我有一個(gè)很長(zhǎng)的數(shù)據(jù)框需要展平。數(shù)據(jù)框看起來(lái)像這樣。我想展平這個(gè)表，用作referenceDate companyId索引，列應(yīng)該有兩層，第一層是data_item，第二層是N。我知道 pd.pivot 會(huì)解決這個(gè)問(wèn)題。+---------------+-----------+-----------+---+-------+| referenceDate | CompanyId | data_item | N | value |+---------------+-----------+-----------+---+-------+| 2020-01-31    |         1 | A         | 1 | 0.1   || 2020-01-31    |         2 | A         | 2 | 0.2   || 2020-01-31    |         3 | A         | 3 | 0.3   |+---------------+-----------+-----------+---+-------+然而，df = pd.pivot(df, values='value', index=['referenceDate', 'companyId'], columns=['data_item', 'N'])總是給出 valueErrorTraceback (most recent call last):  File "C:\Users\\PycharmProjects\venvs\\lib\site-packages\IPython\core\interactiveshell.py", line 3343, in run_code    exec(code_obj, self.user_global_ns, self.user_ns)  File "<ipython-input-56-3738f20d42ed>", line 1, in <module>    df = pd.pivot(df, values='value', index=['referenceDate', 'companyId'], columns=['data_item', 'N'])  File "C:\Users\\PycharmProjects\venvs\\lib\site-packages\pandas\core\reshape\pivot.py", line 429, in pivot    indexed = data._constructor_sliced(data[values].values, index=index)  File "C:\Users\\PycharmProjects\venvs\\lib\site-packages\pandas\core\series.py", line 302, in __init__    "index implies {ind}".format(val=len(data), ind=len(index))ValueError: Length of passed values is 239689, index implies 2pd.pivot_table效果很好，但在這種情況下我不需要聚合，而且我還擔(dān)心數(shù)據(jù)幀很大（數(shù)十億行）時(shí)的性能。實(shí)際上我這里確實(shí)有一個(gè)內(nèi)存錯(cuò)誤，它說(shuō)當(dāng)我執(zhí)行此操作時(shí)無(wú)法為 numpy 數(shù)組分配 1.xxGB：df = pd.pivot_table(df, values='value', index=['referenceDate', 'companyId'],                                            columns=['data_item', 'N'], aggfunc='first')我想知道為什么pd.pivot這里和旁邊失敗pd.pivot，pd.pivot_table如果我的問(wèn)題有最佳解決方案（需要最少的內(nèi)存）？