freecodecamp-data-analysis/demographic-data-analyzer
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

fix: typos in README file and tests (#6)

Browse Source 
* test: fix typo in test assertion error message

* docs: fix typo in README file
This commit is contained in:
PBM 2021-07-08 12:21:38 +02:00 committed by GitHub
parent 9cdd9b4358
commit 1a010b2c49
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
README.md
View File

@ -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?
* 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`.

2
test_module.py
View File

@ -48,7 +48,7 @@ class DemographicAnalyzerTestCase(unittest.TestCase):
def test_highest_earning_country_percentage(self):
actual = self.data['highest_earning_country_percentage']
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):
actual = self.data['top_IN_occupation']