Medical Data Visualizer Confusion

Python
#44

try this
df_cat = df_cat.groupby([‘cardio’,‘variable’, ‘value’], as_index = False).size().rename(columns={‘size’:‘total’})

1 Like
#45

Yes, it works perfectly fine. I wonder what’s the purpose of creating a data-frame which is grouped by cardio…

#46

Doesn’t work for me, I get wired plot in my legend there are two 1 and two 0

#47

I got this solution for the catplot, and it worked!

df_cat = pd.melt(df, id_vars = "cardio", value_vars = ["active", "alco", "cholesterol", "gluc", "overweight", "smoke"])

fig = sns.catplot(x = "variable", hue = "value", col = "cardio", data = df_cat, kind = "count").set_axis_labels("variable", "total")
#48

I have a question, why is gluc and cholesterol ‘normalised’ in a different way? Why can’t cholesterol be ‘normalised’ in the same way as gluc is? Thank you!

#49

Like many of you, I am getting plots that look correct but failing the tests. It didn’t seem like anyone completely solved this.

#50

https://repl.it/@sapienza789/boilerplate-medical-data-visualizer-2#medical_data_visualizer.py

#52

It wasn’t working for me either…I was plotting the catplot just like others taught before but, although I was getting the graphs right, it was failing the tests:
fig = sns.catplot(x = "variable", hue = "value", col = "cardio", data = df_cat, kind = "count")
The point that others explained was:

  1. The catplot as it is returns a FacetGrid object, thus, you need to get the figure attribute to pass as the return of the “draw_cat_plot” function. Kind of like this:
    g = sns.catplot(x = "variable", hue = "value", col = "cardio", data = df_cat, kind = "count")
    fig = g.fig
    return fig

  2. Finally, you need to set the y-label to ‘total’ instead of ‘count’ to match the testing code. And for that, you can simply say :
    img.set_axis_labels(“variable”, “total”)

And that is it. My catplot results worked fine after this.