10.38 Numeric
20180723 Summaries of numeric data are provided using base::summary(). In the following we identify the numeric variables and summarise each. In doing so, as a data scientist, we want to again observe any oddities and to explain them.
ds %>%
sapply(is.numeric) %>%
which() %>%
names %T>%
print() ->
numi## [1] "min_temp" "max_temp" "rainfall" "evaporation"
## [5] "sunshine" "wind_gust_speed" "wind_speed_9am" "wind_speed_3pm"
## [9] "humidity_9am" "humidity_3pm" "pressure_9am" "pressure_3pm"
## [13] "cloud_9am" "cloud_3pm" "temp_9am" "temp_3pm"
## [17] "risk_mm"ds[numi] %>%
summary()## min_temp max_temp rainfall evaporation
## Min. :-8.70 Min. :-4.10 Min. : 0.000 Min. : 0.00
## 1st Qu.: 7.50 1st Qu.:18.10 1st Qu.: 0.000 1st Qu.: 2.80
## Median :12.00 Median :22.80 Median : 0.000 Median : 4.80
## Mean :12.15 Mean :23.36 Mean : 2.241 Mean : 5.53
## 3rd Qu.:16.90 3rd Qu.:28.40 3rd Qu.: 0.600 3rd Qu.: 7.40
## Max. :33.90 Max. :48.90 Max. :474.000 Max. :133.90
## NA's :2349 NA's :2105 NA's :4318 NA's :86289
## sunshine wind_gust_speed wind_speed_9am wind_speed_3pm
## Min. : 0.00 Min. : 2.00 Min. : 0.00 Min. : 0.00
## 1st Qu.: 4.90 1st Qu.: 31.00 1st Qu.: 7.00 1st Qu.:13.00
## Median : 8.50 Median : 39.00 Median :13.00 Median :19.00
## Mean : 7.66 Mean : 40.19 Mean :14.05 Mean :18.72
## 3rd Qu.:10.60 3rd Qu.: 48.00 3rd Qu.:19.00 3rd Qu.:24.00
## Max. :14.50 Max. :135.00 Max. :87.00 Max. :87.00
## NA's :93859 NA's :13036 NA's :2924 NA's :5434
## humidity_9am humidity_3pm pressure_9am pressure_3pm
## Min. : 0.00 Min. : 0.00 Min. : 979.1 Min. : 978.9
## 1st Qu.: 56.00 1st Qu.: 35.00 1st Qu.:1013.1 1st Qu.:1010.6
## Median : 69.00 Median : 51.00 Median :1017.7 Median :1015.3
## Mean : 68.22 Mean : 50.68 Mean :1017.8 Mean :1015.3
## 3rd Qu.: 83.00 3rd Qu.: 65.00 3rd Qu.:1022.5 3rd Qu.:1020.1
## Max. :100.00 Max. :100.00 Max. :1041.1 Max. :1040.1
## NA's :3423 NA's :6523 NA's :19267 NA's :19254
## cloud_9am cloud_3pm temp_9am temp_3pm
## Min. :0.00 Min. :0.00 Min. :-6.20 Min. :-5.10
## 1st Qu.:1.00 1st Qu.:2.00 1st Qu.:12.30 1st Qu.:16.70
## Median :5.00 Median :5.00 Median :16.80 Median :21.30
## Mean :4.52 Mean :4.54 Mean :17.02 Mean :21.82
## 3rd Qu.:7.00 3rd Qu.:7.00 3rd Qu.:21.60 3rd Qu.:26.60
## Max. :9.00 Max. :9.00 Max. :40.20 Max. :48.20
## NA's :73113 NA's :78265 NA's :2445 NA's :5536
## risk_mm
## Min. : 0.000
## 1st Qu.: 0.000
## Median : 0.000
## Mean : 2.244
## 3rd Qu.: 0.600
## Max. :474.000
## NA's :4317Reviewing this information we can make some obvious observations. Temperatures, for example, appears to be in degrees Celsius rather than Fahrenheit. Rainfall looks like millimetres. There are some quite skewed distributions with min and median small but large max values. As data scientists we will further explore the distributions as in Chapter 9.
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