如何在x轴上绘制datetime.time

huangapple
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英文:

How to plot datetime.time on x-axis

问题

  1. import pandas as pd
  2. import matplotlib.pyplot as plt
  4. # 示例数据框
  5. data = {'Id': [1503960366, 1503960366, 1503960366, 1503960366, 1503960366],
  6.         'ActivityHour': ['2016-04-12 00:00:00', '2016-04-12 01:00:00', '2016-04-12 02:00:00', '2016-04-12 03:00:00', '2016-04-12 04:00:00'],
  7.         'Calories': [81, 61, 59, 47, 48],
  8.         'TotalIntensity': [20, 8, 7, 0, 0],
  9.         'AverageIntensity': [0.333333, 0.133333, 0.116667, 0.0, 0.0],
  10.         'StepTotal': [373, 160, 151, 0, 0]}
  11. hourly_activity = pd.DataFrame(data)
  13. hourly_activity['time'] = [d.time() for d in hourly_activity['ActivityHour']]
  14. hourly_activity['date'] = [d.date() for d in hourly_activity['ActivityHour']]
  15. hours_vs_steps = hourly_activity.copy()
  16. hours_vs_steps = hours_vs_steps[['time', 'StepTotal', 'Calories']]
  17. hours_vs_steps = hours_vs_steps.groupby(['time']).sum()
  18. hours_vs_steps.reset_index(inplace=True)
  20. # 初始数据框
  21. Id         ActivityHour  Calories  TotalIntensity  AverageIntensity  StepTotal
  22. 0  1503960366  2016-04-12 00:00:00        81              20          0.333333        373
  23. 1  1503960366  2016-04-12 01:00:00        61               8          0.133333        160
  24. 2  1503960366  2016-04-12 02:00:00        59               7          0.116667        151
  25. 3  1503960366  2016-04-12 03:00:00        47               0          0.000000          0
  26. 4  1503960366  2016-04-12 04:00:00        48               0          0.000000          0
  28. # 使用.groupby后的数据框
  29.      time  StepTotal  Calories
  30. 0  00:00:00      39404     67066
  31. 1  01:00:00      21555     65464
  32. 2  02:00:00      15964     64551
  33. 3  03:00:00       5996     63013
  34. 4  04:00:00      11836     63620
  36. # 绘制图表时的代码
  37. plt.plot(hours_vs_steps.time, hours_vs_steps.StepTotal)

结果会导致以下错误：

  1. ---------------------------------------------------------------------------
  2. TypeError                                 Traceback (most recent call last)
  3. Cell In[28], line 1
  4. ----> 1 plt.plot(hours_vs_steps.time, hours_vs_steps.StepTotal)
  6. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\pyplot.py:2812, in plot(scalex, scaley, data, *args, **kwargs)
  7.    2810 @_copy_docstring_and_deprecators(Axes.plot)
  8.    2811 def plot(*args, scalex=True, scaley=True, data=None, **kwargs):
  9. -> 2812     return gca().plot(
  10.    2813         *args, scalex=scalex, scaley=scaley,
  11.    2814         **({"data": data} if data is not None else {}), **kwargs)
  13. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\axes\_axes.py:1690, in Axes.plot(self, scalex, scaley, data, *args, **kwargs)
  14.    1688 lines = [*self._get_lines(*args, data=data, **kwargs)]
  15.    1689 for line in lines:
  16. -> 1690     self.add_line(line)
  17.    1691 if scalex:
  18.    1692     self._request_autoscale_view("x")
  20. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\axes\_base.py:2304, in _AxesBase.add_line(self, line)
  21.    2301 if line.get_clip_path() is None:
  22.    2302     line.set_clip_path(self.patch)
  23. -> 2304 self._update_line_limits(line)
  24.    2305 if not line.get_label():
  25.    2306     line.set_label(f'_child{len(self._children)}')
  27. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\axes\_base.py:2327, in _AxesBase._update_line_limits(self, line)
  28.    2323 def _update_line_limits(self, line):
  29.    2324     """
  30.    2325     Figures out the data limit of the given line, updating self.dataLim.
  31.    2326     """
  32. -> 2327     path = line.get_path()
  33.    2328     if path.vertices.size == 0:
  34.    2329         return
  36. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\lines.py:1029, in Line2D.get_path(self)
  37.    1027 """Return the `~matplotlib.path.Path` associated with this line."""
  38.    1028 if self._invalidy or self._invalidx:
  39. -> 1029     self.recache()
  40.    1030 return self._path
  42. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\lines.py:657, in Line2D.recache(self, always)
  43.     655 if always or self._invalidx:
  44.     656     xconv = self.convert_xunits(self._xorig)
  45. --> 657     x = _to_unmasked_float_array(xconv).ravel()
  46.     658 else:
  47.     659     x = self._x
  49. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\cbook\__init__.py:1335, in _to_unmasked_float_array(x)
  50.    1333     return np.ma.asarray(x, float).filled(np.nan)
  51.    1334 else:
  52. -> 1335     return np.asarray(x, float)
  54. TypeError: float() argument must be a string or a real number, not 'datetime.time'
英文:

I'm trying to compare the usage of a device during certain hours. My dataset provided a date-time format (YYYY/MM/D HH:MM:SS) that I split in two columns and then grouped by the new time column to get the summary of steps per hour.

  1. import pandas as pd
  2. import matplotlib.pyplot as plt
  4. # sample dataframe
  5. data = {'Id': [1503960366, 1503960366, 1503960366, 1503960366, 1503960366],
  6.         'ActivityHour': ['2016-04-12 00:00:00', '2016-04-12 01:00:00', '2016-04-12 02:00:00', '2016-04-12 03:00:00', '2016-04-12 04:00:00'],
  7.         'Calories': [81, 61, 59, 47, 48],
  8.         'TotalIntensity': [20, 8, 7, 0, 0],
  9.         'AverageIntensity': [0.333333, 0.133333, 0.116667, 0.0, 0.0],
  10.         'StepTotal': [373, 160, 151, 0, 0]}
  11. hourly_activity = pd.DataFrame(data)
  13. hourly_activity['time'] = [d.time() for d in hourly_activity['ActivityHour']]
  14. hourly_activity['date'] = [d.date() for d in hourly_activity['ActivityHour']]
  15. hours_vs_steps = hourly_activity.copy()
  16. hours_vs_steps = hours_vs_steps[['time', 'StepTotal', 'Calories']]
  17. hours_vs_steps = hours_vs_steps.groupby(['time']).sum()
  18. hours_vs_steps.reset_index(inplace=True)

Initial DataFrame:

  1.            Id         ActivityHour  Calories  TotalIntensity  AverageIntensity  StepTotal
  2. 0  1503960366  2016-04-12 00:00:00        81              20          0.333333        373
  3. 1  1503960366  2016-04-12 01:00:00        61               8          0.133333        160
  4. 2  1503960366  2016-04-12 02:00:00        59               7          0.116667        151
  5. 3  1503960366  2016-04-12 03:00:00        47               0          0.000000          0
  6. 4  1503960366  2016-04-12 04:00:00        48               0          0.000000          0

After .groupby:

  1. 	time	StepTotal	Calories
  2. 0	00:00:00	39404	67066
  3. 1	01:00:00	21555	65464
  4. 2	02:00:00	15964	64551
  5. 3	03:00:00	5996	63013
  6. 4	04:00:00	11836	63620

I tried many times to plot the "StepTotal column as y_axis while using the time columns as x_axis but I wasn't able to do it either using matplotlib or seaborn.

Also, tried to plot the time when had it as index using hours_vs_steps.index but didn't work.

  1. plt.plot(hours_vs_steps.time, hours_vs_steps.StepTotal)

Results in the following error

  1. ---------------------------------------------------------------------------
  2. TypeError                                 Traceback (most recent call last)
  3. Cell In[28], line 1
  4. ----> 1 plt.plot(hours_vs_steps.time, hours_vs_steps.StepTotal)
  6. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\pyplot.py:2812, in plot(scalex, scaley, data, *args, **kwargs)
  7.    2810 @_copy_docstring_and_deprecators(Axes.plot)
  8.    2811 def plot(*args, scalex=True, scaley=True, data=None, **kwargs):
  9. -> 2812     return gca().plot(
  10.    2813         *args, scalex=scalex, scaley=scaley,
  11.    2814         **({"data": data} if data is not None else {}), **kwargs)
  13. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\axes\_axes.py:1690, in Axes.plot(self, scalex, scaley, data, *args, **kwargs)
  14.    1688 lines = [*self._get_lines(*args, data=data, **kwargs)]
  15.    1689 for line in lines:
  16. -> 1690     self.add_line(line)
  17.    1691 if scalex:
  18.    1692     self._request_autoscale_view("x")
  20. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\axes\_base.py:2304, in _AxesBase.add_line(self, line)
  21.    2301 if line.get_clip_path() is None:
  22.    2302     line.set_clip_path(self.patch)
  23. -> 2304 self._update_line_limits(line)
  24.    2305 if not line.get_label():
  25.    2306     line.set_label(f'_child{len(self._children)}')
  27. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\axes\_base.py:2327, in _AxesBase._update_line_limits(self, line)
  28.    2323 def _update_line_limits(self, line):
  29.    2324     """
  30.    2325     Figures out the data limit of the given line, updating self.dataLim.
  31.    2326     """
  32. -> 2327     path = line.get_path()
  33.    2328     if path.vertices.size == 0:
  34.    2329         return
  36. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\lines.py:1029, in Line2D.get_path(self)
  37.    1027 """Return the `~matplotlib.path.Path` associated with this line."""
  38.    1028 if self._invalidy or self._invalidx:
  39. -> 1029     self.recache()
  40.    1030 return self._path
  42. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\lines.py:657, in Line2D.recache(self, always)
  43.     655 if always or self._invalidx:
  44.     656     xconv = self.convert_xunits(self._xorig)
  45. --> 657     x = _to_unmasked_float_array(xconv).ravel()
  46.     658 else:
  47.     659     x = self._x
  49. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\cbook\__init__.py:1335, in _to_unmasked_float_array(x)
  50.    1333     return np.ma.asarray(x, float).filled(np.nan)
  51.    1334 else:
  52. -> 1335     return np.asarray(x, float)
  54. TypeError: float() argument must be a string or a real number, not 'datetime.time'

答案1

得分: 2

  • 使用 pandas.DataFrame.plot 直接绘制数据框，该方法使用 matplotlib 作为后端。
  • 使用 .dt 访问器 提取时间和日期组件，而不是使用列表推导。
  • 在 python 3.11.3、pandas 2.0.1、matplotlib 3.7.1 中测试通过
  1. import pandas as pd
  3. # 假设有名为 df 的样本数据框
  4. df = pd.DataFrame(data)
  6. # 将列转换为 datetime[ns] 类型
  7. df.ActivityHour = pd.to_datetime(df.ActivityHour)
  9. # 根据需要提取时间和日期
  10. df['time'] = df.ActivityHour.dt.time
  11. df['date'] = df.ActivityHour.dt.date
  13. # 分组并求和
  14. dfg = df.groupby(['time'])[['StepTotal', 'Calories']].sum()
  16. # 使用 pandas.DataFrame.plot 绘制图表
  17. ax = dfg.plot(secondary_y='Calories', figsize=(9, 5))

如何在x轴上绘制datetime.time

英文:
  • Plot the dataframe directly with pandas.DataFrame.plot, which uses matplotlib as the backend.
  • Use the .dt accessor to extract the time and date components, not a list comprehension.
  • Tested in python 3.11.3, pandas 2.0.1, matplotlib 3.7.1
  1. import pandas as pd
  3. # given the sample dataframe as df
  4. df = pd.DataFrame(data)
  6. # convert the column to a datetime[ns] Dtype
  7. df.ActivityHour = pd.to_datetime(df.ActivityHour)
  9. # extract the time and date as needed
  10. df['time'] = df.ActivityHour.dt.time
  11. df['date'] = df.ActivityHour.dt.date
  13. # group and sum
  14. dfg = df.groupby(['time'])[['StepTotal', 'Calories']].sum()
  16. # plot with pandas.DataFrame.plot
  17. ax = dfg.plot(secondary_y='Calories', figsize=(9, 5))

如何在x轴上绘制datetime.time

huangapple
  • 本文由 发表于 2023年5月28日 17:05:26
  • 转载请务必保留本文链接：https://go.coder-hub.com/76350723.html
  • matplotlib
  • pandas
  • python
  • time
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