Reshape data from long to wide format - more than one variable
I’m trying to reshape my data from long to wide formula using the dcast function from reshape2.
The objective is to use different variables in the value.var parameter but R doesn't let me use more than one value in it.
Is there any other way I could fix it? I've looked at other similar questions but I haven't been able to find a similar examples.
Here is my current dataset:
+---------+------+--------+--------------+------------+
| Country | Year | Growth | Unemployment | Population |
+---------+------+--------+--------------+------------+
| A | 2015 | 2 | 8.3 | 40 |
| B | 2015 | 3 | 9.2 | 32 |
| C | 2015 | 2.5 | 9.1 | 30 |
| D | 2015 | 1.5 | 6.1 | 27 |
| A | 2016 | 4 | 8.1 | 42 |
| B | 2016 | 3.5 | 9 | 32.5 |
| C | 2016 | 3.7 | 9 | 31 |
| D | 2016 | 3.1 | 5.3 | 29 |
| A | 2017 | 4.5 | 8.1 | 42.5 |
| B | 2017 | 4.4 | 8.4 | 33 |
| C | 2017 | 4.3 | 8.5 | 30 |
| D | 2017 | 4.2 | 5.2 | 30 |
+---------+------+--------+--------------+------------+
My objective is to pass year column to the rest of the columns (growth, unemployment and population). I’m using the below dcast function.
data_wide <- dcast(world, country ~ year,
value.var=c("Growth","Unemployment","Population"))
Ideal outcome
+---------+-------------+-------------------+-----------------+-------------+-------------------+-----------------+
| Country | Growth_2015 | Unemployment_2015 | Population_2015 | Growth_2016 | Unemployment_2016 | Population_2016 |
+---------+-------------+-------------------+-----------------+-------------+-------------------+-----------------+
| A | 2 | 8.3 | 40 | 4 | 8.1 | 42 |
| B | 3 | 9.2 | 32 | 3.5 | 9 | 32.5 |
| C | 2.5 | 9.1 | 30 | 3.7 | 9 | 31 |
| D | 1.5 | 6.1 | 27 | 3.1 | 5.3 | 29 |
+---------+-------------+-------------------+-----------------+-------------+-------------------+-----------------+
Answer
If you're not married to a dcast solution, I personally find tidyr easier.
library(tidyr)
df <- df %>%
gather(key, value, -Country, -Year) %>%
unite(new.col, c(key, Year)) %>%
spread(new.col, value)
Result
Country Growth_2015 Growth_2016 Growth_2017 Population_2015 Population_2016 Population_2017 Unemployment_2015 Unemployment_2016 Unemployment_2017
1 A 2.0 4.0 4.5 40 42.0 42.5 8.3 8.1 8.1
2 B 3.0 3.5 4.4 32 32.5 33.0 9.2 9.0 8.4
3 C 2.5 3.7 4.3 30 31.0 30.0 9.1 9.0 8.5
4 D 1.5 3.1 4.2 27 29.0 30.0 6.1 5.3 5.2
This works by
Stacking all values into one column...
Combining variable name and year columns into a single column...
The new column is then spread into wide format