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similarityMat

Example data for `MetCirc`: `similarityMat`

Bundled with MetCirc · exported, loads via data()

Class
matrix
Dimensions
259 × 259
Missing
259
Format
rda · xz
version 2 · 239 KB
File
data/similarityMat.RData
Fingerprint
0a3711bf
About this object
A run with a dimA block of cells folded into columns that share their edges, with empty slots above the columns, because a name here is hung on the whole block and not on one column.

One vector with a dim attribute. Everything in it shares a type, which is the difference between a matrix and a data.frame that happens to be all numeric. R object catalogue

Values

Computed over every cell in the object, reading it as one vector.

numeric
Cells
67,081
Missing
259
Min.
0
1st Qu.
0.00952567
Median
0.0426128
Mean
0.107523
3rd Qu.
0.121239
Max.
1
Std. dev
0.170288
Distinct
26,144
Skewness
2.777
Kurtosis
8.462
Zeros
1,958 2.9%
Outliers
6,974 0 low · 6974 high
Longest missing run
1
Margins

The mean of each row, and of each column, summarised. Reading every cell as one vector gives a matrix and its transpose the same answer; these do not.

MarginMin.1st Qu.MedianMean3rd Qu.Max.Std. dev
Rows0.00236330.0723110.11160.107520.144030.201180.04732
Columns0.00236330.0723110.11160.107520.144030.201180.04732

The row means and the column means vary by a similar amount, so neither margin carries the structure on its own.

Dimensions and labels
MarginLabelsCount
Rows1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, …259
Columns1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, …259
Columns

This object is 259 columns wide. A matrix carries no per-column schema, so its width is what the catalogue records and there is nothing to list one column at a time. What it holds is described whole instead, summarised over every cell: see Values and Margins above.

Version history
VersionReleasedRows × ColsChangeStored asConfidence
3.232026-04-28259 × 259Unchangedrda · xz
version 2 · 239 KB
exact
3.222025-10-29259 × 259Unchangedrda · xz
version 2 · 239 KB
exact
3.212025-04-15259 × 259Unchangedrda · xz
version 2 · 239 KB
exact
3.202024-10-29259 × 259Unchangedrda · xz
version 2 · 239 KB
exact
3.192024-04-30259 × 259Unchangedrda · xz
version 2 · 239 KB
exact
3.182023-10-24259 × 259Unchangedrda · xz
version 2 · 239 KB
exact
3.172023-04-25259 × 259Unchangedrda · xz
version 2 · 239 KB
exact
3.162022-11-01259 × 259Unchangedrda · xz
version 2 · 239 KB
exact
3.152022-04-26259 × 259Unchangedrda · xz
version 2 · 239 KB
exact
3.142021-10-26259 × 259Unchangedrda · xz
version 2 · 239 KB
exact
3.132021-05-19259 × 259Unchangedrda · xz
version 2 · 239 KB
exact
3.122020-10-27259 × 259Unchangedrda · xz
version 2 · 239 KB
exact
3.112020-04-27259 × 259Unchangedrda · xz
version 2 · 239 KB
exact
3.102019-10-29259 × 259Data changed
Dimensions 352 × 352 → 259 × 259 · Missing 0 → 259 · Distinct 21,400 → 26,144 · Value summary
rda · xz
version 2 · 239 KB
exact
3.92019-05-02352 × 352Unchangedrda · xz
version 2 · 220 KB
exact
3.82019-01-04352 × 352Unchangedrda · xz
version 2 · 220 KB
exact
3.72018-04-30352 × 352Unchangedrda · xz
version 2 · 220 KB
exact
3.62017-10-30352 × 352Unchangedrda · xz
version 2 · 220 KB
exact
3.52017-04-24352 × 352Data changed
Value summary
rda · xz
version 2 · 220 KB
exact
3.42016-12-20352 × 352rda · gzip
version 2 · 516 KB
exact

Dimensions is the row and column count. Missing is how many values were recorded as absent. Distinct is how many different values were counted in the object. Value summary is the six-number summary of the values and their spread.

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