Data update 2

Lead: Men are represented seven times more in the nominations of filmmaking roles at the Academy Awards since 2000.

Excel Workbook link and explanation: my spreadsheet tracks the nominations and wins since the 2000s at the Academy Awards. The spreadsheet shows the nominations and wins in the categories of directing, editing and screenwriting. I separated the data into four sets: male nominations, female nominations, male wins and female wins.

Original dataset link

News story/study link and brief explanation: This article from Variety reports that there has been little improvement in the representation of women in non-acting awards at the Academy Awards. The article refers to a report done by the Women's Media Center that women make up 23% of this year's non-acting nominees, a 3% increase from last year. This article relates to my data since I intend to show the difference in nominations in filmmaking roles, and the ratio of female to male nominees.

Practice Embed

Here is my data wrapper chart



That was my data wrapper chart

Data Update 1

1. What dataset will you use for your final report?

I will be using this search filter for finding data of Oscar nominations and wins. I plan to search for all nominees and winners in the categories screenwriting, directing and editing from the year 2000 onward.

2. Describe the dataset. What kind of data does it contain?


The data is customized to the search filters that are applied. For what I want to find out, I ran two searches: all females - nominees and winners -  in the aforementioned categories between my time period and the same search but for males. Unfortunately, the data sets only come up as PDFs, so I have to manually transcribe the data into an excel sheet.


3. Is there anything about your data that you don’t understand? (i.e. what a column heading means). How will you find this out?


The data is a pretty simple set since I can customize it to what I want to know. The only issue with the data is that if a group of people is nominated together, males can show up on the female data and vice-versa. I therefore have to take the extra step to search any unisex names to confirm the gender. I also have to be careful about if there are any nominees/winners outside of these two genders. So far this has not come up in the data, which could be an interesting point as well.


 4. What are some questions you hope to answer with your data? List at least three. (you don’t need the answers at this point)

• What is the ratio of men/women nominated for "creator" roles since 2000?
• Are women simply not winning, or are they not being nominated?
• Has there been an improvement in the diversity of representation over time?

Data Visualization Analysis

This data visualization comes from the Economist provides a look into what is considered as sexual harassment in the workplace dependent on age, sex and nationality. Surveyors asked participants if they would "consider it sexual harassment if a man, who was not a romantic partner, did the following to a woman?." The orange line represents female results and blue male. The X-axis shows the age range and the Y-axis shows the percentage of participants that agreed with the statement. 

I think that the graph does a great job representing the data it's been given in regards to the type of graph that they've used. The fact that they are only comparing male to female makes it easy to compare the results on the graph. The type of graph (dual-line) is great to show the how opinions of participants evolves with age. 

The Y-axis represents the percentage that the participants agreed with the aforementioned statements. Surveyors had the scale start at zero and move up to 100 but 25 intervals. I think that this works well, especially since it represented in percentages. The fact that 50% is also in the middle of the graph makes sense and allows readers to gain a better understanding. 

The X-axis represents the age of the participants and is, in my opinion, unclear. The axis starts at 18

which makes sense for this particular survey. However, the start of the axis ranges 18-30 and then the next landmark isn't until the end of the axis which is 64+. This axis is very unclear as it suggests that the starting point of the graph is the average of the ages 18-30 and that the end point is anyone 64 or over (without offering insight on how old the oldest participant was). With this, readers cannot find out what age agrees with the statements but only how the general census either improves or lowers. The axis as a whole is not clear on what age is at one point in the graph.

Another issue with this visualization is that there are just too many graphs in a single area. In total, there are 35 individual graphs that make up this visualization. It's difficult to compare the results of Britain's survey with that of the United States since they are so far away. If the object is to show how age and gender effect views on sexual harassment, it would have been better to do a single, more detailed graph. If the object is to compare nationalities, then there needs to be a better layout to compare data. 

In summary, I feel that this graph does a great job in laying out how to represent the different in gender and age range. However, I feel that it is trying to do too much with comparing results of five different countries with seven different scenarios on top of age and gender. 

Embed test

Here is the chart I want to embed.

The chart I wanted to embed is right above this sentence.