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I'd like to create five subplots (one for each category in a specific column of a dataframe) on a seaborn histogram (distplot).

My dataset is:

prog score
cool 1.9
cool 3.7
yay  4.5
yay  2.6
neat 1.4
neat 7
neat 6
wow  4.1
wow  1.7
wow  1.4
hooray 6.6
hooray 5.6
hooray 4.9
yikes 1.2
yikes 3.9
yikes 6.9

I don't want all of the 'prog's plotted, just each in a list:

prog_list = ['cool', 'yay', 'neat', 'yikes', 'wow']
scores = df['score']
f, axes = plt.subplots(3, 2, figsize=(15, 15))
# Delete last chart since there are only 5 subplots I need
f.delaxes(ax = axes[2,1])

for i, axes in enumerate(f.axes):
scores = df.loc[(df['prog'] == prog_list[i])]['score']
    axes = sns.distplot(scores, norm_hist=True, color='b')
    sigma = round(scores.std(), 3)
    mu = round(scores.mean(), 2)
    axes.set_xlim(1,7)
    axes.set_xticks(range(2,8))
    axes.set_xlabel('Score - Mean: {} (σ {})'.format(mu, sigma))
    axes.set_ylabel('Density')

But when I do this, it just plots each subset onto the same plot (which is kind of cool, but definitely not what I want here).

enter image description here

1 Answer 1

5

Try this:

# your code use axes and redefine it after every iteration
# I think this would be better
for prog, ax in zip(prog_list, axes.flatten()[:5]):
    scores = df.loc[(df['prog'] == prog)]['score']

    # note how I put 'ax' here
    sns.distplot(scores, norm_hist=True, ax=ax, color='b')

    # change all the axes into ax
    sigma = round(scores.std(), 3)
    mu = round(scores.mean(), 2)
    ax.set_xlim(1,7)
    ax.set_xticks(range(2,8))
    ax.set_xlabel('Score - Mean: {} (σ {})'.format(mu, sigma))
    ax.set_ylabel('Density')

plt.show()

Output:

enter image description here

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1 Comment

I don't think you need [:5] here while zipping because zip already takes care of that in case of unequal lists.

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