dataprep: data preprocessing and plots"

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
library(dataprep)
library(ggplot2)
library(scales)

Figure 1. Line plots for variables with names that are essentially numeric and logarithmic

# Descriptive statistics
descplot(data,5,65)

Figure 2. Line plots for variables whose names are essentially numeric and logarithmic

# Selected descriptive statistics, equal to descdata(data,5,65,c('na','min','max','IQR'))
descplot(data,5,65,c(2,7:9))

Figure 3. Bar charts for the type of variable names that is character

# Descriptive statistics
descplot(data1,3,7)+
  ggplot2::theme(axis.text.x=ggplot2::element_text(angle=30,hjust=1,vjust=1.1))

Figure 4. Bar charts for the type of variable names that is character

# Selected descriptive statistics, equal to descplot(data1,3,7,c('min','max','IQR'))
descplot(data1,3,7,7:9)+
  ggplot2::theme(axis.text.x=ggplot2::element_text(angle=30,hjust=1,vjust=1.1))

Figure 5. Particle number size distributions in logarithmic scales

# Top and bottom percentiles
percplot(data,5,65,4)

Figure 6. Particle number size distributions in logarithmic scales with only one part

# Top percentiles
percplot(data,5,65,4,part=1)

Figure 7. Particle number size distributions in logarithmic scales with only one part

# Bottom percentiles
percplot(data,5,65,4,part=0)

Figure 8. Percentiles of modes in linear scales

# Top and bottom percentiles
percplot(data1,3,7,2)+
  ggplot2::theme(axis.text.x=ggplot2::element_text(angle=30,hjust=1,vjust=1.1))

Figure 9. Percentiles of modes in linear scales with only one part

# Top percentiles
percplot(data1,3,7,2,part=1)+
  ggplot2::theme(axis.text.x=ggplot2::element_text(angle=30,hjust=1,vjust=1.1))

Figure 10. Percentiles of modes in linear scales with only one part

# Bottom percentiles
percplot(data1,3,7,2,part=0)+
  ggplot2::theme(axis.text.x=ggplot2::element_text(angle=30,hjust=1,vjust=1.1))


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dataprep documentation built on July 4, 2021, 5:06 p.m.