You pipe the filter but do not save the result. A reproducible example might
help.
Tim
-----Original Message-----
From: R-help <r-help-boun...@r-project.org> On Behalf Of Neha gupta
Sent: Thursday, February 17, 2022 1:55 PM
To: r-help mailing list <r-help@r-project.org>
Subject: [R] Problem with data distribution
[External Email]
Hello everyone
I have a dataset with output variable "bug" having the following values (at the
bottom of this email). My advisor asked me to provide data distribution of bugs
with 0 values and bugs with more than 0 values.
data = readARFF("synapse.arff")
data2 = readARFF("synapse.arff")
data$bug
library(tidyverse)
data %>%
filter(bug == 0)
data2 %>%
filter(bug >= 1)
boxplot(data2$bug, data$bug, range=0)
But both the graphs are exactly the same, how is it possible? Where I am doing
wrong?
data$bug
[1] 0 1 0 0 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 1 0 0 0 0 0
0 4 1 0
[40] 0 1 0 0 0 0 0 0 1 0 3 2 0 0 0 0 3 0 0 0 0 2 0 0 0 1 0 0 0 0 1 1 1 0 0
0 0 0 0
[79] 1 1 2 1 0 1 0 0 0 2 2 1 1 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 5 0 0 0 0 0 0
7 0 0 1
[118] 0 1 1 0 2 0 3 0 1 0 0 1 0 0 0 0 0 1 1 0 0 0 0 1 0 3 2 1 1 0 0 0 0 0 0
0 1 0 0
[157] 0 0 0 0 0 0 0 0 0 1 0 1 0 0 3 0 0 1 0 1 3 0 0 0 0 0 0 0 0 1 0 4 1 1 0
0 0 0 1
[196] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0
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and provide commented, minimal, self-contained, reproducible code.
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