Python flask interactive graphs

I found the Chart. Based on my experience, I would highly recommend learning the basics of Javascript first I thought the Codecademy course called Learning Javascript provided a great introduction. This blog post provides an introduction to Chart. The documentation for Chart. Within the templates directory, there are separate template files for each of the three examples:.

The first example illustrates utilizing a simple Flask application that originates the data to be displayed by Chart. The data being passed to the chart. In order to use the Chart. Most of the parameters that are set in this section are straight from the Chart. This parameter can be easily changed, but it does provide an example of setting a global parameter that will be applied to all Chart objects in your application.

In order to run the application, go to a terminal and navigate to the top-level directory of the project. Next, run:. You should see the following web page:. As you start to read through the documentation for Chart. One aspect that I really thought was cool was being able to define callback functions when certain actions occur such as clicking on a part of the chart. This new route defines a more complex set of data to display. The Javascript code that creates the chart is updated to add a callback function for changing the caption that is displayed when the user hovers over a data point:.

The Javascript code that creates the callback function to update the text for which data point using a zero-based index has been selected starts by creating a variable for identifying the canvas:. The callback function gets called whenever the user clicks on a data point on the chart and it updates the text below the chart indicating the index of the data point that was selected.

Additionally, you could include some logs to see what additional information is available from the activePoint variable:. Just like with the previous application, you run the application through the terminal by navigating to the top-level directory of the project and running:.

One of the great features of Chart. The biggest problem with example 2 is that the way that the time data is just being defined as a string. The Moment. The Chart. I prefer the method of explicitly including Moment.According to data visualization expert Andy Kirkthere are two types of data visualizations: exploratory and explanatory.

The aim of explanatory visualizations is to tell stories—they're carefully constructed to surface key findings. More often than not, exploratory visualizations are interactive.

While there are many Python plotting libraries, only a handful can create interactive charts that you can embed online and distribute. Today we're sharing five of our favorites. Let us know which libraries you enjoy using in the comments. We use customer requests to prioritize libraries to support in Mode Python Notebooks. Custom plugin example Jake Vanderplas. You can make a plot in matplotlib, add interactive functionality with plugins that utilize both Python and JavaScript, and then render it with D3.

If you're familiar with D3 and JavaScript, there's no end to the kind of plots you can create. When your plot is ready for publication, add an extra line of code at the end to convert your plot into a string of HTML and JavaScript, which can be embedded into any web page. Basic dot plot Florian Mounier. Each chart type is packaged into a method e.

Histogram makes a histogram, pygal. Box makes a box plotand there's a variety of colorful default styles. If you want more control, you can configure almost every element of a plot—including sizing, titles, labels, and rendering.

Charts display tooltips by default, but there's currently no way to zoom in and out or pan across plots. Like mpld3, pygal is suited for smaller datasets.

Cross filters example Continuum Analytics.

python flask interactive graphs

Bokeh is inspired by the concepts outlined in The Grammar of Graphics.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service. The dark mode beta is finally here.

Pygal SVG embedded Graphs - Flask Web Development with Python 33

Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. I'm a new to Highcharts and know a little bit JavaScript. Do not ask why, but I got a task to create some web UI that uses Highcharts based on Python, that get data via Athena. I managed to create static graphs, but I need that this graph changes according to values that in the drop down list.

All examples that I found till now explain how to implement it via JavaScript code and this code have the possible data is created already in this code. In my case I get the data via the Python code. And I have no idea how to connect it to the examples that I found.

Maybe I miss any small point or maybe I try to create something completely not correct? I tried to use this example for interactive code How to set the highcharts interactive with select option. Learn more. Highcharts with Flask and Python: how to create interactive graph? Ask Question.

Asked 2 years, 5 months ago. Active 2 years, 5 months ago. Viewed 2k times. Dmitry 4, 11 11 gold badges 30 30 silver badges 32 32 bronze badges. From JS and Highcharts point of view for dynamic updates - like data change - you could use Series. Active Oldest Votes. Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. Post as a guest Name. Email Required, but never shown. The Overflow Blog.

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python flask interactive graphs

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Creating Charts with Chart.js in a Flask Application

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Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. I am trying to create a Pygal chart and display it in flask - without saving the. Is this possible? Every Combination i have tried has given me an error. Learn more. Asked 5 years, 8 months ago. Active 5 years, 8 months ago. Viewed 6k times. Ashoka Lella 5, 1 1 gold badge 23 23 silver badges 33 33 bronze badges. What error are you getting? Internal Server Error The server encountered an internal error and was unable to complete your request.

Either the server is overloaded or there is an error in the application. What if you run the app in debug mode? Active Oldest Votes. If you are using Python 2. I just tried this - it's still not generating the graph.

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I'm using flask if that is any help? Sign up or log in Sign up using Google. Sign up using Facebook.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service.

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The dark mode beta is finally here. Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. I wish to create dynamic plots based on user input on a flask app.

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However I am getting the following error: string argument expected, got 'bytes'. Learn more. How to create dynamic plots to display on Flask? Ask Question. Asked 3 years, 3 months ago. Active 3 years, 3 months ago. Viewed 12k times.

python flask interactive graphs

However I am getting the following error: string argument expected, got 'bytes' If I use io. BytesIOI am not getting this error, but I am not getting the plot on test. Active Oldest Votes. Thank you! Worked as expected. Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. Post as a guest Name. Email Required, but never shown.

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Linked 3. Related Hot Network Questions. Question feed. Stack Overflow works best with JavaScript enabled.In this Flask web development tutorial with Python, I am going to be showing you how to incorporate Pygal with your Flask web application.

Pygal is highly customize-able, yet also extremely simplistic, which is a very rare combination. You can make line graphs, bar graphs, histograms, pie charts, maps, and a whole lot more. From there you can further customize the look and feel of the graphs. This graph is pretty good looking, interactive, and scales to just about any size. So how do we get this to display with Flask? It turns out, Pygal has a special Flask response, but this means the entire response is a graph, and a graph only.

What if you want to embed the graph into the rest of the webpage? No problem! Let's create a new page, add the code, and see what we need to do:. This gives us the raw SVG data for the graph, which we can next pass into our template. Let's make that template real quick:. Note that we have to use the safe filter here, so the actual graph shows and not the data.

That's all there is to it. I highly encourage you to poke through their documentation. I've never found such an easy integration of graphs and Python for web apps, I am a big fan. You can do things like create your own custom styles and change all sorts of options.They say a graph is more than a thousand words.

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I totally agree with it. I would prefer to look at a network graph, rather than reading through lengthy documents, to understand a complicated network pattern. This post is about a Python interactive network visualization application.

In the first half, it covers the network visualization application features and a introduction of the tools I used for developing this application. In the second half, technical details on how to use NetworkX, Plotly, and Dash are discussed. A network graph reveals patterns and helps to detect anomalies. There is huge potential for network visualization applications in finance, and examples include fraud surveillance and money laundry monitoring.

For this project, I will create a dummy dataset of transactions, and build a network visualization application to interactively plot graphs showing these transactions. Firstly, this application will read in the dummy transaction dataset, and generate graphical representation of the transaction network.

Here, I want to customize the graphical representation, such as the edges are color-coded according to transaction time, and the edge width are varied according to transaction amount.

In this way, it is easy to quickly understand the transaction network graph. Secondly, it will be an interactive application. When the user hovers on a node or edge, rich information will show.

In addition, the user should be able to type in the account to search and the time range to show. I find several useful python packages to enable the development of this application, including NetworkXPlotlyand Dash.

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This session will cover a brief introduction of these libraries, as well as discuss about how they are useful for the development of this application. To represent a transaction network, a graph consists of nodes and edges. Here, the nodes represent accounts, and the associated attributes include customer name and account type. The edges are transactions with associated attributes of transaction date and transaction amount. The transaction network is a directed graph, with each edge pointing from the source account to the target account.

NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. It allows quick building and visualization of a graph with just a few lines of codes:. Apart from building a simple graph with the inline data, NetworkX also supports more complicated graph with dataset imported from csv or database.

Here, I import the dummy csv files containing the transaction records, and built transaction network using NetworkX. Python comes with several useful plotting libraries. Unlike the static Matplotlib and Seaborn libraries, Plotly makes interactive graphs. It supports many common chart types, including line plots, scatter plots, bar charts, histograms and heatmaps.


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