Python Developer Survey Shows Data Analysis More Popular Than Web Development (jetbrains.com)
Over 20,000 programmers from more than 150 different countries provided answers for the second annual Python Developers Survey (conducted by the Python Software Foundation and JeBrains).
An anonymous reader submitted this condensed version of their results: 84% of Python users in our survey use Python as their main language...up 5 percentage points from 79% in 2017. But half of all Python users in the survey also use JavaScript, and 47% more say they use HTML/CSS. Reported use of Bash/Shell has also grown from 36% in 2017 to 45% in 2018. [Later 93% of respondents said that their activities included Software testing/Writing automated tests.] Python users who report that they also use Go and SQL have both increased by 2 percentage points, while many other languages (including C/C++, Java, and C#) have decreased their share...
When asked "What do you use Python for?" data analysis has become more popular than Web development, growing from 50% in 2017 to 58% in 2018. Machine learning also grew by 7 percentage points. These types of development are experiencing faster growth than Web development, which has only increased by 2 percentage points when compared to the previous year...
Almost two-thirds of respondents selected Linux as their development environment OS. Most people are using free or open source databases such as PostgreSQL, MySQL, or SQLite... Twenty-something was the prevalent age range among our respondents, with almost a third being in their thirties. [31% more were between the ages of 30 and 39.]
An anonymous reader submitted this condensed version of their results: 84% of Python users in our survey use Python as their main language...up 5 percentage points from 79% in 2017. But half of all Python users in the survey also use JavaScript, and 47% more say they use HTML/CSS. Reported use of Bash/Shell has also grown from 36% in 2017 to 45% in 2018. [Later 93% of respondents said that their activities included Software testing/Writing automated tests.] Python users who report that they also use Go and SQL have both increased by 2 percentage points, while many other languages (including C/C++, Java, and C#) have decreased their share...
When asked "What do you use Python for?" data analysis has become more popular than Web development, growing from 50% in 2017 to 58% in 2018. Machine learning also grew by 7 percentage points. These types of development are experiencing faster growth than Web development, which has only increased by 2 percentage points when compared to the previous year...
Almost two-thirds of respondents selected Linux as their development environment OS. Most people are using free or open source databases such as PostgreSQL, MySQL, or SQLite... Twenty-something was the prevalent age range among our respondents, with almost a third being in their thirties. [31% more were between the ages of 30 and 39.]
and due in no small part to pandas. link
if used correctly (due to its NumPy foundation) with vectorised operations it rocks
*you're
This sight has really gone downhill...
Creimette?
i sniff youre dog butthoal,
Most of the new users since perhaps around 2012 came for the data analytics side.
IPython, NumPy, SciPy had been around for a while, but with maturing Jupyter, Pandas and TensorFlow/Keras, it really caught on. Other NLP and Machine Learning libraries probably helped too.
My use of Python today is completely different from how I used it earlier, nearly two decades ago, when it was mainly seen as a better Perl, back when Perl was THE scripting language. Now it is seen as a better MATLAB or a better R, even though the base language isn't itself vectorized as the others. The language and the standard library didn't improve much towards this. It was mainly the third party libraries that emerged and matured.
Speaking purely from a language standpoint, Julia has all right features for the analytics side, but the scientific community is right now with Python.
sight
This seems like it should be obvious. Python would be way way down the list of languages I would use for web development. Python is pretty good at handling text and numbers and I sometimes use the Python interpretor as an advanced command line calculator, so it makes sense for data analysis. But why would I want to use a language like Python for web development? That's like using a dead fish as a hammer.
I guess that's different wording for that the group samples isn't representative for the population at large.
s'aight
If you want easy scripting for data mining then you simply can't beat LuaJIT. Some of my very heavy math based algorithms actually run faster in LuaJIT than compiled C code!
Nobody wants to see your Leptotyphlops carlae, buddy, not even the National Enquirer.
Creimette is too busy for you. She is a genius thinking genius thoughts
because the market has shifted, big data and data lakes, led to data scientists and now data analysis are picking up the tail-end with python being the holy-grail of metrics. instead of doing actual, you know, 'better business', it's not market standard to fudge the metrics to make it look like you are doing 'better business'.
I don't know how many times a company has changes their analytics processes, reporting processes and the infrastructure/technology behind it, on the gospel of 'metrics and reporting' is more important then actual data gathering.
I did a contract where a company was spending about 150k for onpremise CRM + tableau reporting annually, to about 1million to move it all to SFDC + mulesoft, in the end, the ROI didn't justify it the move, but because it's new data, faster analytics, mega metrics as the selling point. Now the comp is cutting 10% of their work force just to pay for all the licensing.
but hey, I made bank, so i'm happy.
So you do a survey at X (as in any) language related websites and you expected an answer different than X is the more popular?
Python is OK, but it is really just another scripting language (a fairly good one). But with any scripting language, it can be powerful when use for the right task, and a complete disaster when used for wrong reasons (like anything that requires near real-time performance).
Python & Numba gives you near realtime
The real story is that top US schools are giving rapid paths to Master's and MBA's with a strong focus on data science. These are shortcut degrees and their purpose is to allow those with diploma mill degrees from overseas to come on student visas. Just knock out your micromasters on the cheap online and it knocks out about 25-30% of the requirements for a masters or PhD.
Why the push for these programs? Because the adjustments to the H1B program emphasize people who hold high US degrees such as a Masters or PhD. Why do the universities go for it? First the programs do require some courses in probability, statistics, python, R, and depend on at least multi-variable calculus and Algebra. Second they get their highest rate of tuition on every student.
Of course they don't emphasize these programs here in the US even though you can use them. Instead they disparage online verified university courses that give certificates as not being the same as the same course taken online when registered as a student. That said you can knock out a quick degree from a foreign diploma mill as well but it will cost you more than it does overseas students, you'll have to pay extra to get it certified for acceptance in the US, and you'll have to explain why you got that foreign degree.
Seriously. Python looks and feels kinda like octave fortran and is a natural first stop when a person can't afford matlab or other commercial tech options. Needless to say your're talking about number crunching. For web dev esp. now more than ever, why wouldn't you use the language of the web ie. Javascript/nodejs?
"Consensus" in science is _always_ a political construct.