Read Data Keras

from keras.models import Sequential
from keras.layers import Dense
import numpy as np

import pandas as pd
def ReadData(sf):
  print("Baca file :",sf)
  df = np.array(pd.read_csv(sf,header=None))
  df1 = pd.DataFrame(df)
  return df1.values

def ReadData2(sf,lw):
    print("Baca file :",sf)
    df = np.array(pd.read_csv(sf,header=None))
    y=df[lw:,3:4]
    x=[];
    for i in range(len(df)-lw):
        dm=np.concatenate((df[i:i+lw,0],df[i:i+lw,1],df[i:i+lw,2]))
        x.append(dm)
    x=np.array(x)
 
    return x,y


sf='Data.csv'
X,Y=ReadData2(sf,20)




model = Sequential()
model.add(Dense(1000, input_dim=60, activation='relu'))
model.add(Dense(1, activation='sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
history = model.fit(X, Y, epochs=500, batch_size=1)


https://www.pyimagesearch.com/2019/02/04/keras-multiple-inputs-and-mixed-data/

https://drive.google.com/open?id=13R-SxdZVdNG_2CAACgGnTJxX1Tz8f8zF