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Journalism is the area in which data journalists feel they most excel, with machine learning on the opposite end of the spectrum. While 56% consider themselves advanced at journalism, only 12% say they are advanced in data analysis and 15% in data visualisation. As a result, the previously observed gap between data skills and journalistic skills persists in 2023.
When breaking it down by occupation, most profiles follow the same trends in terms of rating skill level. Overall, students tend to be the most inexperienced in nearly all areas. As in 2022, the biggest gap in proficiency between students and industry is in journalism, where only 16% of students have rated their skill level in journalism as advanced.
Like in 2022, experience in data journalism positively correlates with higher skill level rating, and this is particularly the case in data analysis and data visualisation. The correlation between experience in data journalism and higher skill levels emphasises the value of ongoing professional development and experience in the field. The areas with least improvement over time are machine learning and statistics. These are also amongst the skills where people in the industry would most like to advance. Similar to previous survey editions, journalism is the area in which most respondents have received training (56%). The largest gap where respondents have received training and desire upskilling is in machine learning, where only 14% have been trained on this skill, while 57% desire upskilling in this area. The second and third largest gaps are in data wrangling and web scraping. The interest in upskilling, particularly in areas like machine learning, highlights a growing awareness of the need to adapt to emerging technological trends.
Among those who code as part of their work (19% in 2023), the share of those who use Python is increasing (69%), as is that which uses HTML and CSS (61%) or Javascript (46%). On the other hand, fewer respondents use R in 2023 compared to 2021 (from 46% to 39%). The increasing usage of Python, HTML/CSS, and JavaScript among those who code in their work suggests a trend towards languages and technologies that are versatile and have strong community support. Python's rise could be due to its simplicity and the extensive libraries available for data analysis, machine learning, and visualisation. HTML/CSS's growth can be attributed to the need for data journalists to present their findings on the web attractively and interactively. The slight decrease in R usage (too small to be deemed significant) might be because Python is increasingly able to perform many of the statistical analysis tasks traditionally done in R.
Coding is a skill mostly acquired through self-learning. However, over one in three learns how to programme while pursuing higher education studies. Rarely respondents have learned how to code at work (16%).In terms of experience, in 2023 64% of programmers have known how to code for more than six years, against 46% of respondents in 2022.
The share of those who use coding on a daily basis is increasing rapidly (58% in 2023 against 32% in 2022). While around half of respondents used to programme once a week or occasionally in 2022, this share is down to less than a quarter of programmers in 2023. These shifts might indicate that coding is becoming an integral part of the daily work for some data journalists, possibly due to the growing demand for timely data analysis and the need for rapid development of data-driven stories. This shift may also reflect the increasing ease with which journalists can use programming within some aspects of their work.
The share of respondents working in organisations using predominantly or entirely external graphic tools is increasing over time (from 45% in 2022 to 51% in 2023). Of these, in 2023 more than one in three uses solely external graphic tools. These shifts could point to the wish to seek out-of-the-box solutions that can provide quick and efficient results. This might be due to the limited resources to develop in-house tools or a preference for widely supported and continuously updated platforms. Largest organisations are those which predominantly enjoy in-house custom solutions when it comes to graphic tools.
The tool distribution in 2023 is generally consistent with previous survey editions. Excel is the most commonly used tool, used by nearly three out of four of respondents. More than three out of five respondents use Google Sheets. Among data visualisation software, the gap between Flourish (32%) and Datawrapper (37%) remains constant. Several respondents who indicated "Other" have stated to use the following tools for data analysis or visualisation: Power BI, RAWgraphs, Infogram, QGIS and various programmes belonging to the Adobe Suite, particularly Illustrator.
There are stark national patterns in terms of tool usage, particularly for data visualisation software. While the percentage-point difference from the mean of Datawrapper users is +21 in the US and +18 in Germany, the Flourish equivalent is -5 and -17. Flourish is instead more commonly used in the UK (+21). Similarly, there are patterns in occupation breakdown too. Freelancers are less likely to use Datawrapper and Flourish compared to employees, editors, and educators. In terms of programming languages, Python is more commonly used among employees, while R is more commonly used by students and editors.