# Data Analysis with Python Projects - Medical Data Visualizer

Tell us what’s happening:
I have reviewed the forum but I can’t seem to find the answer. This is the error I’m getting:

## 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: [‘0.0025’, ‘0.0034’, ‘-0.018’, ‘0.00033’, ‘-0.[795 chars].14’] != [‘0.0’, ‘0.0’, ‘-0.0’, ‘0.0’, ‘-0.1’, ‘0.5’, ‘[612 chars]0.1’]

First differing element 0:
‘0.0025’
‘0.0’

Diff is 2250 characters long. Set self.maxDiff to None to see it. : Expected different values in heat map.

Ran 4 tests in 6.473s

FAILED (failures=1)

Describe your issue in detail here.

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

# Import data

pd.set_option(‘display.max_columns’, None)
bmi = df[‘weight’] /( (df[‘height’]/100)**2)
df[‘overweight’] = np.where(bmi > 25, 1, 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[“cholesterol”] = np.where(df[“cholesterol”] == 1, 0,1)
df[“gluc”] = np.where(df[“gluc”] == 1, 0,1)

# 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’.
df_cat = pd.melt(df, id_vars=[ ‘cardio’], value_vars=[‘cholesterol’, ‘gluc’, ‘smoke’, ‘alco’, ‘active’, ‘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_cat.groupby([‘cardio’, ‘variable’]).value_counts()
df_cat = df_cat.reset_index()
df_cat.columns = [‘cardio’, ‘variable’, ‘value’, ‘total’]

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

my_plot = sns.catplot(data=df_cat, x='variable', y='total', col='cardio', kind = 'bar', hue = 'value')

# Get the figure for the output
fig = my_plot.fig

# 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[
``````

(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

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

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

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

Thank you in advance for the assistance

User Agent is: `Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.0.0 Safari/537.36`
This means your results are not rounded/formatted correctly. The documentation for `sns.heatmap()` can help you with that.