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 3
Rarely 4
Sometimes 6
Regularly 4
All the time 6
a Sample size = 23

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 0 20
Java / Scala 3 0 20
Javascript / Typescript 3 0 20
Python 7 0 16
R 17 0 6
SAS 10 0 13
SPSS 11 1 11
SQL 15 0 8
Stata 5 0 18
VBA 11 0 12
a Sample size = 23

Access to programming tools

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Programming language Yes Don't know No
C++ / C# 0 19 4
Java / Scala 2 17 4
Javascript / Typescript 4 15 4
Python 17 4 2
R 22 0 1
SAS 17 4 2
SPSS 12 6 5
SQL 20 2 1
Stata 7 13 3
VBA 17 4 2
a Sample size = 23

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# 0 0 3
Java / Scala 2 0 3
Javascript / Typescript 3 1 2
Python 11 6 1
R 6 16 1
SAS 8 9 1
SPSS 6 6 5
SQL 6 14 1
Stata 5 2 3
VBA 7 10 1
a Sample size = 23

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 6 17
Data Cleaning 6 12
Data Transfer / Migration 6 9
Data Visualisation 8 14
Quality Assurance 11 11
a Sample size = 23

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 1
Slightly worse 4
No change 4
Slightly better 8
Significantly better 4
a Sample size = 21

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 2
In education 9
In private sector employment 1
In public sector employment 6
Self-taught 5
Other 0
a Sample size = 23

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 10 10 15 10 35 20
I follow a standard directory structure when programming 25 0 20 20 25 10
I follow coding guidelines or style guides when programming 10 0 15 15 55 5
I use a source code version control system e.g. Git 20 25 20 15 5 15
Code my team writes is reviewed by a colleague 15 5 10 20 40 10
I write repetitive elements in my code as functions 10 5 5 40 20 20
I collect my code and supporting material into packages 25 30 20 15 10 0
I unit test my code 30 20 15 20 10 5
I write code to automatically quality assure data 15 10 15 45 15 0
My team open sources its code 25 40 25 5 5 0
a Sample size = 20

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 20 10 20 15 25 10
Data or assumptions registers 20 10 10 30 10 20
Documentation for each function or class 20 15 30 10 10 15
Code comments 10 0 5 0 30 55
Flow charts 10 45 10 25 10 0
README files 10 5 40 5 15 25
Desk notes 10 15 5 30 15 25
a Sample size = 20

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 0
No 12
Don't know what they are 8
a Sample size = 20

Source control platform

The number of users of each source control platform.

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Version control platform Yes
GitHub 1
GitLab 9
BitBucket 0
AWS CodeCommit 0
Cloud Source Repository (Google Cloud) 0
a Sample size = 20

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 2
Heard of RAP, have not heard of RAP champions 9
Heard of RAP, does not know department champion 8
Heard of RAP champions, no champion in department 0
Knows department RAP champion 4
a Sample size = 23

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 4.8 14.3 14.3 52.4 14.3
I feel confident implementing RAP in my work 9.5 23.8 19.0 47.6 0.0
I think it is important to implement RAP in my work 0.0 9.5 23.8 33.3 33.3
I feel supported to implement RAP in my work 9.5 9.5 23.8 38.1 19.0
I know where to find resources to help me implement RAP 9.5 14.3 33.3 33.3 9.5
I and/or my team are currently implementing RAP 14.3 33.3 14.3 23.8 14.3
a Sample size = 21

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 8
Peer review Basic 10
Team open source code Basic 1
Use open source software Basic 11
Version control Basic 4
Code packages Advanced 2
Continuous integration Advanced 1
Dependency management Advanced 2
Follow code style guidelines Advanced 12
Function documentation Advanced 5
Functions Advanced 8
Unit testing Advanced 3
a Sample size = 20

Basic RAP scores

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Basic RAP score Count
0 7
1 6
2 5
3 3
4 1
5 1
a Sample size = 20

Advanced RAP scores

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Advanced RAP score Count
0 4
1 6
2 6
3 1
4 3
a Sample size = 20