for loop to plot the top n features importance in bokeh in python without explicitly typing the column names

Question

I want to plot the top n features in RandomForestClassifier() in bokeh without specifying the column name explicitly in the y variable.

1. So firstly, instead of typing the column name in variable y, it can take the column name and value directly from the top feature of the randomclassifier.

   y = df['new']
   x = df.drop('new', axis=1)
   rf = RandomForestClassifier()
   rf.fit(x,y)
   
   #Extract the top feature from above and plot in bokeh
   
   source = ColumnDataSource(df)
   
   p1 = figure(y_range=(0, 10))
   
   # below I would like it to use the top feature in RandomClassifier 
   # instead of explicitly writing the column name, horsePower,
   # from the top features column
   
   p1.line(
       x = 'x',
       y = 'horsePower', 
       source=source,
       legend = 'Car Blue',
       color = 'Blue'
    )
   

2. Instead of specifying the first feature only, or the second feature only, we can build a for loop that plots the n top features in bokeh. I imagine it to be something close to this

   for i in range(5):
       p.line(x = 'x', y = ???? , source=source,) #top feature in randomClassifier
       p.circle(x = 'x', y = ???? , source=source, size = 10)
       row = [p]
   
   output_file('TopFeatures')
   show(p)
   

I have already extracted the top 15 features from the RandomForestClassifier of the model and printed the first 15 using

 new_rf = pd.Series(rf.feature_importances_,index=x.columns).sort_values(ascending=False) 

print(new_rf[:15]) 

Answer 1

Simply iterate through the index values of pandas series, new_rf, since its index is column names:

# TOP 1 FEATURE
p1.line(
    x = 'x',
    y = new_rf.index[0], 
    source = source,
    legend = 'Car Blue',
    color = 'Blue'
 )

# TOP 5 FEATURES
for i in new_rf[:5].index:

    output_file("TopFeatures_{}".format(i))

    p = figure(y_range=(0, 10))
    p.line(x = 'x', y = i, source = source)
    p.circle(x = 'x', y = i, source = source, size = 10)

    show(p)