data1: Example data (aggregated particle number concentrations,...

In dataprep: Fast, Efficient, and Versatile Data Preprocessing and Reshaping with 'C++', 'OpenMP' & 'SIMD'

Example data (aggregated particle number concentrations, SMEAR I Varrio forest)

Description

An already-aggregated seven-column version of data. The 61 size bins of the raw size distribution have been collapsed into three log-normal modes (nucleation, Aitken, accumulation) plus two total concentrations (tconc, TPNC). The dataset covers the same two-month window as data (January and July 2020) and is intended for read-only demos.

Usage

data1

Format

A data frame with 7,640 observations on the following 7 variables.

date

a POSIXct vector, sampling time (10-minute resolution).

monthyear

a character vector, e.g. "January 2020".

Nucleation

a numeric vector, number concentration in the nucleation mode (nominally 3–25 nm).

Aitken

a numeric vector, number concentration in the Aitken mode (nominally 25–100 nm).

Accumulation

a numeric vector, number concentration in the accumulation mode (nominally 100–1000 nm).

tconc

a numeric vector, total number concentration.

TPNC

a numeric vector, total particle number concentration.

Details

Unlike data, which is the raw size-resolved table, data1 contains only mode-integrated values. The three integrated values can remain non-zero even when the smallest raw size bins (1 through 2) are entirely NA in the two-month subset. It has:

• very few missing values,

• no long consecutive missing runs,

• no obvious outliers.

Because of this, data1 is not a useful input for the cleaning pipeline (varidele, obsedele, condextr, shorvalu, dataprep): those steps have nothing to remove on an already-clean table. It is intended for demos that only read the data:

• descdata / descplot — descriptive statistics and plots,

• percdata / percplot — percentile summaries,

• na_diagnose — missing-value diagnostics,

• data_report — compact quality report.

Use data for anything that modifies values.

Source

https://smear.avaa.csc.fi/download

References

Liang, C.-S., Wu, H., Li, H.-Y., Zhang, Q., Li, Z. & He, K.-B. (2020). Efficient data preprocessing, episode classification, and source apportionment of particle number concentrations. Science of the Total Environment, 741, 140923. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.scitotenv.2020.140923")}

Examples

data1

dim(data1)
names(data1)

# The three log-normal modes and the two total concentrations
summary(data1[, 3:7])

# A quick look at how the modes relate to the totals
cor(data1[, 3:7], use = "complete.obs")

# data1 has very few missing values compared with the raw size bins
colMeans(is.na(data1))

# For a read-only descriptive plot
if (interactive()) {
  descplot(data1, cols = 3:7)
}

dataprep documentation built on Oct. 1, 2026, 5:07 p.m.