File data handling - No7

Last few posts, I spent most of time explaining how to generate data and how to manipulate data by using different functions such as matrix, data frame or Vector.

However, In reality, we get a raw data from database or files. 

In this post, I will show you one of the the simplest ways to handle raw data file.
and I will cover database connection later.

I think, most of people are MS excel user. 

Probably, you also have various raw data which come from diverse data source.

Looked at from that point of view, collecting meaningful raw data might be the beginning of your data analysis.  

In this lesson, I will assume that we have a meaningful excel data requires further data analysis.

[ Excel data is just like this ] 

Tree	age	circumference
1	118	30
1	484	58
1	664	87
1	1004	115
1	1231	120
1	1372	142
1	1582	145
2	118	33
2	484	69
2	664	111
2	1004	156
2	1231	172
2	1372	203
2	1582	203
3	118	30
3	484	51
3	664	75
3	1004	108
3	1231	115

You can save your excel data into CSV file on your local computer.

Then you can read the CSV file on R console and  assign data to variable.

> OrangeTree <- read.csv("D:/R/Download/OrangeTree.csv" )

> OrangeTree

   Tree  age circumference

1     1  118            30

2     1  484            58

3     1  664            87

4     1 1004           115

5     1 1231           120

6     1 1372           142

7     1 1582           145

8     2  118            33

9     2  484            69

10    2  664           111

* Assume that CSV file location is "D:\R\Download\OrangeTree.csv"

It seems like that  output data format is data frame.

You can add conditional formula.

> OrangeTree[age>1500,]

   Tree  age circumference

7     1 1582           145

14    2 1582           203

21    3 1582           140

28    4 1582           214

35    5 1582           177

Try it with your excel data.