title: Is there a way to horizontally concatenate dataframes of same length while ignoring the index?
body: <p>I have dataframes I want to horizontally concatenate while ignoring the index.</p>
  
  <p>I know that for arithmetic operations, ignoring the index can lead to a substantial speedup if you use the numpy array <code>.values</code> instead of the pandas Series. Is it possible to horizontally concatenate or merge pandas dataframes whilst ignoring the index? (To my dismay, ignore_index=True does something else.) And if so, does it give a speed gain?</p>
  
  <pre><code>import pandas as pd
  
  df1 = pd.Series(range(10)).to_frame()
  
  df2 = pd.Series(range(10), index=range(10, 20)).to_frame()
  
  pd.concat([df1, df2], axis=1)
  #      0    0
  # 0   0.0  NaN
  # 1   1.0  NaN
  # 2   2.0  NaN
  # 3   3.0  NaN
  # 4   4.0  NaN
  # 5   5.0  NaN
  # 6   6.0  NaN
  # 7   7.0  NaN
  # 8   8.0  NaN
  # 9   9.0  NaN
  # 10  NaN  0.0
  # 11  NaN  1.0
  # 12  NaN  2.0
  # 13  NaN  3.0
  # 14  NaN  4.0
  # 15  NaN  5.0
  # 16  NaN  6.0
  # 17  NaN  7.0
  # 18  NaN  8.0
  # 19  NaN  9.0
  </code></pre>
  
  <p>I know I can get the result I want by resetting the index of df2, but I wonder whether there is a faster (perhaps numpy method) to do this? </p>