Data
PromptBeginner5 minmarkdown
- `rbind` on data frames matches columns **by name**
not position. Missing columns get `NA`.
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Data
PromptBeginner5 minmarkdown
- `cbind` on data frames calls `data.frame(...)`
not `cbind.matrix`. Mixing matrices and data frames can give unexpected results.
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Data
PromptBeginner5 minmarkdown
- Default `by` is `intersect(names(x)
names(y))` — can silently merge on unintended columns if data frames share column names.
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Data
PromptBeginner5 minmarkdown
- Returns an **array** (not a data frame). Class info on return values is **discarded** (e.g.
Date objects become numeric).
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Data
PromptBeginner5 minmarkdown
- On a **data frame**
`apply` coerces to matrix via `as.matrix` first — mixed types become character.
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Data
PromptBeginner5 minmarkdown
- `subset` argument uses **non-standard evaluation** — column names are resolved in the data frame
which can silently pick up wrong variables in programmatic use. Use `[` with explicit logic in functions.
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Data
PromptBeginner5 minmarkdown
- Matrix indexing a data frame (`df[cbind(i
j)]`) coerces to matrix first — avoid.
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Data
PromptBeginner5 minmarkdown
- Data frame `[` with single column: `df[
1]` returns a **vector** (drop=TRUE default for columns)
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Coding & Debugging
PromptBeginner5 minmarkdown
- Factor indexing: `x[f]` uses integer codes of factor `f`
not its character labels. Use `x[as.character(f)]` for label-based indexing.
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Data
PromptBeginner5 minmarkdown
- `ts(data
start
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Data
PromptBeginner5 minmarkdown
- `relist(flesh
skeleton)` — `flesh` is the flat data
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Data
PromptBeginner5 minmarkdown
- Useful pattern: `do.call(rbind
list_of_dfs)` to combine a list of data frames.
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Data
PromptBeginner5 minmarkdown
- **io-and-text.md** — Read when: read.table silently drops data or misparses columns
regex behaves differently than expected
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Data
PromptBeginner5 minmarkdown
- **visualization.md** — Read when: par settings reset unexpectedly
layout/mfrow interaction is confusing
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Data
PromptBeginner5 minmarkdown
- **statistics.md** — Read when: hypothesis test gives surprising result
need to choose correct p.adjust method
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Data
PromptBeginner5 minmarkdown
- **data-wrangling.md** — Read when: subsetting returns wrong type
apply on data frame gives unexpected coercion
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Data
PromptBeginner5 minmarkdown
fit <- aov(value ~ group
data = df)
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Data
PromptBeginner5 minmarkdown
fit <- lm(y ~ x1 + x2
data = df)
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Data
PromptBeginner5 minmarkdown
predict(fit
newdata = new_df)
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Data
PromptBeginner5 minmarkdown
boxplot(value ~ group
data = df
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Data
PromptBeginner5 minmarkdown
saveRDS(obj
data.rds)
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Data
PromptBeginner5 minmarkdown
df <- read.table(data.txt
header = TRUE
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Data
PromptBeginner5 minmarkdown
df <- read.csv(data.csv
stringsAsFactors = FALSE)
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Data
PromptBeginner5 minmarkdown
aggregate(value ~ group
data = df
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