Author: sprabhu

The US has more guns per capita than anywhere else in the world. These days, we have been hearing news, and stories of shooting sprees in the United States. This makes me wonder – is violent crime really getting worse in America? With those thoughts, I happened to read an article which showed the 50 year trends in the violent crime in the United States.  The article had the following chart which showcased the total number of violent crimes in the US from 1960 to 2009 and the overall trends throughout.

What did I like about this graph?

1. The author wants the viewers to compare the number of incidents over the years. I can conclude that numbers are unstable and one can’t accurately make any predict for the upcoming years with this historical data.
2. The graph encompasses a long-time span of 50 years which gives one a pretty decent idea of the crime history in the country.

How will I make it better?

Use of the right type of graph:

The bar graph used is surely giving a good picture of the changes in the crime numbers over the years. However, the use of a line graph would have served the same purpose and would also look neat. A line graph is commonly used to display change over time as a series of data points. Use of bars to cover such a big time frame seems unnecessary.  Owing to this, the simple straight forward information is passed on in a somewhat cluttered manner.

I would make use of line graph instead to provide similar insights. Using a line graph, the same message can be conveyed by just a single line and does not look overwhelming.

Highlighting important years:

By studying the graph in a bit detail, it can be noticed that there are some periods – 1975, 1981, 1992 post which a continuous trend (increasing or decreasing) seems to change. For me, those points are noteworthy as I would like to drill down further and would be more interested to know what exactly must have happened that year which caused the trend to break. Hence if the graph had those years highlighted the readers would not have to struggle to mark those years.

Hence, I would mark such findings so it would catch one’s attention immediately and provide better insights. This reduces the task of the readers who are interested in finding specific patterns and wanting to explore more details.

Audience:

Giving a thought on which group of users would find this information the most useful, it would be perhaps the police department of the United states, the federal and state government and the law makers. So as described above, if the graph highlights the interesting patterns then perhaps that can be used by the government to take decisions related to the staffing of police. The police department may use it to study the crime history in a period say 1992 and introspect on their moves then and improvise their strategies from those take-aways. The law makers might use to check if there had been a specific rule or law being imposed which caused the trend to break.

Claim:

The bar graph does indeed impart a lot of information and the complete statistics. However, it does not have a claim as such. The first visualization in such a long article should better be very impressive as that’s the point where a reader decides whether to continue reading the article further or to just switch to something else!

For e.g. I notice that one of the take-aways from the graph is that the year 1992 was peak of the violent crimes. This could have been added in the form of a brief description or a statement on the top. By doing that, even the very first look at the graph provides a key insight. Also, it would invite more audience.

Improved Y axis:

Currently the Y axis has just 4 values being shown. It does give a fair idea of the number of crime incidents occurred each year. However, since the x axis is spread across around 50 years and that no two years have the same number of incidents happening, there is a room to spread the Y axis across more values.

I would start the Y axis with 0 and then increase it at shorter intervals until I reach 2000000. This gives the readers a better estimate of the actual count of the violent crimes for a specific year.

Aesthetics:

Using bright relevant colors and a bigger font would help reach out to a larger audience. The colors being used also play a role in engaging the viewers. To me, the grey color looks too dull and old.

I would use the red color. Red is a very emotionally intense color as it symbolizes fire and blood. Thus, using red to represent crime figures becomes apt. It helps in connecting well with the audience and inducing the right amount of seriousness in the minds of the readers.

Redesign: Below is my attempt to redesign the visualization to present my ideas based on the data collected from the source in the article. I have taken the dataset from website – The Disaster center which had the complete the data for crime from 1960 to 2009. I have also worked on the aesthetics to make the graphs neat and clean.

References:

Main article: https://lowtechcombat.com/blog/2010/12/50-year-trends-in-violent-crime-in-us

Crime Dataset: http://www.disastercenter.com/crime/

http://www.pewresearch.org/fact-tank/2017/02/21/5-facts-about-crime-in-the-u-s/

Unlike their compatriots in the rest of the country, many New Englanders rely on heating oil to keep their homes warm during the frosty winter. Americans in other regions rely overwhelmingly on electricity or natural gas for heat. But according to a report published by the Energy Information Administration in 2015, in the Northeast (New England plus New Jersey, New York, and Pennsylvania), about 5 million households, or about 20 percent, use heating oil. The percentage of households heating with oil is 64.2 in Maine, 46.1 in New Hampshire, 43.8 in Vermont, 43.7 in Connecticut, 32.6 in Rhode Island, and 29.2 in Massachusetts. While reading on this topic, I stumbled upon the following graph:

The above graph shows the average heating oil prices for the months of October through March which happens to be the peak winter season. The graph covers across the data for an entire decade from 2006 to 2017.

What did I like about this graph?

The author wants the viewers to compare the heating oil prices over the years and across the months. I can conclude that prices are unstable and one can’t accurately predict the price for the upcoming years with this historical data.

The graph encompasses the statistics for the entire winter season. Being among of the coldest regions in America, the MA people would be surely curious to see the change in the prices over of the peak months of winter.

The bar graph labels the price for each month of the most recent year i.e 2016-17 and that helps the readers understand the current pricings because that is something which is presently impacting the state.

How will I make it better?

Claim:

The bar graph simply plots the price changes over time. It does act like a dictionary and tells us about the heating oil prices for a point in time over the past 10 years. However, it does not have a claim and has no significant insight one can take away to influence an appropriate action.

Aesthetics:

We have learnt that efficient visualizations should convey a lot of meaningful insights. But having said that, a graph which tries to put in too much of information might look messy and get too overwhelming for the viewers. And I think that is exactly the situation with this graph. When I gave the first look to the graph, it took me a while to figure out what is it exactly trying to present. Incorporating the data for about six months and that too for an entire decade becomes too much to comprehend.

Though it makes sense to use a different shade to show each year, the legend is not very clear and it takes some effort to match the colors in the legend to those in the actual bar graph. It is hard to distinguish different shades of the blue used as all of them look similar. In fact, the color used for 2010/11 and 2012/13 looks absolutely the same to me.

If the data is split into 2 graphs, one covering the recent 5 years and the other covering the remaining historical data, it is comparatively easy to note the change in prices and how is it varying from time to time. Using distinct colors to represent each year can make the graph more intuitive.

Factors affecting the oil prices:

The heating oil prices may change owing to a variety of reasons which include: the change in the crude oil prices, demand for the year, weather for that season, change in the government rules or regulations. The above graph does not talk about any of these and hence the curious viewers are left to wonder the reasons for the increase/decrease in the price in a particular month for a particular year.

If this data is backed up with at least one of the above factors, the graph becomes more enlightening and gives mores insights. For e.g., if the graph also shows the change in the temperature over the years, then one can correlate the temperature changes with the oil price changes and hence verify if the temperature indeed affects the oil prices as the notion goes.

Audience: The oil consumers, oil dealers, wholesalers, refineries and the government of Massachusetts seem to be the main audience for this graph. However, the graph does not suggest any action that could be taken by the people in any of these categories. For e.g consumers do not get a direction as to how can they deal with the price surge nor does it inform the oil dealers regarding the strategies they could adopt to survive during the lean seasons.

For e.g. if the temperature variance really makes a considerable impact on the heating oil prices, then depending the weather forecast, one can predict how low the temperature might go. The customers can then plan to have enough heating oil storage during the lean periods by purchasing the oil at low prices and then using the same during chilly periods. Or they might as well switch to crude oil.  On the contrary, the wholesalers or dealers can order additional supplies from distant places (Europe or Gulf) to cover the potential rise in customer demand.

Redesign: In the below link, I have tried to redesign the visualization to present my ideas based on the data collected from the source in the article. Additionally, I have also referred to the US Climate Data portal to collect the temperature dataset for Massachusetts. I have also worked on the aesthetics to make the graphs neat and clean.

The below visualizations are drawn for the months Oct to Mar for the years 2012 through 2017. Similar visualizations can be drawn for the previous years. The visualization gives a comparison between the Massachusetts heating oil prices and the temperature which happens to be one of the others affecting the oil prices.

References:

Original article: http://www.mass.gov/eea/energy-utilities-clean-tech/home-auto-fuel-price-info/heating-oil-price-surveys.html

Climate Data: http://www.usclimatedata.com/climate/boston/massachusetts/united-states/usma0046/2017/3

MA Heating Oil Prices Data: http://www.mass.gov/eea/energy-utilities-clean-tech/home-auto-fuel-price-info/historical-heating-oil-prices.pdf

http://abcnews.go.com/Business/story?id=5270588&page=1

http://nhoilheat.com/factors-affecting-heating-oil-prices/

http://www.slate.com/articles/business/the_juice/2015/12/new_england_s_warm_winter_brings_record_low_oil_prices.html

10 Best Or Worst Ways To Visualise Web Analytics Data

“Social Media is not about the exploitation to technology but service to community”

In times like these where the world is constantly changing, keeping oneself up-to-date with current news and affairs is becoming increasingly important. Though not everything that happens around the globe has a significant immediate impact on each one of us, being aware and well informed surely holds an excellent value.

While surfing through Facebook, Twitter or say LinkedIn, I often stumble upon some very interesting news feeds, articles, blog posts. I personally must agree that I spend more time on these sites than on any of the official new websites. Hence, for me, social media happens to a chief source of news. It is really thought provoking as to how social media brings together news, trends and best practices from various parts of the world. Facebook and Twitter also provide platforms that host live videos and real time updates.

Having said all this, recently I came across an article which left me wondering. The article –  People Don’t See Social Media as an ‘Important’ News Source claimed that one in ten US adults get news on Twitter and four in ten get news on Facebook. It had a couple of pie charts which showed that 17 % of US adults use Twitter and 10% get news from Twitter. On the similar lines, it showed that 66% of the US adults use Facebook and 41% get news on Facebook. Reading through the entire article, I learnt that it also provided some more information like the importance level of these sites and how do the younger generation perceive them.

Here’s my analysis over the visualization and the data presented in this article.

What did I like?

• The caption of the figure itself summarizes the findings the pie charts want to convey.
• By putting the numbers in a scale of 10, we can easily interpret what role Facebook and Twitter play in conveying news to the adults in the US.
• It also gives a quick comparison of the popularity of two of the biggest platforms which social media offers today and how adults contemplate them.

What more could it include?

Audience: Giving a thought on which group of users would find this information useful, it would be perhaps website hosts (Facebook and Twitter), news networks (having their official pages and accounts on FB & Twitter) and lastly the general curious public (like me!). As professor has been mentioning in class, every claim must promote some action. This chart is not actionable as it does not really provide much details as to what action each of these audience categories could take for their benefit. If it provided some details on the specific new channel accounts/pages are being followed/liked by those 10% of users(Twitter) and 41% of users(Facebook), it would then help in understanding the demand of various news networks. It enables a news network to take appropriate decisions to improve their visibility. It would also give Facebook and Twitter an opportunity to work on their algorithms of recommendations/suggestions for people.

Important Level: The table included below the graph depicts 3 levels of importance cited for FB and Twitter as a source of news – most important, important, not very important. If this information was included in the pie chart itself, the chart would have been more descriptive. Apart from that, the math being done seems to be incorrect because the percentage breakdown for Twitter users exceeds 100.

Age group: The chart only focuses on the US adults. However, the article also mentions that the younger Facebook and Twitter users tend to see the services differently than their older counterparts. As a viewer, I would also want to see the statistics for the younger generation since they have a comparatively better hold on technology. Hence it makes me ponder if the article title really holds true?

Other sources: The author could have also included data regarding what other sources are people considering to catch up with the news, if not Facebook or Twitter. Hence to me the chart is not completely functional.

Aesthetics: Using bright relevant colors and a bigger font would help reach out to a larger audience. The colors being used also plays a role in engaging the viewers.

Better Design – The author could have also furnished more insights of their research by doing something like this:

http://www.journalism.org/2013/11/14/news-use-across-social-media-platforms/5_profile-of-the-social-media-news-consumer/

The above visualization released 2 years back has a similar domain and is way more descriptive as it also categorizes the audience, news sources and social networks into different classes.

Redesign –  In the below link, I have tried to redesign the visualization to present my ideas based on the data the author must have had post the research.

https://drive.google.com/a/scu.edu/file/d/0Bz_BJfR_3JJDVGhaTEJEUjM0Qm8/view?usp=sharing

Conclusion: The article does provide some very interesting insights. But the charts included did not seem to be complete and are less instructive. Working more around the charts and the visualizations would empower the audience to act in a specific direction!

References:

https://www.gooddata.com/blog/5-data-visualization-best-practices

https://www.digitalready.org.au/training/social-media/why-have-an-online-presence/the-importance-of-social-networking

 

 

http://www.dailymail.co.uk/news/article-2062634/One-American-women-medication-mental-disorder.html

While surfing on internet, I came across a news article which claimed that more number of American women were taking medication to combat mental disorders. The article also included some statistics depicting the percentage of men, women, boys and girls taking medications in 2001 vs 2010.  Later, it also quoted some famous personalities who fought some serious mental ailments.

I had the following thoughts while reading this article. (P.S This blog only talks about the first bar graph in the article – Percent of Population using Mental Health Medications)

• It would have been more engaging if the data was time-sequenced from 2001 to 2010. Seeing the change in the numbers from 2001 through 2010 gives me a deeper understanding of the situation.
• I really liked the way in which they segregated the data into four categories – men, women, girls and boys. But having said that, just by looking at the graph, I cannot interpret the age groups being considered to form those divisions. For e.g. what category would a female who is 23 years in age fall into? It would have made more sense to me, if the X axis also incorporated this information below each of those labels.
• The bars being labelled with numbers helps in understanding the percent increase/decrease in one glance. However, this makes the Y axis and the guidelines redundant. Besides, the colors being used are too dull to catch any attention. Using bright colors and a bigger font would help reach out to a larger audience. As we learnt in the class, putting in 3D effects don’t really help in conveying a message apart from making the graph look hodgepodge.
• The correct placement of the legend also has its role to play for the readers to quickly learn what the visualization is about. Thus, having the legend placed at the top right corner where there is sufficient space would have been appropriate.
• Lastly, incorporating some additional data perhaps the occupation, relationship status, would also help readers gauge the causes of increase in number of people and especially women, moving towards medication due to mental illness.

While it’s clear that the article focuses on a serious subject, the graphs included did not seem to be very intuitive and informative to me. Applying better visualization techniques would have been more effective in proving their point!