How to sort axes in seaborn so that categories with most values are displayed

Question

I have a dataset with about 320k records. Of these, I want to display a swarmplot with the top 20 entities of the category in the x axis (Refined_ID in this case) by their count. How can one achieve that? For example, if my data is:

Refined_ID Refined_Age Name
e123        21         foo1
f123        19         bar1
z123        26         foo2
f123        29         bar2
e123        20         foo1
e1342       19         bar3
f123        20         foo3

I would like my x-axis to be ordered as:

e123 f123 z123   

This is my code:

g = sns.swarmplot(x = dfAnalysis['Refined_ID'].iloc[:20],y = dfAnalysis['Refined_Age'], hue = dfAnalysis['Name'], orient="v")
g.set_xticklabels(g.get_xticklabels(),rotation=30)

As the dataframe is quite large, am limiting the view to first 20 rows for testing.

UPDATE 1

Assuming there isn't a way to dynamically sort the axes in seaborn, this is what I want my output to look like:

Refined_ID Refined_Age     Name   Count_of_Refined_ID
    e123        21         foo1     2
    f123        19         bar1     3
    z123        26         foo2     1
    f123        29         bar2     3
    e123        20         foo1     3
    e1342       19         bar3     1
    f123        20         foo3     3

From this dataframe, I would then want to plot the top two Refined_IDs based on their count. In this case, those two categories will be e123 and f123. The plot will have:

x-axis: Refined ID (e123 and f123)
y-axis: Refined_Age (0 to 30)
Hue: Based on Name

Answer 1

Is this what you want?

counts = df['Refined_ID'].value_counts()
ix = (df['Refined_ID'].apply(lambda x: counts[x])
      .sort_values(ascending=False).index)
df.reindex(ix)

  Refined_ID  Refined_Age  Name
6       f123           20  foo3
3       f123           29  bar2
1       f123           19  bar1
4       e123           20  foo1
0       e123           21  foo1
5      e1342           19  bar3
2       z123           26  foo2