Writing & Content
PromptBeginner5 minmarkdown
use_case: Art history dataset
style transfer model training
0
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Writing & Content
PromptBeginner5 minmarkdown
environmental_storytelling: The dusky city street
glowing lights
0
Writing & Content
PromptBeginner5 minmarkdown
use_case: Training data for style transfer AI
art history analysis
0
Writing & Content
PromptBeginner5 minmarkdown
environmental_storytelling: The interaction of shapes and colors—overlapping
intersecting
0
Writing & Content
PromptBeginner5 minmarkdown
environmental_storytelling: The image is a visual pun on the dachshund's long body
exaggerating it to an absurd degree to create a decorative
0
Writing & Content
PromptBeginner5 minmarkdown
use_case: Art history dataset
style transfer model training
2
Writing & Content
PromptBeginner5 minmarkdown
environmental_storytelling: The dusky city street
glowing lights
2
Writing & Content
PromptBeginner5 minmarkdown
use_case: Training data for style transfer AI
art history analysis
0
Writing & Content
PromptBeginner5 minmarkdown
environmental_storytelling: The interaction of shapes and colors—overlapping
intersecting
0
Writing & Content
PromptBeginner5 minmarkdown
environmental_storytelling: The image is a visual pun on the dachshund's long body
exaggerating it to an absurd degree to create a decorative
0
Data
PromptBeginner5 minmarkdown
Ultra-micro Functional Analyst Prompt
Act as a senior functional analyst: work in phases, state all assumptions, preserve existing behaviour, no UML/Gherkin/specs without explicit approval, be direct and analytical.
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Data
PromptBeginner5 minmarkdown
Small Functional Analyst mode
Functional Analyst Mode
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Writing & Content
PromptBeginner5 minmarkdown
- Never rewrite
delete
0
Writing & Content
PromptBeginner5 minmarkdown
- Write clear user stories
acceptance criteria
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Data
PromptBeginner5 minmarkdown
Functional Analyst
Act as a Senior Functional Analyst. Your role prioritizes correctness, clarity, traceability, and controlled scope, following UML2, Gherkin, and Agile/Scrum methodologies. Below are your core principl...
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Data
PromptBeginner5 minmarkdown
Probably the most useful standalone thing here. Source it and run `check_data(df)` on any data frame to get a formatted report of dimensions
NA counts
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Data
PromptBeginner5 minmarkdown
│ ├── statistics.md # Hypothesis tests
distributions
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Data
PromptBeginner5 minmarkdown
│ ├── visualization.md # par
layout
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Data
PromptBeginner5 minmarkdown
│ ├── data-wrangling.md # Subsetting traps
apply family
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Writing & Content
PromptBeginner5 minmarkdown
writeLines(template
out_file)
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Data
PromptBeginner5 minmarkdown
# boxplot(%s ~ %s
data = df
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Writing & Content
PromptBeginner5 minmarkdown
# write.csv(df
%s_clean.csv
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Data
PromptBeginner5 minmarkdown
fit <- lm(%s ~ %s
data = df)
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Data
PromptBeginner5 minmarkdown
# t.test(%s ~ %s
data = df)
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