Numpy：只有整数标量数组才能转换为标量索引

Question

下面是代码：

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import pandas_datareader as web
import datetime as dt 

from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, LSTM

# Load data
company = 'FB'

start = dt.datetime(2012,1,1)
end = dt.datetime(2020,1,1)

data = web.DataReader(company, 'yahoo', start, end)

#Prepare Data
scaler = MinMaxScaler(feature_range=(0,1))
scaled_date = scaler.fit_transform(data['Close'].values.reshape(-1,1))

prediction_days = 60

x_train = []
y_train = []

for x in range(prediction_days, len(scaled_date)):
    x_train.append(scaled_date[x-prediction_days:x, 0])
    y_train.append(scaled_date[x, 0])

x_train, y_train = np.array(x_train), np.array(y_train)
x_train = np.reshape(x_train, (x_train.shape[0], x_train[1], 1)) #the error's here

我得到以下错误：

回溯（最后一次调用）：文件“/Users/evgenypavlov/Documents/ml_tutorial_1/main.py”，第34行，在x_train=np中。重塑（x_列，（x_列.shape[0]，x_列[1]，1]）文件“

据我所知，我已经把它转换成np了。数组，那么什么会导致此问题以及如何解决它？

Answer 1

元组的第二个元素中缺少形状：

x_train = np.reshape(x_train, (x_train.shape[0], x_train.shape[1], 1))