Multi-index 对于列：如何获取每列 header 的列数？
Multi-index for columns: how do I get # of columns per column header?
每 30 分钟间隔是一列 header。我想在每个子列下面有七个子列。
当我尝试 multi-index 时出现此错误：长度不匹配：预期轴有 13 个元素，新值有 91 个元素
我如何解压它以获得 91 列？
coltime = pd.read_csv('mastercolumntimevalues.csv') #intervals range from 9:30 to 15:30#
coltime = pd.DataFrame(coltime)
thirtymindf = pd.DataFrame(columns=coltime)
thirtymindf.columns = pd.MultiIndex.from_product([thirtymindf.columns, ['open','high','low','close','vol','vwap','trades']])
thirtymindf.columns
更新： csv 文件如下所示：
IIUC 并猜测您的 csv 文件，尝试：
lvl0 = pd.read_csv('mastercolumntimevalues.csv')['thirty'].dropna().tolist()
lvl1 = ['open','high','low','close','vol','vwap','trades']
mi = pd.MultiIndex.from_product([lvl0, lvl1])
thirtymindf = pd.DataFrame(columns=mi)
输出：
>>> thirtymindf
Empty DataFrame
Columns: [(9:30, open), (9:30, high), (9:30, low), (9:30, close), (9:30, vol), (9:30, vwap), (9:30, trades), (10:00, open), (10:00, high), (10:00, low), (10:00, close), (10:00, vol), (10:00, vwap), (10:00, trades), (10:30, open), (10:30, high), (10:30, low), (10:30, close), (10:30, vol), (10:30, vwap), (10:30, trades), (11:00, open), (11:00, high), (11:00, low), (11:00, close), (11:00, vol), (11:00, vwap), (11:00, trades), (11:30, open), (11:30, high), (11:30, low), (11:30, close), (11:30, vol), (11:30, vwap), (11:30, trades), (12:00, open), (12:00, high), (12:00, low), (12:00, close), (12:00, vol), (12:00, vwap), (12:00, trades), (12:30, open), (12:30, high), (12:30, low), (12:30, close), (12:30, vol), (12:30, vwap), (12:30, trades), (13:00, open), (13:00, high), (13:00, low), (13:00, close), (13:00, vol), (13:00, vwap), (13:00, trades), (13:30, open), (13:30, high), (13:30, low), (13:30, close), (13:30, vol), (13:30, vwap), (13:30, trades), (14:00, open), (14:00, high), (14:00, low), (14:00, close), (14:00, vol), (14:00, vwap), (14:00, trades), (14:30, open), (14:30, high), (14:30, low), (14:30, close), (14:30, vol), (14:30, vwap), (14:30, trades), (15:00, open), (15:00, high), (15:00, low), (15:00, close), (15:00, vol), (15:00, vwap), (15:00, trades), (15:30, open), (15:30, high), (15:30, low), (15:30, close), (15:30, vol), (15:30, vwap), (15:30, trades)]
Index: []
每 30 分钟间隔是一列 header。我想在每个子列下面有七个子列。
当我尝试 multi-index 时出现此错误：长度不匹配：预期轴有 13 个元素，新值有 91 个元素
我如何解压它以获得 91 列？
coltime = pd.read_csv('mastercolumntimevalues.csv') #intervals range from 9:30 to 15:30#
coltime = pd.DataFrame(coltime)
thirtymindf = pd.DataFrame(columns=coltime)
thirtymindf.columns = pd.MultiIndex.from_product([thirtymindf.columns, ['open','high','low','close','vol','vwap','trades']])
thirtymindf.columns
更新： csv 文件如下所示：
IIUC 并猜测您的 csv 文件，尝试：
lvl0 = pd.read_csv('mastercolumntimevalues.csv')['thirty'].dropna().tolist()
lvl1 = ['open','high','low','close','vol','vwap','trades']
mi = pd.MultiIndex.from_product([lvl0, lvl1])
thirtymindf = pd.DataFrame(columns=mi)
输出：
>>> thirtymindf
Empty DataFrame
Columns: [(9:30, open), (9:30, high), (9:30, low), (9:30, close), (9:30, vol), (9:30, vwap), (9:30, trades), (10:00, open), (10:00, high), (10:00, low), (10:00, close), (10:00, vol), (10:00, vwap), (10:00, trades), (10:30, open), (10:30, high), (10:30, low), (10:30, close), (10:30, vol), (10:30, vwap), (10:30, trades), (11:00, open), (11:00, high), (11:00, low), (11:00, close), (11:00, vol), (11:00, vwap), (11:00, trades), (11:30, open), (11:30, high), (11:30, low), (11:30, close), (11:30, vol), (11:30, vwap), (11:30, trades), (12:00, open), (12:00, high), (12:00, low), (12:00, close), (12:00, vol), (12:00, vwap), (12:00, trades), (12:30, open), (12:30, high), (12:30, low), (12:30, close), (12:30, vol), (12:30, vwap), (12:30, trades), (13:00, open), (13:00, high), (13:00, low), (13:00, close), (13:00, vol), (13:00, vwap), (13:00, trades), (13:30, open), (13:30, high), (13:30, low), (13:30, close), (13:30, vol), (13:30, vwap), (13:30, trades), (14:00, open), (14:00, high), (14:00, low), (14:00, close), (14:00, vol), (14:00, vwap), (14:00, trades), (14:30, open), (14:30, high), (14:30, low), (14:30, close), (14:30, vol), (14:30, vwap), (14:30, trades), (15:00, open), (15:00, high), (15:00, low), (15:00, close), (15:00, vol), (15:00, vwap), (15:00, trades), (15:30, open), (15:30, high), (15:30, low), (15:30, close), (15:30, vol), (15:30, vwap), (15:30, trades)]
Index: []