Tables, graphs and maps

Transcription

1 Guidelines to visualise statistical information: Tables, graphs and maps THE CONTRACTOR IS ACTING UNDER A FRAMEWORK CONTRACT CONCLUDED WITH THE COMMISSION

2 Statistical data producers, yes! As all of us know, our purpose is to produce highquality statistics 2

3 Statistical data producers, yes! Finally, here we have our perfect figure: But what s the point if nobody knows / finds / understands our data? 3

4 Statistical data producers, yes! So apart from producing high quality statistics, we might be interested in getting our data across How can we do that? 4

5 Statistical data producers, yes! We can: - Provide the user with good metadata - Use user-friendly dissemination channels - Enhance the statistical knowledge of our audience - Publish our outcomes in an easy-to-read way - Etc. 5

6 Statistical data producers, yes! To sum up, the answer to the previous question is too long and wide to be given in this presentation. Here we will just focus on how to publish our results in an easy-to-read way 6

7 Statistical data producers, yes! So, let s give our data a nice, informative package! Tables, graphs and maps : ) 7

8 Statistical data producers, yes! 8

9 Table is a table is a table is a table Table: a set of data organized in a grid We distinguish informative from presentation tables Informative: normally large tables extracted from databases Presentation: small tables that sum up the most important figures of a topic, normally used in publications 9

10 Tables: Do s and Don ts Title: what, when & where Rows and columns tagged Source Units Footnotes if needed 10

11 Tables: Do s and Don ts Information sorted (chronologically, alphabetically...) Same amount of decimals for every figure Numbers right justified Thousand separator (space better than. or, ) No empty cells (identify missing values) 11

12 Tables: Do s and Don ts Which one would you prefer? Why? Registered health professionals in Spain, 2013 Pharmacists Nurses Doctors Opticians-Optometrists Physiotherapists Dentists Veterinarians Occupational therapists [2] 1783 Psychologist [1] Dental Technicians 6255 Chiropodists 6197 Dieticians and nutritionists [2] 2010 Speech therapists [2] 6197 Chemists [1], [2] 424 Physicists [1] 58 Nurses Doctors Pharmacists Physiotherapists Dentists Veterinarians Opticians-Optometrists Psychologist [1] Dental Technicians Chiropodists Speech therapists [2] Dieticians and nutritionists [2] Occupational therapists [2] Chemists [1], [2] 424 Physicists [1] 58 1: include only physicists, chemists and psychologists with a degree in health 2: data regarding speech therapists, dieticians and nutritionists, occupational therapists and chemists with a degree in health are included in this statistics in 2013 for the first time 12

13 Tables: Do s and Don ts Which one would you prefer? Why? Pharmacists Nurses Doctors Opticians-Optometrists Physiotherapists Dentists Veterinarians Occupational therapists [2] 1783 Psychologist [1] Dental Technicians 6255 Chiropodists 6197 Dieticians and nutritionists [2] 2010 Speech therapists [2] 6197 Chemists [1], [2] 424 Physicists [1] 58 - No title: what is this information? - What kind of order is following? - Center-justified names: difficult to read - Center-justified figures: difficult to compare - What s the meaning of those 1s and 2s? - The information is from? 13

14 Tables: Do s and Don ts Which one would you prefer? Why? Registered health professionals in Spain, 2013 Nurses Doctors Pharmacists Physiotherapists Dentists Veterinarians Opticians-Optometrists Psychologist [1] Dental Technicians Chiropodists Speech therapists [2] Dieticians and nutritionists [2] Occupational therapists [2] Chemists [1], [2] 424 Physicists [1] 58 1: include only physicists, chemists and psychologists with a degree in health 2: data regarding speech therapists, dieticians and nutritionists, occupational therapists and chemists with a degree in health are included in this statistics in 2013 for the first time Source: National Statistics Institute - Title what, where, when - Sorted values - Left-justified names: more natural to read - Right-justified figures: easier to compare - Space separating thousands - Footnotes & source 14

15 Charts: a picture is worth a thousand words Visual representation of statistical data Facilitate comparison and identification of trends within the data Many types of them: Pie charts, lines, bars etc. 15

16 In a nutshell, a good chart should have Title: what, when & where Axis labels Gridlines Legend Units Source Values sorted BUT: Avoid unnecessary features that makes the chart difficult to understand 16

17 Graphs: bad & good examples This graph contains results by region as well as at national level Can you identify the value for the region of Madrid in July 2016? How this graph could be improved? 17

18 Graphs: bad & good examples - No legend - Lots of variables: 20 regions 20 lines 20 different colors - National value requires a wide range vertical axis regional values crowded together Impossible to read any region information - Y-axe with decimals is really necessary? - No source, no units 18

19 Graphs: bad & good examples A better option: - No national value - Legend - Much easier to read Still: This is a better option, but maybe not the best option Why? 19

20 Graphs: bad & good examples Too many segments! It s more difficult to compare angles 20

21 Annual greenhouse gas emissions by sector 10,3 10,0 3,4 Residential, commercial and other sources Land use and biomass burning Waste disposal and treatment It s easier to compare size of rectangles than size of angles 21,3 11,3 Power stations Fossi fuel retrieval, processing and distribution Agricultural by products A bit crowded though? 12,5 14,0 Transportation fuels Industrial processes Careful with the colours chosen! 16,8 21

22 Better option: Sorted values Colours so that figures are easier to read But there are things missed still! 22

23 25 Annual greenhouse gas emissions by sector, country C, Industrial processes Transportation fuels Agricultural by products Fossi fuel retrieval, processing and distribution Power stations Waste disposal and treatment Land use and biomass burning Residential, commercial and other sources Much better 23

24 25 Annual greenhouse gas emissions by sector, country C, Power stations Industrial processes Transportation fuels Agricultural by products Fossi fuel retrieval, processing and distribution Residential, commercial and other sources Land use and biomass burning Waste disposal and treatment And if we sort the values even better! 24

25 Graphs: bad & good examples 3-D charts are not the best idea: it is difficult to compare the size of the angles More things to observe? 25

26 Graphs: bad & good examples Better option: 2D + When, where, source, units Values given on the graph: easier to read Source: my mind (fictitious data) Values sorted clockwise 26

27 Graphs: bad & good examples Population of 4 EU countries by sex and year A bit crowded D: difficulties to compare. Even to see the data! Total Males Females Total Males Females Total Males Females Total Males Females Source: BelgiumBelgiumBelgium Bulgaria Bulgaria Bulgaria Czech Czech Republic Czech Republic Republic Denmark Denmark Denmark

28 Graphs: bad & good examples Population of 4 EU countries, total Better option: split the graph in three (total women men) Belgium Bulgaria Czech Republic Denmark 28 Source:

29 Maps: statistics + geography They provide information related to statistical areas Show the spatial distribution of data 29

30 Maps: statistics + geography Two types: Choropleth: shaded areas Dot maps: information displayed using icons 30

31 A good map should have: Title: what, when & where Legend Units Scale Data source 31

32 Maps: bad & good examples 32

33 Maps: bad & good examples - No title: what s the map about? - Wide-range intervals! In terms of population (because it is a map of population): Poland (37 million people) in the same group as Luxembourg (0,5 million people)? 33

34 Maps: bad & good examples - Title, legend, units, source - More reasonable intervals than the previous example - Information easy to compare at country level 34

35 To know more This presentation is strongly based on the UNECE guidelines Making data meaningful Part df Tutorials about data presentation in website: 35

36 Thank you for your attention! 36