View allAll Photos Tagged barchart
On Louisiana's gulf coast - birds on a bar-graph.
Draw your own conclusions from the data. My clear conclusion is that seagulls are slightly more intelligen than pelicans. The bird from the third bar was so smart its self-worth doesn't come from getting its picture taken, so it left to catch a dumb fish.
Red, Blue, Green, Yellow.
The (actual) distribution of my books.
A physical color histogram.
Day 200. July 19 2009.
explored.
and posted to gizmodo. mmhm.
follow me on twitter: twitter.com/patrickgage
Rscript ig-van-january2016-piechart-as-barchart.R see github.com/rtanglao/2016-r-rtgram/blob/master/ig-van-janu...
How to rotate x-axis labels on Gnuplot
If you would like to use this photo, be sure to place a proper attribution linking to xmodulo.com
One of my better finds. According to eBird barcharts, this bird is supposed to be rare in Buenos Aires, at the southernmost tip of its range ... and yet there it was, foraging in and amongst the sidewalk cafes, totally unafraid of people.
This bird is banded (ringed) with color markers. I reported it to the USGS, but never heard back. If anyone knows whom to report it to in Argentina, please let me know.
Annual carbon dioxide emissions per-capita. The image shows the ACTUAL VOLUME of gas emitted with a person for scale.
Annual carbon dioxide emissions per-capita. The image shows the ACTUAL VOLUME of gas emitted with the UN Building in New York for scale.
This bar chart compares the team's attendances for each match day in a season; so the third home game of this season compared against all the other "third home game of the seasons". This year's attendances are in yellow, the 2011 figures are in dark gray, and the previous average (1996 - 2011, leaving this year out) are in the lighter gray.
After a period of five consecutive games in which the team drew higher-than-average crowds, the team plummeted back to work in the last week. One significant cause was the rescheduled home game against Toronto, which pushed the game from a weekend to a Wednesday night (worse, the same night that many local school years began, restricting family attendance even further). Another is undoubtedly the concentration of home games through this stretch of the season.
Shows the percentage by which the human population has increased over the last ten years, by continent. Note Africa's very high growth rate.
How to plot a bar graph on Gnuplot
If you would like to use this photo, be sure to place a proper attribution linking to Ask Xmodulo
Royalty-free financial 3d computer generated clipart picture image of an orange person standing on a silver and green bar graph chart, reaching back to assist another person up to the top.
This is a chart comparing 2012 game day attendance to both the previous year and all time history. While the past season did improve significantly on the previous year, it only regained lost ground and restored levels back to those seen from 2008-2010.
Like all councils, Central Bedfordshire Council is keen to reduce its carbon footprint. The first step is understanding where savings can be made. Breaking down the Council's footprint into different sectors helps, but it also helps to have a feel for scale of the actual emissions. This film combines the best of both worlds - it is a chart that reveals the relative contribution of different council activities but it is also an illustration of the actual rate of emission.
The person standing by the y-axis is to-scale.
Video is available here: www.youtube.com/watch?v=c6PUa_8f4VU
COPD-EMPHYSEMA
Chronic Obstructive Pulmonary Disease.
"Need-to-know" information focusing on emphysema so you can take action for yourself or a loved one.
Per-capita carbon dioxide emissions in 2006 shown as actual volumes of gas creating an animated bar-chart. The countries/regions displayed (in order of emissions) are Somalia, Bangladesh, Africa, India, Central and South America, whole World, China, Italy, United Kingdom, Germany, South Korea, Japan, Russia, Canada, Australia, United States. (Data: CDIAC)
Bastard child design of Juhan Sonin and Stephen Few... WITH A SPRINKLING OF MCCREADY AWESOMENESS!!!! Never picked up by anybody, but I thought it looked cool...
Chart of the mean number of pictures per month uploaded per cat, from when we adopted the cat to now (since I upload pictures of cats that have died).
I'm not entirely sure why I uploaded more pictures of Tigger than any other cat, but that's what the data says. Also, I didn't really start uploading lots of cat pictures until probably 2009 or 2010 with the ready availability of call phones to snapshots at will. (Which is why Assam, Bonkers, Argent, and Norio are relatively low - they were around for a long time (and still are for Bonkers, Argent, and Norio) but without many uploaded pictures. (Also, I lost about 7 months of kitten pictures after we first got Yuba and Tigger due to a hard disk crash.)
Another reason why Tigger and Nobuo (who was with us the shortest amount of time) have more pictures uploaded per month than the others is they made themselves available for pictures by hanging around us a lot while the others were elsewhere in the house (or in the cat run in California).
Because some people asked for it on Twitter, here is a quick chart showing the Crew's average attendance patterns for this year vs. their history. The gray series indicates average attendances for game #N over the team's 16-year history, while the yellow series graphs that game's attendance for this year, 2011.
As you can see, Game 5 has been problematic both this year (7.148) and over time (12,476).
One interesting reading of this chart is that, while the Crew's attendances have certainly been disappointing this season, the game-over-game patterns have - generally - followed the patterns set in previous years. The toughest games, attendance-wise, are not the first games, but those next few after the opening rush is over. As the summer has moved on, attendances have typically risen - peaking around a dozen games into the season.
The last game of the season has done very well, but it should be noted that Game 16 has not always been played due to the length of the season (the last year was 2006). As such, the reported average for that game is artificially inflated. Which is a good thing, as the capacity of Crew Stadium is below what the average for that game at this point.
The chart was produced by Microsoft Excel, with no post-processing. If this sort of thing proves interesting, I may revisit it.
Global carbon dioxide emissions in 2006 (957 tonnes per second) are shown as actual volumes of gas with the United Nations Building for scale. Emissions are divided into two groups - 1) United States and China; 2) the rest of the World. Between them, the US and China account for 40% of the World's emissions. (Data: CDIAC)
This image is excerpted from a U.S. GAO report:
www.gao.gov/products/GAO-15-131
HOUSING FINANCE SYSTEM: A Framework for Assessing Potential Changes
This is an attempt to graphically represent the player combinations being used by the Columbus Crew. In this case, the player in question is Josh Gardner - who has become the first choice left back for the Crew since supplanting Rich Balchan several games ago.
This visualization uses data through the end of June, so it is a bit behind dated at the time of posting (I'm still trying to determine the best way to automate this).
The minutes played by Gardner are depicted in yellow - in this case, just over eight games' worth of time. The time played by every other player is depicted in each column, where the placement of the column indicates the amount of time that player has combined with Gardner. For a player like Sebastian Miranda, who has played nearly every minute of the season, the graph doesn't tell us much - but if you compare Robbie Rogers and Andres Mendoza, for example, it should be evident that Gardner had (as of this dataset) played significantly less time with Rogers than with Mendoza, despite those two players' seeing roughly equal amounts of time.
What does this mean? Combined with data like goalscoring frequencies, this could help shed light on whether a given player is the true cause for his apparent impact, or if there might be other factors at play.
As I refine my routines, I would also like to generate impact figures for player combinations - but that might be some time coming.
To put this another way, Police Reports on collisions in (or on the roads immediately bordering) Clifton and Cabot include about 300 walkers and cyclists getting hurt (or worse) each year. Data from the NHS suggest that there are even more A&E cases that come in from "non-collision injuries" (ice, potholes, broken paving stones, misjudged kerbs and so on).
In the period shown here cycling and walking numbers have gone up a lot and motor vehicle counts (especially cars) have declined.
NB A mistake I made in showing an oddly low figure for the 2005 pedestrian "slight injury" category has now been corrected. (15/03/2015)
Clara Miller is an amazing woman with an enormous amount of knowledge on non-profit funding and equity. Unfortunately for her, her laptop crashed this morning, so we had to improvises for the Pop!Tech Fellows program.
Eric and myself became 2 bars in her bar chart.
Please see animated image below www.flickr.com/photos/flights_of_fancy/12136845345/sizes/o.
Entropy is the measure of disorder within an isolated system and is based on the 2nd Law of Thermodynamics which states that the distribution of energy will become uniform over time.
I have illustrated this as a bar graph with fluctuating energy levels. Where there is a wide variation in height of the bars you can say that the energy is organised and is able to do work. When the bars are at the same level they are disorganised and the Entropy is at its maximum. While the amount of energy remains the same there is no longer the ability to do work, as the energy is no longer concentrated in one place.
The waves also represent Entropy if you think of a choppy sea as being able to rock a boat (do work) which becomes steady as the sea calms.
Juan Tello has kindly given permission to use his water ripple photo www.flickr.com/photos/junctions/2937689351 which I have animated in ‘Sqirlz Water Reflections’. The bar chart was created in MS Excel and the final piece was animated in UnFREEz.
I have provided a translation of some of the tags I use on Flickr which you may find interesting www.flickr.com/photos/flights_of_fancy/6973610225/
This image is excerpted from a U.S. GAO report: www.gao.gov/products/GAO-14-683R
FOREIGN ASSISTANCE: Briefing on U.S. International Water-Related Assistance
Note: Amounts shown may not sum to total because of rounding. Amounts shown include about $4.3 million in reported interagency transfers and about $6.9 million in "other" funding such as staff and travel costs. USAID data include about $17 million in State funding for water-related programs. All agencies except USAID reported obligations data; USAID reported "allocations" data. According to State and USAID, USAID's financial accounting systems are not configured to easily link obligations data to congressional spending requirements, because single obligations can be used to satisfy more than one requirement. USAID therefore uses allocations data as a proxy when reporting on spending requirements to Congress. DOD data include funding reported by the U.S. Army Corps of Engineers and multiple combatant commands. One combatant command reported data for disaster risk reduction efforts broadly, not for water-related disaster risk reduction only; therefore, actual DOD funding for water-related assistance may be less than shown. See appendix II for more details on U.S. agency grants and contracts funding data.
This image is excerpted from a U.S. GAO report: www.gao.gov/products/GAO-14-683R
FOREIGN ASSISTANCE: Briefing on U.S. International Water-Related Assistance
Note: USAID, State, and MCC provided assistance in 39 countries in sub-Saharan Africa: USAID in 33 countries, State in 25 countries, and MCC in 10 countries. USAID officials noted that funds for central or regional programs may reach additional countries. Various other U.S. agencies also provide assistance in 31 of these countries as well as in 1 additional country, Togo, where USAID, State, and MCC do not provide water-related assistance.