Eurostat regional yearbook using statistical maps and graphs to tell a story. Teodóra Brandmüller and Åsa Önnerfors, Eurostat

Transcription

1 Eurostat regional yearbook using statistical maps and graphs to tell a story Teodóra Brandmüller and Åsa Önnerfors, Eurostat

2

3 Gross domestic product (GDP) at current market prices per inhabitant in Euros, 2014

4 Gross domestic product (GDP) at current market prices per inhabitant in purchasing power standards (PPS), 2014

5 Gross domestic product (GDP) at current market prices per employed person in PPS, 2014

6 Principles for the NUTS classification: 1. Population thresholds for the 3 NUTS levels:

7 Nomenclature of territorial units for statistics = NUTS 1342 NUTS 3 regions 276 NUTS 2 regions 98 NUTS 1 regions 28 Member states of the EU

8 Gross domestic product (GDP) at current market prices per inhabitant in PPS, 2012

9 Gross domestic product (GDP) at current market prices per inhabitant in PPS, 2012

10 Principles for the NUTS classification: 1. Population thresholds for the 3 NUTS levels: 2. NUTS favours administrative divisions Data availability Regional policies 3. NUTS favours general geographical units

11 NUTS amendments 11

12 Gross Domestic Product per inhabitant in PPS in 2012 (EU28=100%)

13 Gross Domestic Product per inhabitant in PPS in 2012 at NUTS 1 level (EU28=100%)

14 Gross Domestic Product per inhabitant in PPS in 2012 at NUTS 2 level (EU28=100%)

15 Gross Domestic Product per inhabitant in PPS in 2012 at NUTS 3 level (EU28=100%)

16

17 Nights spent in tourist accommodation establishments, by NUTS level 2 region, 2013 per 1000 inhabitants per km 2

18 Gross Domestic Product per inhabitant in PPS, by NUTS level 2 region, 2013 EU 28=100 change in percentage points compared to 2008

19 Early leavers from education and training, by NUTS level 2 regions, 2014 % share of year-olds change in percentage points compared to 2008

20

21

22 Source: N. Lamber, C. Zanin (2013): Mapping Guide

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37 Regional unemployment in media in April 2015 October 2014

38 Best practice for map making Would you like to: Use an already produced map and include it in your report, presentation, publication, information brochure, tweet, etc.? Actively extract data and produce statistical maps yourself? There are a couple of things you need to consider before you make your choices.

39 Choropleth map: a thematic map in which areas are shaded or patterned in proportion to the measurement of the statistical variable being displayed on the map. Proportional symbol map: the map uses symbols of different sizes to represent data associated with areas or locations, i.e. cities. Dot distribution map: individual events are marked with a dot, allowing users to identify geographic patterns /clusters.

40 Title information: Statistical indicator or variable Different breakdowns: age group, gender, classification(s), geographical level etc. Latest reference year Measurement unit Example: Avoid using abbreviations, if not very well known! The map title should be selfexplanatory! Female employment rate, persons aged 20-64, by NUTS 2 regions, 2014 (%)

41 Class division, selecting thresholds: Different class division methods: Quantile: each class contains an equal number of values, e.g. 4 classes with 25 % or 5 classes with 20 % of the values in each class. Equal interval: divides the range of attribute values into equally sized sub-ranges, e.g. 3 classes for values from 0 to 300, will give 0-100, , , no matter how the values are distributed. Natural breaks (Jenks): based on natural groupings inherent in the data. If you use an even number of classes with the quantile method, the middle value represents the median = a good choice when using two contrasting colours.

42 Selecting the colour shades Sequential: from lighter to darker Diverging: contrasting colours, dark-light-dark Qualitative: each class have a different colour For colour advice use:

43 Actual map information Decide on your geographical coverage. Decide on scale and generalisation level. For EU-territory: show overseas territories in inlets. Use a separate colour for "Data not available". Administrative borders: better to use a thicker black line for country borders - easier to locate regions. Don't mix geographical and statistical content - too much information will clutter the map (i.e. lakes). Political implications of incorrect administrative borders or labels. Be cautious!

44 Footnote and source information A footnote is used for listing information relating to extracted data: definitions or exceptions to the reference year, NUTS level etc. mentioned in the main title. Source information is obligatory on statistical maps, can either be general ("Source: Eurostat") or better: include hyperlink to the live dataset or to static data extracted to produce the map.

45 Presentation techniques You also need to think carefully on how to present the map(s) you now have selected or produced. Using several maps side by side can reinforce your message and help to tell a story. A map in combination with a graph or table can also be a very efficient way of highlighting different aspects of the data.

46 Life expectancy at birth, male and female

47 Employment rate and change rate

48 GDP per inhabitant in PPS, NUTS 2 and 3

49 Using colours to signalise gender gap Life expectancy at birth Activity rate Part-time employment

50 Reinforcing the message with map and graph: showing the gender gap in life expectancy

51 Any questions or comments? Remember "less is more", don't be afraid to show relatively simple maps! Tailor-made your data visualisations depending on the audience / target group. Are you already using maps and graphs in your work what is your experience?

52 "My region" mobile app A new development we now are finalising. Indicator selection and bug-fixing. The new app will be launched for ios and Android in the beginning of next year.

53 Select and compare up to 3 regions at a time

54 National comparison, timeline graph and ranking

55 Any questions or comments? Interesting topics for the next edition of the Eurostat regional yearbook? What kind of data on regions and cities are you looking for? Have you been visiting the Eurostat website and database what is your experience?

56 Thank you for your attention!