Merging tables using R
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The document explains how to merge datasets in R using the merge() function, including various types of joins such as inner, outer, left outer, and right outer joins. It provides practical examples of each type of join using specific R code to demonstrate how to load, merge, and view datasets based on a common key. The document emphasizes the versatility of the merge() function in data manipulation and mentions future topics on handling missing values.
Merging tables using R
- 2. Just like any other join functions in apache hive, pig, sql, excel. R also comes with the feature of joining two or more datasets using the same universal join concepts: Inner join Outer join – Left outer join, right outer join and full outer join Inner join: is also known as equijoin which returns rows when there is a match in both the tables of the dataset based on a common key or a value. #load the dataset >join1<-read.csv(join1.csv, header = TRUE) >join2<-read.csv(join2.csv, header = TRUE) #join the two tables based on Transcation_ID >joined<-merge(x=join1,y=join2,by="Transaction_ID") >View(joined) Joins: Inner and Outer
- 3. Full outer join: returns all the rows from both the tables irrespective of any match between the tables. In other words it means it will join even if there is no match in the common key. Example: >joined_full<-merge(x=join1,y=join2,by="Transaction_ID“, all = TRUE); >View(joined_full) Full Outer Join ID Name Dept. 202 Bob Eng. 203 Vika Admin 207 Ryan IT 209 Paul IT ID Name Dept. 202 Bob Eng. 203 Vika Admin 204 Chris Med. 205 Robin Med. ID Name Dept. 202 Bob Eng. 203 Vika Admin 204 Chris Med. 205 Robin Med. 206 Ryan IT 209 Paul IT ID Based on Rupak Roy
- 4. Left outer join returns all the rows of left table and only the matching rows of the right table. For example: #to apply left outer join set all.x = TRUE >joined_left<-merge(x=join1,y=join2, by="Transaction_ID", all.x = TRUE) >View(joined_left) Left Outer Join ID Name Dept. 202 Bob Eng. 203 Vika Admin 207 Ryan IT 209 Paul IT ID Name Dept. 202 Bob Eng. 203 Vika Admin 204 Chris Med. 205 Robin Med. ID Name Dept. 202 Bob Eng. 203 Vika Admin 206 Ryan IT 209 Paul IT ID Based on Rupak Roy
- 5. Right outer join is the opposite of left join. It returns all the rows of right table and only the matching rows of the left table. For example: #to apply right outer join set all.y = TRUE >joined_right<-merge(x=join1,y=join2, by="Transaction_ID", all.y = TRUE) >View(joined_right) Right Outer Join ID Name Dept. 202 Bob Eng. 203 Vika Admin 207 Ryan IT 209 Paul IT ID Name Dept. 202 Bob Eng. 203 Vika Admin 204 Chris Med. 205 Robin Med. ID Name Dept. 202 Bob Eng. 203 Vika Admin 204 Chris Med. 205 Robin Med. ID Based on Rupak Roy
- 6. Merge() is one of the important function to join different datasets. To know more about the functions of merge() use ?merge Merging Tables Rupak Roy
- 7. Next: We will see how to impute the missing values. Merging tables Rupak Roy