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 |
n |
The number of intervals to split |
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
Returns a summarised data frame with new columns for the mean and upper / lower 95 percent 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)