corrr | Explore correlations in R | Data Visualization library

by tidymodels R Version: v0.4.4 License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | corrr Summary

corrr is a R library typically used in Analytics, Data Visualization applications. corrr has no bugs, it has no vulnerabilities and it has low support. However corrr has a Non-SPDX License. You can download it from GitHub.

corrr is a package for exploring correlations in R. It focuses on creating and working with data frames of correlations (instead of matrices) that can be easily explored via corrr functions or by leveraging tools like those in the tidyverse. This, along with the primary corrr functions, is represented below:.

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Quality

Security

License

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Support

corrr has a low active ecosystem.

It has 569 star(s) with 54 fork(s). There are 18 watchers for this library.

It had no major release in the last 12 months.

There are 8 open issues and 111 have been closed. On average issues are closed in 123 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of corrr is v0.4.4

Quality

corrr has 0 bugs and 0 code smells.

Security

corrr has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

corrr code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

corrr has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

corrr releases are available to install and integrate.

Installation instructions are not available. Examples and code snippets are available.

It has 442 lines of code, 0 functions and 1 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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corrr Key Features

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corrr Examples and Code Snippets

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Community Discussions

Trending Discussions on corrr

Error converting and exporting tbl_df result to xlsx in R

R round correlate function from corrr package

R: K Means Clustering vs Community Detection Algorithms (Weighted Correlation Network) - Have I overcomplicated this question?

zoo::rollapply does not give the entire run of rolling correlation

Error: `data` and `reference` should be factors with the same levels. Confusion matrix for Logistic Regression

Calculate bulk pair-wise correlation using purrr and nested data.frame

Why does this correlation matrix not rearrange (corrr)?

Wrong visual plot representation of a correlation

Correlations between the selected column and the rest of the data.frame in R

tidyverse - filtering within a nested column/list based on number of NA's per row

QUESTION

Error converting and exporting tbl_df result to xlsx in R

Asked 2021-Jun-30 at 21:10

I did the correlation of some variables, however when exporting the results I got an error, because instead of exporting the correlation results the function returns the original data.frame.

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ANSWER

Answered 2021-Jun-30 at 21:10

You could assign your correlations back to data_land to have it in this object. Then saving it is xlsx should work. Try adding -> data_land after the call of focus:

Source https://stackoverflow.com/questions/68201522

QUESTION

R round correlate function from corrr package

Asked 2021-May-16 at 18:04

I'm creating a correlation table using the correlate function in the corrr package. Here is my code and a screenshot of the output.

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ANSWER

Answered 2021-May-16 at 17:40

We can use:

Source https://stackoverflow.com/questions/67559723

QUESTION

R: K Means Clustering vs Community Detection Algorithms (Weighted Correlation Network) - Have I overcomplicated this question?

Asked 2020-Nov-27 at 20:08

I have data that looks like this: https://imgur.com/a/1hOsFpF

The first dataset is a standard format dataset which contains a list of people and their financial properties.

The second dataset contains "relationships" between these people - how much they paid to each other, and how much they owe each other.

I am interested learning more about network and graph based clustering - but I am trying to better understand what type of situations require network based clustering, i.e. I don't want to use graph clustering where its not required (avoid a "square peg round hole" type situation).

Using R, first I created some fake data:

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ANSWER

Answered 2020-Nov-27 at 15:29

I am trying to better understand what type of situations require network based clustering

This is completely dependent on your problem domain and the questions you are asking. You really need to have focused questions about the data that you are trying to answer. That being said, there is an set of clustering techniques you can apply that can use both edge weights and node attributes: Hierarchical Clustering.

Edge and node attributes come into play in how you determine the similarity/dissimilarity matrix which drives the clustering. Note that there are many, many implementations of this, take your time and find one that you can apply to your data and problem set.

Source https://stackoverflow.com/questions/64849921

QUESTION

zoo::rollapply does not give the entire run of rolling correlation

Asked 2020-Aug-12 at 16:43

I was trying to do some manual labour to calculate my own rolling beta for some stock log returns and bumped into this peculiar issue. To actually reproduce this issue I have paste my full dataset(csv file) here.

This dataset has a date column but when I was doing my calculate I have excluded it. Below snippet shall create identical dataset to what I have experimented with.

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ANSWER

Answered 2020-Aug-12 at 16:43

The function should return a vector, not a matrix. Use the following (or omit the fill argument if you don't want the result to be filled with leading NAs):

Source https://stackoverflow.com/questions/63329301

QUESTION

Error: `data` and `reference` should be factors with the same levels. Confusion matrix for Logistic Regression

Asked 2020-May-29 at 15:13

I have seen lots of answers with regards to this particular error. I haven't found any answer to it with specifics to my particular issue. Therefore, my problem

This is what I do:

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ANSWER

Answered 2020-May-29 at 15:13

Try to convert your predicted probabilities to labels, and then run your confusionMatrix on this:

Source https://stackoverflow.com/questions/62088364

QUESTION

Calculate bulk pair-wise correlation using purrr and nested data.frame

Asked 2020-Apr-13 at 17:02

I want to calculate the pair-wise correlations between "mpg" and all other numeric variables of interest for each cyl in the mtcars dataset. I would like to adopt the tidy data principle.

It's rather easy with corrr::correlate().

...

ANSWER

Answered 2020-Apr-13 at 11:29

Would this work for you? I have done this in the past but on smallish datasets and have not bench marked it so not sure of performance. I use pivot_longer to reshape the data prior to nesting. The variables you pass essentially work as the filtering step, sort of

Source https://stackoverflow.com/questions/61184133

QUESTION

Why does this correlation matrix not rearrange (corrr)?

Asked 2020-Apr-02 at 20:45

Using corrr to produce a Pearson correlation matrix, I get a nice data frame and can rearrange to have a organised-looking matrix. However, when I plot this with rplot, the rearrangement seems to be thrown out.

Here is a subset of the correlation data frame, with the matrix run:

...

ANSWER

Answered 2020-Apr-02 at 20:45

I used mtcars which is also the example in corrr's blog, and I get the same results:

Source https://stackoverflow.com/questions/60996395

QUESTION

Wrong visual plot representation of a correlation

Asked 2020-Mar-28 at 05:50

I built this code to check the correlation between Bitcoin and other altCoins, the table data is working fine, my only issue is when I try to plot the result to get a visual representation, I get the below result:

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ANSWER

Answered 2020-Mar-28 at 05:50

You need backticks around the variable name.

Source https://stackoverflow.com/questions/60897574

QUESTION

Correlations between the selected column and the rest of the data.frame in R

Asked 2020-Feb-25 at 15:18

My data is about 270 columns with 160.000 mainly non-numeric observations.

I need to find patterns and dependencies between the columns. As example, I need a correlation of the column "Material" to other columns.

...

ANSWER

Answered 2020-Feb-25 at 15:18

Your code uses the function GKtauDataframe, which tries to calculate the metrics for all 270 x 270 combinations simultanuously. That is too much.

However, as you mentioned, you want rather to compare one column against all others. This should be feasible, and not need that much memory. The function GKtau does this between a pair of columns:

Source https://stackoverflow.com/questions/60397205

QUESTION

tidyverse - filtering within a nested column/list based on number of NA's per row

Asked 2020-Feb-18 at 07:09

Trying to extend my own workflow (from columns) here: [1] tidyverse - delete a column within a nested column/list to filtering within a nested column/list, I found this potential solution: [2] Use filter() (and other dplyr functions) inside nested data frames with map()

My problem is that I want to filter in each "nest" on those rows that are not completely NA (i.e. I want to keep any row that has at least one non-missing value.

However, the simple solution in [2] doesn't work for me, probably because I want to filter on the sum of NA's per row, which might involve another map function within the filter.

(Note: I'm using the current github version of dplyr within tidyverse which offers some new experimental functions, like condense - which I'm using below, but I think that's not relevant for my problem/question).

I have the following data:

Data:

...

ANSWER

Answered 2020-Feb-17 at 21:59

Here, we can use filter_all

Source https://stackoverflow.com/questions/60270864

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