Tell us what’s happening:
So yeah, I did it. I created my own plot and heatmap in the Medical Data Visualizer Challenge. I know the code is not pretty but I did it at the end lmao.
But I keep getting Failed (error = 2) and it says it’s an error in test_module.py
How does one get through this problem? If you can, tell me what to fix and not how to fix it. Because I want to learn BABY!
Anyway, thank you before hand
Your code so far
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
Import data
df = pd.read_csv(“medical_examination.csv”)
Add ‘overweight’ column
df[‘overweight’] = “”
mask0 = df.weight / (df.height/100)**2 <= 25
mask1 = df.weight / (df.height/100)**2 > 25
df.overweight[mask0] = 0
df.overweight[mask1] = 1
df = df.astype({“overweight”: int})
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.
maskC0 = df.cholesterol <= 1
maskC1 = df.cholesterol > 1
df.cholesterol[maskC0] = 0
df.cholesterol[maskC1] = 1
maskC0 = df.gluc <= 1
maskC1 = df.gluc > 1
df.gluc[maskC0] = 0
df.gluc[maskC1] = 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=[‘active’,‘alco’,‘cholesterol’,‘gluc’,‘overweight’,‘smoke’])
# 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 = pd.melt(df, id_vars='cardio',value_vars=['active','alco','cholesterol','gluc','overweight','smoke'])
# Draw the catplot with 'sns.catplot()'
fig = sns.catplot(x="variable", hue="value", col="cardio", data=df_cat, kind="count")
fig.set_axis_labels(y_var="Total")
# Do not modify the next two lines
fig.savefig('catplot.png')
return fig
Draw Heat Map
def draw_heat_map():
# Clean the data
df_mask = (df.ap_hi >= df.ap_lo) & (df.height.quantile(0.025) <= df.height) & (df.weight.quantile(0.025) <= df.weight) & (df.weight.quantile(0.975) >= df.weight) & (df.height.quantile(0.975) >= df.height)
df_heat = df[df_mask]
# Calculate the correlation matrix
corr = df_heat.corr(method="pearson")
# Generate a mask for the upper triangle
mask = np.zeros_like(corr)
Triangle = np.triu_indices_from(mask)
mask[Triangle] = True
# Set up the matplotlib figure
fig, ax = plt.subplots(figsize=(12, 12))
# Draw the heatmap with 'sns.heatmap()'
sns.heatmap(corr,mask=mask,annot=True,fmt='.1f')
# Do not modify the next two lines
fig.savefig('heatmap.png')
return fig
The Error
ERROR: test_bar_plot_number_of_bars (test_module.CatPlotTestCase)
Traceback (most recent call last):
File “/home/runner/boilerplate-medical-data-visualizer-5/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-5/test_module.py”, line 13, in test_line_plot_labels
actual = self.ax.get_xlabel()
AttributeError: ‘numpy.ndarray’ object has no attribute ‘get_xlabel’
Your browser information:
User Agent is: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.99 Safari/537.36
Challenge: Medical Data Visualizer
Link to the challenge: