freecodecamp-data-analysis/demographic-data-analyzer
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fix: typos in README file and tests (#6)

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* test: fix typo in test assertion error message

* docs: fix typo in README file
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PBM 2021-07-08 12:21:38 +02:00 committed by GitHub
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README.md
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@ -24,7 +24,7 @@ You must use Pandas to answer the following questions:
* What country has the highest percentage of people that earn >50K and what is that percentage? * 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. * Identify the most popular occupation for those who earn >50K in India.
Use the starter code in the file `demographic_data_anaylizer`. Update the code so all variables set to "None" are set to the appropriate calculation or code. Round all decimals to the nearest tenth. 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`. Unit tests are written for you under `test_module.py`.

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test_module.py
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@ -48,7 +48,7 @@ class DemographicAnalyzerTestCase(unittest.TestCase):
def test_highest_earning_country_percentage(self): def test_highest_earning_country_percentage(self):
actual = self.data['highest_earning_country_percentage'] actual = self.data['highest_earning_country_percentage']
expected = 41.9 expected = 41.9
self.assertAlmostEqual(actual, expected, msg="Expected different value for heighest earning country percentage.") self.assertAlmostEqual(actual, expected, msg="Expected different value for highest earning country percentage.")
def test_top_IN_occupation(self): def test_top_IN_occupation(self):
actual = self.data['top_IN_occupation'] actual = self.data['top_IN_occupation']