found in the pandas/asv_bench directory. asv supports both python2 and python3. Note: The asv benchmark suite was translated from the previous framework, vbench, so many stylistic issues are likely a 0 To install asv: pip install git+https://github.com/spacetelescope/asv If you need to run a benchmark, change your directory to asv_bench/ and run: asv continuous -f 1.1 upstream/master HEAD You can report benchmarks that changed by more than 10%. The command uses conda by default for creating the benchmark environments. If you want to use virtualenv instead, write: asv continuous -f 1.1 -E virtualenv

found in the pandas/asv_bench directory. asv supports both python2 and python3. Note: The asv benchmark suite was translated from the previous framework, vbench, so many stylistic issues are likely a 1 To install asv: pip install git+https://github.com/spacetelescope/asv If you need to run a benchmark, change your directory to asv_bench/ and run: asv continuous -f 1.1 upstream/master HEAD You can report benchmarks that changed by more than 10%. The command uses conda by default for creating the benchmark environments. If you want to use virtualenv instead, write: asv continuous -f 1.1 -E virtualenv

Contributing to pandas pandas: powerful Python data analysis toolkit, Release 0.17.0 Note: The asv benchmark suite was translated from the previous framework, vbench, so many stylistic issues are likely a To install ‘’asv’‘: pip install git+https://github.com/spacetelescope/asv If you need to run a benchmark, change your directory to asv_bench/ and run the following if you have been developing on master: benchmarks and use your local python that comes from your $PATH. Information on how to write a benchmark can be found in *asv*’s documentation http://asv.readthedocs.org/en/latest/writing_benchmarks.html

requests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3004 4.5.11 Benchmark machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3004 4.5.12 To install asv: pip install git+https://github.com/airspeed-velocity/asv If you need to run a benchmark, change your directory to asv_bench/ and run: asv continuous -f 1.1 upstream/main HEAD You can report benchmarks that changed by more than 10%. The command uses conda by default for creating the benchmark environments. If you want to use virtualenv instead, write: asv continuous -f 1.1 -E virtualenv

To install asv: pip install git+https://github.com/spacetelescope/asv If you need to run a benchmark, change your directory to asv_bench/ and run: asv continuous -f 1.1 upstream/master HEAD You can report benchmarks that changed by more than 10%. The command uses conda by default for creating the benchmark environments. If you want to use virtualenv instead, write: asv continuous -f 1.1 -E virtualenv groupby.groupby_agg_builtins will only run the groupby_agg_builtins benchmark defined in groupby.py. You can also run the benchmark suite using the version of pandas already installed in your current

To install asv: pip install git+https://github.com/spacetelescope/asv If you need to run a benchmark, change your directory to asv_bench/ and run: asv continuous -f 1.1 upstream/master HEAD You can report benchmarks that changed by more than 10%. The command uses conda by default for creating the benchmark environments. If you want to use virtualenv instead, write: asv continuous -f 1.1 -E virtualenv groupby.groupby_agg_builtins will only run the groupby_agg_builtins benchmark defined in groupby.py. You can also run the benchmark suite using the version of pandas already installed in your current

To install asv: pip install git+https://github.com/spacetelescope/asv If you need to run a benchmark, change your directory to asv_bench/ and run: asv continuous -f 1.1 upstream/master HEAD You can report benchmarks that changed by more than 10%. The command uses conda by default for creating the benchmark environments. If you want to use virtualenv instead, write: asv continuous -f 1.1 -E virtualenv groupby.groupby_agg_builtins will only run the groupby_agg_builtins benchmark defined in groupby.py. You can also run the benchmark suite using the version of pandas already installed in your current

To install asv: pip install git+https://github.com/spacetelescope/asv If you need to run a benchmark, change your directory to asv_bench/ and run: asv continuous -f 1.1 upstream/master HEAD You can report benchmarks that changed by more than 10%. The command uses conda by default for creating the benchmark environments. If you want to use virtualenv instead, write: asv continuous -f 1.1 -E virtualenv upstream/master HEAD -b groupby.GroupByMethods will only run the GroupByMethods benchmark defined in groupby.py. You can also run the benchmark suite using the version of pandas already installed in your current

To install asv: pip install git+https://github.com/spacetelescope/asv If you need to run a benchmark, change your directory to asv_bench/ and run: asv continuous -f 1.1 upstream/master HEAD You can report benchmarks that changed by more than 10%. The command uses conda by default for creating the benchmark environments. If you want to use virtualenv instead, write: asv continuous -f 1.1 -E virtualenv upstream/master HEAD -b groupby.GroupByMethods will only run the GroupByMethods benchmark defined in groupby.py. You can also run the benchmark suite using the version of pandas already installed in your current

To install asv: pip install git+https://github.com/spacetelescope/asv If you need to run a benchmark, change your directory to asv_bench/ and run: asv continuous -f 1.1 upstream/master HEAD You can report benchmarks that changed by more than 10%. The command uses conda by default for creating the benchmark environments. If you want to use virtualenv instead, write: asv continuous -f 1.1 -E virtualenv commands that run benchmarks. The default value is defined in asv.conf.json. Running the full benchmark suite can be an all-day process, depending on your hardware and its resource utiliza- tion. However