Pandas merge two datasets with same number of rows

Question

I have two tables with same number of rows (second table is computed from first one by processing of text inside T1). I have both of them stored as pandas dataframe. T2 is no common column with T1. This is example because my tables are huge:

T1:
| name  | street  | city   |
|-------|---------|--------|
| David | street1 | Prague |
| John  | street2 | Berlin |
| Joe   | street3 | London |

T2:
| computed1 | computed2 |
|-----------|-----------|
| 0.5       | 0.3       |
| 0.2       | 0.8       |
| 0.1       | 0.6       |

Merged:
| name  | street  | city   | computed1 | computed2 |
|-------|---------|--------|-----------|-----------|
| David | street1 | Prague | 0.5       | 0.3       |
| John  | street2 | Berlin | 0.2       | 0.8       |
| Joe   | street3 | London | 0.1       | 0.6       |

I tried these commands:

pd.concat([T1,T2])
pd.merge([T1,T2])
result=T1.join(T1)

With concat and merge I will get only first thousand combined and rest is filled with nan (I double checked that both are same size), and with .join it not combine them because there is nothing in common.

Is there any way how to combine these two tables in pandas?

Thanks

Answer 1

You need reset_index() before concat for default indices:

df = pd.concat([T1.reset_index(drop=True),T2.reset_index(drop=Tru‌​e)], axis=1)