Python 如何解决np.Reforme异常：数据必须是一维的

我正在尝试为多项式回归重塑数据。这是我的密码

data = pd.read_csv('GBPJPY.csv')

data.columns = np.array(['Date', 'open', 'high', 'low', 'close', 'vol'])

data.Date = pd.to_datetime(data.Date)

data = data.set_index(data.Date)

data = data[['open', 'high', 'low', 'close', 'vol']]

data = data.drop_duplicates(keep=False)

price = data.close.copy()

price = np.reshape(price,(-1,1))

# Polynomial Regression

polyReg = PolynomialFeatures(degree=3)
price_poly = polyReg.fit_transform(price)

我在一个地方出错了

price = np.reshape(price,(-1,1))

这是我的追踪

(main) C:\Users\Owner\Desktop\TradingAlgorithm>python main.py
Traceback (most recent call last):
  File "main.py", line 28, in <module>
    price = np.reshape(price,(-1,1))
  File "<__array_function__ internals>", line 6, in reshape
  File "C:\Users\Owner\Anaconda3\envs\main\lib\site-packages\numpy\core\fromnumeric.py", line 301, in reshape
    return _wrapfunc(a, 'reshape', newshape, order=order)
  File "C:\Users\Owner\Anaconda3\envs\main\lib\site-packages\numpy\core\fromnumeric.py", line 58, in _wrapfunc
    return _wrapit(obj, method, *args, **kwds)
  File "C:\Users\Owner\Anaconda3\envs\main\lib\site-packages\numpy\core\fromnumeric.py", line 51, in _wrapit
    result = wrap(result)
  File "C:\Users\Owner\Anaconda3\envs\main\lib\site-packages\pandas\core\generic.py", line 1918, in __array_wrap__
    return self._constructor(result, **d).__finalize__(self)
  File "C:\Users\Owner\Anaconda3\envs\main\lib\site-packages\pandas\core\series.py", line 305, in __init__
    data = sanitize_array(data, index, dtype, copy, raise_cast_failure=True)
  File "C:\Users\Owner\Anaconda3\envs\main\lib\site-packages\pandas\core\construction.py", line 482, in sanitize_array
    raise Exception("Data must be 1-dimensional")
Exception: Data must be 1-dimensional

---

应该做一些类似的事情：

price = data.close.copy()
price = price.values.reshape(-1,1)

或者，如果您愿意：

price = data.close.copy()
price = np.reshape(price.values, (-1,1))

---

应该做一些类似的事情：

price = data.close.copy()
price = price.values.reshape(-1,1)

或者，如果您愿意：

price = data.close.copy()
price = np.reshape(price.values, (-1,1))

---

price=data.close.values

系列的熊猫整形应该是

np.resporate（price.values，（-1,1））

price=data.close.values

系列的熊猫整形应该是

np.resporate（price.values，（-1,1））

。