Coding frequency and tools

Coding frequency

We asked our respondents, “In my current role, I write code to complete my work objectives _____”.

Show chart Show table
Coding frequency Count
Never 22
Rarely 14
Sometimes 25
Regularly 40
All the time 37
a Sample size = 138

Access to and knowledge of programming languages

For each of the most popular programming languages from last year’s CARS data, we asked respondents to answer “yes”, “no” or “I don’t know” for the following statements:

  • I know how to program with this tool to a level suitable for my work
  • This tool is available to use for my work

Knowledge of programming tools

Show chart Show table
Programming language Yes Don't know No
C++ / C# 21 5 112
Java / Scala 11 5 122
Javascript / Typescript 11 5 122
Python 55 3 80
R 61 6 71
SAS 16 7 115
SPSS 29 8 101
SQL 72 5 61
Stata 14 8 116
VBA 46 8 84
a Sample size = 138

Access to programming tools

Show chart Show table
Programming language Yes Don't know No
C++ / C# 36 59 43
Java / Scala 26 69 43
Javascript / Typescript 26 68 44
Python 89 28 21
R 104 19 15
SAS 24 65 49
SPSS 34 64 40
SQL 85 36 17
Stata 21 79 38
VBA 78 40 20
a Sample size = 138

Access and knowledge gaps

We used the above data to calculate the number of respondents who have access but no knowledge, access and knowledge, and knowledge but no access for each programming language.

Show chart Show table
Programming language Access only Access and knowledge Knowledge only
C++ / C# 24 12 9
Java / Scala 19 7 4
Javascript / Typescript 18 8 3
Python 42 47 8
R 49 55 6
SAS 14 10 6
SPSS 18 16 13
SQL 23 62 10
Stata 12 9 5
VBA 35 43 3
a Sample size = 138

What are people using code for?

We asked respondents what data operations they do in their work, and whether they use code to do them.

Show chart Show table
Data operation I do this without coding I do some or all of this by coding
Data Analysis 21 104
Data Cleaning 17 81
Data Transfer / Migration 26 48
Data Visualisation 38 76
Quality Assurance 37 61
a Sample size = 138

Coding capability

We asked respondents a series of questions about whether they feel their coding ability is improving in their current role and where they first learned to code.

Change in coding ability during current role

Respondents who had coding experience outside of their current role were asked whether there has been a change in their coding ability during current employment.

Show chart Show table
Coding ability changes Count
Significantly worse 6
Slightly worse 14
No change 18
Slightly better 34
Significantly better 34
a Sample size = 106

Where respondents have learned to code

Respondents were asked whether they had coding experience outside their current role and, if so, where.

Show chart Show table
First coding experience Count
In current role 23
In education 55
In private sector employment 6
In public sector employment 14
Self-taught 25
Other 1
a Sample size = 125

Coding practices

We asked respondents to report how often they make use of each of the coding practices. Please note that while there are many different coding practices listed below, we understand that not all are proportionate for every coding project.

General coding practices

Show chart Show table
Percent
Question I don't understand this question Never Rarely Sometimes Regularly All the time
I use open source software when programming 5.2 15.5 12.1 19.8 26.7 20.7
I follow a standard directory structure when programming 22.4 7.8 10.3 21.6 28.4 9.5
I follow coding guidelines or style guides when programming 3.4 10.3 12.9 31.0 28.4 13.8
I use a source code version control system e.g. Git 11.2 22.4 19.0 19.8 13.8 13.8
Code my team writes is reviewed by a colleague 1.7 11.2 20.7 26.7 19.8 19.8
I write repetitive elements in my code as functions 3.4 9.5 13.8 18.1 29.3 25.9
I collect my code and supporting material into packages 11.2 34.5 16.4 19.0 10.3 8.6
I unit test my code 30.2 22.4 10.3 13.8 13.8 9.5
I write code to automatically quality assure data 6.0 29.3 16.4 25.0 13.8 9.5
My team open sources its code 12.1 49.1 9.5 19.0 8.6 1.7
a Sample size = 116

Documentation

Show chart Show table
Percent
Question I don't understand this question Never Rarely Sometimes Regularly All the time
Analytical Quality Assurance (AQA) logs 20.7 56.0 9.5 6.9 3.4 3.4
Data or assumptions registers 22.4 43.1 10.3 8.6 9.5 6.0
Documentation for each function or class 8.6 25.0 16.4 19.8 20.7 9.5
Code comments 1.7 6.0 3.4 6.9 34.5 47.4
Flow charts 4.3 34.5 23.3 25.9 8.6 3.4
README files 2.6 22.4 17.2 26.7 19.0 12.1
Desk notes 17.2 29.3 12.9 22.4 12.9 5.2
a Sample size = 116

Reproducible workflow packages

We asked respondents “do you use reproducible workflow packages e.g. drake, make or pymake?”.

Show chart Show table
Use reproducible workflow packages Count
Yes 11
No 64
Don't know what they are 41
a Sample size = 116

Source control platform

The number of users of each source control platform.

Show chart Show table
Version control platform Yes
GitHub 43
GitLab 22
BitBucket 22
AWS CodeCommit 0
Cloud Source Repository (Google Cloud) 2
a Sample size = 116

RAP knowledge and opinions

Knowledge of RAP and RAP champions

We asked our respondents whether they had heard of RAP and what their knowledge is of their own department RAP champion.

Show chart Show table
RAP champion knowledge Count
Have not heard of RAP 84
Heard of RAP, have not heard of RAP champions 22
Heard of RAP, does not know department champion 16
Heard of RAP champions, no champion in department 5
Knows department RAP champion 10
a Sample size = 138

Opinions on RAP

We asked our respondents who had heard of RAP the extent to which they agree with the following statements:

  • “I understand what the key components of the RAP methodology are”
  • “I feel confident implementing RAP in my work”
  • “I think it is important to implement RAP in my work”
  • “I feel supported to implement RAP in my work”
  • “I know where to find resources to help me implement RAP”
  • “I and/or my team are currently implementing RAP”

The figure and table show the percentage of respondents who picked each response option. Percentages are out of a sample of respondents who said they had heard of RAP.

Show chart Show table
Percent
Question Strongly disagree Disagree Neutral Agree Strongly agree
I understand what the key components of the RAP methodology are 5.6 20.4 16.7 50.0 7.4
I feel confident implementing RAP in my work 13.0 31.5 27.8 20.4 7.4
I think it is important to implement RAP in my work 7.4 3.7 18.5 44.4 25.9
I feel supported to implement RAP in my work 18.5 11.1 40.7 25.9 3.7
I know where to find resources to help me implement RAP 18.5 18.5 31.5 25.9 5.6
I and/or my team are currently implementing RAP 18.5 24.1 22.2 27.8 7.4
a Sample size = 54

RAP scores

RAP components

The frequencies for each RAP component below are derived from a series of questions on coding practices (see the coding practices page). These were used to calculate scores for each component (0/1) where respondents answered “regularly” or “all the time” to the relevant questions. The list of RAP components used here is based on the RAP minimum viable product guidance agreed by the RAP champions network.

Show chart Show table
Component Type Count
Documentation Basic 32
Peer review Basic 46
Team open source code Basic 12
Use open source software Basic 55
Version control Basic 32
Code packages Advanced 22
Continuous integration Advanced 22
Dependency management Advanced 34
Follow code style guidelines Advanced 49
Function documentation Advanced 35
Functions Advanced 64
Unit testing Advanced 27
a Sample size = 116

Basic RAP scores

Show chart Show table
Basic RAP score Count
0 46
1 48
2 17
3 17
4 6
5 4
a Sample size = 116

Advanced RAP scores

Show chart Show table
Advanced RAP score Count
0 26
1 27
2 20
3 17
4 8
5 9
6 5
7 4
a Sample size = 116