Appending two dataframes with same columns, different order
append, join, pandas, python
Solution
You could also use pd.concat:
In [36]: pd.concat([noclickDF, clickDF], ignore_index=True)
Out[36]:
click id location
0 0 123 321
1 0 1543 432
2 1 421 123
3 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.
Problem
I have two pandas dataframes. ``` noclickDF = DataFrame([[0, 123, 321], [0, 1543, 432]], columns=['click', 'id', 'location']) clickDF = DataFrame([[1, 123, 421], [1, 1543, 436]], columns=['click', 'location','id']) ``` I simply want to join such that the final DF will look like: ``` click | id | location 0 123 321 0 1543 432 1 421 123 1 436 1543 ``` As you can see the column names of both original DF's are the same, but not in the same order. Also there is no join in a column.