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I'm quite a beginner with R and I'm playing round with some deprivation data which I've read into a DataFrame in the following form:

   FeatureCode DateCode Measurement              Units Value `DCLG Homelessness Acceptances Ratio Concept Scheme`
   <chr>          <dbl> <chr>                    <lgl> <dbl> <chr>                                               
 1 E06000021      2017. Homelessness-Acceptances NA     0.47 Acceptances per thousand households                 
 2 E06000021      2016. Homelessness-Acceptances NA     0.35 Acceptances per thousand households                 
 3 E06000021      2018. Homelessness-Acceptances NA     0.51 Acceptances per thousand households                 
 4 E06000021      2019. Homelessness-Acceptances NA     0.49 Acceptances per thousand households                 
 5 E06000022      2012. Homelessness-Acceptances NA     0.43 Acceptances per thousand households                 
 6 E06000022      2011. Homelessness-Acceptances NA     0.64 Acceptances per thousand households                 
 7 E06000022      2013. Homelessness-Acceptances NA     0.64 Acceptances per thousand households                 
 8 E06000022      2016. Homelessness-Acceptances NA     0.51 Acceptances per thousand households                 
 9 E06000023      2011. Homelessness-Acceptances NA     0.6  Acceptances per thousand households                 
10 E06000023      2014. Homelessness-Acceptances NA     0.71 Acceptances per thousand households      
11 E06000023      2013. Homelessness-Acceptances NA     0.71 Acceptances per thousand households      
12 E06000023      2015. Homelessness-Acceptances NA     0.71 Acceptances per thousand households

This is just a snippet of the data. Now what I want to do is create a new DataFrame that has a named row for each unique value of FeatureCode and a column for each unique value of DateCode, and the DataFrame is then filled with the corresponding Value.

So the end result I want is something like:

           2011. 2012. 2013. 2014. 2015. 2016. 2017. 2018. 2019.
           <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
E06000021     NA    NA    NA    NA    NA   0.35  0.47  0.51  0.49
E06000022   0.64  0.43  0.64    NA    NA   0.51    NA    NA    NA
E06000023   0.6     NA  0.71  0.71  0.71     NA    NA    NA    NA

I don't really know where to start, can anyone help? Thanks

FinnIK
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  • Oops, messed up my first comment. `tidyr::pivot_wider(your_data, id_cols = FeatureCode, names_from = DateCode, values_from = Value)` should do it. – Gregor Thomas Oct 27 '22 at 01:46

0 Answers0