ddply for regression in R

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I'm I have a data frame that contains an 'output', average temperature, humidity, and time (given as 24 factors, not continuous) data for 100 cities (given by codes). I want to apply a regression formula to predict the output for each city based on the temperature, humidity, and time data. I hope to get 100 different regression models. I used the ddply function and came up with the following line of code with help from this thread.

df = ddply(data, "city", function(x) coefficients(lm(output~temperature+humidity, data=x)))

This code works for the numeric data, temperature and humidity. But when I add in the time zone factor data (which is 23 factor variables) I get an error:

df = ddply(data, "city", function(x) coefficients(lm(output~temperature+humidity+time, data=x)))

"Error: contrasts can be applied only to factors with 2 or more levels"

Does anyone know why this is? Here is an example chunk of my data frame:

city    temperature   humidity   time
 11        51            34        01  
 11        43            30        02  
 11        55            50        03  
 11        64            54        10  
 22        21            52        11  
 22        43            65        04  
 22        51            66        09  
 22        51            78        16  
 05        45            70        01  
 05        51            54        10 

So I would want three models for the three cities here, based on temperature, humidity, and the time factor.

asked 28 secs ago

Ore M

6

ddply for regression in R