I am reading a .csv into a data-frame index by date using the following code:

```
def getCSVData(rawStaticDataPath):

    pattern = 'Overview-trade-pos'+'.csv'

    staticPath = rawStaticDataPath

    with open(staticPath+pattern,'rt') as f:

        csv=pd.read_csv(f,engine='c',header=0,index_col='date', parse_dates=True, infer_datetime_format=True,names=['date','id','settle_price','settle_price_acc','pos','trade'])        
        print(csv.sort_index().tail())           

    return csv 

```

When I tail the file I get the following:

```
                         id  settle_price  
date                                                                       
2017-12-01  BBG.XTKS.7942.S     23.745497        
2017-12-01  BBG.XTKS.3926.S     26.499680       
2017-12-01  BBG.XTKS.9678.S     27.328124        
2017-12-01  BBG.XTKS.8153.S     29.855033        
2017-12-01  BBG.XTKS.2060.S      1.482091 

```

Please note that the 31 March 2017 is the latest record date in the .csv. I sorted the .csv by date and below are the final few records:

```
31/03/2017  BBG.XASX.SCP.S  1.70883133  
31/03/2017  BBG.XASX.IFL.S  6.50754463  
31/03/2017  BBG.XASX.MFG.S  18.02732459 
31/03/2017  BBG.XASX.BHP.S  18.340116   
31/03/2017  BBG.XASX.MND.S  9.406557    
31/03/2017  BBG.XASX.VCX.S  2.15897147  

```

You can see that in reading the file in the date has been reformatted.

Please note that the dates are beyond the final day in the .csv that I read in. I think the date has some how been reformatted. 

Is there a way that I can change the format of the date index when I read in the .csv? So I believe the desired output would be:

```
2017-03-09      4740.969526
2017-01-10      2299.551489
2017-02-10   -255026.329808
2017-03-10    -22969.779504
2017-01-11    -11577.120402
2017-01-12    -73150.201727

```

Obviously the order of the records as a result would change.