Tell us what’s happening:
There is an issue with the pythn version compatible with the numpy python version.
Your code so far
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
Import data
df = pd.read_csv(‘medical_examination.csv’)
Add ‘overweight’ column
Add ‘overweight’ column
df[‘overweight’] = (df[‘weight’] / (df[‘height’] / 100) ** 2 > 25).astype(int)
Normalize data by making 0 always good and 1 always bad. If the value of ‘cholestorol’ or ‘gluc’ is 1,
make the value 0. If the value is more than 1, make the value 1.
df[‘cholesterol’] = (df[‘cholesterol’] > 1).astype(int)
df[‘gluc’] = (df[‘gluc’] > 1).astype(int)
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 collumns for the catplot to work correctly.
df_cat = df_cat.groupby(['cardio', 'variable', 'value']).size().reset_index()
df_cat = df_cat.rename(columns={0: 'total'})
# Draw the catplot with 'sns.catplot()'
graph = sns.catplot(data=df_cat, kind="bar", x="variable", y="total", hue="value", col="cardio")
fig = graph.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
mask = np.triu(np.ones_like(corr, dtype=bool))
# Set up the matplotlib figure
fig, ax = plt.subplots(figsize=(16, 9))
# Draw the heatmap with 'sns.heatmap()'
sns.heatmap(corr, mask=mask, square=True, linewidths=0.5, annot=True, fmt="0.1f")
# Do not modify the next two lines
fig.savefig('heatmap.png')
return fig
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Challenge Information:
Data Analysis with Python Projects - Medical Data Visualizer