数据归一化 MinMaxScaler 时报错

我的代码：

import math
import datetime
import numpy as np
import pandas as pd
from pandas_datareader import data
import pandas_datareader.data as web
from sklearn.preprocessing import MinMaxScaler
from keras.models import Sequential
from keras.layers import Dense, LSTM
import matplotlib.pyplot as plt

# get data
start = datetime.datetime(2012,1,1)
end =datetime.datetime(2019,12,17)
df = web.DataReader("AAPL", "yahoo", start, end)

data = df.filter(['close'])
#convert dataframe to numpy array
dataset = data.values

trainning_data_len =math.ceil(len (dataset)*.8)

#scale the data
scaler = MinMaxScaler(feature_range=(0,1))
scaled_data = scaler.fit_transform(dataset)

我在查看 scaled_data 时报错如下：

ValueError: Found array with 0 feature(s) (shape=(2003, 0)) while a minimum of 1 is required by MinMaxScaler.

不清楚这个问题应该怎么解决