Change column type change value from another column (Python script)

Python script:

import pandas as pd
import numpy as np
from keras.layers import Dense, LSTM
from keras.models import Sequential
from keras.preprocessing.sequence import TimeseriesGenerator

def get_prediction_dates(num_prediction, df):

           last_date = df['date'].max()

           date_test = pd.date_range(last_date, periods=num_prediction+1, freq='M').to_frame(index=False,            name='date')

           date_test = date_test['date'].apply(lambda x : x.replace(day=1))

           return date_test

def predict(num_prediction, model):

           prediction_list = arr[-look_back:]

           for _ in range(num_prediction):

                      x = prediction_list[-look_back:]

                      x = x.reshape((1, look_back, 1))

                      out = model.predict(x)[0][0]

                      prediction_list = np.append(prediction_list, out)

           prediction_list = prediction_list[look_back-1:]

return prediction_list

look_back = 12
batch_size = 4

arr = dataset['quantity'].values
arr = arr.reshape((-1, 1))

generator = TimeseriesGenerator(arr, arr, length=look_back, batch_size = batch_size)

model = Sequential()
model.add(
LSTM(128,
activation='linear',
input_shape=(look_back, 1),
name="LSTM")
)
model.add(Dense(1, activation='linear', name="Dense"))
model.compile(optimizer='adam', loss='mse', metrics=['mean_absolute_percentage_error'])

model.fit(generator, epochs=70)

num_prediction = 6

forecast = predict(num_prediction, model)
forecast_dates = get_prediction_dates(num_prediction, dataset)

dataset = pd.DataFrame(list(zip(forecast_dates, forecast)), columns=['date', 'prediction'])

dataset['date'] = pd.to_datetime(dataset['date'])

I placed a seed, but is there any other way to prevent this from happening?