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19,395 skills indexed with the new KISS metadata standard.

Showing 24 of 19,395Categories: Productivity, Communication, Data, Coding & Debugging
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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Data
PromptBeginner5 minmarkdownQuality: 28

- Default kernel: gaussian. Range of density extends beyond data range (controlled by cut

default 3 bandwidths).

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Data
PromptBeginner5 minmarkdownQuality: 28

- Default bandwidth: bw = nrd0 (Silverman's rule of thumb). For multimodal data

consider SJ or bcv.

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Data
PromptBeginner5 minmarkdownQuality: 24

- Returns a matrix of p-values

not test statistics.

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Data
PromptBeginner5 minmarkdownQuality: 28

- For composite hypotheses (parameters estimated from data)

p-values are conservative (too large). Use dgof or ks.test with exact = NULL for discrete distributions.

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