In this post, I will describe how to import data from CSV and Excel files into R. First, I prepared my two sample datasets, one as a CSV and the other as an Excel file on my personal computer. Download: csv file and Excel file.
Preparing the dataset is a primary step to import the data fast and efficiently. Therefore, there are some practices we all need to follow to avoid issues while importing :
The missing values in the data set need to be indicated with NA.
It is best to avoid blank spaces between words; instead, we can use “_” to connect them; otherwise, R will identify them as different variables.
Use short words and try to avoid symbols.
So, once I have my dataset saved in CSV and Excel file in my desktop, I start importing it into R. You should also know the file path in your pc because it is needed when writing down the code.
Let's start loading the 'readr' package.
library("readr")
read_csv("sample1.csv")
## # A tibble: 18 x 6
## Seq_Number Gender Age Ethnicity Blood_Pressure Diabetes
## <dbl> <chr> <dbl> <chr> <dbl> <chr>
## 1 1 M 32 Mexican_American 110 yes
## 2 2 M 35 Black 120 no
## 3 3 F 30 White 135 yes
## 4 4 M 37 Other 127 no
## 5 5 F 37 Multiracial 100 no
## 6 6 M 33 Black 105 no
## 7 7 M 34 Black 140 yes
## 8 8 M 38 Other 100 no
## 9 9 F 36 White 105 no
## 10 10 F 31 Mexican_American 120 no
## 11 11 F 35 White 130 yes
## 12 12 M 38 Mexican_American 140 yes
## 13 13 F 33 White 90 no
## 14 14 M 39 Black 98 no
## 15 15 M 40 Other 99 no
## 16 16 F 40 Mexican_American 100 no
## 17 17 F 32 White 105 no
## 18 18 M 37 Black 110 no
Meanwhile, for the excel file I load the 'readxl' library and then the code as below:
library("readxl")
read_excel("sample1.xlsx")
## # A tibble: 18 x 6
## Seq_Number Gender Age Ethnicity Blood_Pressure Diabetes
## <dbl> <chr> <dbl> <chr> <dbl> <chr>
## 1 1 M 32 Mexican_American 110 yes
## 2 2 M 35 Black 120 no
## 3 3 F 30 White 135 yes
## 4 4 M 37 Other 127 no
## 5 5 F 37 Multiracial 100 no
## 6 6 M 33 Black 105 no
## 7 7 M 34 Black 140 yes
## 8 8 M 38 Other 100 no
## 9 9 F 36 White 105 no
## 10 10 F 31 Mexican_American 120 no
## 11 11 F 35 White 130 yes
## 12 12 M 38 Mexican_American 140 yes
## 13 13 F 33 White 90 no
## 14 14 M 39 Black 98 no
## 15 15 M 40 Other 99 no
## 16 16 F 40 Mexican_American 100 no
## 17 17 F 32 White 105 no
## 18 18 M 37 Black 110 no
Hope it is helpful!