This is practice by going through the dataset at https://www.kaggle.com/c/shelter-animal-outcomes. The goal is to investigate the outcomes for shelter animals.

## 'data.frame':    26729 obs. of  10 variables:
##  $ AnimalID      : Factor w/ 26729 levels "A006100","A047759",..: 5420 1604 11614 10239 3502 7396 17152 18183 5373 7574 ...
##  $ Name          : Factor w/ 6375 levels ""," Joanie"," Mario",..: 2353 1849 4442 1 1 1837 2763 1 3458 1 ...
##  $ DateTime      : Factor w/ 22918 levels "2013-10-01 09:31:00",..: 3362 351 12682 7191 1234 5022 13873 14619 3214 5210 ...
##  $ OutcomeType   : Factor w/ 5 levels "Adoption","Died",..: 4 3 1 5 5 5 5 5 1 1 ...
##  $ OutcomeSubtype: Factor w/ 17 levels "","Aggressive",..: 1 17 8 14 14 14 14 14 1 13 ...
##  $ AnimalType    : Factor w/ 2 levels "Cat","Dog": 2 1 2 1 2 2 1 1 2 2 ...
##  $ SexuponOutcome: Factor w/ 6 levels "","Intact Female",..: 4 5 4 3 4 2 3 6 5 5 ...
##  $ AgeuponOutcome: Factor w/ 45 levels "","0 years","1 day",..: 7 7 23 27 23 4 27 27 34 7 ...
##  $ Breed         : Factor w/ 1380 levels "Abyssinian Mix",..: 1222 641 1067 641 915 370 641 641 46 365 ...
##  $ Color         : Factor w/ 366 levels "Agouti","Agouti/Brown Tabby",..: 131 168 87 43 275 37 64 105 251 319 ...
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

Exploratory Graphs

Graphs to explore the data and hypothesize on factor causality on outcome of animal (Adoption, Died, Euthanasia, Returned to Ownder, or Transfered) 

## Warning: Removed 18 rows containing non-finite values (stat_boxplot).

## Warning: Removed 18 rows containing non-finite values (stat_boxplot).