Medical Data Visualizer - 'Expected different values in heat map.'

Python
1

Hello everyone,

First of all, apologies for creating yet another thread about this issue, but the reality is none of the ones I found were able to solve my problem… I keep getting the following error in the heatmap exercise:

FAIL: test_heat_map_values (test_module.HeatMapTestCase)

Traceback (most recent call last):
File “/home/runner/boilerplate-medical-data-visualizer-2/test_module.py”, line 48, in test_heat_map_values
self.assertEqual(actual, expected, “Expected different values in heat map.”)
AssertionError: Lists differ: [‘0.0[569 chars], ‘0.0’, ‘-0.0’, ‘-0.0’, ‘0.4’, ‘0.0’, ‘0.1’, [38 chars]0.1’] != [‘0.0[569 chars], ‘0.1’, ‘-0.1’, ‘-0.1’, ‘0.7’, ‘0.0’, ‘0.2’, [38 chars]0.1’]

First differing element 79:
‘0.0’
‘0.1’

[‘0.0’,
‘0.0’,
‘-0.0’,
‘0.0’,
‘-0.1’,
‘0.5’,
‘0.0’,
‘0.1’,
‘0.1’,
‘0.3’,
‘0.0’,
‘0.0’,
‘0.0’,
‘0.0’,
‘0.0’,
‘0.0’,
‘0.2’,
‘0.1’,
‘0.0’,
‘0.2’,
‘0.1’,
‘0.0’,
‘0.1’,
‘-0.0’,
‘-0.1’,
‘0.1’,
‘0.0’,
‘0.2’,
‘0.0’,
‘0.1’,
‘-0.0’,
‘-0.0’,
‘0.1’,
‘0.0’,
‘0.1’,
‘0.4’,
‘-0.0’,
‘-0.0’,
‘0.3’,
‘0.2’,
‘0.1’,
‘-0.0’,
‘0.0’,
‘0.0’,
‘-0.0’,
‘-0.0’,
‘-0.0’,
‘0.2’,
‘0.1’,
‘0.1’,
‘0.0’,
‘0.0’,
‘0.0’,
‘0.0’,
‘0.3’,
‘0.0’,
‘-0.0’,
‘0.0’,
‘-0.0’,
‘-0.0’,
‘-0.0’,
‘0.0’,
‘0.0’,
‘-0.0’,
‘0.0’,
‘0.0’,
‘0.0’,
‘0.2’,
‘0.0’,
‘-0.0’,
‘0.2’,
‘0.1’,
‘0.3’,
‘0.2’,
‘0.1’,
‘-0.0’,
‘-0.0’,
‘-0.0’,
‘-0.0’,

  • ‘0.1’,
  • ‘-0.1’,
  • ‘-0.1’,
  • ‘0.7’,
    ‘0.0’,
  • ‘-0.0’,
  • ‘-0.0’,
  • ‘0.4’,
    ? ^
  • ‘0.2’,
    ? ^
  • ‘0.0’,
    ‘0.1’,
    ‘0.1’,
  • ‘0.0’,
    ‘-0.0’,
    ‘0.0’,
    ‘-0.0’,
    ‘0.1’] : Expected different values in heat map.

I have looked and relooked at my code, and nothing seems to explain why this is happening… Here is the code:

# Draw Heat Map
def draw_heat_map():
    # Clean the data
    df_heat = df[(df['ap_lo'] <= df['ap_hi']) & 
             (df['height'] >= (df['height'].quantile(0.025))) & 
             (df['height'] <= (df['height'].quantile(0.975))) & 
             (df['weight'] >= (df['weight'].quantile(0.025))) & 
             (df['weight'] <= (df['weight'].quantile(0.975)))]

    # Calculate the correlation matrix
    corr = df_heat.corr()

    # Generate a mask for the upper triangle
    mask = np.triu(np.ones_like(corr, dtype=bool))

    # Set up the matplotlib figure
    fig, ax = plt.subplots()

    # Draw the heatmap with 'sns.heatmap()'

    sns.heatmap(corr, 
                mask=mask, 
                vmax=.3, 
                square=True,
                linewidths=.5,
                annot = True,
                fmt='.1f')

# Do not modify the next two lines
    fig.savefig('heatmap.png')
    return fig

You can access the link here as well, in case it is helpful: https://replit.com/@DiogoSilvano/boilerplate-medical-data-visualizer-2#medical_data_visualizer.py

Thank you!

2

Your data cleaning is incorrect.

# overweight, first calculate their BMI by dividing their weight in 
# kilograms by the square of their height in meters. If that value is > 25 
# then the person is overweight. Use the value 0 for NOT overweight and the 
# value 1 for overweight.
df['overweight'] = np.where(df['weight']/(np.sqrt((df['height']/10)))>25, 1, 0)

“Square” and “square root” are not the same thing. And the height must be meters, not decimeters.

3

Ah, that was exactly it! Was focusing so much on last bit of code, that completely missed the impact that could have. Thanks a lot!

4

Hi @jeremy.a.gray.
could you please help me out too?
I have a similar issue.

5

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