Replacing missing values with mean in R
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The document discusses a method for replacing missing values in a dataset using R, specifically by substituting missing values in the 'time' and 'sec' columns with their respective means. It includes detailed steps for importing the dataset and executing the replacement in R Studio. The document also provides a reference link to the dataset used.
![Detailed Steps
1. Read DataSet
samplehousing <- read.csv("~/Desktop/samplehousing.csv")
2. View DataSet
view(samplehousing)
3. Replace missing values in time column with mean
samplehousing$time[is.na(samplehousing$time)] <- mean(samplehousing$time, na.rm = TRUE)
4. Replace missing values in time column with mean
samplehousing$sec[is.na(samplehousing$sec)] <- mean(samplehousing$sec, na.rm = TRUE)](https://image.slidesharecdn.com/replacingmissingvalueswithmean-161008140302/85/Replacing-missing-values-with-mean-in-R-6-320.jpg)
Replacing missing values with mean in R
- 1. Replacing Missing Values With mean Sarith Divakar M Research Scholar, CUSAT [email protected]
- 2. Sample DataSet X id y time sec 1 1 1 1 2 1 2 6 1 3 1 2 12 4 1 2 24 1 5 2 1 1 6 2 2 6 7 2 2 12 1 8 2 1 24 1 9 3 0 1 10 3 2 6 1 11 3 2 12 1 12 3 2 24 13 4 1 1
- 3. Import DataSet in R Studio
- 4. Imported DataSet- NA for missing Values
- 5. Replaced time with mean of the column
- 6. Detailed Steps 1. Read DataSet samplehousing <- read.csv("~/Desktop/samplehousing.csv") 2. View DataSet view(samplehousing) 3. Replace missing values in time column with mean samplehousing$time[is.na(samplehousing$time)] <- mean(samplehousing$time, na.rm = TRUE) 4. Replace missing values in time column with mean samplehousing$sec[is.na(samplehousing$sec)] <- mean(samplehousing$sec, na.rm = TRUE)