# Medical Data Analyzer - Data Analysis with Python

Hi! I’ve been trying to debug my code to the best of my ability for a while now and it’s waning on me. Would someone mind taking a look and letting me know what I’m missing? Thank you so much!

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np

# Import data

df['overweight'] = df['weight'] / ((df['height']/100)**2)
df.loc[df['overweight'] > 25, 'overweight'] = 1
df.loc[df['overweight'] != 1, 'overweight'] = 0
# Normalize data by making 0 always good and 1 always bad. If the value of 'cholesterol' or 'gluc' is 1, make the value 0. If the value is more than 1, make the value 1.
df.loc[df['cholesterol'] == 1, 'cholesterol'] = 0
df.loc[df['cholesterol'] > 1, 'cholesterol'] = 1
df.loc[df['gluc'] == 1, 'gluc'] = 0
df.loc[df['gluc'] > 1, 'gluc'] = 1
# Draw Categorical Plot
def draw_cat_plot():
# Create DataFrame for cat plot using `pd.melt` using just the values from 'cholesterol', 'gluc', 'smoke', 'alco', 'active', and 'overweight'.

# Group and reformat the data to split it by 'cardio'. Show the counts of each feature. You will have to rename one of the columns for the catplot to work correctly.
df_cat = df.melt(id_vars = ['cardio'], value_vars = ['cholesterol', 'gluc', 'smoke', 'alco', 'active', 'overweight'])

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

# Get the figure for the output
fig = sns.catplot(data = df_cat, x = 'variable', kind='count', hue='value', col='cardio')

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

# Draw Heat Map
def draw_heat_map():
# Clean the data
df_heat = df.loc[(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['height'] <= df['height'].quantile(0.975))]

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

# Generate a mask for the upper triangle

# Set up the matplotlib figure
fig, ax = plt.subplots(figsize=(9,7))

# Draw the heatmap with 'sns.heatmap()'
sns.heatmap(corr,
vmin=-0.16,
vmax=0.32,
center=0,
annot=True,
fmt=".1f",
cbar_kws={"shrink": 0.5, 'ticks': [-0.08, 0.00, 0.08, 0.16, 0.24]})

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

Here’s the output in the console on replit:

 python main.py
EE/home/runner/boilerplate-medical-data-visualizer/venv/lib/python3.8/site-packages/seaborn/matrix.py:268: PendingDeprecationWarning:
The label function will be deprecated in a future version. Use Tick.label1 instead.
fontsize = tick.label.get_size()
.['0.0', '0.0', '-0.0', '0.0', '-0.1', '0.5', '0.0', '0.1', '0.1', '0.2', '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',
 python main.py
EE/home/runner/boilerplate-medical-data-visualizer/venv/lib/python3.8/site-packages/seaborn/matrix.py:268: PendingDeprecationWarning:
The label function will be deprecated in a future version. Use Tick.label1 instead.
fontsize = tick.label.get_size()
.['0.0', '0.0', '-0.0', '0.0', '-0.1', '0.5', '0.0', '0.1', '0.1', '0.2', '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',
 python main.py
EE/home/runner/boilerplate-medical-data-visualizer/venv/lib/python3.8/site-packages/seaborn/matrix.py:268: PendingDeprecationWarning:
The label function will be deprecated in a future version. Use Tick.label1 instead.
fontsize = tick.label.get_size()
.['0.0', '-0.0', '-0.1', '-0.0', '-0.1', '0.6', '-0.0', '0.0', '0.3', '0.4', '0.0', '0
 python main.py
EE/home/runner/boilerplate-medical-data-visualizer/venv/lib/python3.8/site-packages/seaborn/matrix.py:268: PendingDeprecationWarning:
The label function will be deprecated in a future version. Use Tick.label1 instead.
fontsize = tick.label.get_size()
.['0.0', '-0.0', '-0.1', '-0.0', '-0.1', '0.6', '-0.0', '0.0', '0.3', '0.4', '0.0', '0
 python main.py
EE/home/runner/boilerplate-medical-data-visualizer/venv/lib/python3.8/site-packages/seaborn/matrix.py:268: PendingDeprecationWarning:
The label function will be deprecated in a future version. Use Tick.label1 instead.
fontsize = tick.label.get_size()
.['0.0', '-0.0', '-0.1', '-0.0', '-0.1', '0.6', '-0.0', '0.0', '0.3', '0.4', '0.0', '0
 python main.py
EE/home/runner/boilerplate-medical-data-visualizer/venv/lib/python3.8/site-packages/seaborn/matrix.py:268: PendingDeprecationWarning:
The label function will be deprecated in a future version. Use Tick.label1 instead.
fontsize = tick.label.get_size()
.['0.0', '-0.0', '-0.1', '-0.0', '-0.1', '0.6', '-0.0', '0.0', '0.3', '0.4', '0.0', '0
 python main.py
EE/home/runner/boilerplate-medical-data-visualizer/venv/lib/python3.8/site-packages/seaborn/matrix.py:268: PendingDeprecationWarning:
The label function will be deprecated in a future version. Use Tick.label1 instead.
fontsize = tick.label.get_size()
.['0.0', '0.0', '-0.0', '0.0', '-0.1', '0.5', '0.0', '0.1', '0.1', '0.2', '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',
 python main.py
EE/home/runner/boilerplate-medical-data-visualizer/venv/lib/python3.8/site-packages/seaborn/matrix.py:268: PendingDeprecationWarning:
The label function will be deprecated in a future version. Use Tick.label1 instead.
fontsize = tick.label.get_size()
.['0.0', '0.0', '-0.0', '0.0', '-0.1', '0.5', '0.0', '0.1', '0.1', '0.2', '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', '0.6', '0.0', '0.2', '0.1', '0.1', '-0.0', '0.0', '-0.0', '0.1', '', '', '']
F
======================================================================
ERROR: test_bar_plot_number_of_bars (test_module.CatPlotTestCase)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/runner/boilerplate-medical-data-visualizer/test_module.py", line 26, in test_bar_plot_number_of_bars
actual = len([rect for rect in self.ax.get_children() if isinstance(rect, mpl.patches.Rectangle)])
AttributeError: 'numpy.ndarray' object has no attribute 'get_children'

======================================================================
ERROR: test_line_plot_labels (test_module.CatPlotTestCase)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/runner/boilerplate-medical-data-visualizer/test_module.py", line 13, in test_line_plot_labels
actual = self.ax.get_xlabel()
AttributeError: 'numpy.ndarray' object has no attribute 'get_xlabel'

======================================================================
FAIL: test_heat_map_values (test_module.HeatMapTestCase)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/runner/boilerplate-medical-data-visualizer/test_module.py", line 47, in test_heat_map_values
self.assertEqual(actual, expected, "Expected different values in heat map.")
AssertionError: Lists differ: ['0.0[59 chars], '0.2', '0.0', '0.0', '0.0', '0.0', '0.0', '0[560 chars], ''] != ['0.0[59 chars], '0.3', '0.0', '0.0', '0.0', '0.0', '0.0', '0[548 chars]0.1']

First differing element 9:
'0.2'
'0.3'

First list contains 3 additional elements.
First extra element 91:
''

Diff is 1045 characters long. Set self.maxDiff to None to see it. : Expected different values in heat map.

----------------------------------------------------------------------
Ran 4 tests in 24.444s

FAILED (failures=1, errors=2)

It seems like some of the math is slightly off, but I’m not sure where I’ve gone wrong along the way. Any help is appreciated!

The AttributeErrors are because you are not returning the correct object in fig for the tests. There are many examples in the forums of the solution. You have to return a matplotlib figure object.

The heatmap problem is because this data cleaning is incorrect: