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8 | 8 | matplotlib.use('Agg')
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9 | 9 |
|
10 | 10 |
|
11 |
| -class Plotting(object): |
12 |
| - |
13 |
| - def setup(self): |
14 |
| - self.s = Series(np.random.randn(1000000)) |
15 |
| - self.df = DataFrame({'col': self.s}) |
16 |
| - |
17 |
| - def time_series_plot(self): |
18 |
| - self.s.plot() |
19 |
| - |
20 |
| - def time_frame_plot(self): |
21 |
| - self.df.plot() |
| 11 | +class SeriesPlotting(object): |
| 12 | + params = [['line', 'bar', 'area', 'barh', 'hist', 'kde', 'pie']] |
| 13 | + param_names = ['kind'] |
| 14 | + |
| 15 | + def setup(self, kind): |
| 16 | + if kind in ['bar', 'barh', 'pie']: |
| 17 | + n = 100 |
| 18 | + elif kind in ['kde']: |
| 19 | + n = 10000 |
| 20 | + else: |
| 21 | + n = 1000000 |
| 22 | + |
| 23 | + self.s = Series(np.random.randn(n)) |
| 24 | + if kind in ['area', 'pie']: |
| 25 | + self.s = self.s.abs() |
| 26 | + |
| 27 | + def time_series_plot(self, kind): |
| 28 | + self.s.plot(kind=kind) |
| 29 | + |
| 30 | + |
| 31 | +class FramePlotting(object): |
| 32 | + params = [['line', 'bar', 'area', 'barh', 'hist', 'kde', 'pie', 'scatter', |
| 33 | + 'hexbin']] |
| 34 | + param_names = ['kind'] |
| 35 | + |
| 36 | + def setup(self, kind): |
| 37 | + if kind in ['bar', 'barh', 'pie']: |
| 38 | + n = 100 |
| 39 | + elif kind in ['kde', 'scatter', 'hexbin']: |
| 40 | + n = 10000 |
| 41 | + else: |
| 42 | + n = 1000000 |
| 43 | + |
| 44 | + self.x = Series(np.random.randn(n)) |
| 45 | + self.y = Series(np.random.randn(n)) |
| 46 | + if kind in ['area', 'pie']: |
| 47 | + self.x = self.x.abs() |
| 48 | + self.y = self.y.abs() |
| 49 | + self.df = DataFrame({'x': self.x, 'y': self.y}) |
| 50 | + |
| 51 | + def time_frame_plot(self, kind): |
| 52 | + self.df.plot(x='x', y='y', kind=kind) |
22 | 53 |
|
23 | 54 |
|
24 | 55 | class TimeseriesPlotting(object):
|
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