OHLCデータの可視化

前提・実現したいこと

PythonのJupyterNotebookを使い、pandasで金融のOHLCデータを可視化したいのですが、エラーが出てしまい、なかなか思うようにできません。。

発生している問題・エラーメッセージ

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-10-4c00f491470f> in <module>()
     20     return ret.dropna()
     21 
---> 22 ohlc = TF_ohlc(dataM1, '5min') #１時間足データの作成
     23 
     24 

<ipython-input-10-4c00f491470f> in TF_ohlc(df, tf)
     11 # dfのデータからtfで指定するタイムフレームの4本足データを作成する関数
     12 def TF_ohlc(df, tf):
---> 13     x = df.resample(tf).ohlc()
     14     O = x['Open']['open']
     15     H = x['High']['high']

/anaconda3/lib/python3.6/site-packages/pandas/core/generic.py in resample(self, rule, how, axis, fill_method, closed, label, convention, kind, loffset, limit, base, on, level)
   7102                      axis=axis, kind=kind, loffset=loffset,
   7103                      convention=convention,
-> 7104                      base=base, key=on, level=level)
   7105         return _maybe_process_deprecations(r,
   7106                                            how=how,

/anaconda3/lib/python3.6/site-packages/pandas/core/resample.py in resample(obj, kind, **kwds)
   1146     """ create a TimeGrouper and return our resampler """
   1147     tg = TimeGrouper(**kwds)
-> 1148     return tg._get_resampler(obj, kind=kind)
   1149 
   1150 

/anaconda3/lib/python3.6/site-packages/pandas/core/resample.py in _get_resampler(self, obj, kind)
   1274         raise TypeError("Only valid with DatetimeIndex, "
   1275                         "TimedeltaIndex or PeriodIndex, "
-> 1276                         "but got an instance of %r" % type(ax).__name__)
   1277 
   1278     def _get_grouper(self, obj, validate=True):

TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'Index'

該当のソースコード

import numpy as np
import pandas as pd
import indicators as ind #indicators.pyのインポート
from pandas_highcharts.display import display_charts

dataM1 = pd.read_csv('20180820.csv', sep=';',
                     names=('Time','Open','High','Low','Close', ''),
                     index_col='Time', parse_dates=True)


# dfのデータからtfで指定するタイムフレームの4本足データを作成する関数
def TF_ohlc(df, tf):
    x = df.resample(tf).ohlc()
    O = x['Open']['open']
    H = x['High']['high']
    L = x['Low']['low']
    C = x['Close']['close']
    ret = pd.DataFrame({'Open': O, 'High': H, 'Low': L, 'Close': C},
                       columns=['Open','High','Low','Close'])
    return ret.dropna()

ohlc = TF_ohlc(dataM1, '5min') #１時間足データの作成


FastMA = ind.iMA(ohlc, 5) #短期移動平均
SlowMA = ind.iMA(ohlc, 12) #長期移動平均


df = pd.DataFrame({'Close': ohlc['Close'], 'FastMA': FastMA, 'SlowMA': SlowMA})
display_charts(df, chart_type="stock", title="MA cross", figsize=(640,480), grid=True)