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== tidyr Package ==
== tidyr Package ==
http://vita.had.co.nz/papers/tidy-data.pdf
http://vita.had.co.nz/papers/tidy-data.pdf
<source lang="rsplus">
<source lang="rsplus">
# gather()
# gather()
If we have a dataset with multiple variables stored in one column, for example:<br />
If we have a dataset with multiple variables stored in one column, for example:<br />
grade, male_1, female_1, male_2, female_2, are colums storing grades for two diferent classes.
grade, male_1, female_1, male_2, female_2, are colums storing grades for two diferent classes.
<source lang="rsplus">
<source lang="rsplus">
res <- gather(students2, sex_class, count, -grade)
res <- gather(students2, sex_class, count, -grade)
2 Sally final C <NA> C <NA> <NA></nowiki>
2 Sally final C <NA> C <NA> <NA></nowiki>
This code will tidy the data:
<source lang="rsplus">
students3 %>%
gather(class, grade, class1:class5, na.rm = TRUE) %>%
print
</source>
spread()<br />
Spreads a colum into its variables.
<source lang="rsplus">
students3 %>%
gather(class, grade, class1:class5, na.rm = TRUE) %>%
spread(test, grade) %>%
print
</source>
To change the values from clas1, clas2... to 1, 2...
<source lang="rsplus">
<source lang="rsplus">
students3 %>%
students3 %>%
gather(class, grade, class1:class5, na.rm = TRUE) %>%
gather(class, grade, class1:class5, na.rm = TRUE) %>%
spread(test, grade) %>%
mutate(class= extract_numeric(class)) %>%
print
print
</source>
</source>