pydata/pandas — pull request #4457 by jreback (2013-08-03 17:38:27+00:00)
Title: PERF: enhance HDFStore Table writing performance

Took out all of the cython code, turns out you can assign directly to numpy recarrays per
column if you put in the correct shape yourself

```
Invoked with :
--ncalls: 5
--repeats: 5
-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
write_store_table_mixed | 45.6208 | 121.5352 | 0.3754 |
write_store_table_panel | 59.4140 | 99.5456 | 0.5969 |
write_store_table | 40.2264 | 65.8978 | 0.6104 |
write_store_table_dc | 143.3910 | 174.9424 | 0.8196 |
read_store_table_wide | 16.8930 | 17.5310 | 0.9636 |
query_store_table_wide | 9.6692 | 9.7564 | 0.9911 |
write_store_table_wide | 117.8906 | 118.8232 | 0.9922 |
read_store_table_mixed | 4.7604 | 4.7478 | 1.0026 |
query_store_table | 4.2646 | 4.2320 | 1.0077 |
read_store_table | 2.3678 | 2.3178 | 1.0216 |
read_store_table_panel | 20.9388 | 20.3526 | 1.0288 |
-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------

Ratio < 1.0 means the target commit is faster then the baseline.
Seed used: 1234

Target [d11041d] : PERF: enhance HDFStore Table writing performance
Base [aca1a42] : Merge pull request #4437 from cpcloud/fix-astype-calls

```