我有一些学校资料：
data = {'name': ['school a', 'school b', 'school c', 'school d', 'school e', 'school f'],
'type': ['a', 'a', 'b', 'b', 'a', 'b'],
'location': ['county a', 'county a', 'county b', 'county b', 'county b', 'county a'],
'avg_score': [9, 7, 5, 7, 6, 8]
}
df = pd.DataFrame(data)
Out:
name type location avg_score
0 school a a county a 9
1 school b a county a 7
2 school c b county b 5
3 school d b county b 7
4 school e a county b 6
5 school f b county a 8
我想比较学校分数与每个位置的学校类型的平均值。
我可以使用groupby来做到这一点：df.groupby(['type', 'location']).mean().round(2)
Out:
avg_score
type location
a county a 8
county b 6
b county a 8
county b 6
但是，我想获得一个额外的列，而不是分组表，该列的每个位置的该学校类型的平均值。
喜欢此：
name type location avg_score compare_score
0 school a a county a 9 8
1 school b a county a 7 5
2 school c b county b 5 7
3 school d b county b 7 7
4 school e a county b 6 3
5 school f b county a 8 7
我发现了这个问题
Python Pandas average based on condition into new column
并尝试对我的问题应用一些可能的解决方案：
for atype, alocation in df.groupby('type'):
df.loc[df.type == type, 'compare'] = (df.where(df['type' == atype]).where(df['location' == alocation]).mean()).avg_score.round(2)```
引发此错误：
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
~/.local/share/virtualenvs/schule-jwiURUl3/lib/python3.6/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
2656 try:
-> 2657 return self._engine.get_loc(key)
2658 except KeyError:
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
KeyError: False
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
<ipython-input-27-4b3cf2b7aaf6> in <module>
1 for atype, alocation in df.groupby('type'):
----> 2 df.loc[df.type == type, 'compare'] = (df.where(df['type' == atype]).where(df['location' == alocation]).mean()).avg_score.round(2)
~/.local/share/virtualenvs/schule-jwiURUl3/lib/python3.6/site-packages/pandas/core/frame.py in __getitem__(self, key)
2925 if self.columns.nlevels > 1:
2926 return self._getitem_multilevel(key)
-> 2927 indexer = self.columns.get_loc(key)
2928 if is_integer(indexer):
2929 indexer = [indexer]
~/.local/share/virtualenvs/schule-jwiURUl3/lib/python3.6/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
2657 return self._engine.get_loc(key)
2658 except KeyError:
-> 2659 return self._engine.get_loc(self._maybe_cast_indexer(key))
2660 indexer = self.get_indexer([key], method=method, tolerance=tolerance)
2661 if indexer.ndim > 1 or indexer.size > 1:
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
KeyError: False
也许这根本不是一个好尝试。你有什么建议吗？任何提示都受到高度赞赏。
df['compare_score']=df.groupby(['type', 'location']).transform('mean').round(2)
print(df)
---------------
name type location avg_score compare_score
0 school a a county a 9 8
1 school b a county a 7 8
2 school c b county b 5 6
3 school d b county b 7 6
4 school e a county b 6 6
5 school f b county a 8 8