INFO 4602-5602: Project 2


This project explores the National Center for Women in Technology(NCWIT) dataset. All of our four visualizations focus on comparisons between female and male from different aspects: time, enrollment number, graduated number, drop-out(left institution) number, major declaration time and race distribution.

The Ratio of Female to Male in Enrollment, Graduated and Dropout Count with Years


Data Queries

Mouseover to get detailed data information. Click on legends to filter data.

Conclusions:

  • The enrollment ratio gradually incresed indicates that more and more female enrolled in CS-related major.

  • The ratio of female/male in Enrollment and Graduated are higher than Dropout, indicating less female per male dropout during school years.

Chart

The Actual Count in Enrollment, Graduated and Dropout of Female and Male with Years


Data Queries

Enrollment:
Graduated:
Quit:
Mouseover to get detailed data information.

Conclusions:

  • The number of male is much more than female in all enrollment, graduated and dropout aspects.

Chart

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The Enrollment Count with Major Declaration Time of Female and Male


Data Queries

Female:

Male:

Mouseover to get tooltips; Click on legends to filter data.

Conclusions:

  • Enrollment trend is almost the same between male and female students.

  • Enrollment count decreases as time goes by.

Chart

The Race Distribution of Total Female and Male with year


Vis4 Description


We use color depth to indicate amount.

Click on pie chart to zoom in; click on center to zoom out.

Conclusions:

  • Number of male students are much more than female students no matter which year.
    (first layer)

  • Number of students increased sharply after 2010 no matter which gender.
    (second layer after zooming in)

  • White, asian and hispanics are top dominated races no matter which year which gender.
    (third layer after zooming in)

Chart