seaborn: barplot of a dataframe by group-CodePudding

I am having difficulty with this. I have the results from my initial model (`Unfiltered´), that I plot like so:

df = pd.DataFrame(
    {'class': ['foot', 'bike', 'bus', 'car', 'metro'],
     'Precision': [0.7, 0.66, 0.41, 0.61, 0.11],
     'Recall': [0.58, 0.35, 0.13, 0.89, 0.02],
     'F1-score': [0.64, 0.45, 0.2, 0.72, 0.04]}
)

groups = df.melt(id_vars=['class'], var_name=['Metric'])
sns.barplot(data=groups, x='class', y='value', hue='Metric')

To produce this nice plot:

Now, I obtained a second results from my improved model (filtered), so I add a column (status) to my df to indicate the results from each model like this:

df2 = pd.DataFrame(
    {'class': ['foot','foot','bike','bike','bus','bus',
               'car','car','metro','metro'],
 'Precison': [0.7, 0.62, 0.66, 0.96, 0.41, 0.42, 0.61, 0.75, 0.11, 0.3],
 'Recall': [0.58, 0.93, 0.35, 0.4, 0.13, 0.1, 0.89, 0.86, 0.02, 0.01],
 'F1-score': [0.64, 0.74, 0.45, 0.56, 0.2, 0.17, 0.72, 0.8, 0.04, 0.01],
 'status': ['Unfiltered', 'Filtered', 'Unfiltered','Filtered','Unfiltered',
           'Filtered','Unfiltered','Filtered','Unfiltered','Filtered']}
)

df2.head()
    class  Precison  Recall  F1-score   status
0   foot    0.70      0.58    0.64     Unfiltered
1   foot    0.62      0.93    0.74     Filtered
2   bike    0.66      0.35    0.45     Unfiltered
3   bike    0.96      0.40    0.56     Filtered
4   bus     0.41      0.13    0.20     Unfiltered

And I want to plot this, in similar grouping as above (i.e. foot, bike, bus, car, metro). However, for each of the metrics, I want to place the two values side-by-side. Take for example, the foot group, I would have two bars Precision[Unfiltered, filtered], then 2 bars for Recall[Unfiltered, filtered] and also 2 bars for F1-score[Unfiltered, filtered]. Likewise all other groups.

My attempt:

group2 = df2.melt(id_vars=['class', 'status'], var_name=['Metric'])
sns.barplot(data=group2, x='class', y='value', hue='Metric')

Totally not what I want.

CodePudding user response：

You can pass in hue any sequence as long as it has the same length as your data, and assign colours through it. So you could try with

group2 = df2.melt(id_vars=['class', 'status'], var_name=['Metric'])
sns.barplot(data=group2, x='class', y='value', hue=group2[['Metric','status']].agg(tuple, axis=1))
plt.legend(fontsize=7)

But the result is a bit hard to read:

CodePudding user response：

Seaborn grouped barplots don't allow for multiple grouping variables. One workaround is to recode the two grouping variables (Metric and status) as one variable with 6 levels. Another possibility is to use facets. If you are open to another plotting package, I might recommend