Areas of Expertise

In the course of questions and answers participants get reputation points, while the system defies their so to say primary areas of expertise (programming languages, frameworks, technologies). Based on this information one can build a picture of interest, popularity and/or usability.

Combining this information with other detail one can get more complete picture.

Top 10 list of assigned areas of expertise looks like:

If we will refine it to languages the list will look like:

Looking how much assigned AOE corresponds to number and sum of gold, silver and bronze badges we get:


gold

silver

bronze


count

sum

count

sum

count

sum

c#

5298

26066

25736

263239

89539

939706

java

4639

20323

24526

210789

102866

878861

javascript

3956

19070

21891

191944

95742

803849

php

2888

13357

17714

140253

85629

668528

net

3493

17214

16147

169797

56771

589661

sql

2564

11276

14136

112936

78403

563798

python

1972

9869

12399

112161

52977

443391

c++

1953

9019

11631

111772

46767

435483

html

1506

6702

9552

67381

57104

391183

ruby

1255

5407

9003

74244

29518

266255


The area vs reputation ranking


So, as can see here we have substantial order change depending on the characteristics. Somehow the site users more value Microsoft languages (c#,.net) than others, or looking at the picture from another angle, people using/interested in Microsoft technologies are more willing to acknowledge their value.

Exercise your guess:

Overall distribution of questions by languages (top 10) looks like:

What language had

the biggest:
the smallest:
c# java js php .net sql python c++ html ruby
fraction of unanswered questions?

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