The method
Use this prompt set to deeply explore datasets. Start by providing a dataset, then use the prompts sequentially for analysis, visualization, and insight generation. Adapt the prompts to specify data columns and desired analysis types for optimal results.
The prompts
Prompt 1
I have the following dataset (provide data in CSV format or a link to a data source): [Insert Dataset Here]. Please provide a summary of the dataset including the data types of each column, the number of missing values in each column, and basic descriptive statistics (mean, median, standard deviation, min, max) for numerical columns.
Prompt 2
Based on the dataset summary, identify potential relationships or trends between variables. Generate a list of 5-7 relevant research questions that could be explored further with this dataset. For each research question, suggest appropriate statistical tests or visualization techniques that could be used to investigate it.
Prompt 3
Choose one of the research questions you identified in the previous step: [Insert Research Question Here]. Perform the suggested statistical test or create the suggested visualization to explore this question. Provide a detailed explanation of the results, including any limitations of the analysis and potential biases.
Prompt 4
Based on your analysis, what are the key insights or findings from this dataset? Summarize these findings in a concise and actionable manner. Suggest 3-5 potential business implications or recommendations based on these insights. Consider different stakeholder perspectives (e.g., marketing, sales, product development).
Prompt 5
Generate code (in Python with libraries like pandas, matplotlib, and seaborn) to reproduce the data cleaning, analysis, and visualization steps you performed. Ensure the code is well-documented and easy to understand. Provide clear instructions on how to run the code and interpret the results.