django-rest-pandas | πŸ“ŠπŸ“ˆ Serves up Pandas dataframes | Data Visualization library

Β by Β  wq JavaScript Version: v1.1.0 License: MIT

kandi X-RAY | django-rest-pandas Summary

kandi X-RAY | django-rest-pandas Summary

django-rest-pandas is a JavaScript library typically used in Analytics, Data Visualization, React applications. django-rest-pandas has no bugs, it has no vulnerabilities, it has a Permissive License and it has high support. You can install using 'npm i @wq/pandas' or download it from GitHub, npm.

Django REST Pandas (DRP) provides a simple way to generate and serve [pandas] DataFrames via the [Django REST Framework]. The resulting API can serve up CSV (and a number of [other formats] #supported-formats)) for consumption by a client-side visualization tool like [d3.js]. The design philosophy of DRP enforces a strict separation between data and presentation. This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. This capability can often be leveraged by sending users to the same URL that your visualization code uses internally to load the data. DRP does not include any JavaScript code, leaving the implementation of interactive visualizations as an exercise for the implementer. That said, DRP is commonly used in conjunction with the [wq.app] library, which provides [wq/chart.js] and [wq/pandas.js], a collection of chart functions and data loaders that work well with CSV served by DRP.
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            kandi-support Support

              django-rest-pandas has a highly active ecosystem.
              It has 1166 star(s) with 122 fork(s). There are 47 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 6 open issues and 32 have been closed. On average issues are closed in 379 days. There are 1 open pull requests and 0 closed requests.
              It has a positive sentiment in the developer community.
              The latest version of django-rest-pandas is v1.1.0

            kandi-Quality Quality

              django-rest-pandas has 0 bugs and 0 code smells.

            kandi-Security Security

              django-rest-pandas has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              django-rest-pandas code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              django-rest-pandas is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              django-rest-pandas releases are available to install and integrate.
              Deployable package is available in npm.
              Installation instructions, examples and code snippets are available.
              django-rest-pandas saves you 782 person hours of effort in developing the same functionality from scratch.
              It has 1800 lines of code, 111 functions and 24 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed django-rest-pandas and discovered the below as its top functions. This is intended to give you an instant insight into django-rest-pandas implemented functionality, and help decide if they suit your requirements.
            • Unstack the dataframe .
            • Return the template context .
            • Render a dataframe
            • Returns the serializer class .
            • Create a dataframe from data .
            • Compute box plots for the given interval .
            • Default grouping .
            • Returns the README . md description .
            • Handle GET requests .
            • Return the unstacked header fields .
            Get all kandi verified functions for this library.

            django-rest-pandas Key Features

            No Key Features are available at this moment for django-rest-pandas.

            django-rest-pandas Examples and Code Snippets

            Bulk Export and Interactive Charting
            Pythondot img1Lines of Code : 6dot img1License : Permissive (MIT)
            copy iconCopy
            # myproject/urls.py
            from vera.results.views import TimeSeriesView
            
            urlpatterns = [
                url(r'^data/(?P[^\.]+)/timeseries$', cls.as_view())
            ]
              

            Community Discussions

            QUESTION

            Connecting All Nodes Together on a Graph
            Asked 2022-Mar-30 at 20:34

            I have the following network graph:

            ...

            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.

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

            QUESTION

            R: Connecting Points in Arbitrary Order
            Asked 2022-Mar-15 at 18:09

            I am working with the R programming language.

            I generated the following random data set in R and made a plot of these points:

            ...

            ANSWER

            Answered 2022-Mar-15 at 17:00

            You can order your data like so:

            Source https://stackoverflow.com/questions/71485862

            QUESTION

            Fixing Cluttered Titles on Graphs
            Asked 2022-Mar-07 at 19:08

            I made the following 25 network graphs (all of these graphs are copies for simplicity - in reality, they will all be different):

            ...

            ANSWER

            Answered 2022-Mar-03 at 21:12

            While my solution isn't exactly what you describe under Option 2, it is close. We use combineWidgets() to create a grid with a single column and a row height where one graph covers most of the screen height. We squeeze in a link between each widget instance that scrolls the browser window down to show the following graph when clicked.

            Let me know if this is working for you. It should be possible to automatically adjust the row size according to the browser window size. Currently, this depends on the browser window height being around 1000px.

            I modified your code for the graph creation slightly and wrapped it in a function. This allows us to create 25 different-looking graphs easily. This way testing the resulting HTML file is more fun! What follows the function definition is the code to create a list of HTML objects that we then feed into combineWidgets().

            Source https://stackoverflow.com/questions/71244872

            QUESTION

            Adding Contour Lines to 3D Plots
            Asked 2022-Mar-04 at 20:53

            I am working with the R programming language. I made the following 3 Dimensional Plot using the "plotly" library:

            ...

            ANSWER

            Answered 2022-Mar-04 at 17:52

            You were almost there.
            The contours on z should be defined according to min-max values of z:

            Source https://stackoverflow.com/questions/71313167

            QUESTION

            How can I create a doughnut chart with rounded edges only on one end of each segment?
            Asked 2022-Feb-28 at 08:52

            I'm trying to build a doughnut chart with rounded edges only on one side. My problem is that I have both sided rounded and not just on the one side. Also can't figure out how to do more foreground arcs not just one.

            ...

            ANSWER

            Answered 2022-Feb-28 at 08:52

            The documentation states, that the corner radius is applied to both ends of the arc. Additionally, you want the arcs to overlap, which is also not the case.

            You can add the one-sided rounded corners the following way:

            1. Use arcs arc with no corner radius for the data.
            2. Add additional path objects corner just for the rounded corner. These need to be shifted to the end of each arc.
            3. Since corner has rounded corners on both sides, add a clipPath that clips half of this arc. The clipPath contains a path for every corner. This is essential for arcs smaller than two times the length of the rounded corners.
            4. raise all elements of corner to the front and then sort them descending by index, so that they overlap the right way.

            Source https://stackoverflow.com/questions/71258718

            QUESTION

            Understanding "list" and "do.call" commands
            Asked 2022-Feb-25 at 10:55

            Over here (Directly Adding Titles and Labels to Visnetwork), I learned how to directly add titles to graphs made using the "visIgraph()" function:

            ...

            ANSWER

            Answered 2022-Feb-25 at 10:55

            Please find below one possible solution.

            Reprex

            • Your data

            Source https://stackoverflow.com/questions/71262761

            QUESTION

            Is it possible to not reorder elements when using d3.join?
            Asked 2022-Feb-18 at 23:13

            In d3, we may change the order of elements in a selection, for example by using raise.

            Yet, when we rebind the data and use join, this order is discarded.

            This does not happen when we use "the old way" of binding data, using enter and merge.

            See following fiddle where you can click a circle (for example the blue one) to bring it to front. When you click "redraw", the circles go back to their original z-ordering when using join, but not when using enter and merge.

            Can I achive that the circles keep their z-ordering and still use join?

            ...

            ANSWER

            Answered 2022-Feb-18 at 23:13

            join does an implicit order after merging the enter- and update-selection, see https://github.com/d3/d3-selection/blob/91245ee124ec4dd491e498ecbdc9679d75332b49/src/selection/join.js#L14.

            The selection order after the data binding in your example is still red, blue, green even if the document order is changed. So the circles are reordered to the original order using join.

            You can get around that by changing the data binding reflecting the change in the document order. I did that here, by moving the datum of the clicked circle to the end of the data array.

            Source https://stackoverflow.com/questions/71179024

            QUESTION

            Is there way in ggplot2 to place text on a curved path?
            Asked 2022-Feb-02 at 10:17

            Is there a way to put text along a density line, or for that matter, any path, in ggplot2? By that, I mean either once as a label, in this style of xkcd: 1835, 1950 (middle panel), 1392, or 2234 (middle panel). Alternatively, is there a way to have the line be repeating text, such as this xkcd #930 ? My apologies for all the xkcd, I'm not sure what these styles are called, and it's the only place I can think of that I've seen this before to differentiate areas in this way.

            Note: I'm not talking about the hand-drawn xkcd style, nor putting flat labels at the top

            I know I can place a straight/flat piece of text, such as via annotate or geom_text, but I'm curious about bending such text so it appears to be along the curve of the data.

            I'm also curious if there is a name for this style of text-along-line?

            Example ggplot2 graph using annotate(...):

            Above example graph modified with curved text in Inkscape:

            Edit: Here's the data for the first two trial runs in March and April, as requested:

            ...

            ANSWER

            Answered 2021-Nov-08 at 11:31

            Great question. I have often thought about this. I don't know of any packages that allow it natively, but it's not terribly difficult to do it yourself, since geom_text accepts angle as an aesthetic mapping.

            Say we have the following plot:

            Source https://stackoverflow.com/questions/69867669

            QUESTION

            How to add/append customized plot in for loop to Single subplot in Python using Matplotlib?
            Asked 2022-Jan-04 at 09:09

            I do realize this has already been addressed here (e.g., matplotlib loop make subplot for each category, Add a subplot within a figure using a for loop and python/matplotlib). Nevertheless, I hope this question was different.

            I have customized plot function pretty-print-confusion-matrix stackoverflow & github. Which generates below plot

            I want to add the above-customized plot in for loop to one single plot as subplots.

            ...

            ANSWER

            Answered 2022-Jan-04 at 09:09

            Okay so I went through the library's github repository and the issue is that the figure and axes objects are created internally which means that you can't create multiple plots on the same figure. I created a somewhat hacky solution by forking the library. This is the forked library I created to do what you want. And here is a an example piece of code:

            Source https://stackoverflow.com/questions/70574478

            QUESTION

            Constructing a hexagonal heat-map with custom colors in each cell
            Asked 2021-Dec-29 at 16:28

            I would like to generate a hexagonal lattice heat-map in which each cell represents a group. Likewise, each cell would be a hexagon with a unique color (fill, set by a column color in the data-frame) value, and a saturation (alpha) value corresponding to continuous decimal values from a chemical concentration dateset.

            I would like to use a standardized data format which would allow me to quickly construct figures based on standardized datasets containing 25 groups.

            For example, a datasheet would look like this:

            ...

            ANSWER

            Answered 2021-Dec-22 at 01:52

            If you're open to creating the plot in Python, the following approach would work:

            Source https://stackoverflow.com/questions/70439033

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

            Vulnerabilities

            No vulnerabilities reported

            Install django-rest-pandas

            NOTE: Django REST Pandas relies on pandas, which itself relies on NumPy and other scientific Python libraries written in C. This is usually fine, since pip can use Python Wheels to install precompiled versions. If you are having trouble installing DRP due to dependency issues, you may need to pre-install pandas using apt or conda.

            Support

            The following output formats are provided by default. These are provided as [renderer classes] in order to leverage the content type negotiation built into Django REST Framework. This means clients can specify a format via:. The HTTP header and format parameter are enabled by default on every pandas view. Using the extension requires a custom URL configuration (see below). Format | Content Type | pandas DataFrame Function | Notes -------|--------------|---------------------------|-------------- HTML | text/html | to_html() | See notes on [HTML output](#html-output) CSV | text/csv | to_csv() |   TXT | text/plain | to_csv() | Useful for testing, as most browsers will download a CSV file instead of displaying it JSON | application/json | to_json() | [date_format and orient][to_json] can be provided in URL (e.g. /path.json?orient=columns) XLSX | application/vnd.openxml...sheet | to_excel() |   XLS | application/vnd.ms-excel | to_excel() |   PNG | image/png | plot() | Currently not very customizable, but a simple way to view the data as an image. SVG | image/svg | plot() | Eventually these could become a fallback for clients that can’t handle d3.js. The underlying implementation is a set of [serializers] that take the normal serializer result and put it into a dataframe. Then, the included [renderers] generate the output using the built in pandas functionality.
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