Go to TogaWare.com Home Page. Data Science Desktop Survival Guide
by Graham Williams
Duck Duck Go

Data Glimpse

20200317 Another useful tool to quickly review the dataset is dplyr::glimpse(). Data from all columns is presented, including the first observations of the individual columns.

glimpse(ds)
## Rows: 176,747
## Columns: 24
## $ Date          <date> 2008-12-01, 2008-12-02, 2008-12-03, 2008-12-04, 2...
## $ Location      <chr> "Albury", "Albury", "Albury", "Albury", "Albury", ...
## $ MinTemp       <dbl> 13.4, 7.4, 12.9, 9.2, 17.5, 14.6, 14.3, 7.7, 9.7, ...
## $ MaxTemp       <dbl> 22.9, 25.1, 25.7, 28.0, 32.3, 29.7, 25.0, 26.7, 31...
## $ Rainfall      <dbl> 0.6, 0.0, 0.0, 0.0, 1.0, 0.2, 0.0, 0.0, 0.0, 1.4, ...
## $ Evaporation   <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA...
## $ Sunshine      <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA...
## $ WindGustDir   <ord> W, WNW, WSW, NE, W, WNW, W, W, NNW, W, N, NNE, W, ...
## $ WindGustSpeed <dbl> 44, 44, 46, 24, 41, 56, 50, 35, 80, 28, 30, 31, 61...
## $ WindDir9am    <ord> W, NNW, W, SE, ENE, W, SW, SSE, SE, S, SSE, NE, NN...
## $ WindDir3pm    <ord> WNW, WSW, WSW, E, NW, W, W, W, NW, SSE, ESE, ENE, ...
## $ WindSpeed9am  <dbl> 20, 4, 19, 11, 7, 19, 20, 6, 7, 15, 17, 15, 28, 24...
## $ WindSpeed3pm  <dbl> 24, 22, 26, 9, 20, 24, 24, 17, 28, 11, 6, 13, 28, ...
## $ Humidity9am   <int> 71, 44, 38, 45, 82, 55, 49, 48, 42, 58, 48, 89, 76...
## $ Humidity3pm   <int> 22, 25, 30, 16, 33, 23, 19, 19, 9, 27, 22, 91, 93,...
## $ Pressure9am   <dbl> 1007.7, 1010.6, 1007.6, 1017.6, 1010.8, 1009.2, 10...
## $ Pressure3pm   <dbl> 1007.1, 1007.8, 1008.7, 1012.8, 1006.0, 1005.4, 10...
## $ Cloud9am      <int> 8, NA, NA, NA, 7, NA, 1, NA, NA, NA, NA, 8, 8, NA,...
## $ Cloud3pm      <int> NA, NA, 2, NA, 8, NA, NA, NA, NA, NA, NA, 8, 8, 7,...
## $ Temp9am       <dbl> 16.9, 17.2, 21.0, 18.1, 17.8, 20.6, 18.1, 16.3, 18...
## $ Temp3pm       <dbl> 21.8, 24.3, 23.2, 26.5, 29.7, 28.9, 24.6, 25.5, 30...
## $ RainToday     <fct> No, No, No, No, No, No, No, No, No, Yes, No, Yes, ...
## $ RISK_MM       <dbl> 0.0, 0.0, 0.0, 1.0, 0.2, 0.0, 0.0, 0.0, 1.4, 0.0, ...
## $ RainTomorrow  <fct> No, No, No, No, No, No, No, No, Yes, No, Yes, Yes,...

Notice the style used for variable names here. Different datasets will use different styles. It is useful to convert the variable names (and the levels of a factor) to a canonical form across all of the dataset that we deal with and so avoid having to remember particular naming schemes. We do this next.


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