I have a data-frame which is df.
id time internet lat lng
103 1 1385913600 14.057844 1 0
247 2 1385913600 14.062213 2 0
391 3 1385913600 14.066863 3 0
535 4 1385913600 14.045190 4 0
679 5 1385913600 12.772210 5 0
823 10 1385913600 8.101804 10 0
I added a new column and put values of all of them 0 by using one of the below methods:
df["cluster"] <- 0
df$cluster <- 0
And then by using my algorithm I changed value of each df$cluster which you can see the method I used to change value of df$cluster:
clusternumber <- clusternumber + 1
df$cluster[df$id == minid] <- clusternumber
At the end I got the result I'm looking but I've faced with a new problem. When I'm trying to get summary of my result I'm getting strange result.
> summary(df)
id internet lat lng cluster
Min. : 1 Min. : 0.00 Min. : 1.00 Min. : 0.00 1 : 121
1st Qu.: 2500 1st Qu.: 15.57 1st Qu.: 25.25 1st Qu.: 25.00 2 : 121
Median : 5000 Median : 36.09 Median : 51.00 Median : 49.50 3 : 121
Mean : 5000 Mean : 75.73 Mean : 50.50 Mean : 49.51 4 : 121
3rd Qu.: 7501 3rd Qu.: 78.88 3rd Qu.: 75.75 3rd Qu.: 75.00 9 : 121
Max. :10000 Max. :6663.23 Max. :100.00 Max. :100.00 15 : 121
(Other):9272
I'm looking to know how do I have to make a new column or change value of a column because now I'm getting this:
> summary(df$cluster)
1 2 3 4 9 15 16 17 34 52 85 147 8 6 7 36
121 121 other(2727)
The output of your summary function clearly shows that the cluster column is factor. Below is a simple example.
# Create an example data frame
dat <- data.frame(Col_f = c("1.1", "1.1", "2.1", "2.1", "3.1", "3.1",
"4.1", "4.1", "4.1"),
Col_n = c(1.1, 1.1, 2.1, 2.1, 3.1, 3.1, 4.1, 4.1, 4.1))
# Check the structure of the data frame
str(dat)
# 'data.frame': 9 obs. of 2 variables:
# $ Col_f: Factor w/ 4 levels "1.1","2.1","3.1",..: 1 1 2 2 3 3 4 4 4
# $ Col_n: num 1.1 1.1 2.1 2.1 3.1 3.1 4.1 4.1 4.1
# Use summary
summary(dat)
# Col_f Col_n
# 1.1:2 Min. :1.100
# 2.1:2 1st Qu.:2.100
# 3.1:2 Median :3.100
# 4.1:3 Mean :2.767
# 3rd Qu.:4.100
# Max. :4.100
Notice that in Col_f summary function simply reports the number in each level.
To convert the factor to numeric, You may want to convert the column to character first, then convert to numeric. Here is an example.
# Convert the column of factor to numeric
dat$Col_fn <- as.numeric(as.character(dat$Col_f))
Notice that Col_fn is the same as Col_n.
# Call str again
str(dat)
# 'data.frame': 9 obs. of 3 variables:
# $ Col_f : Factor w/ 4 levels "1.1","2.1","3.1",..: 1 1 2 2 3 3 4 4 4
# $ Col_n : num 1.1 1.1 2.1 2.1 3.1 3.1 4.1 4.1 4.1
# $ Col_fn: num 1.1 1.1 2.1 2.1 3.1 3.1 4.1 4.1 4.1
If you directly convert factor to numeric, it will be based on the level. Here is an example.
# Convert the column of factor to numeric
dat$Col_ff <- as.numeric(dat$Col_f)
# Use str again
str(dat)
# 'data.frame': 9 obs. of 4 variables:
# $ Col_f : Factor w/ 4 levels "1.1","2.1","3.1",..: 1 1 2 2 3 3 4 4 4
# $ Col_n : num 1.1 1.1 2.1 2.1 3.1 3.1 4.1 4.1 4.1
# $ Col_fn: num 1.1 1.1 2.1 2.1 3.1 3.1 4.1 4.1 4.1
# $ Col_ff: num 1 1 2 2 3 3 4 4 4
Notice that col_ff are integers ranging from 1 to 4 because those were the level numbers.