LIME XAI shows wrong Location of the record in the Dataset

Question

import pandas as pd
import numpy as np



df=pd.read_csv('C:/gag/lpd.csv', engine='python',encoding='unicode_escape')

x = df.iloc[: , 0:-1]#Takes all rows of all columns except the last colum
y = df.iloc[: , -1] # Takes all rows of the last column

from sklearn.preprocessing import StandardScaler
sc_x = StandardScaler()
x_train = sc_x.fit_transform(x_train)
x_test = sc_x.transform(x_test)

import xgboost as xgb 
model=xgb.XGBClassifier(random_state=1,learning_rate=0.55,eval_metric='mlogloss')
model=xgb.XGBClassifier(random_state=1,learning_rate=0.55,eval_metric='mlogloss')
model.fit(x_train, y_train)
y_predxgb = model.predict(x_test)
model.score(x_test,y_test)

0.9973937123309985

explainer=lime_tabular.LimeTabularExplainer(training_data=np.array(x_train       ),
                                            class_names=['Affected' , 'Not Affected'],
                                            mode="classification",
                                           feature_names=x_train.columns,
                                           categorical_features=[0])

x_test.iloc[0]
    Age of the patient                       37.0
Gender of the patient                     0.0
Total Bilirubin                           8.9
Direct Bilirubin                          4.5
 Alkphos Alkaline Phosphotase           272.0
 Sgpt Alamine Aminotransferase           31.0
Sgot Aspartate Aminotransferase          61.0
Total Protiens                            5.8
 ALB Albumin                              2.0
A/G Ratio Albumin and Globulin Ratio      0.5
**Name: 5302**, dtype: float64

exp=explainer.explain_instance(data_row=x_test.iloc[0],
                              predict_fn=model.predict_proba)

exp.show_in_notebook(show_table=True)

Here the 'x_test.iloc[0]' the position iloc have given is zero but the result of the explainer shows 5302th record. how to get the correct position record result please help me to solve this problem.