This is the time for scatter plots in the 10 x 10 charting tips series:
- A scatter plot is square by definition (I forget that sometimes…);
- In some cases, it makes more sense to use a scatter plot than two column charts: for example, instead of having a column chart to display product market share and another chart to display product growth, consider merging both into a scatter plot (market share on the x axis and growth on the y axis);
- If you are plotting several data series, color code them instead of using different markers…
- … but consider using several charts;
- In scatter plots, use empty circles as markers to let the reader see the overlapping points;
- Use a scatter plot matrix to analyze pairwise relationships between series;
- Use a scatter plot as an alternative to horizontal bar charts, like in a population pyramid;
- If needed, use a scatter plot instead of a line chart if you have an unevenly-spaced time series;
- You can use a scatter plot to create a basic map;
- An outline can ruin your scatter plot. If possible, remove it and explain it;
As you can see, you can use a scatter plot in Excel to create many other charts. Just use your imagination and share it in the comments.
These are 10 basic tips for column and bar chart design:
- A column chart is not a skyline: if you can’t see the individual patterns, consider removing some series or create several smaller charts;
- If you are charting categorical data sort the columns; if there is more than one series, allow the user to sort the data herself;
- If you are displaying time series, column charts are not interchangeable with line charts: column charts allow you to compare individual data points, while a line chart shows the trend; be sure to select what your audience wants to see;
- For target/actual series (like budget/actual) overlap them but make sure they can’t be taken for stacked bars; you can do it by using a different column width for each series or by setting filling to none (usually the target series);
- Use horizontal bar charts when x labels are too large to be correctly displayed;
- The y axis scale should start at zero; this is particularly important if you are using bar charts; make sure you have a (very) good reason to break this rule;
- If you really need to label each column try to minimize its impact; in Excel 2003, select Format Data Labels / Alignment / Label Position: Inside Base;
- Don’t use multiple colors for a single data series;
- Avoid stacked bar charts;
- Use category/subcategory to label the x axis. For example, instead of having Mar-2008, Apr-2008… use Mar, Apr and place 2008 in the second line.
As usual, feel free to add your own tips in the comments.
Following the 10 x 10 post series on tips for better charts, these are the 10 tips for line charts:
- Don’t use line markers unless you really need them to identify b&w printed charts;
- Don’t use a legend; directly label the series, instead;
- If you can’t easily see the pattern of each series you may have too many;
- In a time series, the spacing between markers in the x-axis should be proportional. For example, if you have data for years 1980, 1990, 2000 and 2008, the spacing between 2000 and 2008 should be smaller than between other dates; if you can’t do it with line charts use a scatter plot;
- If you are comparing two series like imports/exports or profit/expenses, chart the differences, not the actual series (or at least add a small chart with the differences, below the main chart;
- If you are comparing two time series with very different units of measurement, consider using a logarithmic scale;
- You don’t have to start the Y-axis scale at zero; break the scale if you need;
- If you are using different line styles you may be emphasizing some series more than the others; make sure that’s consistent with your users needs (emphasize what is important);
- Add a trend line (make sure the trend is plausible…);
- Don’t use line charts for categorical data; if you need a profile chart use a scatter plot and switch axis.
Feel free (and I would appreciate) to comment or add your own tips…
How do you create a map like the one above for your next presentation if you don’t have a mapping tool? Simple, create it in Excel. Easier said than done, right? Well, not really…
Following the “geo-scatterplot”, in this screencast tutorial I’ll show you how to create a thematic map and color-code it, based on your own data. You don’t need add-ins or additional software, just a little time to set it up. Please note that this is not intended to replace even the simplest mapping tool.
To start the tutorial just click the link below:
Screencast: How to create a thematic map in Excel.
Note that you need a map. You can draw it yourself or you can import it. Drawing a States map is simple:
- Import an image to the Excel file (you can use this one, for example);
- Draw the shapes using the map as a reference.
The other option is to obtain a file. You can get an ESRI Shape file from the National Atlas but you’ll have to convert it to Windows Metafile (WMF) or similar format.
Hope you’ll find this technique useful and feel free to suggest any improvements.
If you liked this tutorial you may be interested in How to create population pyramids and the “Howto Edition” fo the Demographic Dashboard. And you may consider subscribing…
I know, I know, no one likes pie charts, but I can’t ignore them. A pie chart compares proportions but it is of limited use: either the data is too complex and a pie chart can’t handle it, or it is too simple and you should just use a table. So, the first tip should be:
- Do you really need a pie chart?
- Pie charts shouldn’t be compared (comparing market shares in two regions, for example);
- Don’t use the “exploded” option;
- Five is in general the maximum number of slices you can use in a pie chart, but two is better…;
- If there is no other meaningful order, order the slices from maximum to minimum;
- Put “other” in a gray slice;
- Don’t use a legend, just label the slices;
- Use a very small pie chart in a supporting role for a more complex chart;
- Use the appropriate color codes to identify groups of slices;
- Start the first slice at 0º (noon);
I am sure you can come up with some ideas to make a better pie. Please share your receipt in the comments.
This is the second of 10 posts where I’m listing tips for better charts. Please take a look at the first post where the project is discussed. These are my chart formatting tips:
- Use the right chart type for the data and the problem;
- Apply sound design principles;
- Use color strategically: mute axis and grid lines by graying them out; gray out some contextual data also; use soft colors; use saturated colors sparingly and with a clear purpose of emphasis;
- What the users see is not what you see in your monitor: if needed, test for other monitors and output formats (b&w print, color print, PDF, overhead projector);
- There is no rational justification to use pseudo-3D charts and other dubious effects (gradients, glow…), so never use them if you what to be rational;
- Use a clear font;
- Don’t emphasize everything (for obvious reasons);
- The y axis scale should start at zero; this is particularly important if you are using bar charts; make sure you have a good reason to break this rule;
- A chart is not a table: by labeling every single data point you make it harder for the user to search for trends or patterns; if you have to, place the labels where they can do no harm;
- Annotate: Add labels for the last, the lowest, the highest or any other relevant data point; add data or comments where appropriate;
- Bonus tips: Use smaller charts and never accept the Excel defaults;
What are your best chart formatting tips? Please share them in the comments!
This is the first in a series of 10 posts where I’ll suggest a (hopefully) coherent set of tips to improve our charts and, more important, to improve the way we make sense of the data. These are the planned posts:
- General charting;
- Formating;
- Column/Bar charts;
- Line charts;
- Scatterplots (XY charts);
- Pie charts;
- Other chart formats;
- Dynamic charts;
- Dashboards;
- Miscellaneous tips;
- Bonus post: online resources.
These will be very short tips, and I’m sure some of them will require further explanation. In time, all of them will be properly linked to a more detailed post (that will keep me off the streets for a while…). This is a kind of road map for the next few months and, when finished, a (partial) table of contents for the blog.
So, general tips on charting:
- A chart shows trends, patterns, outliers; if you already strive to make them apparent, you don’t need to read the next 99 tips…;
- Do you really need a chart? Sometimes the task and the data suggest another method of data analysis;
- Know your audience. If your audience is uncomfortable with some formats your message will be lost;
- Make sure you have enough data to create a pattern (two data points are not enough to create a trend line);
- Make sure you don’t have more than enough data: just because you have it, you don’t have to show it…; keep removing interesting data until only relevant data for your problem remains;
- A chart should be able to answer elementary, intermediate and global questions regarding the data;
- Don’t assume that the charts you see in the media are the ones you need to run your business;
- Learn how to lie with charts and, of course, avoid those lies;
- Let the reader see related charts simultaneously;
- Chart overload is as bad as information overload.
It’s your turn, now. What are your best tips in this category? Please share them in the comments (if you have specific tips please save them for the next posts). I believe that Tufte’s principles (avoid chart junk, maximize data/ink ratio, high data density…) are already implicit in some of these tips.
You can’t write a novel just because you can type. You can’t create a chart just because you know how to do it in Excel. First, you have to know the job, then the tool. Research for best practices in your field. Read what some authors have to say about specific formats and options. Then, build a framework and let it guide your information display needs.
(And, of course, never use Excel default options…)
[Update: designers have a similar problem: software doesn't make design easy...]
How to create better charts? Search the web and you’ll find many specific advices, not always backed up by scientific evidence (can there be any?). Tufte’s advices are great for us, rational, positivist members of the human race, but what about those emotional poor fellows for whom a minimalistic chart is just a boring chart?
Can we remove personal aesthetics from the equation? Probably not, but we can minimize it. And if you have a set of basic principles that acts as a framework and guides you through the selection and design of charts you’ll end up getting a more efficient display than just relying on your preferences of the moment.
This six-part series focus on the generic design principles of simplicity, consistency, compatibility, congruence, relevance and conventionality (there will be a separate post for each one). These principles are defined by Michael Schiff in his master’s thesis, “Designing Graphic Presentations from First Principles” (you can get the PDF file here).
Let’s start with simplicity…
The simplicity principle states that a “simpler” chart will be easier to understand. By “simpler” it means fewer types of objects and properties used to encode information. This can be linked to Tufte’s minimalistic approach (the data/ink ratio, maximization of data density, no “chart junk”…) but extends beyond that, while having a more abstract nature.
What happens when you apply this principle to the well known Excel chart defaults? You can see it on the left: after an extreme makeover you can really see the data on the second chart. There is a quote by Michelangelo that expresses quite well what happened: “I saw the angel in the marble and carved until I set him free.“
Note that each of the formatting options has a different nature:
- The gray background is pure chart junk and must be removed;
- The decimal place on the Y-axis gives us an irrelevant illusion of precision that doesn’t make sense; you can also remove the percent sign;
- The gridlines are supporting actors that you can leave muted in the background;
- Removing the legend and replacing it with direct labeling of each series has a deep impact on the user experience: there is no need for the movement of the eyes between the data and the legend and you can free up your working memory;
As you can see, the simplicity principle alone can improve dramatically your chart message. Please remember: a chart is not a product, a chart is a delivery boy.
