Still have the same error after reshaping

I set my column 1 to 13 as X and column 14 as my Y.

My data set has 14 columns and 401 rows including the parameters

Bp,Sg,Al,Su,Rbc,Bu,Sc,Sod,Pot,Hemo,Wbcc,Rbcc,Htn,Class

80,1.02,1,0,1,36,1.2,137.53,4.63,15.4,7800,5.2,1,1

50,1.02,4,0,1,18,0.8,137.53,4.63,11.3,6000,4.71,0,1

80,1.01,2,3,1,53,1.8,137.53,4.63,9.6,7500,4.71,0,1

70,1.005,4,0,1,56,3.8,111,2.5,11.2,6700,3.9,1,1

80,1.01,2,0,1,26,1.4,137.53,4.63,11.6,7300,4.6,0,1

This is my code

import pandas as pd

from sklearn.metrics import accuracy_score

from sklearn.model_selection import train_test_split

from sklearn.ensemble import RandomForestClassifier

from PIL import Image

import streamlit as st

skipinitialspace = True

data = pd.read_csv("C:/Users/ADMIN/PycharmProjects/pythonProject/venv/KidneyPrediction/Kidney.csv")


st.subheader('Data Information: ')

st.dataframe(data)

st.write(data.describe())

chart = st.bar_chart(data)


X = data.iloc[:,0:13].values

X.reshape(-1, 13)

Y = data.loc[:,'Class'].values

Y.reshape(-1,1)

X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.25, random_state=0)



The error is 
ValueError: Expected 2D array, got scalar array instead: array=nan. Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.
Traceback:
File "C:UsersADMINPycharmProjectspythonProjectvenvKidneyPredictionKidney_Prediction.py", line 72, in <module>
    prediction = RandomForestClassifier.predict(user_input)