We asked our respondents, “In my current role, I write code to complete my work objectives _____”. Most of respondents either coded regularly or all the time.
Show chart Show table| Coding frequency | Count |
|---|---|
| Never | 160 |
| Rarely | 137 |
| Sometimes | 216 |
| Regularly | 315 |
| All the time | 232 |
| a Sample size = 1060 |
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:
Most common programming tool was R followed by SQL.
Show chart Show table| Programming language | Yes | Don't know | No |
|---|---|---|---|
| C++ / C# | 97 | 56 | 907 |
| Java / Scala | 75 | 56 | 929 |
| Javascript / Typescript | 100 | 59 | 901 |
| Python | 390 | 36 | 634 |
| R | 620 | 29 | 411 |
| SAS | 336 | 47 | 677 |
| SPSS | 410 | 49 | 601 |
| SQL | 567 | 42 | 451 |
| Stata | 163 | 58 | 839 |
| VBA | 317 | 52 | 691 |
| a Sample size = 1060 |
The programming tools with the greatest access were R and Python respectively.
Show chart Show table| Programming language | Yes | Don't know | No |
|---|---|---|---|
| C++ / C# | 102 | 580 | 378 |
| Java / Scala | 116 | 601 | 343 |
| Javascript / Typescript | 150 | 592 | 318 |
| Python | 662 | 227 | 171 |
| R | 863 | 107 | 90 |
| SAS | 447 | 353 | 260 |
| SPSS | 439 | 349 | 272 |
| SQL | 662 | 285 | 113 |
| Stata | 276 | 493 | 291 |
| VBA | 572 | 350 | 138 |
| a Sample size = 1060 |
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. The tool with the greatest access only was Python and the tool with the greatest access and knowledge was R.
Show chart Show table| Programming language | Access only | Access and knowledge | Knowledge only |
|---|---|---|---|
| C++ / C# | 67 | 35 | 62 |
| Java / Scala | 87 | 29 | 46 |
| Javascript / Typescript | 90 | 60 | 40 |
| Python | 342 | 320 | 70 |
| R | 298 | 565 | 55 |
| SAS | 183 | 264 | 72 |
| SPSS | 183 | 256 | 154 |
| SQL | 176 | 486 | 81 |
| Stata | 183 | 93 | 70 |
| VBA | 282 | 290 | 27 |
| a Sample size = 1060 |
We asked respondents what data operations they do in their work, and whether they use code to do them. The data operation with the highest frequency done with some or all code is data analysis. The data operation with the highest frequency done without coding is quality assurance.
Show chart Show table| Data operation | I do this without coding | I do some or all of this by coding |
|---|---|---|
| Data Analysis | 200 | 791 |
| Data Cleaning | 131 | 650 |
| Data Transfer / Migration | 155 | 364 |
| Data Visualisation | 336 | 567 |
| Quality Assurance | 342 | 585 |
| a Sample size = 1060 |
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.
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. Most respondents coding ability improved during current role.
Show chart Show table| Coding ability changes | Count |
|---|---|
| Significantly worse | 67 |
| Slightly worse | 113 |
| No change | 137 |
| Slightly better | 292 |
| Significantly better | 237 |
| a Sample size = 846 |
Respondents were asked whether they had coding experience outside their current role and, if so, where. Most of the respondents first learnt code in education.
Show chart Show table| First coding experience | Count |
|---|---|
| In current role | 175 |
| In education | 466 |
| In private sector employment | 38 |
| In public sector employment | 141 |
| Self-taught | 147 |
| Other | 9 |
| a Sample size = 986 |
We asked respondents to report how often they make use of each of the coding practices presented below. Please note that while there are many different coding practices listed below, we understand that not all are proportionate for every coding project.
The most used coding practice is “I write repetitive elements in my code as functions”.
Show chart Show table| Question | I don't understand this question | Never | Rarely | Sometimes | Regularly | All the time |
|---|---|---|---|---|---|---|
| I use open source software when programming | 7.0 | 15.6 | 10.0 | 17.0 | 23.9 | 26.6 |
| I follow a standard directory structure when programming | 25.9 | 6.4 | 9.4 | 19.7 | 26.8 | 11.8 |
| I follow coding guidelines or style guides when programming | 3.9 | 7.3 | 10.4 | 27.2 | 36.0 | 15.1 |
| I use a source code version control system e.g. Git | 10.7 | 37.3 | 13.9 | 12.4 | 12.1 | 13.6 |
| Code my team writes is reviewed by a colleague | 1.8 | 7.9 | 13.8 | 27.9 | 27.8 | 20.9 |
| I write repetitive elements in my code as functions | 4.4 | 9.8 | 9.4 | 22.9 | 30.1 | 23.3 |
| I collect my code and supporting material into packages | 11.1 | 40.0 | 16.8 | 15.3 | 11.3 | 5.4 |
| I unit test my code | 29.0 | 24.4 | 12.9 | 13.8 | 12.4 | 7.4 |
| I write code to automatically quality assure data | 4.1 | 26.4 | 17.7 | 29.7 | 15.2 | 6.9 |
| My team open sources its code | 16.1 | 48.6 | 13.1 | 13.6 | 6.1 | 2.6 |
| a Sample size = 900 |
The most used documentation is code comments.
Show chart Show table| Question | I don't understand this question | Never | Rarely | Sometimes | Regularly | All the time |
|---|---|---|---|---|---|---|
| Analytical Quality Assurance (AQA) logs | 19.4 | 39.6 | 14.0 | 11.2 | 9.3 | 6.4 |
| Data or assumptions registers | 21.4 | 32.3 | 13.4 | 15.8 | 11.7 | 5.3 |
| Documentation for each function or class | 11.4 | 23.9 | 14.6 | 20.9 | 19.4 | 9.8 |
| Code comments | 2.2 | 4.7 | 2.8 | 6.0 | 29.8 | 54.6 |
| Flow charts | 5.0 | 34.9 | 22.8 | 26.3 | 9.1 | 1.9 |
| README files | 7.4 | 24.9 | 14.3 | 25.8 | 16.8 | 10.8 |
| Desk notes | 15.6 | 20.7 | 11.2 | 21.2 | 23.1 | 8.2 |
| a Sample size = 900 |
We asked respondents “do you use reproducible workflow packages e.g. drake, make or pymake?”. Most respondents didn’t use reproducible workflow packages.
Show chart Show table| Use reproducible workflow packages | Count |
|---|---|
| Yes | 37 |
| No | 509 |
| Don't know what they are | 354 |
| a Sample size = 900 |
The number of users of each source control platform. If a source control platform was used most respondents used GitHub.
Show chart Show table| Version control platform | Yes |
|---|---|
| GitHub | 270 |
| GitLab | 182 |
| BitBucket | 42 |
| AWS CodeCommit | 2 |
| Cloud Source Repository (Google Cloud) | 21 |
| a Sample size = 900 |
We asked our respondents whether they had heard of RAP and what their knowledge is of their own department RAP champion. The most frequent response was “Have not heard of RAP”.
Show chart Show table| RAP champion knowledge | Count |
|---|---|
| Have not heard of RAP | 397 |
| Heard of RAP, have not heard of RAP champions | 170 |
| Heard of RAP, does not know department champion | 240 |
| Heard of RAP champions, no champion in department | 24 |
| Knows department RAP champion | 179 |
| a Sample size = 1060 |
We asked our respondents who had heard of RAP the extent to which they agree with the following statements:
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. The statement most respondents agree with is “I think it is important to implement RAP in my work”.
Show chart Show table| Question | Strongly disagree | Disagree | Neutral | Agree | Strongly agree |
|---|---|---|---|---|---|
| I understand what the key components of the RAP methodology are | 6.0 | 17.6 | 12.8 | 45.6 | 17.9 |
| I feel confident implementing RAP in my work | 13.7 | 25.2 | 21.1 | 27.6 | 12.4 |
| I think it is important to implement RAP in my work | 3.0 | 7.2 | 20.1 | 39.2 | 30.5 |
| I feel supported to implement RAP in my work | 10.3 | 16.6 | 34.2 | 26.5 | 12.4 |
| I know where to find resources to help me implement RAP | 11.3 | 26.2 | 22.3 | 28.7 | 11.5 |
| I and/or my team are currently implementing RAP | 16.0 | 25.0 | 22.3 | 23.4 | 13.3 |
| a Sample size = 663 |
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. The RAP components most used were “Functions” and “Follow code style guidelines” respectively which are both in “Advanced” components.
Show chart Show table| Component | Type | Count |
|---|---|---|
| Documentation | Basic | 235 |
| Peer review | Basic | 438 |
| Team open source code | Basic | 78 |
| Use open source software | Basic | 454 |
| Version control | Basic | 231 |
| Code packages | Advanced | 151 |
| Continuous integration | Advanced | 128 |
| Dependency management | Advanced | 196 |
| Follow code style guidelines | Advanced | 460 |
| Function documentation | Advanced | 263 |
| Functions | Advanced | 481 |
| Unit testing | Advanced | 179 |
| a Sample size = 900 |
| Basic RAP score | Count |
|---|---|
| 0 | 361 |
| 1 | 295 |
| 2 | 183 |
| 3 | 129 |
| 4 | 72 |
| 5 | 20 |
| a Sample size = 900 |
| Advanced RAP score | Count |
|---|---|
| 0 | 220 |
| 1 | 195 |
| 2 | 157 |
| 3 | 137 |
| 4 | 86 |
| 5 | 57 |
| 6 | 27 |
| 7 | 21 |
| a Sample size = 900 |