corrplot | Create a correlation plot , as in the corrplot R package | Time Series Database library

by louridas Python Version: Current License: No License

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kandi X-RAY | corrplot Summary

corrplot is a Python library typically used in Database, Time Series Database applications. corrplot has no bugs, it has no vulnerabilities and it has low support. However corrplot build file is not available. You can download it from GitHub.

Create a correlation plot, as in the corrplot R package.

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Support

corrplot has a low active ecosystem.

It has 5 star(s) with 1 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

corrplot has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of corrplot is current.

Quality

corrplot has 0 bugs and 0 code smells.

Security

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

corrplot code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

corrplot does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

corrplot releases are not available. You will need to build from source code and install.

corrplot has no build file. You will be need to create the build yourself to build the component from source.

It has 60 lines of code, 1 functions and 1 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed corrplot and discovered the below as its top functions. This is intended to give you an instant insight into corrplot implemented functionality, and help decide if they suit your requirements.

Plots corrplot .

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corrplot Key Features

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corrplot Examples and Code Snippets

No Code Snippets are available at this moment for corrplot.

Community Discussions

Trending Discussions on corrplot

How to replicate correlation plot with greyscale coefficients in the lower half and circles in upper half?

Problem Fitting Model in Tidymodels: Error: ! Can't use NA as column index with `[` at positions 3 and 4:\

Change color of legend in correlation matrix in R

Generate correlation matrix with specific columns and only with significant values in corrplot

Clustering differences between pheatmap and corrplot() using ward.D2 method

Saving displayed plots using for loop as SVG

Add a color for each row in a corrplot with R

ggcorrplot2 shows different significance asterisks

plotting chi-square results with corrplot raises matrix error

Error in eval(predvars, data, env) : object 'oly.success' in Regression model

QUESTION

How to replicate correlation plot with greyscale coefficients in the lower half and circles in upper half?

Asked 2022-Apr-16 at 10:49

I'm looking to replicate this correlation plot, or at least get as close as possible to it.

Specifically, I want:

the correlation values in the lower half, with values varying on a greyscale based on absolute value
the circles in the top half, with varying diameter and on the colour scale.
I want to be able to edit the axis scale labels so that full descriptions are on the y-axis, and numeric references on the x-axis

I have gotten relatively close, but have not managed precise enough replication. I describe my closest attempts below with reproducible code. The corrplot package has gotten me closest.

...

ANSWER

Answered 2022-Apr-16 at 10:49

Out-of-the-box options are quick and nice. However, when it comes to customizing then IMHO it may be worthwhile to build up the plot from scratch using ggplot2. As a first step this involves some data wrangling to get you correlation matrix into the right shape. Also in this step I convert the categories to factors and a numeric id. Based on the ids I split the data in the upper and lower diagonal values which could then be plotted separately using a geom_point and a geom_text. Besides that it's important to add the drop=FALSE to the x and y scale to keep all factor levels and the right order. Also I use some functions to get the desired axis labels:

EDIT: Following the suggestion by @AllanCameron I added a coord_equal as the "final" touch to get a nice square matrix like look. And Thanks to @RichtieSacramento the code now maps the absolute value on the size aes.

Source https://stackoverflow.com/questions/71890644

QUESTION

Problem Fitting Model in Tidymodels: Error: ! Can't use NA as column index with `[` at positions 3 and 4:\

Asked 2022-Mar-21 at 01:32

I am writing a project in Tidymodels. I have created a train and test set, set out a recipe and a model. When I call workflow(), add the recipe and model, then call fit(data = df_train, I am getting the following error.

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ANSWER

Answered 2022-Mar-20 at 09:32

I am responding to my own question.

One thing I have realised is that the problem is in the recipe step. When I replace step_str2factor with step_dummy, then everything works fine.

I still do not know why this is the case. Maybe I will need to study Tidymodels more keenly!!

Source https://stackoverflow.com/questions/71545287

QUESTION

Change color of legend in correlation matrix in R

Asked 2022-Jan-15 at 16:54

I have done the following visualization of a correlation matrix:

...

ANSWER

Answered 2022-Jan-15 at 16:50

You could define your own colorRampPalette:

Source https://stackoverflow.com/questions/70723397

QUESTION

Generate correlation matrix with specific columns and only with significant values in corrplot

Asked 2022-Jan-12 at 21:45

I have a data.frame database with 14 columns. I split these columns into two groups: [,1:6] and [,7:14].

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ANSWER

Answered 2021-Dec-21 at 21:23

I would use the well established Hmisc::rcorr for the calculations. In corrplot::corrplot, subset both the corr= and the p.mat= with [1:6, 7:14].

Source https://stackoverflow.com/questions/70430772

QUESTION

Clustering differences between pheatmap and corrplot() using ward.D2 method

Asked 2021-Dec-20 at 21:46

I have performed Spearman correlation for my data. Then I tried to cluster and plot my data using the "ward.D2" method for corrplot()and pheatmap(). However, the order of the variables is different between the two plots.

Could someone help me clarify this point, thus correcting my code and creating the two plots with the same order of clustered variables? Thank you so much.

...

ANSWER

Answered 2021-Dec-20 at 21:46

You can create a corrplot with the same order given by pheatmap as follows:

Source https://stackoverflow.com/questions/70340505

QUESTION

Saving displayed plots using for loop as SVG

Asked 2021-Oct-22 at 10:37

How can I save an R plot that is only displayed in the "plots-pane" and not saved in the workspace?

Here simplified example on how I create my plot:

...

ANSWER

Answered 2021-Oct-22 at 09:47

You are trying to save a loop. Try this:

Source https://stackoverflow.com/questions/69674440

QUESTION

Add a color for each row in a corrplot with R

Asked 2021-Oct-19 at 10:33

I want to add a colour to each "row" of the corrplot but I haven't found any solution yet.

My code looks like this:

...

ANSWER

Answered 2021-Oct-19 at 10:33

It doesn't look like corrplot offers the functionality to colour by row. The alternative would be to build the chart in ggplot. More work, for sure, but it allows the flexibility to colour rows.

As a start of a solution:

Source https://stackoverflow.com/questions/69628822

QUESTION

ggcorrplot2 shows different significance asterisks

Asked 2021-Oct-13 at 07:40

does anybody have an idea why ggcorrplot2 shows different significance asterisks than ggcorrplot? Very confusing to me.

https://github.com/caijun/ggcorrplot2

...

ANSWER

Answered 2021-Oct-13 at 07:40

data(mtcars)
cor.matrix <- corr.test(mtcars,method = "spearman", adjust = "BH", alpha = 0.05, ci = F)
corr <- cor.matrix[["r"]]
p.mat <- cor.matrix[["p"]]
p.mat[lower.tri(p.mat)] <- t(p.mat)[lower.tri(p.mat)] #to get only the adjusted p.Values symmetrically over the plot

p.mat[lower.tri(p.mat, diag = T)] <- 1 #to set the lower triangle to 1 (this way the asterisks wont be displayed on this part of the graph)
corrplot.mixed(corr, order= "original",mar=c(0,0,2,0), tl.col = 'black', p.mat = p.mat, insig = "label_sig", sig.level = c(.001, .01, .05), pch.cex=1.5, tl.cex = .8, number.font=2, number.cex=0.8)

Source https://stackoverflow.com/questions/69539460

QUESTION

plotting chi-square results with corrplot raises matrix error

Asked 2021-Oct-06 at 23:02

I'm trying to visualize the results of chisq.test with the corrplot package and I'm getting an error I don't understand. Hope someone can enlighten me.

...

ANSWER

Answered 2021-Oct-06 at 23:02

I don't think "M" is a correlation matrix, so if you set is.corr = FALSE you get output (although I'm not sure whether the output is correct or not; p.mat is only 4 values, but you have 14 values in M so you get a bunch of warnings):

Source https://stackoverflow.com/questions/69472854

QUESTION

Error in eval(predvars, data, env) : object 'oly.success' in Regression model

Asked 2021-Sep-29 at 10:30

I have look into this problem and some people suggest that changing column name might work. But I can't seems to figure out which column is causing the issue.

my code

...

ANSWER

Answered 2021-Sep-29 at 10:30

First of all in your dput(data.new) the target variable is called oly_success and in the formula, you use oly.success, second you remove the target variable with:

Source https://stackoverflow.com/questions/69374342

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install corrplot

You can download it from GitHub.
You can use corrplot like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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