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In this project we analyze demographic data using Pandas. we are given a dataset of demographic data that was extracted from the 1994 Census database.

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Demographic Data Analyzer

In this project we analyze demographic data using Pandas. we are given a dataset of demographic data that was extracted from the 1994 Census database.

We use Pandas to answer the following questions:

  1. How many people of each race are represented in this dataset? This should be a Pandas series with race names as the index labels. (race column)
  2. What is the average age of men?
  3. What is the percentage of people who have a Bachelor's degree?
  4. What percentage of people with advanced education (Bachelors, Masters, or Doctorate) make more than 50K?
  5. What percentage of people without advanced education make more than 50K?
  6. What is the minimum number of hours a person works per week?
  7. What percentage of the people who work the minimum number of hours per week have a salary of more than 50K?
  8. What country has the highest percentage of people that earn >50K and what is that percentage?
  9. Identify the most popular occupation for those who earn >50K in India.
  • All the calculation code are in "demographic_data_analyzer.py"
  • We rounded all decimals to the nearest tenth.
  • For development, you can use "main.py" to test the code.

Testing

The unit tests for this project are in test_module.py. We imported the tests from test_module.py to main.py for your convenience.

Dataset Source

Dua, D. and Graff, C. (2019). UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science.

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In this project we analyze demographic data using Pandas. we are given a dataset of demographic data that was extracted from the 1994 Census database.

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