Plotting Stock Price Prediction - Random Forest

Question

i am new here and not very skillfull in Python. I have some ongoing school project and I am stuck at the end of the project.

I would like to have a graph as this one: https://i.stack.imgur.com/wICq2.png

Some of the code:

close_stock = closedf.copy()
del closedf['Date']
scaler=MinMaxScaler(feature_range=(0,1))
closedf=scaler.fit_transform(np.array(closedf).reshape(-1,1))

training_size=int(len(closedf)*0.8)
test_size=len(closedf)-training_size
train_data,test_data=closedf[0:training_size,:],closedf[training_size:len(closedf),:1]

def create_dataset(dataset, time_step=1):
    dataX, dataY = [], []
    for i in range(len(dataset)-time_step-1):
        a = dataset[i:(i+time_step), 0]
        dataX.append(a)
        dataY.append(dataset[i + time_step, 0])
    return np.array(dataX), np.array(dataY)

time_step = 15
X_train, y_train = create_dataset(train_data, time_step)
X_test, y_test = create_dataset(test_data, time_step)

regressor = RandomForestRegressor(n_estimators = 100, random_state = 0)
regressor.fit(X_train, y_train)

train_predict=regressor.predict(X_train)
test_predict=regressor.predict(X_test)

train_predict = train_predict.reshape(-1,1)
test_predict = test_predict.reshape(-1,1)

train_predict = scaler.inverse_transform(train_predict)
test_predict = scaler.inverse_transform(test_predict)
original_ytrain = scaler.inverse_transform(y_train.reshape(-1,1)) 
original_ytest = scaler.inverse_transform(y_test.reshape(-1,1))

data = stock_data.filter(['Close'])
train = data[:training_size]
validation = data[training_size:]
validation['Predictions'] = test_predict
plt.figure(figsize=(16,8))
plt.title('Model')
plt.xlabel('Date')
plt.ylabel('Close Price EUR (€)')
plt.plot(train)
plt.plot(validation[['Close', 'Predictions']])
plt.legend(['Train', 'Validation', 'Predictions'], loc='lower right')
plt.show()

What I am doing wrong by plotting a graph?

Thank you very much for your help.