python - Pandas MultiIndex 分层列的选择

Question

目标:转换通过 Pandas DataReader 从 EuroStat 提取的原始数据，并 reshape 数据，使其具有 Pandas DateTime 对象作为索引，国家/地区作为列。

代码:

import pandas as pd
import pandas_datareader as web  
import datetime
start = datetime.datetime(1900,1,1)
end = datetime.date.today()
df2 = web.DataReader('tipsii20', 'eurostat', start = start,end = end)
df2.columns

查看列，我们可以看到我们正在使用 MultiIndex

MultiIndex(levels=[[u'Rest of the world'], [u'Net liabilities (liabilities minus assets)'], [u'Net external debt'], [u'Percentage of gross domestic product (GDP)'], [u'Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data)'], [u'Austria', u'Belgium', u'Bulgaria', u'Croatia', u'Cyprus', u'Czech Republic', u'Denmark', u'Estonia', u'Finland', u'France', u'Germany (until 1990 former territory of the FRG)', u'Greece', u'Hungary', u'Ireland', u'Italy', u'Latvia', u'Lithuania', u'Luxembourg', u'Malta', u'Netherlands', u'Poland', u'Portugal', u'Romania', u'Slovakia', u'Slovenia', u'Spain', u'Sweden', u'United Kingdom'], [u'Annual']], labels=[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 2, 4, 5, 10, 6, 7, 11, 25, 8, 9, 3, 12, 13, 14, 16, 17, 15, 18, 19, 20, 21, 22, 26, 24, 23, 27], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], names=[u'PARTNER', u'STK_FLOW', u'BOP_ITEM', u'UNIT', u'S_ADJ', u'GEO', u'FREQ'])

我想转换此数据集以使其保持其 DateTime 索引，但使用 names['GEO'] 作为列。这应该是 df2.xs 吗？

Answer 1

您可以使用 droplevel :

df2.columns = df2.columns.droplevel([0,1,2,3,4,6])

另一个解决方案，如果知道级别名称类似于 Bharath shetty' solution :

df2.columns =  df2.columns.get_level_values('GEO')