Google Panda is a major change to Google's search results ranking algorithm that was first released in February 2011. The change aimed to lower the rank of "low-quality sites" or "thin sites", in particular "content farms", and return higher-quality sites near the top of the search results. CNET reported a surge in the rankings of news websites and social networking sites, and a drop in rankings for sites containing large amounts of advertising. This change reportedly affected the rankings of almost 12 percent of all search results. Soon after the Panda rollout, many websites, including Google's webmaster forum, became filled with complaints of scrapers/copyright infringers getting better rankings than sites with original content. At one point, Google publicly asked for data points to help detect scrapers better. In 2016, Matt Cutts, Google's head of webspam at the time of the Panda update, commented that "with Panda, Google took a big enough revenue hit via some partners that Google actually needed to disclose Panda as a material impact on an earnings call. But I believe it was the right decision to launch Panda, both for the long-term trust of our users and for a better ecosystem for publishers." Google's Panda received several updates after the original rollout in February 2011, and their effect went global in April 2011. To help affected publishers, Google provided an advisory on its blog, thus giving some direction for self-evaluation of a website's quality. Google has provided a list of 23 bullet points on its blog answering the question of "What counts as a high-quality site?" that is supposed to help webmasters "step into Google's mindset". It has been incorporated in Google's core algorithm since year 2015. The name "Panda" comes from Google engineer Navneet Panda, who developed the technology that made it possible for Google to create and implement the algorithm. (Wikipedia).
Panda's Daily Routine | Panda's Curiosity | Wild Life | Wild Animals | Documental Series
🐼The giant panda, also known as the panda bear (or simply the panda), is a bear species endemic to China. It is characterised by its bold black-and-white coat and rotund body. The name "giant panda" is sometimes used to distinguish it from the red panda, a neighboring musteloid. Find out w
From playlist Meet Bears
What is pandas? (Introduction to the Q&A series)
pandas is a full-featured Python library for data analysis, manipulation, and visualization. This video series is for anyone who wants to work with data in Python, regardless of whether you are brand new to pandas or have some experience. Each video will answer a student question about pa
From playlist Data analysis in Python with pandas
“There should be one—and preferably only one—obvious way to do it,” — Zen of Python. I certainly wish that were the case with pandas. In reading the docs it feels like there are a thousand ways to do each operation. And it is hard to tell if they do the exact same thing or which one you
From playlist Python pandas — An Opinionated Guide
What is Pandas? (Data & Data Science) #shorts
Interested in data or data science? You should probably be familiar with pandas! Pandas is a python library used for manipulating data. It allows us to slice, group, join, and reshape data with relative ease. #DataScience #KenJee #short ⭕ Subscribe: https://www.youtube.com/c/kenjee1?su
From playlist Data Science Beginners
“There should be one—and preferably only one—obvious way to do it,” — Zen of Python. I certainly wish that were the case with pandas. In reading the docs it feels like there are a thousand ways to do each operation. And it is hard to tell if they do the exact same thing or which one you
From playlist Python pandas — An Opinionated Guide
Giant Pandas 101 | Nat Geo Wild
Giant pandas' habitat in the wild today is limited to the mountains of China, but their appetite remains unlimited. They spend nearly every waking moment eating bamboo. Learn about giant pandas and how their diet shapes their lives. ➡ Subscribe: http://bit.ly/NatGeoWILDSubscribe #NatGeoWI
From playlist Animals & Wildlife | Nat Geo Wild
Giant Panda - The Resident of Asia | See Panda Behavior | Wild Life | Wild Animals | Nature Movie
🐼 The giant panda also known as the panda bear (or simply the panda), is a bear species endemic to China. It is characterised by its bold black-and-white coat and rotund body. The giant panda lives in a few mountain ranges in central China, mainly in Sichuan, and also in neighbouring Shaan
From playlist Meet Bears
If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist Google Docs
More of your pandas questions answered!
In this video, I'm answering a few of the pandas questions I've received in the YouTube comments: 0:22 Could you explain how to read the pandas documentation? 6:25 What is the difference between ufo.isnull() and pd.isnull(ufo)? 9:27 Why are DataFrame slices inclusive when using .loc, but e
From playlist Data analysis in Python with pandas
!!Con 2016 - How to trick a neural network! By Julia Evans
How to trick a neural network! By Julia Evans I used to think neural networks were magical black boxes that I could never understand. And they kind of are! But in this talk, we're going to trick an awesome smart neural network, trained by Google, into thinking a panda is a vulture. Live.
From playlist !!Con 2016
pandas is more than 10 years old now. In this time, it became almost a standard for building data pipelines and perform data analysis in Python. As the popularity of the project grows, it also grows the number of projects that depend or interact with pandas. This talk will cover this ecos
From playlist Python
Python pandas—Time Series Exercises—Apple Stock
Sometimes we learn best by doing. Unlike my other videos, I’ll be going through these exercises cold. Sometimes we’ll encounter ambiguous questions, and sometimes I'll be wrong. Learning from our mistakes can be a powerful teacher. So, it’s OK to be wrong now, because we’ll know how to avo
From playlist Python pandas -- Learning by doing
Install new Spark 3.2 on Google Colab - latest PySpark code update
Short "How-to-install" video on: brand new SPARK 3.2 running on free Google Colab. Simple install process and a. test for spark dataframe plus b. test the new Pandas-on-Spark API. code-in-real-time real time coding Databricks Apache Spark 3.2 #PandasAPI #Pandas_on_Spark #COLAB instal
From playlist Large-scale data analytics and data science: Apache Spark w/ PySpark
“There should be one—and preferably only one—obvious way to do it,” — Zen of Python. I certainly wish that were the case with pandas. In reading the docs it feels like there are a thousand ways to do each operation. And it is hard to tell if they do the exact same thing or which one you
From playlist Python pandas — An Opinionated Guide
Jordan Hagan: Optimizing SQL + Python Pipelines for Data Science
Poorly written SQL and Python can make data extraction and manipulation tedious and painful. Streamlined processes utilizing SQL best practices will save hours of frustration. My goal is to teach attendees proven SQL methodologies and what python tools to use when.
From playlist PyColorado 2019
Pandas with Python 2.7 Part 1 - Downloading and dependencies
Welcome to the introduction of my Pandas module tutorial video. The Pandas module is a massive collaboration of many modules along with some unique features to make a very powerful module. Pandas is great for data manipulation, data analysis, and data visualization. Here, we cover download
From playlist Pandas with Python 2.7
Python and Pandas for Sentiment Analysis and Investing 6 - Basics for a Strategy
Full Python + Pandas + Sentiment analysis Playlist: http://www.youtube.com/watch?v=0ySdEYUONz0&list=PLQVvvaa0QuDdktuSQRsofoGxC2PTSdsi7&feature=share This series uses python with Pandas for data analysis. Our data set will be a database dump from Sentdex.com sentiment analysis, containi
From playlist Python with Pandas and Sentiment Analysis for Investing
Pandas Apply Exercises—US Crime Rates
Maybe the main take away here is even “real data scientists” with a decade of experience sometimes ride the struggle bus. So, when you’re on the struggle bus give yourself some grace. Don’t give up. We ALL struggle sometimes. Sometimes we learn best by doing. Unlike my other videos,
From playlist Python pandas -- Learning by doing
Indexing and Selecting - Pandas
“There should be one—and preferably only one—obvious way to do it,” — Zen of Python. I certainly wish that were the case with pandas. In reading the docs it feels like there are a thousand ways to do each operation. And it is hard to tell if they do the exact same thing or which one you
From playlist Python pandas — An Opinionated Guide