Appending two dataframes with same columns, different order

You could also use pd.concat:

In [36]: pd.concat([noclickDF, clickDF], ignore_index=True)Out[36]:    click    id  location0      0   123       3211      0  1543       4322      1   421       1233      1   436      1543

Under the hood, DataFrame.append calls pd.concat.DataFrame.append has code for handling various types of input, such as Series, tuples, lists and dicts. If you pass it a DataFrame, it passes straight through to pd.concat, so using pd.concat is a bit more direct.

For future users (sometime >pandas 0.23.0):

You may also need to add sort=True to sort the non-concatenation axis when it is not already aligned (i.e. to retain the OP's desired concatenation behavior). I used the code contributed above and got a warning, see Python Pandas User Warning. The code below works and does not throw a warning.

In [36]: pd.concat([noclickDF, clickDF], ignore_index=True, sort=True)Out[36]:    click    id  location0      0   123       3211      0  1543       4322      1   421       1233      1   436      1543

You can use append for that

 df = noclickDF.append(clickDF) print df     click    id  location 0      0   123       321   1      0  1543       432 0      1   421       123 1      1   436      1543

and if you need you can reset the index by

df.reset_index(drop=True)print df   click    id  location0      0   123       3211      0  1543       4322      1   421       1233      1   436      1543