Coding frequency and tools

Coding frequency

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

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Coding frequency Count
Never 37
Rarely 31
Sometimes 33
Regularly 44
All the time 21
a Sample size = 166

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

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Programming language Yes Don't know No
C++ / C# 3 13 150
Java / Scala 3 12 151
Javascript / Typescript 6 13 147
Python 57 7 102
R 70 5 91
SAS 54 8 104
SPSS 120 3 43
SQL 46 8 112
Stata 26 10 130
VBA 16 12 138
a Sample size = 166

Access to programming tools

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Programming language Yes Don't know No
C++ / C# 1 110 55
Java / Scala 12 105 49
Javascript / Typescript 5 110 51
Python 119 32 15
R 141 18 7
SAS 82 51 33
SPSS 105 28 33
SQL 80 61 25
Stata 53 74 39
VBA 41 91 34
a Sample size = 166

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.

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Programming language Access only Access and knowledge Knowledge only
C++ / C# 1 0 3
Java / Scala 10 2 1
Javascript / Typescript 4 1 5
Python 63 56 1
R 76 65 5
SAS 40 42 12
SPSS 21 84 36
SQL 43 37 9
Stata 36 17 9
VBA 25 16 0
a Sample size = 166

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.

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Data operation I do this without coding I do some or all of this by coding
Data Analysis 42 106
Data Cleaning 24 74
Data Transfer / Migration 26 30
Data Visualisation 69 53
Quality Assurance 70 75
a Sample size = 166

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.

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Coding ability changes Count
Significantly worse 14
Slightly worse 20
No change 24
Slightly better 28
Significantly better 28
a Sample size = 114

Where respondents have learned to code

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

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First coding experience Count
In current role 41
In education 61
In private sector employment 5
In public sector employment 25
Self-taught 12
Other 1
a Sample size = 150

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

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Percent
Question I don't understand this question Never Rarely Sometimes Regularly All the time
I use open source software when programming 12.4 20.9 12.4 17.8 20.2 16.3
I follow a standard directory structure when programming 38.0 7.0 5.4 20.9 21.7 7.0
I follow coding guidelines or style guides when programming 7.0 9.3 14.0 30.2 32.6 7.0
I use a source code version control system e.g. Git 17.1 41.9 15.5 11.6 9.3 4.7
Code my team writes is reviewed by a colleague 1.6 8.5 10.9 29.5 24.8 24.8
I write repetitive elements in my code as functions 7.8 15.5 15.5 33.3 20.2 7.8
I collect my code and supporting material into packages 17.8 43.4 15.5 8.5 11.6 3.1
I unit test my code 42.6 20.9 8.5 13.2 7.8 7.0
I write code to automatically quality assure data 6.2 34.9 22.5 20.2 10.1 6.2
My team open sources its code 27.9 48.1 10.1 8.5 5.4 0.0
a Sample size = 129

Documentation

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Percent
Question I don't understand this question Never Rarely Sometimes Regularly All the time
Analytical Quality Assurance (AQA) logs 23.3 41.9 10.9 10.1 8.5 5.4
Data or assumptions registers 28.7 34.9 10.9 13.2 8.5 3.9
Documentation for each function or class 18.6 32.6 10.9 22.5 10.1 5.4
Code comments 4.7 7.8 3.1 10.1 28.7 45.7
Flow charts 9.3 43.4 17.1 20.9 7.0 2.3
README files 11.6 42.6 14.0 17.8 11.6 2.3
Desk notes 11.6 17.8 10.1 26.4 21.7 12.4
a Sample size = 129

Reproducible workflow packages

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

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Use reproducible workflow packages Count
Yes 1
No 54
Don't know what they are 74
a Sample size = 129

Source control platform

The number of users of each source control platform.

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Version control platform Yes
GitHub 31
GitLab 26
BitBucket 0
AWS CodeCommit 0
Cloud Source Repository (Google Cloud) 4
a Sample size = 129

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.

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RAP champion knowledge Count
Have not heard of RAP 79
Heard of RAP, have not heard of RAP champions 37
Heard of RAP, does not know department champion 36
Heard of RAP champions, no champion in department 3
Knows department RAP champion 10
a Sample size = 166

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.

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Percent
Question Strongly disagree Disagree Neutral Agree Strongly agree
I understand what the key components of the RAP methodology are 10.3 32.2 16.1 36.8 4.6
I feel confident implementing RAP in my work 29.9 31.0 18.4 16.1 4.6
I think it is important to implement RAP in my work 2.3 10.3 31.0 36.8 19.5
I feel supported to implement RAP in my work 11.5 28.7 43.7 13.8 2.3
I know where to find resources to help me implement RAP 16.1 37.9 25.3 17.2 3.4
I and/or my team are currently implementing RAP 19.5 24.1 31.0 21.8 3.4
a Sample size = 87

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.

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Component Type Count
Documentation Basic 17
Peer review Basic 64
Team open source code Basic 7
Use open source software Basic 47
Version control Basic 18
Code packages Advanced 19
Continuous integration Advanced 12
Dependency management Advanced 14
Follow code style guidelines Advanced 51
Function documentation Advanced 20
Functions Advanced 36
Unit testing Advanced 19
a Sample size = 129

Basic RAP scores

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Basic RAP score Count
0 78
1 47
2 24
3 11
4 5
5 1
a Sample size = 129

Advanced RAP scores

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Advanced RAP score Count
0 58
1 27
2 16
3 11
4 9
5 6
6 1
7 1
a Sample size = 129