`binData.Rd`

Bin a variable and calculate mean an uncertainties in mean

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

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. |

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

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.

# 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() # }