ENH: Adding DataFrame plotting benchmarks for large datasets #61546
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@rhshadrach do you have an opinion about this? |
mroeschke
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Jun 4, 2025
asv_bench/benchmarks/plotting.py
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| def time_plot_large_dataframe_single_column(self, size, datetime_index): | ||
| """Baseline: plotting single column for comparison""" | ||
| self.df.iloc[:, 0].plot() |
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Can you do the iloc operation in setup so its not part of the timing?
shadnikn
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@shadnikn - what is the runtime of these benchmarks on your machine? |
rhshadrach
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Jun 19, 2025
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| [(1000, 10), (1000, 50), (1000, 100), (5000, 20), (10000, 10)], | ||
| [True, False] # DatetimeIndex or not |
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I think this is too many cases. Can you just do [(1000, 100)]
| @@ -161,4 +161,45 @@ def time_get_plot_backend_fallback(self): | |||
| _get_plot_backend("pandas_dummy_backend") | |||
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| from .pandas_vb_common import setup # noqa: F401 isort:skip | |||
| class DataFramePlottingLarge: | |||
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I think what differentiates this from FramePlotting is that these are wide. Can you rename this class to FramePlottingWide.
| [(1000, 10), (1000, 50), (1000, 100), (5000, 20), (10000, 10)], | ||
| [True, False] # DatetimeIndex or not | ||
| ] | ||
| param_names = ["size", "datetime_index"] |
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Can you rename size -> shape.
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DataFrame.plotusingLineCollection#61532 - Adding in performance benchmarks for DataFrame plotting with large datasets.DataFrame.plotwithDatetimeIndex#61398 and ENH: speed upDataFrame.plotusingLineCollection#61532. Tests multiple DataFrame sizes with/w/o DatetimeIndex & provides a baseline single-column comparison.- DataFrame sizes: (1000,10) to (10000,10)
- DatetimeIndex vs. regular index comparison
- Multi-column vs. single-column plotting.