Data Science Desktop Survival Guide by Graham Williams
Desktop Survival Project Home Preface Data Science Introducing R R Constructs R Tasks R Strings R Read, Write, and Create Data Template Data Exploration Data Wrangling Data Visualisation Statistics ML Template ML Scenarios ML Activities ML Applications ML Algorithms Cluster Analysis Decision Trees Computer Vision Graph Data Privacy Literate Data Science Coding with Style Resources Bibliography Index

CLICK HERE TO VISIT THE UPDATED SURVIVAL GUIDE

Random Observations

20180721 It is also useful to review some random observations from the dataset to provide a little more insight. Here we use dplyr::sample_n() to randomly select six rows from the dataset.

# Review a random sample of observations.

sample_n(ds, size=6) %>% print.data.frame()

##         date      location min_temp max_temp rainfall evaporation sunshine
## 1 2011-12-30  PerthAirport     18.0     31.6      0.0         7.8     10.9
## 2 2010-05-09    Townsville     16.0     27.3      0.0         6.4      4.4
## 3 2017-06-29 NorfolkIsland     14.0     19.2      0.0         3.0       NA
## 4 2012-06-18        Cairns     16.5     26.5      0.0         6.2      9.5
## 5 2020-01-18 SydneyAirport     18.2     22.8     14.0         3.2      0.0
## 6 2015-02-14          Sale     18.5     23.0     15.6          NA       NA
##   wind_gust_dir wind_gust_speed wind_dir_9am wind_dir_3pm wind_speed_9am
## 1           WSW              35            N          WSW              9
## 2            SE              41          SSW           SE              9
## 3           SSE              30          SSE           SE             17
....