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• WebRTC books – a brief review

  1er janvier 2014, par silvia

  I just finished reading Rob Manson’s awesome book “Getting Started with WebRTC” and I can highly recommend it for any Web developer who is interested in WebRTC.

  Rob explains very clearly how to create your first video, audio or data peer-connection using WebRTC in current Google Chrome or Firefox (I think it also now applies to Opera, though that wasn’t the case when his book was published). He makes available example code, so you can replicate it in your own Web application easily, including the setup of a signalling server. He also points out that you need a ICE (STUN/TURN) server to punch through firewalls and gives recommendations for what software is available, but stops short of explaining how to set them up.

  Rob’s focus is very much on the features required in a typical Web application :

  • video calls
  • audio calls
  • text chats
  • file sharing

  In fact, he provides the most in-depth demo of how to set up a good file sharing interface I have come across.

  Rob then also extends his introduction to WebRTC to two key application areas : education and team communication. His recommendations are spot on and required reading for anyone developing applications in these spaces.

  —

  Before Rob’s book, I have also read Alan Johnson and Dan Burnett’s “WebRTC” book on APIs and RTCWEB protocols of the HTML5 Real-Time Web.

  Alan and Dan’s book was written more than a year ago and explains that state of standardisation at that time. It’s probably a little out-dated now, but it still gives you good foundations on why some decisions were made the way they are and what are contentious issues (some of which still remain). If you really want to understand what happens behind the scenes when you call certain functions in the WebRTC APIs of browsers, then this is for you.

  Alan and Dan’s book explains in more details than Rob’s book how IP addresses of communication partners are found, how firewall holepunching works, how sessions get negotiated, and how the standards process works. It’s probably less useful to a Web developer who just wants to implement video call functionality into their Web application, though if something goes wrong you may find yourself digging into the details of SDP, SRTP, DTLS, and other cryptic abbreviations of protocols that all need to work together to get a WebRTC call working.

  —

  Overall, both books are worthwhile and cover different aspects of WebRTC that you will stumble across if you are directly dealing with WebRTC code.

• How Media Analytics for Piwik gives you the insights you need to measure how effective your video and audio marketing is – Part 1

  31 janvier 2017, par InnoCraft — Community

  Do you have video or audio content on your website or in your app ? If you answered this with yes, you should continue reading and learn everything about our Media Analytics premium feature.

  When you produce video or audio content, you are either spending money or time or often both money and time on your content in the hope of increasing conversions or sales. This means you have to know how your media is being used, when it is used, for how long and by whom. You can simply not afford not to know how this content affects your overall business goals as you are likely losing money and time by not making the most out of it. Would you be able to answer any of the above questions ? Do you know whether you can justify the cost and time for producing them, which videos work better than others and how they support your marketing strategy ? Luckily, getting all these insights is now so trivial it is almost a crime to not measure it.

  Getting Media Analytics and Installation

  Media Analytics can be purchased from the Piwik Marketplace where you find all sorts of free plugins as well as several premium features such as A/B Testing or Funnel. After the purchase you will receive a license key that you can enter in your Piwik to install and update the plugin with just one click.

  The feature will in most cases automatically start tracking your media content and you don’t even need to change the tracking code on your website. Currently supported players are for example YouTube, Vimeo, HTML 5, JW Player, VideoJS and many more players. You can also easily extend it by adding a custom media player or simply by letting us know which player you use and we will add support for it for you.

  By activating this feature, you get more than 15 new media reports, even more exportable widgets, new segments, APIs, and more. We will cover some of those features in this blog post and in part 2. For a full list of features check out the Media Analytics page on the Piwik Marketplace.

  Media Overview

  As the name says, it gives you an overview over your media usage and how it performs over time. You can choose any media metrics in the big evolution graph and the sparklines below give you an overview over all important metrics in a glance.

  

  It lets you for example see how often media was shown to your users, how often users start playing your media, for how long they watched it, how often they finished it, and more. If you see some spikes there, you should definitely have a deeper look at the other reports. When you hover a metric, it will show you a tooltip explaining how the data for this is collected and what it means.

  Real-Time Media

  On the Real-Time page you can see how your content is being used by your visitors right now, for example within the last 30 minutes, last 60 minutes and last 24 hours.

  It shows you how many plays you had in the last minutes, for how long they played it, and it shows you currently most popular media titles. This is great to discover which media content performs best right now and lets you make decisions based on user behaviour that is happening right now.

  

  Below you can see our Audience Real-Time Map that shows you from where in the world your media is being played. A bigger circle indicates that a media play happened more recently and of course you can zoom in down to countries and regions.

  

  All the reports update every few seconds so you can always have a look at it and see in just a second how your content is doing and how certain marketing campaigns affect it. All these real-time reports can be also added as widgets to any of your Piwik Dashboards and they can be exported for example as an iframe.

  Video, Audio and Media Player reports

  Those reports come with so many features, we need a separate blog post and cover this in part 2.

  Events

  Media Analytics will automatically track events so you can see how often users pressed for example play or pause, how often they resumed a video and how often they finished a video. This helps you better understand how your media is being used.

  

  For example in the past we noticed a couple of videos with lots of pause and resume events. We then had a look at the Audience Log – which we will cover next – to better understand why visitors paused the videos so often. We then realized they did this especially for videos that were served from a specific server and because the videos were loading so slow, users often pressed pause to let the media buffer, then played the media for a few seconds and then paused it again as they had to wait for the video to load. Moving those videos to another, faster server showed us immediate results in the number of pauses going down and on average visitors watched the videos for much longer.

  Audience Log

  At InnoCraft, we understand that not only aggregated metrics matter but also that you often need the ability to dig into your data and “debug” certain behaviours to understand the cause for some unusual high or low metrics. For example you may find out that many of your users often pause a video, then you wonder how each individual user behaved so you can better understand the why.

  

  The audience log shows you a detailed log of every visitor. You can chronologically see every action a visitor has performed during their whole visit. If you click on the visitor profile link, you can even see all visits of a specific visitor, and all actions they have ever performed on your website.

  This lets you ultimately debug and understand your visitors and see exactly which actions they performed before playing your media, which media they played, how they played your media, and how they behaved after playing your media.

  The visitor log of course also shows important information about each visitor like where they came from (referrer), their location, software, device and much more information.

  Audience Map

  The Audience Map is similar to the Real-Time Map but it shows you the locations of your visitors based on a selected date range and not in real time. The darker the blue, the more visitors from that country, region or city have interacted with your media.

  

  Coming in part 2

  In the next part we will cover which video, audio and media player reports Media Analytics provides, how segmenting gives you insights into different personas, and how nicely it integrates into Piwik.

  How to get Media Analytics and related features

  You can get Media Analytics on the Piwik Marketplace. If you want to learn more about this feature, you might be also interested in the Media Analytics User Guide and the Media Analytics FAQ.

• How to visualize matplotlib animation in Jupyter notebook

  23 avril 2020, par anonymous13

  I am trying to create a racing bar chart similar to the one in the link (https://towardsdatascience.com/bar-chart-race-in-python-with-matplotlib-8e687a5c8a41). 
However I am unable to see the animation in my Jupyter notebook

  



  code

  



  import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import matplotlib.animation as animation
from IPython.display import HTML

df = pd.read_csv('https://gist.githubusercontent.com/johnburnmurdoch/4199dbe55095c3e13de8d5b2e5e5307a/raw/fa018b25c24b7b5f47fd0568937ff6c04e384786/city_populations', 
                 usecols=['name', 'group', 'year', 'value'])

current_year = 2018
dff = (df[df['year'].eq(current_year)]
       .sort_values(by='value', ascending=True)
       .head(10))

colors = dict(zip(
    ['India', 'Europe', 'Asia', 'Latin America',
     'Middle East', 'North America', 'Africa'],
    ['#adb0ff', '#ffb3ff', '#90d595', '#e48381',
     '#aafbff', '#f7bb5f', '#eafb50']
))
group_lk = df.set_index('name')['group'].to_dict()


fig, ax = plt.subplots(figsize=(15, 8))
def draw_barchart(year):
    dff = df[df['year'].eq(year)].sort_values(by='value', ascending=True).tail(10)
    ax.clear()
    ax.barh(dff['name'], dff['value'], color=[colors[group_lk[x]] for x in dff['name']])
    dx = dff['value'].max() / 200
    for i, (value, name) in enumerate(zip(dff['value'], dff['name'])):
        ax.text(value-dx, i,     name,           size=14, weight=600, ha='right', va='bottom')
        ax.text(value-dx, i-.25, group_lk[name], size=10, color='#444444', ha='right', va='baseline')
        ax.text(value+dx, i,     f'{value:,.0f}',  size=14, ha='left',  va='center')
    # ... polished styles
    ax.text(1, 0.4, year, transform=ax.transAxes, color='#777777', size=46, ha='right', weight=800)
    ax.text(0, 1.06, 'Population (thousands)', transform=ax.transAxes, size=12, color='#777777')
    ax.xaxis.set_major_formatter(ticker.StrMethodFormatter('{x:,.0f}'))
    ax.xaxis.set_ticks_position('top')
    ax.tick_params(axis='x', colors='#777777', labelsize=12)
    ax.set_yticks([])
    ax.margins(0, 0.01)
    ax.grid(which='major', axis='x', linestyle='-')
    ax.set_axisbelow(True)
    ax.text(0, 1.12, 'The most populous cities in the world from 1500 to 2018',
            transform=ax.transAxes, size=24, weight=600, ha='left')
    ax.text(1, 0, 'by @pratapvardhan; credit @jburnmurdoch', transform=ax.transAxes, ha='right',
            color='#777777', bbox=dict(facecolor='white', alpha=0.8, edgecolor='white'))
    plt.box(False)

draw_barchart(2018)

import matplotlib.animation as animation
from IPython.display import HTML
fig, ax = plt.subplots(figsize=(15, 8))
animator = animation.FuncAnimation(fig, draw_barchart, frames=range(1968, 2019))
HTML(animator.to_jshtml()) 



  



  Below is what I tried using and the errors

  



  HTML(animator.to_jshtml())  <-- Static output with buttons unable to visualize animation
plt.rcParams["animation.html"] = "jshtml"  <- no error and output
HTML(animator.to_html5_video())  <---Requested MovieWriter (ffmpeg) not available 



  



  Note I have FFmpeg installed in my system.
Can you help me with the issue