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phantomstatistician · 12 hours ago

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Fandom: Cars

Sample Size: 836 stories

Source: AO3

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emergingindiaanalyticsnoida · 2 years ago

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Different Job Profiles in Data Science:

Introduction:

If you have made your mind about Data Science as a career field, you must have the knowledge regarding the different job opportunities available. This article is aimed to walk you through different job profiles in data Science. It will also shed a light on the responsibilities they entail and remuneration you will get.

Data Engineer

Responsibilities:

The primary responsibility of a data engineer is to capture data and feed it to Data Scientists. He is also responsible for creating infrastructure that allows the storage of data.

Requisite Skills:

Software engineering and Programming skills

Knowledge of database systems (SQL and NoSQL)

Data modeling and ETL tools

Expertise in R, Pig, MATLAB, Hive, SAS, Java, Python, Ruby, and Perl

Salary:

A data engineer can earn up to ₹1,270,879 per year in India.

Data Analyst:

Responsibilities:

A Data Analyst’s job is to perform a statistical analysis of the data and provide data based solutions for the growth and extension of the business.

Requisite Skills:

Data cleaning

Data visualization

Knowledge of database systems (SQL and NoSQL )

Statistics

Probability

Understanding of Python, R, HTML, JavaScript, C/C++, and SQL

Salary:

They can earn up to ₹875,249 per year in India.

Data Scientist

Responsibilities:

This position entails the responsibility to extract meaningful insights from data by visualization. These insights are then used to build predictive models and ML algorithms for automated systems.

Requisite Skills:

Machine Learning

Deep Learning

Statistics

Data Analysis

Data mining

Salary:

A data scientist in India can earn up to ₹978,625 per year.

Business Analyst

Responsibilities:

Their primary responsibility is to reduce the gap between technology and business. They gather business related data and apply it to construct operational procedures that help in the development of a business.

Requisite Skills:

Knowledge of Data visualisation tools.

Statistics

SQL

Data Visualization

Business Intelligence

Salary:

A Business Analyst in India can earn up to ₹1,745,264 per year.

Statistician

Responsibilities:

Their responsibility is to apply statistical concepts in analysis and interpretation of data

Requisite Skills:

Knowledge of Statistical Concepts

R, Python, SQL, SAS, Spark and Hive.

Hadoop

Data Mining

Salary:

They can earn an average of ₹489,234 per year in India.

#data science #data scientist #phantom statistician #business analyst #data analyst #data engineers

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buffydataviz · 1 year ago

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Tutorial for basic data on AO3 Top Ships

Earlier (while researching the BTVS Goncharov Index) I stumbled across the fact that Giles x Buffy is now #3 on the ship list for number of AO3 works! This is a change from before, the old top 5 in order were Spuffy, Spander, Bangel, Tillow, and Fuffy. I wanted to check the ranking of BTVS ships.

Ignoring the crossover effect (which is not too bad for BTVS ships), there is a very easy way to check what are the top ships on AO3. If you don't know how to do this, keep reading for simple directions and screenshots. I'll do another post with the Top 20+ ship results!

Pick your fandom on AO3, in this case "Buffy the Vampire Slayer (TV)." You want the screen that lists all the works. Today there are 38K works for BTVS (TV). It looks like this:

(The default is sorted by Date Updated. Don't get distracted from your research by the new-to-you fic! Research!)

2. On the right hand side, under the Include section, click on the triangle by Relationships to expand it. It will show the top 10 ships. Next to each ship in parenthesis is the number of works.

3. Let's say you are bored by the top 5 (or 10) and want to dig into the even more rare ships. This is when the Exclude section is helpful. The Exclude section is under the Include section. Scroll down to it, expand the Relationships. Now click on the X, it will turn red once you exclude that ship. In the image I've excluded the top 4. Once you are done, click on Sort and Filter back up at the top.

4. The number of works will drop dramatically. Excluding the top 10 ships I end up with 22K works. Repeat the second step to expand the Relationships. You will find a new batch of 10 ships!

If you want to dig in on AO3 data, Destination Toast has a detailed tutorial that gets into more advanced stuff. I highly recommend it!

If you have a burning interest in non-Buffy fandom stats, but don't want to do the work yourself, you could nicely ask phantom statistician for some results. (You may have to wait a while, there's a long list of requests.) There is already a lot posted, so perhaps your question is already answered there. (She can use both AO3 and FFN as data sources.)

Shout out to Phantom Statistician who created the original pie chart of top ships in BTVS back in 2020, which is how I knew what the previous top 5 ships were.

And I know I've said it before, but while using AO3 data is easy, it does not include all fanworks, or even all fanfic for BTVS. Since Buffy went off the air before AO3 started, lots of works are on other websites and/or lost.

Also Elysian Fields is a huge long-standing Spuffy-only fanfic site, so focusing only on AO3 undercounts the amount of Spuffy fanworks. Even with that undercounting, Spuffy is still the number one BTVS ship on AO3.

#how to #btvs data #buffy the vampire slayer data #data source: AO3 #top btvs ships

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sethshead · 2 years ago

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“I’ve seen some variation of this rant a few times:

“‘I survived lead paint, wooden spoons, no seatbelts, no helmets, second hand smoke, playing unsupervised, drinking from the hose, and riding in the back of a truck.’

“This ‘you kids that I raised are soft and it’s all your fault’ nostalgia misses something in the quest to make asbestos great again; a lot of people didn��t survive this fuckery.

“Today’s Moment of Science… Survivorship bias & phantom bullet holes.

“We like to think that we’re rational thinkers, able to spot logical fallacies out in the wilderness. But what happens when the cause of your logical fallacy is information that’s long gone? This is a kind of selection bias known as survivorship bias, and it’s annoyingly common.

“‘Old houses were better constructed.’ Or you only see the sturdiest of the old ones today because nobody made an effort to save the 14th century shacks.

“‘Music from back in the day is standing the test of time.’ There’s caterwauling that deserves its fate buried in the bowels of music history from every era, I’m afraid.

“‘You can become a billionaire without going to college if you just work hard and read books, look at this tech bro who I think is irl Tony Stark.’

“Truly, I enjoy an inspiring story about not having student loan debt as much as the next millennial going through an existential crisis. But every story of someone who got rich or famous tells the quieter story of far more people who wanted it just as badly, tried, and failed.

“So, airplanes.

“Abraham Wald was a Hungarian Jew who fled Europe for the US in the late 1930s because of that whole ‘Hitler was a murderous cockface’ thing. He had his PhD in mathematics and went to work for the Statistical Research Group (SRG) at Columbia University. The SRG has been described as a collection of the ‘most extraordinary group of statisticians ever organized.’

“Planes kept coming back from the war with bullet holes in a certain pattern, if they came back at all. Damage clustered around the wing tips and tail. Weight needed to be kept low while giving the plane more protection, and the areas that had sustained a lot of fire seemed like the obvious places to armor up. Right?

“But Wald suggested that planes were likely to be hit fairly evenly, not that the enemy fire was clustering around these spots tactically. He considered the data he didn’t have: the planes that never came home. Where were they being hit?

“If he was right that planes took fire everywhere, then the planes should be armored heavily where the surviving planes hadn’t taken damage. The engine and the cockpit came back seemingly unscathed every time in otherwise bullet ridden planes. Those areas were subsequently fortified.

“It’s a good lesson in survivorship bias. And saved untold lives.

“Abraham Wald’s work contributed considerably to the burgeoning field of operational research. Because of his immigration status, he reportedly wasn’t able to get a security clearance or even look at the final reports he contributed to. He died in a plane crash in 1950 on the way to India for a lecture tour at just 48 years old.

“This has been your Moment of Science, never sure I have all the data.

“To get the MOS delivered to your inbox every weekday with rocket scientist orgies, NASA funded dolphin handjobs, and friggin… Australia… head to patreon.com/scibabe.”

h/t SciBabe

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riverkingmarley · 6 months ago

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its a shame how few polysiders fics there are but god bless jademonarch and glaisne for keeping us fee

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phantomstatistician · 3 days ago

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