我在对数据集进行 strat 采样时遇到了这个问题
i faced this problem while i was strat sampling the dataset
In [16] : Strat_d3=d3.groupby('Label', group_keys=False).apply(lambda x: x.sample(1000))
Traceback (most recent call last):
File "<ipython-input-16-f54910ba8f95>", line 1, in <module>
Strat_d3=d3.groupby('Label', group_keys=False).apply(lambda x: x.sample(1000))
File "C:\Users\Msi\anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 894, in apply
result = self._python_apply_general(f, self._selected_obj)
File "C:\Users\Msi\anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 928, in _python_apply_general
keys, values, mutated = self.grouper.apply(f, data, self.axis)
File "C:\Users\Msi\anaconda3\lib\site-packages\pandas\core\groupby\ops.py", line 238, in apply
res = f(group)
File "<ipython-input-16-f54910ba8f95>", line 1, in <lambda>
Strat_d3=d3.groupby('Label', group_keys=False).apply(lambda x: x.sample(1000))
File "C:\Users\Msi\anaconda3\lib\site-packages\pandas\core\generic.py", line 5350, in sample
locs = rs.choice(axis_length, size=n, replace=replace, p=weights)
File "mtrand.pyx", line 959, in numpy.random.mtrand.RandomState.choice
ValueError: Cannot take a larger sample than population when 'replace=False'
这些消息意味着至少在一组中您没有足够的样本 (< 1000)。
2 个解决方案:
- 使用
replace=True
获得 1000 个样本,但有些重复:
# You don't need apply here
Strat_d3 = d3.groupby('Label', group_keys=False).sample(1000, replace=True)
- 如果您接受某些组的样本少于 1000 个,请使用此技巧:
Strat_d3 = d3.groupby('Label', group_keys=False).apply(lambda x: x.sample(min(len(x), 1000)))
要调试您的组,请使用以下代码检查样本数量低于 1000 的标签:
d3.value_counts('Label').loc[lambda x: x < 1000]
In [16] : Strat_d3=d3.groupby('Label', group_keys=False).apply(lambda x: x.sample(1000))
Traceback (most recent call last):
File "<ipython-input-16-f54910ba8f95>", line 1, in <module>
Strat_d3=d3.groupby('Label', group_keys=False).apply(lambda x: x.sample(1000))
File "C:\Users\Msi\anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 894, in apply
result = self._python_apply_general(f, self._selected_obj)
File "C:\Users\Msi\anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 928, in _python_apply_general
keys, values, mutated = self.grouper.apply(f, data, self.axis)
File "C:\Users\Msi\anaconda3\lib\site-packages\pandas\core\groupby\ops.py", line 238, in apply
res = f(group)
File "<ipython-input-16-f54910ba8f95>", line 1, in <lambda>
Strat_d3=d3.groupby('Label', group_keys=False).apply(lambda x: x.sample(1000))
File "C:\Users\Msi\anaconda3\lib\site-packages\pandas\core\generic.py", line 5350, in sample
locs = rs.choice(axis_length, size=n, replace=replace, p=weights)
File "mtrand.pyx", line 959, in numpy.random.mtrand.RandomState.choice
ValueError: Cannot take a larger sample than population when 'replace=False'
这些消息意味着至少在一组中您没有足够的样本 (< 1000)。 2 个解决方案:
- 使用
replace=True
获得 1000 个样本,但有些重复:
# You don't need apply here
Strat_d3 = d3.groupby('Label', group_keys=False).sample(1000, replace=True)
- 如果您接受某些组的样本少于 1000 个,请使用此技巧:
Strat_d3 = d3.groupby('Label', group_keys=False).apply(lambda x: x.sample(min(len(x), 1000)))
要调试您的组,请使用以下代码检查样本数量低于 1000 的标签:
d3.value_counts('Label').loc[lambda x: x < 1000]