Coding & Debugging
PromptBeginner5 minmarkdownQuality: 28
Architecture & UI/UX Audit
Act as a senior frontend engineer and product-focused UI/UX reviewer with experience building scalable web applications.
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25,201 skills indexed with the new KISS metadata standard.
Showing 24 of 25,201Categories: Data, Education, Coding & Debugging, Creative
Data
PromptBeginner5 minmarkdownQuality: 28
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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Creative
PromptBeginner5 minmarkdownQuality: 24
Start every task by restating requirements
constraints
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Data
PromptBeginner5 minmarkdownQuality: 24
Small Functional Analyst mode
Functional Analyst Mode
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Data
PromptBeginner5 minmarkdownQuality: 28
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 minmarkdownQuality: 28
Probably the most useful standalone thing here. Source it and run check_data(df) on any data frame t...
NA counts
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Data
PromptBeginner5 minmarkdownQuality: 24
│ ├── visualization.md # par
layout
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Data
PromptBeginner5 minmarkdownQuality: 24
│ ├── statistics.md # Hypothesis tests
distributions
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Data
PromptBeginner5 minmarkdownQuality: 24
│ ├── data-wrangling.md # Subsetting traps
apply family
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Coding & Debugging
PromptBeginner5 minmarkdownQuality: 28
I'm a political science PhD candidate who uses R regularly but would never call myself an R person....
without ggplot2
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Data
PromptBeginner5 minmarkdownQuality: 24
boxplot(%s ~ %s
data = df
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Data
PromptBeginner5 minmarkdownQuality: 24
fit_aov <- aov(%s ~ %s
data = df)
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Data
PromptBeginner5 minmarkdownQuality: 24
t.test(%s ~ %s
data = df)
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Data
PromptBeginner5 minmarkdownQuality: 24
fit <- lm(%s ~ %s
data = df)
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Data
PromptBeginner5 minmarkdownQuality: 24
if (is.null(datafile)) datafile <- paste0(project_name
.csv)
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Data
PromptBeginner5 minmarkdownQuality: 24
check_data <- function(df
topnlevels = 8) {
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Data
PromptBeginner5 minmarkdownQuality: 24
saveRDS(df
data_clean.rds)
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Data
PromptBeginner5 minmarkdownQuality: 24
fitaov <- aov(outcomevar ~ group_var
data = df)
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Data
PromptBeginner5 minmarkdownQuality: 24
t.test(outcomevar ~ groupvar
data = df)
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Data
PromptBeginner5 minmarkdownQuality: 24
abline(lm(outcome_var ~ predictor
data = df)
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Data
PromptBeginner5 minmarkdownQuality: 24
df <- read.csv(your_data.csv
stringsAsFactors = FALSE)
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Coding & Debugging
PromptBeginner5 minmarkdownQuality: 24
- arrows: code = 1 (head at start)
code = 2 (head at end
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Data
PromptBeginner5 minmarkdownQuality: 24
- Formula interface: `pairs(~ var1 + var2 + var3
data = df)`.
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Data
PromptBeginner5 minmarkdownQuality: 24
- Formula interface: `cor.test(~ x + y
data = df) — note the ~` with no LHS.
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