パンダのティッカーto ohlc

-1

行例

[{'date': datetime.datetime(2017, 3, 21, 13, 27, 20), 'tid': 648605515L, 'price': Decimal('1080.04000000'), 'type': 1, 'amount': Decimal('10.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 20), 'tid': 648605549L, 'price': Decimal('1081.55000000'), 'type': 1, 'amount': Decimal('16.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 20), 'tid': 648605547L, 'price': Decimal('1081.33000000'), 'type': 1, 'amount': Decimal('20.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 20), 'tid': 648605545L, 'price': Decimal('1081.30000000'), 'type': 1, 'amount': Decimal('16.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 20), 'tid': 648605543L, 'price': Decimal('1081.29000000'), 'type': 1, 'amount': Decimal('20.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 20), 'tid': 648605541L, 'price': Decimal('1080.46000000'), 'type': 1, 'amount': Decimal('26.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 20), 'tid': 648605517L, 'price': Decimal('1080.04000000'), 'type': 1, 'amount': Decimal('8.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 22), 'tid': 648605601L, 'price': Decimal('1079.69000000'), 'type': -1, 'amount': Decimal('70.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 25), 'tid': 648605686L, 'price': Decimal('1079.72000000'), 'type': -1, 'amount': Decimal('4.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 26), 'tid': 648605765L, 'price': Decimal('1079.45000000'), 'type': 1, 'amount': Decimal('6.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 26), 'tid': 648605753L, 'price': Decimal('1079.60000000'), 'type': -1, 'amount': Decimal('106.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 26), 'tid': 648605751L, 'price': Decimal('1079.60000000'), 'type': -1, 'amount': Decimal('80.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 26), 'tid': 648605749L, 'price': Decimal('1079.67000000'), 'type': -1, 'amount': Decimal('430.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 26), 'tid': 648605747L, 'price': Decimal('1079.70000000'), 'type': -1, 'amount': Decimal('66.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 26), 'tid': 648605745L, 'price': Decimal('1079.74000000'), 'type': -1, 'amount': Decimal('12.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 27), 'tid': 648605785L, 'price': Decimal('1079.45000000'), 'type': 1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 27), 'tid': 648605774L, 'price': Decimal('1079.45000000'), 'type': 1, 'amount': Decimal('6.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 27), 'tid': 648605771L, 'price': Decimal('1079.45000000'), 'type': 1, 'amount': Decimal('14.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 28), 'tid': 648605827L, 'price': Decimal('1079.45000000'), 'type': 1, 'amount': Decimal('42.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 28), 'tid': 648605842L, 'price': Decimal('1079.45000000'), 'type': 1, 'amount': Decimal('10.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 32), 'tid': 648605973L, 'price': Decimal('1079.45000000'), 'type': 1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 37), 'tid': 648606114L, 'price': Decimal('1079.44000000'), 'type': 1, 'amount': Decimal('24.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 37), 'tid': 648606116L, 'price': Decimal('1079.45000000'), 'type': 1, 'amount': Decimal('40.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 42), 'tid': 648606258L, 'price': Decimal('1079.45000000'), 'type': 1, 'amount': Decimal('56.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 45), 'tid': 648606345L, 'price': Decimal('1079.46000000'), 'type': -1, 'amount': Decimal('10.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 46), 'tid': 648606392L, 'price': Decimal('1079.69000000'), 'type': 1, 'amount': Decimal('44.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 48), 'tid': 648606418L, 'price': Decimal('1079.60000000'), 'type': -1, 'amount': Decimal('40.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 48), 'tid': 648606420L, 'price': Decimal('1079.46000000'), 'type': -1, 'amount': Decimal('36.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 48), 'tid': 648606422L, 'price': Decimal('1079.46000000'), 'type': -1, 'amount': Decimal('94.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 50), 'tid': 648606499L, 'price': Decimal('1079.31000000'), 'type': 1, 'amount': Decimal('80.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 50), 'tid': 648606478L, 'price': Decimal('1079.31000000'), 'type': -1, 'amount': Decimal('6.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 50), 'tid': 648606476L, 'price': Decimal('1079.31000000'), 'type': -1, 'amount': Decimal('34.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 50), 'tid': 648606474L, 'price': Decimal('1079.55000000'), 'type': -1, 'amount': Decimal('8.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 55), 'tid': 648606666L, 'price': Decimal('1079.31000000'), 'type': 1, 'amount': Decimal('44.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 55), 'tid': 648606650L, 'price': Decimal('1079.17000000'), 'type': 1, 'amount': Decimal('8.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 27, 55), 'tid': 648606648L, 'price': Decimal('1079.17000000'), 'type': 1, 'amount': Decimal('8.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 1), 'tid': 648606820L, 'price': Decimal('1079.03000000'), 'type': -1, 'amount': Decimal('28.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 2), 'tid': 648606825L, 'price': Decimal('1079.03000000'), 'type': 1, 'amount': Decimal('30.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 2), 'tid': 648606836L, 'price': Decimal('1079.02000000'), 'type': -1, 'amount': Decimal('22.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 5), 'tid': 648606945L, 'price': Decimal('1078.58000000'), 'type': -1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 5), 'tid': 648606943L, 'price': Decimal('1078.61000000'), 'type': -1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 5), 'tid': 648606941L, 'price': Decimal('1078.63000000'), 'type': -1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 5), 'tid': 648606939L, 'price': Decimal('1078.88000000'), 'type': -1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 5), 'tid': 648606926L, 'price': Decimal('1078.88000000'), 'type': -1, 'amount': Decimal('428.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 6), 'tid': 648606984L, 'price': Decimal('1078.58000000'), 'type': 1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 6), 'tid': 648606982L, 'price': Decimal('1078.05000000'), 'type': -1, 'amount': Decimal('10.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 6), 'tid': 648606971L, 'price': Decimal('1078.58000000'), 'type': 1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 6), 'tid': 648606957L, 'price': Decimal('1078.05000000'), 'type': -1, 'amount': Decimal('74.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 6), 'tid': 648606955L, 'price': Decimal('1078.15000000'), 'type': -1, 'amount': Decimal('6.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 6), 'tid': 648606953L, 'price': Decimal('1078.15000000'), 'type': -1, 'amount': Decimal('14.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 6), 'tid': 648606951L, 'price': Decimal('1078.42000000'), 'type': -1, 'amount': Decimal('16.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 7), 'tid': 648606992L, 'price': Decimal('1078.05000000'), 'type': -1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 7), 'tid': 648606995L, 'price': Decimal('1078.58000000'), 'type': 1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 7), 'tid': 648607023L, 'price': Decimal('1078.06000000'), 'type': -1, 'amount': Decimal('4.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 8), 'tid': 648607047L, 'price': Decimal('1078.86000000'), 'type': 1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 10), 'tid': 648607113L, 'price': Decimal('1078.06000000'), 'type': -1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 10), 'tid': 648607115L, 'price': Decimal('1078.03000000'), 'type': -1, 'amount': Decimal('148.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 12), 'tid': 648607192L, 'price': Decimal('1079.00000000'), 'type': -1, 'amount': Decimal('10.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 13), 'tid': 648607218L, 'price': Decimal('1078.99000000'), 'type': 1, 'amount': Decimal('98.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 13), 'tid': 648607220L, 'price': Decimal('1079.00000000'), 'type': 1, 'amount': Decimal('42.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 13), 'tid': 648607222L, 'price': Decimal('1079.03000000'), 'type': 1, 'amount': Decimal('342.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 13), 'tid': 648607224L, 'price': Decimal('1079.16000000'), 'type': 1, 'amount': Decimal('512.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 14), 'tid': 648607250L, 'price': Decimal('1078.98000000'), 'type': 1, 'amount': Decimal('44.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 14), 'tid': 648607252L, 'price': Decimal('1078.98000000'), 'type': 1, 'amount': Decimal('12.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 14), 'tid': 648607254L, 'price': Decimal('1079.00000000'), 'type': 1, 'amount': Decimal('106.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 14), 'tid': 648607256L, 'price': Decimal('1079.16000000'), 'type': 1, 'amount': Decimal('40.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 20), 'tid': 648607431L, 'price': Decimal('1079.16000000'), 'type': 1, 'amount': Decimal('28.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 20), 'tid': 648607429L, 'price': Decimal('1079.01000000'), 'type': 1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 20), 'tid': 648607427L, 'price': Decimal('1079.01000000'), 'type': 1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 23), 'tid': 648607518L, 'price': Decimal('1079.16000000'), 'type': 1, 'amount': Decimal('8.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 24), 'tid': 648607544L, 'price': Decimal('1079.16000000'), 'type': 1, 'amount': Decimal('344.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 25), 'tid': 648607593L, 'price': Decimal('1078.79000000'), 'type': -1, 'amount': Decimal('6.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 26), 'tid': 648607631L, 'price': Decimal('1079.16000000'), 'type': 1, 'amount': Decimal('430.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 26), 'tid': 648607623L, 'price': Decimal('1079.16000000'), 'type': 1, 'amount': Decimal('18.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 26), 'tid': 648607621L, 'price': Decimal('1078.79000000'), 'type': 1, 'amount': Decimal('14.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 29), 'tid': 648607695L, 'price': Decimal('1079.16000000'), 'type': 1, 'amount': Decimal('776.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 32), 'tid': 648607803L, 'price': Decimal('1079.16000000'), 'type': 1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 32), 'tid': 648607805L, 'price': Decimal('1079.16000000'), 'type': 1, 'amount': Decimal('10.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 36), 'tid': 648607905L, 'price': Decimal('1079.16000000'), 'type': 1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 37), 'tid': 648607940L, 'price': Decimal('1079.31000000'), 'type': 1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 42), 'tid': 648608110L, 'price': Decimal('1079.46000000'), 'type': -1, 'amount': Decimal('12.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 46), 'tid': 648608211L, 'price': Decimal('1079.88000000'), 'type': -1, 'amount': Decimal('12.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 46), 'tid': 648608213L, 'price': Decimal('1079.88000000'), 'type': -1, 'amount': Decimal('6.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 57), 'tid': 648608534L, 'price': Decimal('1080.29000000'), 'type': 1, 'amount': Decimal('14.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 28, 57), 'tid': 648608536L, 'price': Decimal('1080.30000000'), 'type': 1, 'amount': Decimal('2.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 29, 2), 'tid': 648608683L, 'price': Decimal('1080.59000000'), 'type': 1, 'amount': Decimal('40.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 29, 3), 'tid': 648608733L, 'price': Decimal('1080.59000000'), 'type': 1, 'amount': Decimal('360.00000000')}, {'date': datetime.datetime(2017, 3, 21, 13, 29, 7), 'tid': 648608838L, 'price': Decimal('1080.90000000'), 'type': 1, 'amount': Decimal('82.00000000')}]

私はset_indexを使用しなかった場合、それはTypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'RangeIndex'

if rows: 
    df = pd.DataFrame(rows) 
    print df.head() 
    # TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'RangeIndex' 
    df = df.set_index("date") 
    print df.head() 
    resample_data = df.resample("1min", how={"price": "ohlc", "amount": "sum"}) 
    print resample_data

結果があります：

Connected to pydev debugger (build 162.1967.10) 
     amount    date   price  tid type 
0 2.00000000 2017-03-21 11:15:12 1075.83000000 648370156 -1 
1 10.00000000 2017-03-21 11:15:15 1076.00000000 648370241 -1 
2 10.00000000 2017-03-21 11:15:17 1075.83000000 648370297 -1 
3 10.00000000 2017-03-21 11:15:17 1075.83000000 648370311  1 
4 8.00000000 2017-03-21 11:15:19 1076.13000000 648370370  1 
          amount   price  tid type 
date                
2017-03-21 11:15:12 2.00000000 1075.83000000 648370156 -1 
2017-03-21 11:15:15 10.00000000 1076.00000000 648370241 -1 
2017-03-21 11:15:17 10.00000000 1075.83000000 648370297 -1 
2017-03-21 11:15:17 10.00000000 1075.83000000 648370311  1 
2017-03-21 11:15:19 8.00000000 1076.13000000 648370370  1 
/Users/wyx/bitcoin_workspace/fibo-strategy/ticker.py:45: FutureWarning: how in .resample() is deprecated 
the new syntax is .resample(...)..apply(<func>) 
    resample_data = df.resample("1min", how={"price": "ohlc", "amount": "sum"}) 
Traceback (most recent call last): 
    File "/Applications/PyCharm.app/Contents/helpers/pydev/pydevd.py", line 1580, in <module> 
    globals = debugger.run(setup['file'], None, None, is_module) 
    File "/Applications/PyCharm.app/Contents/helpers/pydev/pydevd.py", line 964, in run 
    pydev_imports.execfile(file, globals, locals) # execute the script 
    File "/Users/wyx/bitcoin_workspace/fibo-strategy/ticker.py", line 45, in <module> 
    resample_data = df.resample("1min", how={"price": "ohlc", "amount": "sum"}) 
    File "/Users/wyx/bitcoin_workspace/fibo-strategy/.env/lib/python2.7/site-packages/pandas/core/generic.py", line 4216, in resample 
    limit=limit) 
    File "/Users/wyx/bitcoin_workspace/fibo-strategy/.env/lib/python2.7/site-packages/pandas/tseries/resample.py", line 582, in _maybe_process_deprecations 
    r = r.aggregate(how) 
    File "/Users/wyx/bitcoin_workspace/fibo-strategy/.env/lib/python2.7/site-packages/pandas/tseries/resample.py", line 320, in aggregate 
    result, how = self._aggregate(arg, *args, **kwargs) 
    File "/Users/wyx/bitcoin_workspace/fibo-strategy/.env/lib/python2.7/site-packages/pandas/core/base.py", line 549, in _aggregate 
    result = _agg(arg, _agg_1dim) 
    File "/Users/wyx/bitcoin_workspace/fibo-strategy/.env/lib/python2.7/site-packages/pandas/core/base.py", line 500, in _agg 
    result[fname] = func(fname, agg_how) 
    File "/Users/wyx/bitcoin_workspace/fibo-strategy/.env/lib/python2.7/site-packages/pandas/core/base.py", line 483, in _agg_1dim 
    return colg.aggregate(how, _level=(_level or 0) + 1) 
    File "/Users/wyx/bitcoin_workspace/fibo-strategy/.env/lib/python2.7/site-packages/pandas/core/groupby.py", line 2652, in aggregate 
    return getattr(self, func_or_funcs)(*args, **kwargs) 
    File "/Users/wyx/bitcoin_workspace/fibo-strategy/.env/lib/python2.7/site-packages/pandas/core/groupby.py", line 1128, in ohlc 
    lambda x: x._cython_agg_general('ohlc')) 
    File "/Users/wyx/bitcoin_workspace/fibo-strategy/.env/lib/python2.7/site-packages/pandas/core/groupby.py", line 3103, in _apply_to_column_groupbys 
    return func(self) 
    File "/Users/wyx/bitcoin_workspace/fibo-strategy/.env/lib/python2.7/site-packages/pandas/core/groupby.py", line 1128, in <lambda> 
    lambda x: x._cython_agg_general('ohlc')) 
    File "/Users/wyx/bitcoin_workspace/fibo-strategy/.env/lib/python2.7/site-packages/pandas/core/groupby.py", line 808, in _cython_agg_general 
    raise DataError('No numeric types to aggregate') 
pandas.core.base.DataError: No numeric types to aggregate 

Process finished with exit code 1

私はパンダのためのルーキーだが。

どのようにエラーを解決しますか？
最後の終値を使用して、次のNaNを入力する場合 min ohlc。どうやってするか？

出典

2017-03-21 wyx

あなたはそれが答えた後に質問を変更するつもりですか？ –

私はあなたが答える前にset_indexを試みます。私は別のエラーを編集した後、私はあなたの答えを見る.Sorry、@Stephen Rauch – wyx

あなたは私の答えに同じ問題はないことに気づくことができます。したがって、他の人があなたの問題を再現できるようにデータを投稿する必要があります。データを投稿する方法に注意した場合、これは結果が再現可能であることを確認する1つの方法です。 –

日付を使用してインデックスを設定する必要があります。

コード：

from io import StringIO 
df = pd.read_csv(StringIO(
    u"""amount date   price  tid type 
    6.00000000 2017-03-21t10:46:32 1059.26000000 648313975 -1 
    4.00000000 2017-03-21t10:46:37 1059.42000000 648314094 -1 
    2.00000000 2017-03-21t10:46:37 1059.42000000 648314096 -1 
    2.00000000 2017-03-21t10:46:41 1059.26000000 648314176 -1 
    32.00000000 2017-03-21t10:46:41 1059.26000000 648314189 -1 
"""), sep='\s+', parse_dates='date'.split()) 
print(df) 

resample_data = df.set_index('date').resample(
    "1min", how={"price": "ohlc", "amount": "sum"}) 

print(resample_data)

結果：

amount    date price  tid type 
0  6.0 2017-03-21 10:46:32 1059.26 648313975 -1 
1  4.0 2017-03-21 10:46:37 1059.42 648314094 -1 
2  2.0 2017-03-21 10:46:37 1059.42 648314096 -1 
3  2.0 2017-03-21 10:46:41 1059.26 648314176 -1 
4 32.0 2017-03-21 10:46:41 1059.26 648314189 -1 

         price       amount 
         open  high  low close amount 
date               
2017-03-21 10:46:00 1059.26 1059.42 1059.26 1059.26 46.0

出典

2017-03-21 03:22:08

私はset_indexを使うと 'pandas.core.base.DataError：集計する数値型がありません 'というエラーがあります。私は質問を更新しました。私は泣きたいです。@ Stephen Rauch – wyx

パンダのティッカーto ohlc

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