R: Bin data, calculate mean and bootstrap 95% confidence...

binData {openair} | R Documentation

## Bin data, calculate mean and bootstrap 95% confidence interval in the mean

### Description

Bin a variable and calculate mean an uncertainties in mean

### Usage

    binData(mydata, bin = "nox", uncer = "no2", n = 40, interval = NA, breaks = NA)

### Arguments

`mydata` | Name of the data frame to process.
`bin` | The name of the column to divide into intervals
`uncer` | The name of the column for which the mean, lower and upper uncertainties should be calculated for each interval of `bin`.
`n` | The number of intervals to split `bin` into.
`interval` | The interval to be used for binning the data.
`breaks` | User specified breaks to use for binning.

### Details

This function summarises data by intervals and calculates the mean and bootstrap 95% confidence intervals in the mean of a chosen variable in a data frame. Any other numeric variables are summarised by their mean intervals.

There are three options for binning. The default is to bon `bin` into 40 intervals. Second, the user can choose an binning interval e.g. `interval = 5`. Third, the user can supply their own breaks to use as binning intervals.

### Value

Retruns a summarised data frame with new columns for the mean and upper / lower 95% confidence intervals in the mean.

### Examples

    # how does nox vary by intervals of wind speed?
    results <- binData(mydata, bin = "ws", uncer = "nox")

    # easy to plot this using ggplot2
    ## Not run:
    library(ggplot2)
    ggplot(results, aes(ws, mean, ymin = min, ymax = max)) +
    geom_pointrange()

    ## End(Not run)

[Package openair version 2.8-5 Index]