Bringing interactivity to network visualization in Jupyter notebooks: visJS2Jupyter. For more introductory information and sample notebooks go to jupyter. A PyBEL extension for Jupyter notebooks. If Open3D is installed from pip or conda repository, Jupyter supported is enabled by default. html") The result should look like this. map_dataframe(). Visualizations. In this tutorial we’ll build a map visualization of the United States Electoral College using Python’s plotly module and a Jupyter Notebook. The field of geospatial analysis is no exception. 3-D interactive molecular visualization. Jupyter Notebooks. I have a pandas data frame with several entries, and I want to calculate the correlation between the income of some type of stores. It provides a custom user interface by combining the classic notebook editor with a large interactive map. Once Escher and the appropriate extension are installed (next section), you should be able to run this notebook in Jupyter Notebook or Jupyter Lab. The earner is able to use the Folium library to visualize geospatial data and to create choropleth maps. The Databricks Runtime includes the seaborn visualization library so it's easy to create a seaborn plot. Opening in a new browser tab is the default behavior when the %snakeviz magics are used outside of notebooks. The last data point is 2012, but its still interesting to see. This example will show you how to leverage Plotly’s API for Python (and Pandas) to visualize data from a Socrata dataset. Christopher Erdmann was a featured community member in the March Jupyter Newsletter. Reproducible spatial analyses with ArcPy and R using Jupyter Notebook. ipynb) into a new jupyter dashboard called dashboard_finse_metno. Data needs to be parsed and intuitively understood before you can use it for modeling and extracting insights. You are a manager or professional in a business where data can be used to boost your. Please tell us your use cases through the Discourse or on github so that we can continue to build out these features to meet your needs. This event focuses on graduate students, early career researchers and data scientists who use or are interested in Jupyter Notebook. Learn Python with Jupyter notebook. Most of the analysis and tools in the Salish Sea MEOPAR project are written in Python, though Matlab makes occasional guest appearances. In addition, since TensorWatch is a Python library, researchers can also build their own custom UIs or use TensorWatch in the vast Python data science ecosystem. Visualizations. GraphLab Canvas can be used interactively in a browser-based application or directly via API methods. Not being able to track the status of Spark jobs and intermediate data can make it difficult for data scientists to monitor and optimize what they are doing inside the Jupyter Notebook. We're using the. Manipulate your data in Python, then visualize it in a Leaflet map via folium. Altair is a declarative statistical visualization library for Python, based on Vega and Vega-Lite, and the source is available on GitHub. The most natural method is to create a new SAS notebook, available from the New menu in the Jupyter Home window and from the File menu in an active notebook: From a SAS notebook, you can enter and run SAS code directly from a cell:. A bar chart with interactivity bar_chart_with_update. mapboxgl is a high-performance, interactive, WebGL-based data visualization tool that drops directly into Jupyter. To see your own graph, run TensorBoard pointing it to the log directory of the job, click. If you find this content useful, please consider supporting the work by buying the book!. Jupyter Lab and Jupyter Notebooks offer open-source web applications that allow you to create and share documents that contain live code, equations, visualizations and narrative text. js, and to extend this capability with high-performance interactivity over very large or streaming datasets. we will generate point maps using plotly and Pandas. Race Results Part 2 - Analyzing and Visualizing Finish Times A Jupyter notebook. Most of the analysis and tools in the Salish Sea MEOPAR project are written in Python, though Matlab makes occasional guest appearances. Jupyter notebooks with embedded interactive heatmaps can be shared on the web using GitHub and the notebook rendering service, NBviewer , Clustergrammer visualizations embedded within Jupyter. students to develop their own visualization and data-serving products. IPython is a growing project, with increasingly language-agnostic components. See more examples. With HoloViews, you can usually express what you want to do in very few lines of code, letting you focus on what you are trying to explore and convey, not on the process of plotting. Reproducible spatial analyses with ArcPy and R using Jupyter Notebook. js for more visualization and charting options. Used to create and share documents that contain live code, equations, visualizations and narrative text. Your final application will provide a near-live feed of global earthquakes and their relative magnitudes. 2014-12-23, Zeppelin project became incubation project in Apache Software Foundation. I select the region from a table, and I will map each value into a different color. Ai pipelines powered by jupyter notebooks. Africa will be blue, Europe will be gold, America will be green, and Asia will be coral. Manipulate your data in Python, then visualize it in a Leaflet map via folium. One of the most common ways of visualizing a dataset is by using a table. In this tutorial, we step through how install Jupyter on your Spark cluster and use PySpark for some ad hoc analysis of reddit comment data on Amazon S3. class MapViz¶. pyThreejs: A 3-D visualization library enabling GPU-accelerated computer graphics in Jupyter. There are a lot of plots in the notebook, and some of them are 3d plots. display function; displayHTML function; Additional topics and example notebooks. Please visit zeppelin. You are a manager or professional in a business where data can be used to boost your. Still, Basemap is a useful tool for Python users to have in their virtual toolbelts. Data visualization is an interdisciplinary field, which requires design, web development, database and coding skills. In most cases these tools can be used without pandas but I think the combination of pandas + visualization tools is so common, it is the best place to start. Python Visualization Environment Setup. For visualization, the focus will be on using ggplot2 and other packages that allow for interactivity. I’m currently enrolled in a four-course Machine Learning Specialization offered through Coursera and taught by researchers at the University of Washington. In part 1 we covered how to do basic visualizations with python and folium. It is an ideal environment for experimenting with different ideas and/or datasets. If you want to display this map in a Jupyter notebook, just type the name of your map in a separate cell and run the cell. The Jupyter Notebook • Project Jupyter (https://jupyter. Us State Map Visualization Using D3js; Project Explanation: We have the sample data of US States: Number of serious accidents reported for every state in US. Using ipwidgets, sliders on the dashboard allow emergency managers to vary the properties of the storm such as wind velocity and landfall location to update the map with likely storm surge computed from the estimation matrix. Data values are usually mapped to different color saturations for numerical variables or color hues for categorical variables. pybel_jupyter. " More often than not, exploratory visualizations are interactive. Learn how to use PixieDust in Jupyter Notebooks to create quick, easy, and powerful visualizations for exploring your data. generate data on a Sphere; run diffusion maps; visualisation; Rotating the dataset; 2D Four-well potential. " ggplot2 is the essential R data visualization package. Jupyter Notebook is a popular open source web application used to create and share documents that contain live code, equations, visualizations, and text, commonly used among data scientists to. Once you have gained experience of creating your own map with Leaflet, you will move on to combining Leaflet with GeoJSON and adding geometry objects and features to your maps. The right way to install a package from Jupyter Notebook that will work in general is # Install a conda package in the current Jupyter kernel import sys !conda install --yes --prefix {sys. Its goal is to provide elegant, concise construction of novel graphics in the style of D3. Some quick announcement. html') instead of display(map) Choropleth map. N2 - The ever-growing datasets in observational astronomy have challenged scientists in many aspects, including an efficient and interactive data exploration and visualization. TensorFlow computation graphs are powerful but complicated. Note that you need 2 elements to build a chloropleth map. The Jupyter project’s JupyterHub is the most widely used multi-user server for Jupyter. Learn online and earn valuable credentials from top universities like Yale, Michigan, Stanford, and leading companies like Google and IBM. Bluemapia: Multi-Map(Google,Microsoft,Open Street Map, NOAA/BSB Charts,self-calibrated raster) location-based GPS app for Windows Mobile. Each graph generates its own HTML file. ipynb) into a new jupyter dashboard called dashboard_finse_metno. For those of you who don't remember, the goal is to create the same chart in 10 different python visualization libraries and compare the effort involved. Commonly used for spatial analysis and visualization. The Big List of D3. Really, we're trying to compress this extremely high-dimensional structure into two dimensions. Creating a world map of metal bands in Python. To do this, we. Featured Visualization. Bokeh for Python Data Visualization Bokeh is a Python interactive visualization library that uses modern web browsers for presentation. gl for Jupyter - vis. Try out our rich gallery of interactive charts and data tools. Description. Contribute to pbugnion/gmaps development by creating an account on GitHub. Really, we're trying to compress this extremely high-dimensional structure into two dimensions. Jupyter Notebooks. Predictive Analytics for Business. Mapshaper map conversion. Here is a basic example for a bar chart (adapted from pygal's documentation) and take a look at the visualization (hint: it's interactive!). The key doing this is the push_notebook() function described above. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. In this article, we discussed about deriving various visualizations in Python. This is a very powerful feature of JupyterLab: you can stack notebooks, place notebooks side by side, organize notebooks by tabs, etc. This is a tool for exploring the global connections between Wikipedia's pages and its users. Jupyter Map Visualization. It can be used in Python and IPython shells, Python scripts, Jupyter notebook, web application servers, etc. Qlik Sense - Creating a Map Visualization See: Qlik Sense 3. How to use Jupyter Notebooks and pandas to analyse data. In this tutorial, we step through how install Jupyter on your Spark cluster and use PySpark for some ad hoc analysis of reddit comment data on Amazon S3. Apply interactive coding environments such as Jupyter and techniques of exploratory spatial data analysis (ESDA) using the Python programming language to process geographical information. visJS2jupyter takes parameters specified by the user and then creates an HTML file that contains the vis. Data needs to be parsed and intuitively understood before you can use it for modeling and extracting insights. It is designed as a data visualization tool. Then we should make the rural masses aware of what their rights are and how can they use it. Custom image map visualization to plot x,y coordinates in pixels on a flat image using Leaflet Maps. In this tutorial on Python for Data Science, you will learn about how to create Point maps in Python. Bluemapia: Multi-Map(Google,Microsoft,Open Street Map, NOAA/BSB Charts,self-calibrated raster) location-based GPS app for Windows Mobile. This guide describes how to use pandas and Jupyter notebook to analyze a Socrata dataset. topic modeling, topic modeling python lda visualization gensim pyldavis nltk data cleasing , Python , text mining , topic modeling , unsupervised learning Posted on April 25, 2017. More examples are included in the examples directory of the basemap source distribution. In this tutorial, you learn how to use Microsoft Power BI to visualize data in an Apache Spark cluster in Azure HDInsight. Why Jupyter? "Why would I use Jupyter notebooks to work with Azure Sentinel data rather than the built-in query and investigation tools?" might be your first question. It's very easy to create and present data visualizations using Matplotlib. There are some really nice tutorials there, which alone is reason enough to check out this list. We're using the. TensorBoard's graph visualization with tf. Seems good for data visualization but less map-specific. You can also use other Python libraries to generate visualizations. js graphs with R. Plotly's team maintains the fastest growing open-source visualization libraries for R, Python, and JavaScript. Weather maps in Python with Mapbox-gl, xarray, and netcdf4 Published December 18, 2017 December 18, 2017 by modern. Jupyter notebooks are a popular way of exploring data sets by setting out your code, data and visualisations in an interactive, web-based notebook. Folium is a powerful data visualization library in Python that was built primarily to help people visualize geospatial data. Plotly has a new R API and ggplot2 library for making beautiful graphs. Reproducible spatial analyses with ArcPy and R using Jupyter Notebook. Much easier than matplotlib (but you can still use matplotlib. And the first answer is that, usually, you wouldn't. On this page:. This allows users to create Jupyter Notebooks and use JupyterHub both of which are very commonly used within the data science community. This is controlled by the "n_jobs=-1" setting in the Jupyter workbook. Getting started¶. js into the Jupyter notebook,. Plotting in Julia is available through external packages. Jun 29, 2016. Jupyter supports a fairly wide array of widgets including the following: Numeric Boolean Selection String Image Button Output Animation Date picker …. Graph visualization is a way of representing structural information as diagrams of abstract graphs and networks. Another option, which is written in JavaScript, is Vega-Lite. Y1 - 2017/7/1. If you don’t use Jupyter, you can also save standalone visualizations as HTML files using Escher Python. The visualization represents 246 languages, 212 locations, and 1190 connections. If you want to display this map in a Jupyter notebook, just type the name of your map in a separate cell and run the cell. The Jupyter notebook cell then renders this HTML file to produce the visualization. In 2012 we exported $20. May 30, 2019- Explore Alla Khrystych's board "Jupyter / IPython", followed by 123 people on Pinterest. i/ A shape file in the geojson format: it gives the boundaries of every zone that you want to represent. Migrate Deprecated Line Charts; Visualization Deep Dive in Python; Visualization Deep Dive in Scala; HTML, D3, and SVG in Notebooks; Bokeh in Python Notebooks; Matplotlib and ggplot in Python Notebooks; htmlwidgets in R Notebooks; Plotly in Python. This will plot a graph of the model and save it to a file: from keras. Jupyter supports a fairly wide array of widgets including the following: Numeric Boolean Selection String Image Button Output Animation Date picker …. In this tutorial you: Set up an environment to run Jupyter notebooks. Introduction. Müller ??? Hi everybody. ii/ A data frame that gives the values of each zone. x was the last monolithic release of IPython, containing the notebook server, qtconsole, etc. Bringing interactivity to network visualization in Jupyter notebooks: visJS2Jupyter. I’m currently enrolled in a four-course Machine Learning Specialization offered through Coursera and taught by researchers at the University of Washington. Commonly used for spatial analysis and visualization. The earner is able to use the Folium library to visualize geospatial data and to create choropleth maps. If you want to run the examples, make sure you execute them in a directory where you have write permissions, or you copy the examples into such a directory. This will plot a graph of the model and save it to a file: from keras. The Federal Highway Administration (FHWA) Visualization Working Group (VWG) was created to investigate applications and opportunities for the use of visualization techniques in highway project development, delivery, and analysis. A Jupyter notebook is an open source environment run in the web browser that allows you to create and share documents belonging to the Python and R program. For visualization, the focus will be on using ggplot2 and other packages that allow for interactivity. Plotly, also known by its URL, Plot. Seaborn is a Python data visualization library based on matplotlib. Your shapefile map consists of several files. R and their aesthetics is up for grabs. The main goal of this exercise is to write a blog/paper using Jupyter dashboards. if the df has a lot of rows or columns, then when you try to show the df, pandas will auto detect the size of the displaying area and automatically hide some part of the data by replacing with. HTML widgets work just like R plots except they produce interactive web visualizations. IPython Interactive Computing and Visualization Cookbook, Second Edition (2018), by Cyrille Rossant, contains over 100 hands-on recipes on high-performance numerical computing and data science in the Jupyter Notebook. In this tutorial, you’ll learn about two common options that Bokeh provides: generating a static HTML file and rendering your visualization inline in a Jupyter Notebook. You can run many copies of the Jupyter Notebook App and they will show up at a similar address (only the number after “:”, which is the port, will increment for each new copy). Map(location=[40. With Folium, one can create a map of any location in the world if its latitude and longitude values are known. All of the Jupyter notebooks to create these charts are stored in a public github repo Python-Viz-Compared. It is an ideal working environment for ArcGIS Pro users working with Python 3, as well as the ArcGIS API for Python. the SNOWPACK and METEOIO library (compiled and ready to use). This means that even a novice can use bqplot to build full scale web applications with 10 lines of Python code. While Pandas, Matplotlib, and Seaborn libraries are excellent data plotting libraries, they can only plot static graphs. When in need of animation functionalities, the simple animation framework present in Matplotlib from version 1. Visualizing GraphLab data structures in GraphLab. If you find this content useful, please consider supporting the work by buying the book!. We can start with vague ideas and in Jupyter we can crystallize, after various experiments, our ideas for building our projects. Lying at the heart of modern data science and analysis is the Jupyter project lifecycle. How do I make an interactive PCA scatterplot in Python? Browse other questions tagged python visualization pca jupyter or ask your own Bouncing map back into. Sessions will focus on application and tools for this open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Open source data visualization tools require the user to have some programming ability, whereas free visualization tools may not necessarily need the user to have programming ability. I am having problems with two things on my map: 1. Wolfram Community forum discussion about ipynb2docx - Convert Jupyter notebooks to Word preserving LaTeX formatting. I find performing visualization in Python much easier as compared to R. This post has five examples. Vector maps mean your map is your data. GeoNotebook extends the Jupyter Notebook interface by adding a large Open Street Map style map to the right of the traditional notebook cells. We love contributions! folium is open source, built on open source, and we'd love to have you hang. Data is everywhere these days, and being able to interact with visual representations of that data in real time can help bring it to life. Here we will dig a little deeper and make custom map overlays. Tables allow your data consumers to gather insight by reading the underlying data. About This Book. Graphviz is open source graph visualization software. Hi-C contact map viewer. D3 helps you bring data to life using HTML, SVG, and CSS. 2-D interactive data visualization. Keras provides utility functions to plot a Keras model (using graphviz). It provides a custom user interface by combining the classic notebook editor with a large interactive map. The kernel protocol, which allows the server to offload the task of running code to a language-specific kernel. 13-10-07 Update: Please see the Vincent docs for updated map plotting syntax. Data is everywhere these days, and being able to interact with visual representations of that data in real time can help bring it to life. In addition, basic programming concepts and techniques are introduced. gl that runs on the site by the same name doesn’t store data or map configuration for privacy reasons. Graphviz is open source graph visualization software. In this post, I describe another powerful feature of Jupyter Notebooks: The ability to use interactive widgets to build interactive dashboards. With Vega, you can describe the visual appearance and interactive behavior of a visualization in a JSON format, and generate web-based views using Canvas or SVG. In this meetup, learn. When relevantly applied, time-series analysis can reveal unexpected trends, extract helpful statistics, and even forecast trends ahead into the future. Showing a visualization of the data is done by chaining the plotly function to the data wrapper. Jupyter Notebooks in one click Access Jupyter Notebooks from a cloud based environment, without the need of installing anything locally. The same technique can be applied to embed any javascript library, such as D3. 5, tiles='cartodbpositron') I then try to add lines connecting points on the map using folium. A Jupyter notebook is an open source environment run in the web browser that allows you to create and share documents belonging to the Python and R program. Jupyter is language agnostic and its name is a reference to core programming languages supported by Jupyter, which are Julia, Python, and R. The Jupyter stack is built from the ground up to be extensible and hackable. Matplotlib is the most popular data visualization library in Python. show all the rows or columns from a DataFrame in Jupyter QTConcole. igv-jupyter Extension for Jupyter Notebook which. we will generate point maps using plotly and Pandas. Learn how to use PixieDust in Jupyter Notebooks to create quick, easy, and powerful visualizations for exploring your data. In this process, we made use of matplotlib and seaborn in python. 2-D interactive data visualization. Continue reading "River Map of The specific requirement has been getting data from Spark into D3 and using Jupyter is a quick way. In this tutorial, you'll learn about two common options that Bokeh provides: generating a static HTML file and rendering your visualization inline in a Jupyter Notebook. Jupyter Notebook for retrieving JSON data from REST APIs; Using the Tree Map visualization component – to compare relative sizes and distributions. Visualizations. He is a leader of the Python project, co-founder of Project Jupyter and is an active contributor to a number of other open source projects focused on data science in Python. We also used the Jupyter Widget bqplot to visualize single cell location data using voronoi plots. We next describe how Enrichment Map works and how it can be used to interpret enrichment analysis results using frequently encountered experimental designs. Whether you're a full-time geo-web developer or a hobby map maker, chances are you've used and even created your own slippy web map tiles. It can be used in Python and IPython shells, Python scripts, Jupyter notebook, web application servers, etc. Let's see what we have so far. Embeddable. Jupyter ships with kernels for Python 2 and Python 3, but kernels for many other languages are available. This guide describes how to use pandas and Jupyter notebook to analyze a Socrata dataset. students to develop their own visualization and data-serving products. Refer to the official Jupyter documentation and this quick start guide for further details. Vega is a visualization grammar, a declarative language for creating, saving, and sharing interactive visualization designs. But, if you presenting your visualization to a particular audience or submitting on some platform, you will need beautiful visualizations. Map viewers become map listeners with this data visualization as each dot can stream that city’s playlist. Jupyter supports a fairly wide array of widgets including the following: Numeric Boolean Selection String Image Button Output Animation Date picker …. folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the Leaflet. Qlik Sense - Creating a Map Visualization See: Qlik Sense 3. This will plot a graph of the model and save it to a file: from keras. I was excited to be invited to give a talk at the JavaScript Open Day Montreal about data visualization in JavaScript. This post has five examples. I do this as follows:. This activity shows students how to read and interpret a common data representation, the heat map. Map with leaflet and folium Altair + Vega. In 2012 we exported $20. This is something that you can't do today on hosted Jupyter notebooks, which prevents developers from using a large number of spark package add-ons. Getting started¶. pythreejs (3-D scene visualization with three. All visualizations are npm modules, built with the latest web technologies, and endlessly customizable. It provides a custom user interface by combining the classic notebook editor with a large interactive map. Head to our docs to get a key and you can start making, embedding, and sharing plots. Here is an example of a choropleth map made using the Folium library. Bringing interactivity to network visualization in Jupyter notebooks: visJS2Jupyter. Applied Data Science with Python and Jupyter is ideal for professionals with a variety of job descriptions across a large range of industries, given the rising popularity and accessibility of data science. Note that you need 2 elements to build a chloropleth map. latitude and longitude) to glue the maps together, so that when a user selects (e. I suspect this might be the issue. About a year ago, I looked high and low for a python word cloud library that I could use from within my Jupyter notebook that was flexible enough to use counts or tfidf when needed or just accept a set of words and corresponding weights. KNIME Analytics Platform offers a few Javascript based nodes for visual investigation, including some classic charts - like the bar chart or the scatter plot – and some more innovative. js, have Jupyter-Python widget. For outsiders (like me) the details aren't that important, but some brief background might be useful so we can transfer the takeaways to Python. Visualize and explore data quickly, with less code required, all from a single local or cloud-based notebook. Many popular visualization tools, such as Matplotlib, Plotly, leaflet. Template widget project. i/ A shape file in the geojson format: it gives the boundaries of every zone that you want to represent. Manipulate your data in Python, then visualize it in a Leaflet map via folium. This is a simple jupyter widget for kepler. More modern solutions such as leaflet or the Google Maps API may be a better choice for more intensive map visualizations. Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, charts and graphics, and descriptive text. If Open3D is compiled from source, please refer to 2. To address these challenges, we are adding cutting edge job execution and visualization experiences into the HDInsight Spark in-cluster Jupyter Notebook. Plotting in Julia is available through external packages. Us State Map Visualization Using D3js; Project Explanation: We have the sample data of US States: Number of serious accidents reported for every state in US. The field of geospatial analysis is no exception. The name Jupyter is an indirect acronyum of the three core languages it was designed for: Julia, Python, and R and is inspired by the planet Jupiter. The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Last Wednesday marked a historic day for biodata science. Much easier than matplotlib (but you can still use matplotlib. Description. Matplotlib. Your shapefile map consists of several files. When using plotly with dstools, the plotly function creates the. There are a lot of plots in the notebook, and some of them are 3d plots. So, using Brunel within notebooks is a very natural fit. 2013-2019, VisPy developers Code licensed under BSD license , documentation under CC BY 3. They also can be sub-selected using a lasso-like tool for further analysis using standard Python functions from inside a Jupyter notebook. We will be using "Data Visualization - Student. Example gallery¶. It is one of the essential steps in every Data Science process. What is Jupyter? Jupyter is a web application that allows you to create notebooks that contain live code, visualizations, and explanatory text. In this article, I will show how I have created a Data Flow in Oracle Analytics Cloud to enrich a data set with geocoding data from a different data set, in order to be able to create a map based visualization of data. Now, we have language agnostic Jupyter which was forked from IPython, we can take the D3 into Notebook without lots of effeorts. We can start with vague ideas and in Jupyter we can crystallize, after various experiments, our ideas for building our projects. Exploratory visualizations, on the other hand, "create an interface into a dataset or subject matter they facilitate the user exploring the data, letting them unearth their own insights: findings they consider relevant or interesting. We can use data visualizations to make an argument, or to support a hypothesis, or to explore our world in different ways. GraphLab Canvas can be used interactively in a browser-based application or directly via API methods. NET dev can implement machine learning without switching language is cool. Jupyter Notebooks; Pandas; Advantages of Visualizing Spatial Data using Maps. Notebooks are a great tool for doing data-analysis, so we used these to create simple charts and graphs that answer basic questions and give us insights into the data. py When I run the identical script from. Analyzing 1. We can use data visualizations to make an argument, or to support a hypothesis, or to explore our world in different ways. Map viewers become map listeners with this data visualization as each dot can stream that city’s playlist. cookiecutter. Description. With Folium, one can create a map of any location in the world if its latitude and longitude values are known. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits. It is an interactive computational environment, in which you can combine code execution, rich text, mathematics, plots and rich media. Template widget project. 3-D data visualization. Description. 5 Best Python Libraries For Data Visualization 1. While Pandas, Matplotlib, and Seaborn libraries are excellent data plotting libraries, they can only plot static graphs. We next describe how Enrichment Map works and how it can be used to interpret enrichment analysis results using frequently encountered experimental designs.