Data Science Desktop Survival Guide by Graham Williams
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Party Tree

The party package can be used to draw rpart decision trees using as.party() from partykit which can be installed from R-Forge:

install.packages("partykit", repos="http://R-Forge.R-project.org")
library(partykit)

class(model)

## [1] "rpart"

plot(as.party(model))

The textual presentation of an rpart decision tree can also be improved using party.

print(as.party(model))

## 
## Model formula:
## rain_tomorrow ~ rain_today + temp_3pm + temp_9am + cloud_3pm + 
##     cloud_9am + pressure_3pm + pressure_9am + humidity_3pm + 
##     humidity_9am + wind_speed_3pm + wind_speed_9am + wind_dir_3pm + 
##     wind_dir_9am + wind_gust_speed + wind_gust_dir + sunshine + 
##     evaporation + rainfall + max_temp + min_temp
## 
## Fitted party:
## [1] root
## |   [2] humidity_3pm < 72.5: No (n=105547, err=14.1%)
## |   [3] humidity_3pm >= 72.5
## |   |   [4] humidity_3pm < 83.5
## |   |   |   [5] rainfall < 2.7
## |   |   |   |   [6] wind_gust_speed < 47: No (n=5118, err=33.8%)
....