can operate on the actual project context.
2
Copy the prompt text
Use the copy button above and paste the prompt into the AI assistant or prompt input area.
3
Review the output critically
Check whether the result matches your data, assumptions, and desired format before moving on.
4
Chain into the next prompt
Once you have the first result, continue deeper with related prompts in Feature Engineering.
Frequently asked questions
What does the Date Feature Extraction prompt do?+
It gives you a structured feature engineering starting point for data scientist work and helps you move faster without starting from a blank page.
Who is this prompt for?+
It is designed for data scientist workflows and marked as beginner, so it works well as a guided starting point for that level of experience.
What type of prompt is this?+
Date Feature Extraction is a single prompt. You can copy it as-is, adapt it, or use it as one step inside a larger workflow.
Can I use this outside MLJAR Studio?+
Yes. The prompt text works in other AI tools too, but MLJAR Studio is the best fit when you want local execution, visible Python code, and reusable notebooks.
What should I open next?+
Natural next steps from here are Embedding Features from Text, Feature Ideas Generator, Feature Selection.