按名称访问Pandas MultiIndex列
按名称访问Pandas MultiIndex列
提问于 2018-08-20 15:01:54
我有一个用熊猫进口的电子表格，像这样：
df = pd.read_excel('my_spreadsheet.xlsx',header = [0,1],index_col=0,sheetname='Sheet1')df.columns的输出是：
MultiIndex(levels=[[u'MR 1', u'MR 10', u'MR 11', u'MR 12', u'MR 13', u'MR 14', u'MR 15', u'MR 16', u'MR 17', u'MR 18', u'MR 19', u'MR 2', u'MR 20', u'MR 21', u'MR 22', u'MR 3', u'MR 4', u'MR 5', u'MR 6', u'MR 7', u'MR 8', u'MR 9'], [u'BIRADS', u'ExamDesc', u'completedDTTM']],
labels=[[0, 0, 0, 11, 11, 11, 15, 15, 15, 16, 16, 16, 17, 17, 17, 18, 18, 18, 19, 19, 19, 20, 20, 20, 21, 21, 21, 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 12, 12, 12, 13, 13, 13, 14, 14, 14], [1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0]],
names=[None, u'De-Identified MRN'])我一直试图访问名为“非标识的MRN”的列的值，但似乎找不到这样做的方法。
我尝试过的(基于类似职位)：
[in] df.index.get_level_values('De-Identified MRN')
[out] KeyError: 'Level De-Identified MRN must be same as name (None)'和
[in] df.index.unique(level='De-Identified MRN')
[out] KeyError: 'Level De-Identified MRN must be same as name (None)'更新:由于某些原因，下面的操作很成功。我真的不明白MultiIndex Pandas的格式：
pd.Series(df.index)回答 2
Stack Overflow用户
发布于 2018-08-20 15:09:51
通过使用你的数据
s="MultiIndex(levels=[[u'MR 1', u'MR 10', u'MR 11', u'MR 12', u'MR 13', u'MR 14', u'MR 15', u'MR 16', u'MR 17', u'MR 18', u'MR 19', u'MR 2', u'MR 20', u'MR 21', u'MR 22', u'MR 3', u'MR 4', u'MR 5', u'MR 6', u'MR 7', u'MR 8', u'MR 9'], [u'BIRADS', u'ExamDesc', u'completedDTTM']],labels=[[0, 0, 0, 11, 11, 11, 15, 15, 15, 16, 16, 16, 17, 17, 17, 18, 18, 18, 19, 19, 19, 20, 20, 20, 21, 21, 21, 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 12, 12, 12, 13, 13, 13, 14, 14, 14], [1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0]],names=[None, u'De-Identified MRN'])"
idx=eval(s, {}, {'MultiIndex': pd.MultiIndex})
df=pd.DataFrame(index=idx)
df.index.get_level_values(level=1) # df.index.get_level_values('De-Identified MRN')
Out[336]:
Index(['ExamDesc', 'completedDTTM', 'BIRADS', 'ExamDesc', 'completedDTTM',
'BIRADS', 'ExamDesc', 'completedDTTM', 'BIRADS', 'ExamDesc',...另外，如果以上所有内容仍然不起作用，请尝试。
df.reset_index()['De-Identified MRN']Stack Overflow用户
发布于 2018-08-20 15:15:31
尝试以下几点：
midx = pd.MultiIndex(
levels=[[u'MR 1', u'MR 10', u'MR 11', u'MR 12', u'MR 13', u'MR 14', u'MR 15', u'MR 16', u'MR 17', u'MR 18', u'MR 19', u'MR 2', u'MR 20', u'MR 21', u'MR 22', u'MR 3', u'MR 4', u'MR 5', u'MR 6', u'MR 7', u'MR 8', u'MR 9'], [u'BIRADS', u'ExamDesc', u'completedDTTM']],
labels=[[0, 0, 0, 11, 11, 11, 15, 15, 15, 16, 16, 16, 17, 17, 17, 18, 18, 18, 19, 19, 19, 20, 20, 20, 21, 21, 21, 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 12, 12, 12, 13, 13, 13, 14, 14, 14], [1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0]],
names=[None, u'De-Identified MRN']
)
midx.levels[1] # returns the following
Index(['BIRADS', 'ExamDesc', 'completedDTTM'], dtype='object', name='De-Identified MRN')
midx.levels[1].values # returns the following
array(['BIRADS', 'ExamDesc', 'completedDTTM'], dtype=object)页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/51933550
复制相关文章
相似问题
腾讯云开发者
