Open   High    Low  Close
2016-06-01  69.60  70.20  69.44  69.76
2016-06-02  70.00  70.15  69.45  69.54
2016-06-03  69.51  70.48  68.62  68.91
2016-06-04  69.51  70.48  68.62  68.91
2016-06-05  69.51  70.48  68.62  68.91
2016-06-06  70.49  71.44  69.84  70.11
2016-06-07  70.11  70.11  68.00  68.35

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
from matplotlib.finance import candlestick2_ochl
import matplotlib.dates as mdates
import datetime as dt

start_date='2016-06-01'
end_date='2017-02-13'
symbols=['EFERT']

def data(symbols):
    dates=pd.date_range(start_date,end_date)
    df=pd.DataFrame(index=dates)
    for symbol in symbols:
        df_temp=pd.read_csv('/home/furqan/Desktop/Data/{}.csv'.format(str(symbols[0])),
                    usecols=['Date','Open','High','Low','Close'],
                    parse_dates=True,index_col='Date',na_values=['nan'])
        #df_temp = df_temp.rename(columns={'Close': symbol})
        #df.index=df['Date']
        df=df.join(df_temp)
        df=df.fillna(method='ffill')
        df=df.fillna(method='bfill')
    return df
df=data(symbols)
#df['index']=mdates.date2num(df['index'].astype(dt.date))
print(df)

ax1=plt.plot()
candlestick2_ochl(ax1,df['Open'],df['Close'],df['High'],df['Low'],alpha=0.75)
plt.show()