title: Pandas read csv dateint columns to datetime
body: <p>I'm new to both StackOverflow and pandas. I am trying to read in a large CSV file with stock market bin data in the following format:</p>
  
  <pre><code>date,time,open,high,low,close,volume,splits,earnings,dividends,sym
  20130625,715,49.2634,49.2634,49.2634,49.2634,156.293,1,0,0,JPM
  20130625,730,49.273,49.273,49.273,49.273,208.39,1,0,0,JPM
  20130625,740,49.1866,49.1866,49.1866,49.1866,224.019,1,0,0,JPM
  20130625,745,49.321,49.321,49.321,49.321,208.39,1,0,0,JPM
  20130625,750,49.3306,49.369,49.3306,49.369,4583.54,1,0,0,JPM
  20130625,755,49.369,49.369,49.369,49.369,416.78,1,0,0,JPM
  20130625,800,49.369,49.369,49.3594,49.3594,1715.05,1,0,0,JPM
  20130625,805,49.369,49.369,49.3306,49.3306,1333.7,1,0,0,JPM
  20130625,810,49.3306,49.3786,49.3306,49.3786,1567.09,1,0,0,JPM
  </code></pre>
  
  <p>I have the following code to read it into a DataFrame in Pandas</p>
  
  <pre><code>import numpy as np
  import scipy as sp
  import pandas as pd
  import datetime as dt
  fname  = 'bindat.csv'
  df     = pd.read_csv(fname, header=0, sep=',')
  </code></pre>
  
  <p>The problem is that the date and time columns are read in as int64. I would like to merge these two to a single timestamp such as: 2013-06-25 07:15:00.</p>
  
  <p>I am struggling to even get the time read in properly using:</p>
  
  <pre><code>df['date'] = pd.to_datetime(df['date'].astype(str))
  df['time'] = pd.to_datetime(df['time'].astype(str))
  </code></pre>
  
  <p>The first command works to convert, but the time seems weird.</p>
  
  <pre><code>df.info()
  &lt;class 'pandas.core.frame.DataFrame'&gt;
  Int64Index: 9999 entries, 0 to 9998
  Data columns (total 11 columns):
  date         9999 non-null datetime64[ns]
  time         9999 non-null object
  open         9999 non-null float64
  high         9999 non-null float64
  low          9999 non-null float64
  close        9999 non-null float64
  volume       9999 non-null float64
  splits       9999 non-null float64
  earnings     9999 non-null int64
  dividends    9999 non-null float64
  sym          9999 non-null object
  dtypes: datetime64[ns](1), float64(7), int64(1), object(2)None
  </code></pre>
  
  <p>And then I'll want to merge into a single DatetimeIndex.</p>
  
  <p>Any suggestions are greatly appreciated.</p>
  
  <p>Cheers!</p>