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-### Assignment
-
 # Demographic Data Analyzer
 
-In this challenge you must analyze demographic data using Pandas. You are given a dataset of demographic data that was extracted from the 1994 Census database. Here is a sample of what the data looks like:
-
-|    |   age | workclass        |   fnlwgt | education   |   education-num | marital-status     | occupation        | relationship   | race   | sex    |   capital-gain |   capital-loss |   hours-per-week | native-country   | salary   |
-|---:|------:|:-----------------|---------:|:------------|----------------:|:-------------------|:------------------|:---------------|:-------|:-------|---------------:|---------------:|-----------------:|:-----------------|:---------|
-|  0 |    39 | State-gov        |    77516 | Bachelors   |              13 | Never-married      | Adm-clerical      | Not-in-family  | White  | Male   |           2174 |              0 |               40 | United-States    | <=50K    |
-|  1 |    50 | Self-emp-not-inc |    83311 | Bachelors   |              13 | Married-civ-spouse | Exec-managerial   | Husband        | White  | Male   |              0 |              0 |               13 | United-States    | <=50K    |
-|  2 |    38 | Private          |   215646 | HS-grad     |               9 | Divorced           | Handlers-cleaners | Not-in-family  | White  | Male   |              0 |              0 |               40 | United-States    | <=50K    |
-|  3 |    53 | Private          |   234721 | 11th        |               7 | Married-civ-spouse | Handlers-cleaners | Husband        | Black  | Male   |              0 |              0 |               40 | United-States    | <=50K    |
-|  4 |    28 | Private          |   338409 | Bachelors   |              13 | Married-civ-spouse | Prof-specialty    | Wife           | Black  | Female |              0 |              0 |               40 | Cuba             | <=50K    |
-
-
-You must use Pandas to answer the following questions:
-* 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)
-* What is the average age of men?
-* What is the percentage of people who have a Bachelor's degree?
-* What percentage of people with advanced education (`Bachelors`, `Masters`, or `Doctorate`) make more than 50K?
-* What percentage of people without advanced education make more than 50K?
-* What is the minimum number of hours a person works per week?
-* What percentage of the people who work the minimum number of hours per week have a salary of more than 50K?
-* What country has the highest percentage of people that earn >50K and what is that percentage?
-* Identify the most popular occupation for those who earn >50K in India. 
-
-Use the starter code in the file `demographic_data_analyzer`. Update the code so all variables set to "None" are set to the appropriate calculation or code. Round all decimals to the nearest tenth.
-
-Unit tests are written for you under `test_module.py`.
-
-### Development
-
-For development, you can use `main.py` to test your functions. Click the "run" button and `main.py` will run.
-
-### Testing 
-
-We imported the tests from `test_module.py` to `main.py` for your convenience. The tests will run automatically whenever you hit the "run" button.
-
-### Submitting
-
-Copy your project's URL and submit it to freeCodeCamp.
-
-### Dataset Source
-
-Dua, D. and Graff, C. (2019). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.
\ No newline at end of file
+This is the boilerplate for the Demographic Data Analyzer project. Instructions for building your project can be found at https://www.freecodecamp.org/learn/data-analysis-with-python/data-analysis-with-python-projects/demographic-data-analyzer