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wwdata | Python package | Data Visualization library

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kandi X-RAY | wwdata Summary

wwdata is a Python library typically used in Analytics, Data Visualization, Jupyter applications. wwdata has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.
Python package to analyse, validate, fill and visualise data acquired in the context of (waste) water treatment

kandi-support Support

  • wwdata has a low active ecosystem.
  • It has 7 star(s) with 9 fork(s). There are 1 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 22 open issues and 11 have been closed. On average issues are closed in 101 days. There are 6 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of wwdata is v0.2.0

quality kandi Quality

  • wwdata has no bugs reported.

securitySecurity

  • wwdata has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

license License

  • wwdata is licensed under the GPL-3.0 License. This license is Strong Copyleft.
  • Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

buildReuse

  • wwdata releases are available to install and integrate.
  • Build file is available. You can build the component from source.
Top functions reviewed by kandi - BETA

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

  • Calculate daily profile .
  • Fill missing data in the dataset .
  • Drop peaks from the dataframe .
  • Selects the slope of the data .
  • Join multiple files together .
  • Write a dataframe to a file .
  • Sort data .
  • Convert a date value to a timestamp .
  • Convert raw data into a DataFrame
  • Find and replace file with replacement .

wwdata Key Features

Python package to analyse, validate, fill and visualise data acquired in the context of (waste) water treatment

wwdata Examples and Code Snippets

No Code Snippets are available at this moment for wwdata.Refer to component home page for details.

No Code Snippets are available at this moment for wwdata.Refer to component home page for details.

Community Discussions

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Trending Discussions on Data Visualization

QUESTION

Connecting All Nodes Together on a Graph

Asked 2022-Mar-30 at 20:34

I have the following network graph:

library(tidyverse)
library(igraph)


set.seed(123)
n=5
data = tibble(d = paste(1:n))

relations = data.frame(tibble(
  from = sample(data$d),
  to = lead(from, default=from[1]),
))

graph = graph_from_data_frame(relations, directed=T, vertices = data) 

V(graph)$color <- ifelse(data$d == relations$from[1], "red", "orange")

plot(graph, layout=layout.circle, edge.arrow.size = 0.2)

enter image description here

I want to connect each Node to every Node on this graph - I can do this manually by redefining the "relations" data frame:

relations_1 = data.frame("from" = c(1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5,5), "to" = c(2,3,4,5,1,3,4,5,1,2,4,5,1,2,3,5,1,2,3,4))

Then, I can re-run the network graph:

graph = graph_from_data_frame(relations_1, directed=T, vertices = data) 

V(graph)$color <- ifelse(data$d == relations_1$from[1], "red", "orange")

plot(graph, layout=layout.circle, edge.arrow.size = 0.2)

enter image description here

  • But would there have been a way to "automatically" connect all the points in the graph directly using the "relations" data frame without manually creating a new data frame "relations_1"? Could a single line (or a few lines) of code have been added that would have automatically taken the "relations" data frame and connected everything together?

Thank you!

ANSWER

Answered 2022-Mar-30 at 04:35

You could just update relations using complete, and than filter out the rows where from is equal to to, which gives arrows from a node to itself.

relations <- relations %>% 
  complete(from, to) %>% 
  dplyr::filter(from != to)

Source https://stackoverflow.com/questions/71671488

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

Vulnerabilities

No vulnerabilities reported

Install wwdata

You can download it from GitHub.
You can use wwdata 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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