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.
Your code so far
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as npImport data
df = pd.read_csv(“medical_examination.csv”)
Add ‘overweight’ column
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 usingpd.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 datadf_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(df_heat.corr(), dtype=bool)) # Set up the matplotlib figure fig, ax = plt.subplots() # Draw the heatmap with 'sns.heatmap()' sns.heatmap(corr, mask = mask, annot=True) # Do not modify the next two lines fig.savefig('heatmap.png') return fig
Thank you in advance for the assistance
Your browser information:
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
Challenge: Data Analysis with Python Projects - Medical Data Visualizer
Link to the challenge: