SHAP plotting waterfall using an index value in dataframe

Question

I am working on a binary classification using random forest algorithm

Currently, am trying to explain the model predictions using SHAP values.

So, I referred this useful post here and tried the below.

from shap import TreeExplainer, Explanation
from shap.plots import waterfall
sv = explainer(ord_test_t)
exp = Explanation(sv.values[:,:,1], 
                  sv.base_values[:,1], 
                  data=ord_test_t.values, 
                  feature_names=ord_test_t.columns)
idx = 20
waterfall(exp[idx])

I like the above approach as it allows to display the feature values along with waterfall plot. So, I wish to use this approach

However, this doesn't help me get the waterfall for a specific row in ord_test_t (test data).

For example, let's consider that ord_test_t.Index.tolist() returns 3,5,8,9 etc...

Now, I want to plot the waterfall plot for ord_test_t.iloc[[9]] but when I pass exp[9], it just gets the 9th row but not the index named as 9.

When I try exp.iloc[[9]] it throws error as explanation object doesnt have iloc.

Can help me with this please?