GITNUX MARKETDATA REPORT 2024
Statistics About The Average Of A List Python
The average of a list in Python can be calculated by summing all the values in the list and dividing by the total number of values.
With sources from: insights.stackoverflow.com, wakatime.com, anaconda.com, octoverse.github.com and many more
Sources
In this post, we explore a comprehensive overview of Python’s prominence in the world of programming and data science. With a myriad of statistics showcasing Python’s widespread adoption and popularity among developers and data professionals, it’s evident that Python has solidified its position as a top choice for various computational tasks. We delve into key insights such as usage percentages, developer preferences, code metrics, library preferences, and more, shedding light on why Python continues to be a leading language in the tech industry.
Statistic 1
"On average, Python is used by 41% of developers globally."
Statistic 2
"In 2021, Python was the second most loved language after Rust, with an approximate 66.7% of developers expressing their fondness."
Statistic 3
"Python is used by 70% of data scientists for data analysis."
Statistic 4
"Third-party Python Libraries, like NumPy, are used by 66% of data scientists."
Statistic 5
"Approximately 78% of people complete a Python course in three months or less."
Statistic 6
"About 32.5% of large organizations use Python for data science."
Statistic 7
"Python is the top language choice for data scientists, with 50% preferring it over others."
Statistic 8
"Python is the third most known programming language among developers worldwide, with 79.5% claiming to understand the language."
Statistic 9
"Since 2011, Python has consistently been within the top 3 most popular programming languages."
Statistic 10
"The average Python developer writes 2281 lines of code per month."
Statistic 11
"TensorFlow, a common machine learning framework, is imported in 1.98% of all Python code on GitHub."
Statistic 12
"Nearly 89.7% of data professionals used Python on a regular basis for their work."
Statistic 13
"Python’s use in academic scholarly publications has grown by about 35% since 2010."
Statistic 14
"One of the main reasons Python is extensively used is because it has a strong support community, with over 1 million questions tagged for Python on StackOverflow."
Statistic 15
"As of 2020, there are over 215k packages freely available in the Python package index, PyPi."
Statistic 16
"As for data science libraries, almost 70% of data scientists prefer to use Pandas in Python."
Statistic 17
"Python’s popularity among early-stage data scientists is high, with a full 94% of respondents indicating they use Python."
Interpretation
In conclusion, Python's widespread adoption and popularity within the developer and data science communities are evident through a multitude of statistics. With a high usage rate globally, Python is not only loved by a significant percentage of developers but is also a top choice for data analysis, machine learning, and academic research. The language's versatility, extensive libraries like NumPy and Pandas, and strong support community contribute to its continued dominance in the programming world.
Jannik Lindner
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