mplfinance KeyError：“打开”

Question

我试着用熊猫的mplfinance数据创建OHLC图表。原始数据存储在一个数据库中，其中包含date ( data )、time (hora)和last，因此，在尝试创建图表之前，我必须重采样到OHLC。

cur = conn.cursor()
nameddict=({"ticker": "GFGC90.0JU"})
select="""SELECT 
    EXTRACT(EPOCH FROM (fecha || ' ' || hora)::timestamp) as datetime, last from preciosrt
    where ticker=%(ticker)s and last is not null 
    """
df = pandas.read_sql_query(select, conn, params=nameddict)
df['datetime'] = pandas.to_datetime(df['datetime'], unit='s')
df = df.set_index('datetime')
ohlc = df.resample('5Min').ohlc()
print(ohlc)
mpf.plot(ohlc)

如您所见，生成的dataframe包含所需的结果：

                     last                   
                     open  high   low  close
datetime                                    
2020-05-04 16:15:00  5.10  5.10  5.10  5.100
2020-05-04 16:20:00  5.14  5.14  5.02  5.140
2020-05-04 16:25:00  5.00  5.25  5.00  5.249
2020-05-04 16:30:00  5.29  5.45  5.29  5.450
2020-05-04 16:35:00  5.45  5.50  5.30  5.300
2020-05-04 16:40:00  5.21  5.30  5.20  5.200
2020-05-04 16:45:00  5.20  5.30  5.20  5.200
2020-05-04 16:50:00  5.21  5.30  5.21  5.260
2020-05-04 16:55:00  5.26  5.33  5.10  5.100

但是，当我试图用mpf.plot(ohlc)绘制图表时，我会得到以下错误：

...

~/.local/lib/python3.6/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   2646                 return self._engine.get_loc(key)
   2647             except KeyError:
-> 2648                 return self._engine.get_loc(self._maybe_cast_indexer(key))
   2649         indexer = self.get_indexer([key], method=method, tolerance=tolerance)
   2650         if indexer.ndim > 1 or indexer.size > 1:

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 'Open'

我怎样才能解决这个问题？

Answer 1

我也有类似的问题，我认为强积金在列的名称上非常特别，尝试用以下方法重命名列和索引：

df.columns = ['Open', 'High', 'Low', 'Close', 'Volume']
df.index.name = "Date"