Getting data from 2 columns in a data frame

[anotherhoward]

From an object named “education,” which contains the contents of a CSV file, I want to extract those rows in which the column Region (column 3) is equal to 3 and the column Minor.Population (column 6) is greater than 310, and then view the results so that I can do an analysis of their contents.

How can I do that?

[FJCC]

Here is one way using the dplyr package.

library(dplyr)
df <- filter(education, Region == 3, Minor.Population > 310)

[anotherhoward]

Thank you. Any idea about how many bytes are in the dplyr package?

[anotherhoward]

I found the answer. It is 6.5 MB.

[anotherhoward]

@FJCC

df <- filter(education, Region == 3, Minor.Population > 310)

When I run it in RStudio, I get this error message: >
"Error in match.arg(method) : object 'Minor.Population' not found"

However, this code works, so Minor.Population is the correct column name:
education$Minor.Population

Any idea why?

[FJCC]

If you do not want to use the dplyr package you can use base R.

df <- education[education$Region == 3 & education$Minor.Population > 310, ]

[anotherhoward]

I would like to use the dplyr package. Any idea what is causing the error?

[jdb]

This might be an instance of conflicting function names. See here for example

Does the following work?

df <- dplyr::filter(education, Region == 3, Minor.Population > 310)

[andresrcs]

To help us help you, and to avoid these back and forths, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[anotherhoward]

@jdb

df <- dplyr::filter(education, Region == 3, Minor.Population > 310)

When I entered "?filter" I got this: " Linear Filtering on a Time Series," so there appears to be a second "filter" function, and they conflict. Your revision with "dplyr::filter" worked.

Thanks again. I appreciate your help.