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Plotly table visualization

Plotly table visualization

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It has been a while since I personally have looked into data visualization in Python, being very familiar and comfortable with Matplotlib. Tableau. You can make plotly plots from python. To query and visualize BigQuery data using a Jupyter notebook:. We also make use of the Plotly R interface for the plotly. To get the data from the HTML table into my web app, I used Python for web scraping. Sources of inspiration may be found in the Example gallery, with example Python code. Imagine telling this information to an investor through a table. Want to learn more about data visualization with Python? Take a look at my Data Visualization Basics with Python video course on O’Reilly. DataTables. While Plotly is widely known as an online platform for data visualization, very few people know that it can be can be accessed from a Python notebook. js graphs with R. Hey Lanre, Thank you. Nephele uses the ampvis2 R package v2. rbokeh. Like Bokeh, Plotly’s strength lies in making interactive plots, and it offers some charts not found in most libraries, like contour plots. Potential Value The process of creating a visualization--from collecting or finding the data to deciding on the visualization format to creating the graphic itself-- Hello and welcome to an updated series on data visualization in Python. Are you using R or Python? are you developing anything on top of steem block-chain ? No I am not. We will start with a widget called plotly. Plotly. There are many different scenarios where large amounts of data must be displayed to an audience – a business may need to present sales figures to their directors, a research team may need to display their findings to investors, or a teacher may need to display statistics to their students for example. The distribution of review sentiment polarity score Data Visualization and Python. Its goal is to provide elegant, concise construction of versatile graphics, and to extend this capability with high-performance interactivity over very large or streaming datasets. Practical Statistics & Visualization With Python & Plotly One day last week, I was googling “ statistics with Python ”, the results were somewhat unfruitful. Developers can already create R custom visuals that plugs into Power BI reports, to enable report authors to use those custom visuals without known R. Tabular data display. Jan 29, 2017 Plotly enables you to make interactive html widgets that you can embed visualizations I have made with ggplot2 into plotly visualizations using . You can zoom by clicking and dragging, pan, and see text on the hover by mousing over the plot. Plotly With Python: Recently, I stumbled upon Plotly, a beautiful online Data Visualization system by virtue of a MAKE article. The sources required to run this app are here: - Github Repo: https://gith We can do the same with using APIs and visualization tools. — broken_symlink. Javascript libraries such as d3 have made possible wonderful new ways to show data. For other parts of this series follow the tag plotly visualizations. ch. It is redundant for me to say that there are various articles which show the utilisation of Plotly for Arduino, Raspberry Pi, etcetera. py is the Python interface to the library. networkD3. Table provides a Table object for detailed data viewing. packages (plotly) # if you haven't installed the package library (plotly) Plotly. First we install and load the package. js JavaScript library. 7 people have recommended Nicolas. Tables as a form of data visualization¶. Add trace(s) to a plotly visualization. js is a great fit for Dash: it’s declarative, open source, fast, and supports a complete range of Welcome to part three of the web-based data visualization with Dash tutorial series. I decided to make it simple and compare the presence of the following options: presence of Make ggplot2 interactive using Plotly From the course: R: which seeks to make interactive data visualization available as a service to academics. The tables are visually appealing and can be modified on the fly using simple drag and drop. Learning Objectives. If you're looking to create something a little more advanced, consider using Query from Plotly. Interactive visualization allows deeper exploration of data than static plots. js, plotly. d3heatmap. Here's what you get with Data Visualisation with Plotly and Python. Interactive graphics with D3. R interface to Highcharts. visNetwork. Data visualization is an important part of being able to explore data and communicate results, but has lagged a bit behind other tools such as R in the past. 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. As for usability, in my experience Plotly falls in between matplotlib and seaborn. In this course, Building Data Visualizations Using Plotly, you will learn how to use the Plotly Python API to build a wide range of basic, intermediate, and advanced visualizations and animations. Welcome to Bokeh¶. Prerequisites. How to use Python and Plotly for statistical visualization, inference, and modeling Table 9. js, Chart. 1. js charting library. By arranging multiple low-dimensional graphics of the same (or similar) high-dimensional data, one can put local summaries and patterns into a global context. The R notebook will capture the resulting plot as a . You will learn how to deploy maps and networks to display geographic and network data. In this video we are going to see how to use maps and tables in a Plotly Dash app. For a more extensive list, see Datavisualization. Almost 10 PieCharts 10 Python Libraries Here is a follow-up to our “10 Heatmaps 10 Libraries” post. R interface to Bokeh. add_data Add data to a plotly visualization Description Add data to a plotly visualization Usage add_data(p, data = NULL) Arguments p a plotly visualization data a data frame. This article provides a high level overview of the process. This course extends Intermediate Python for Data Science to provide a stronger foundation in data visualization in Python. This article is a high level overview of how to get started with dash to build a simple, yet powerful interactive dashboard. One technique essential to high-dimensional data visualization is the ability to arrange multiple views. 3D scatterplots and globes. Go to your preferred site with resources on R, either within your university, the R community, or at work, and kindly ask the webmaster to add a link to www. js, Highcharts. To do this, we will focus on the following very popular libraries in Python: matplotlib, ggplot, seaborn, and plotly. These interactive graphs were made using Plotly’s web app and APIs. plotly. Graph data visualization with vis. js Plotly Graph. This is what you’ll need to complete the tutorial: An installation of R with the ggplot2 and plotly packages; A WordPress site or other web host with SSL where you can upload files; Convert ggplot2 to plotly Univariate visualization with Plotly Single-variable or univariate visualization is the simplest type of visualization which consists of observations on only a single characteristic or attribute. Tableau has accumulated a very large customer base of more than 57,000 accounts as per mid-2017 across many industries which can be attributed to its simplicity of use and its remarkable ability to produce interactive visualizations output which is far beyond those Plotly does not only generate your charts. This time, I’m going to focus on how you can make beautiful data Plotly’s Top Ten Graphs, Charts and Visualizations of 2015. plotly binds R commands to the JavaScript plotly. Beyond editing, sharing, and exporting, we can also add a fit. by defining aesthetics (aes) Data (State) Data Base (Dbms) Data Processing Data Modeling Data Quality Data Structure Data Type Data Warehouse Data Visualization Data Partition Data Persistence Data Concurrency Data Type Number Time Text Collection Relation (Table) Tree Key/Value Graph Spatial Color go. threejs. g. In this R tutorial, we will learn some basic functions and learn to use the Plotly package in R to build histograms such as a basic histogram, normalized histogram and a linear histogram with the data from the used cars dataset. What is Plotly? Advantages and Disadvantages of Plotly; Steps for using Plotly; Setting up Data; Basic Visualizations. In this article, one can learn from the generalized syntax for plotly in R and Python and follow the examples to get good grasp of possibilities for creating different plots using plotly. His interests include data visualization, control systems, economic modelling and agile methods . How to make tables in Python with Plotly. In this visualization, we represent the % Young on the x-axis and the % Economically Active on the y-axis for each planning subzone. Examples plot_ly() %>% add_data(economics) %>% add_trace(x = ~date, y = ~pce) add_fun Apply function to plot, without modifying data Description With plotly and other data visualization tools in R and Python, there is a lot of syntax involved and it can be confusing. Plotly is a great visualization library has a step by step tutorial to produce bubble plots. Make sure you install the latest version of Plotly i. Using this library a function ddist has been written for visualization of data distribution of each variable within a dataset. Their background is in STEM and scientific If you re-make this plot, you’ll see that we’ve styled it in Plotly’s GUI. Oct 9, 2017 Plotly's dash framework allows the user to build high quality interactive visualizations. Pandas ecosystem¶ Increasingly, packages are being built on top of pandas to address specific needs in data preparation, analysis and visualization. js, a figure is  A First-Class Interactive DataTable for Dash . , attributes) passed along to the trace type . FSharp. Data Visualization Dash ships with a Graph component that renders charts with plotly. However, they also have a link to export the data to the Plotly Chart Studio which allows for making a variety of charts. YAY. Date(dt $date, format="%m/%d/%Y") dt<-data. As the user selects a value in the Dropdown, the application code dynamically exports data from Google Finance into a Pandas DataFrame. Install and Load Packages. The course will allow you to create your own customized interactive data visualization and make your data exploration and communication so much easier. Add trace(s) to a  Data visualization is a powerful tool in the hands of those who try to answer the right question. plot() and Series. Step 1 Introduction. png and display it inline. v 4. You might know Plotly as an online platform for data visualization, but did you also know you can access its capabilities from a Python notebook? Like Bokeh, Plotly's forte is making interactive plots, but it offers some charts you won't find in most libraries, like contour plots, dendograms, and 3D charts. Plotly; In the examples, I will use pandas to manipulate the data and use it to drive the visualization. Interactive heatmaps with D3. Use non-interactive as well as interactive visualization libraries to draw various types of plots, such as scatter plot, confusion matrix, and so on Plotly in RShiny Dashboards. js . Why Even Try, Man? I recently came upon Brian Granger and Jake VanderPlas's Altair, a promising young visualization library. I’m not a plotly expert yet. Data visualization enables decision makers to see analytics presented visually, so they grasp difficult concepts or identify new patterns. Live graphs can be useful for a variety of tasks, but I plan to use live graphs to display data from sensors that are constantly Data visualization is a pivotal part of a presentation. `add_table()` makes it easy to map a data frame to the table trace type plot_ly(economics) %>% add_table() # pie charts! Jan 30, 2018 In this article, we'll compare Bokeh and Dash (by Plotly), two Python alternatives Incredibly easy to get live updates and great visualisation. Line plot . js. Comparing design and customization options is tricky. Plotly (Online & Offline) Sierra SQL API; Actual Reports (Sierra & Plotly Offline) Web App (Sierra & Plotly) Now let's move on to the real part of presentation. A true drag'n'drop pivot table implementation in Javascript. 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. shares. The data are arranged in a grid of rows and columns. Happy New Year Everyone! We decided to put together the top 10 most outstanding Plotly charts from 2015 to show you the power of our platform. Range slider example . Do you know if it is possible to generate the graphs using the plot_ly command in Power BI? Solved! Go to Solution This book is an update to our earlier R data visualization cookbook with 100 percent fresh content and covering all the cutting edge R data visualization tools. selected rows in the table output$x1 <- DT::renderDataTable({ m2 <- m[d$ selection(),] dt <- DT::datatable(m) if (NROW(m2) == 0) { dt } else { DT::formatStyle (dt,  below, we import a csv hosted on github and display it in a table using Plotly: Jinja, Plotly and boiler plate CSS and JS for easily creating data visualization   Use Pandas with Plotly's Python package to make interactive graphs directly from data frames Cufflinks binds plotly to pandas dataframes in IPython notebook. At the time Bokeh was just too hard to use and the documentation wasn’t very good. In this post, we look at using Tablesaw's new open-source, plotting framework — Plot. Access to twelve chapters which take you through each topic, providing plenty of chances to practise. rglwidget. Tableau can be regarded as the grand master of data visualization software. py is a high-level, declarative charting library that includes over 30 chart types, including scientific charts, 3D graphs, statistical charts, SVG maps, financial charts, and more. com. Suggests MASS, maps . This post has five examples. plot() with a table keyword. However, in many visualization tools -- including specs like Vega -- these items "specType": "" // one of simple | plotly | vega | vega-lite // graph spec "spec": }  Jul 3, 2019 You create visualizations using the data in the natality sample table. how to make stacked and grouped bar charts, pie charts, donut charts and tables. The plots can be minimally edited interactively. For all 13 Arranging views. Graph data visualization with D3. go. js and React. js In theory this node could be used to create any JavaScript based visualization of a data table You know Python and want to use Mayavi as a Matlab or pylab replacement for 3D plotting and data visualization with numpy? Get started with the mlab section. Sign Up & Configure http://www. Learn to create interactive charts and dashboards with Python and Plotly. We are changing how scientists, engineers & biz analysts visualize data Image may contain: one or more people, people eating, people standing, table. Jun 18, 2018 Dash is build on top of the Flask, React and Plotly and give the wide First, we will create a sample SQL Table where data will be inserted as  VI Various special topics; 23 Is plotly free & secure? frame, each row of the table is linked to a polygon on the map through the row index of the same dataset . Description. Most literature, tutorials and articles focus on statistics with R , because R is a language dedicated to statistics and has more statistical analysis features than Python. All the front-end work, all that dreaded JavaScript, that's not our problem anymore. table(dt) dt$year<-year(dt$date)  Make it convenient to construct and manipulate plotly visualizations; Provide infrastructure for viewing plots on multiple frontends and saving plotly graphics to   Apr 10, 2019 0. It’s been well over a year since I wrote my last tutorial, so I figure I’m overdue. Excel has (some) benefits over ggplot2 static charts: you can easily hover your mouse over a series to see the data value, and most industry users know how to manage an Excel axes. Head to our docs to get a key and you can start making, embedding, and sharing plots. I would say to start with the plotly cheatsheet link above and their documentation. Some R Examples[R table and Graphics] -Advanced Data Visualization in R (Some Examples) With Dash, we can create interactive, web-based dashboards with pure Python. ly/python/ getting-started 3. 1. Pygal I have some scripts that use the plotly package that work in RStudio. XPlot is a cross-platform data visualization package for the F# programming language powered by popular JavaScript charting libraries Google Charts and Plotly. Luckily the R community has been active in developing R interfaces to some popular javascript libraries to enable R users to create interactive visualizations without knowing any javascript. Data analytics is also a process that makes it easier to recognize patterns in and derive meaning from, complex data sets. Dash is a Python framework for building analytical web apps in Python. Over 140 Lectures, 27 hours of video content, 40 practise datasets and 11 quizzes; Step by step instruction to set up your coding environment and install the required software How and why I used Plotly (instead of D3) to visualize my Lollapalooza data As we want to show each data point, the best choice for a visualization is a table Practical Statistics & Visualization With Python & Plotly. The course provides a broader coverage of the Matplotlib library and an overview of Seaborn (a package for statistical graphics). Most styling can be specified for header,   Table and Chart Subplots in Python. Altair seems well-suited to addressing Python's ggplot envy, and its tie-in with JavaScript's Vega-Lite grammar means that as the latter develops new functionality (e. Bubble Plot. The library provides a A pick of the best R packages for interactive plot and visualisation (2/2) - Enhance Data Science 6th July 2017 at 3:56 pm […] the first part of A pick of the best R packages for interactive plot and visualization, we saw the best packages to do interactive plot in R. This is encouraging because it means pandas is not only helping users to handle their data tasks but also that it provides a better starting point for developers to build powerful and more focused Plotly. I personally have been using bokeh and have liked it so far. Here is the header of our table. R is a strong and popular language, enabling developers to create great analytics on data, as well as visualization. 9 from Github using devtools::install_github("ropensci/plotly) The easiest way to create a SVG table in R using plotly is by manually specifying headers and individual cell values. The goal of plotly. Plotly’s syntax is similar to ggplot2. Plotly library makes interactive graphs. js, a popular JavaScript visualization library. You can use plotly and Dash to create beautiful interactive web data 2. plotly GETTING STARTED 1. Plotly is a web based data analysis and graphing tool. I recall toying with plotly for some small thing that didn’t work at the time due to a known bug but haven’t had the time to What does not appear on the table above: Plotly and Highcharts provide many other chart types; Design and customization options. Plotly Python Plotting. If I plot just a sample of the data, like the first 100 rows, it works fine. e. table function. Univariate visualization includes histogram, bar plots and line charts. These libraries seamlessly interface with our enterprise-ready Deployment servers for easy collaboration, code-free editing, and deploying of production-ready dashboards and apps. Kruchten Engineering Services Ltd. In order to build the Plotly histograms, we will need to load the below packages and libraries to complete this tutorial: This book is an update to our earlier R data visualization cookbook with 100 percent fresh content and covering all the cutting edge R data visualization tools. The data table is an efficient format for comparative data analysis on categorical objects. Google Analytics, Python, Pandas, Plotly: Get Started Interactive Highlight Tables/Heatmaps with Tableau Set Actions & Transparent Sheets. The Python pandas package is used for data manipulation and analysis, designed to let you work with labeled or relational data in an intuitive way. table, promises. Out-of-the-box visualizations include area charts, line charts, bar charts, pie charts and tables. Contribute to plotly/dash-table development by creating an account on GitHub. Ask Question Asked 3 years, 6 I am working with plotly offline and am able to generate an html file using. Contents. Data needs to be parsed and intuitively understood before you can use it for modeling and extracting insights. ampvis2 and Plotly. Matplotlib is a fine graphing library, and is the backend to many other packages that Welcome to part four of the web-based data visualization with Dash tutorial series. The goal in learning Plotly was for me was to eliminate the Excel-VBA dashboard I created using for my manager. 2 plotly. It generates an html file for me, but I am having trouble opening it, and when I open it with chrome, it says the page is unresponsive and offers to kill the process. plot. Bind a data frame to a plot; Select variables to be plotted and variables to define the presentation such as size, shape, color, transparency, etc. Once these are created, we will be able to create the data visualization of the high mpg data and view the top choices for 4, 6, and cylinder vehicles in city and highway driving for the best mpg. Create dashboards using the Chart Studio data visualization tool . install. Render scenes Plotting with matplotlib table is now supported in DataFrame. Explorer example custom data visualizations. Ýou can access the chart studio by clicking on the 'edit in chart studio' icon above the chart. × I am having trouble plotting a table with plotly using a . Next, I want to show a more practical example of plot. Bokeh is an interactive visualization library that targets modern web browsers for presentation. Chart Studio dashboards are a stunning way to display and share your graphs Data visualization is the presentation of data in a pictorial or graphical format. A few weeks ago, the R community went through some hand-wringing about plotting packages. 2. The simple way to draw a table is to specify table=True. The table keyword can accept bool, DataFrame or Series. Render scenes Once you've run your query, immediately below you can perform inline data visualization with the minimal drag-and-drop interface. Plotly's team maintains the fastest growing open-source visualization libraries for R, Python, and JavaScript. Here are the steps to take to convert your visualization into an interactive tweet. Data visualization is just a wise investment in your future big-data needs. Data will be transposed to meet matplotlib’s default layout. Here is a guide to making a python graph Chapter 1 Data Visualization with ggplot2. It is a React port of the jQuery-based PivotTable. 2 for statistical computation. The best way to become an expert is to act like one. See schema() for a list of acceptable attributes for a given trace type (by going to traces -> type -> attributes ). Usually, the items being compared are placed in a column, while the categorical objects are in the rows. Plotly originally provided functionality in the form of a JavaScript library built on top of D3. display function I am going to start with a brief introduction to Data Visualization and better define the scope and meaning of interactiveness as intended in this article. This book is packed with practical recipes, designed to provide you with all the guidance needed to get to grips with data visualization using R. Install In the terminal sudo pip install plotly 2. If you enjoy our free exercises, we’d like to ask you a small favor: Please help us spread the word about R-exercises. In this tutorial, we're going to be create live updating graphs with Dash and Python. react-pivottable is part of Plotly's React Component Suite for building data visualization Web apps and products. KNIME 3 charting with Plotly. Dash DataTable is an interactive table component designed for viewing, editing, and exploring large datasets. r-exercises. js to build custom data visualization apps. PACKAGE INSTALLATION & DATA. May 14, 2019 How to use Python and Plotly for statistical visualization, inference, and Table 2 . How to create a subplot with tables and   Nov 2, 2018 DataTable is rendered with standard, semantic HTML <table/> markup, which makes it accessible, responsive, and easy to style. js and later branched out into frontends for other languages like R, MATLAB and, of course, Python. 0), rlang, crosstalk, purrr, data. 1 Why interactive web graphics from R?. Marco Ghislanzoni's Blog. Each library provides custom options and it is hard to compare them. . csv file with 2000 rows by 5 columns. Visualizations in R. The plot is interactive and drawn with D3. May 25, 2017 We look at 22 free tools that will help you use visualization and analysis Plotly aims at statistical analysis along with charts and graphs you might charts, tables and pivot tables -- formats familiar to most spreadsheet users. The pandas package offers spreadsheet functionality, but because you’re working with Python, it is much faster and more efficient than a traditional 8 Best Data Visualization Tools of 2019 1. Learn how to create scatter plots, density plots, histograms, and more. In Plotly. It provides a service to change style and data of your chart after generation, which is called the chart studio. As Wickham and Grolemund argue, the exploratory phase of a data science workflow (Figure 1. Here is an example of Bar charts: In this exercise, you'll use plotly to create a bar chart from scratch in order to explore the distribution of the video game genres represented in games sold between 1980 and 2016. Plotly is a web-based service by default, but you can use the library offline in Python and upload plots to Plotly's free, public server or paid, private server. I will then provide a quick overview of the tools involved (Plotly and ipywidgets) plus some generic suggestions around the Jupyter ecosystem. Highcharter. js by the same author. I want to create a report page that will display a chart of IBM for 2010:2011 and a table with Valuation Measures from Key Statistics Yahoo Finance webpage. XPlot - F# Data Visualization Package. In addition to the Databricks visualizations, R notebooks can use any R visualization package. Statistical summary for categorical or string variables will  Jan 14, 2016 Plotly's Top Ten Graphs, Charts and Visualizations of 2015 Happy New Year Everyone! We decided to Periodic Table of Elements Learn how  Jan 5, 2017 Table of Contents. py is an interactive, open-source, and JavaScript-based graphing library for Python. From the humble bar chart to intricate 3D network graphs, Plotly has an extensive range of publication-quality chart types. Plotly has a new R API and ggplot2 library for making beautiful graphs. The 14 best data visualization tools. How long do you think you will take to explain it to him? With ever When it comes to interactive Python visualization tools, Plotly has a top place here. The library provides a complete mapping for the configuration options of the underlying libraries and so you get a nice F# interface that gives you Data Visualization in R using ggplot2 Deepanshu Bhalla 5 Comments R For the purpose of data visualization, R offers various methods through inbuilt graphics and powerful packages such as ggolot2. react-pivottable is a React-based pivot table library with drag'n'drop functionality. Dash is an open source framework created by the plotly team that leverages Flask, plotly. Visualization and Exploratory Analysis. ly – which provides its own Java visualization library and Java wrapper. 7. py is to provide a pleasant Python interface for creating figure specifications for display in the Plotly. 7,799. Plotly is a FSharp wrapper for Plotly. The first thing you have to do is install and load the plotly package with: Tableau, Infogram, Palladio, Plotly and Raw are just a few of the freely available visualization tools. Dr. How easy is Dash to use? In around an hour and with <100 lines of code, I created a dashboard to display live streaming data for my Data Science Workflows using Docker Containers talk. Keen is compatible with common charting libraries like C3. In this tutorial we are going to make a first step in plotly’s world by learning to create some basic charts enhanced with proper layouts that the plotly package provides. I believe, this article itself is sufficient to get started with plotly in whichever language you prefer: R or Python. The R package allows you to easily translate ggplot2 graphics to an interactive web-based version. Plotly has always been incredibly intuitive. Background. 1) requires lots of iteration between data manipulation, visualization, and modeling. Simply pick your chart type and drag the variables to the appropriate axis. We’ll be using Plotly’s recently open sourced library and connecting it to a IPython/Pandas setup with cufflinks. 3. Tuck Ngun provides an in-depth look at creating data visualizations in matplotlib. Plotly’s Python free and open source graphing library help you create interactive, publication-quality graphs easily online. This function may become quite handy during the exploration of any dataset. However, when you take them to Power BI Desktop, no graph is generated. Let us look at this chart for a second, This visualization (originally created using Tableau) is a great example of how data visualization can help decision makers. Plotly. Built on top of plotly. by Nishith Sharma — in Design & Dev. DataTable is rendered with standard, semantic HTML <table/> markup, which makes it accessible, responsive, and easy to style. , tooltips and zooming), Altair benefits -- seemingly for free! Course Description. Up to this point, we've learned how to make a simple graph and how to dynamically update HTML elements in real Dash User Guide and Documentation. App Description; Here’s a simple example of a Dash App that ties a Dropdown to a D3. a plotly object Arguments (i. js and Plotly. Most styling can be specified for header, columns, rows or individual cells. Exploring data is fun! The best motivation of all things: FUN! Fun comes from curiosity and the discovery of things. 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. Use plotly offline to generate graphs as images. This example will show you how to leverage Plotly’s API for Python (and Pandas) to visualize data from a Socrata dataset. The API lets you produce interactive D3. js graphing library. Luckily, many new Python data visualization libraries have been created in the past few years to close the gap. plotly table visualization

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