[英]Dropping a group of columns based on a condition fulfilled by a column in Pandas
我有一个 dataframe,列名是元组。 下面是我的 dataframe 的示例数据:
data = {"('7086', 'Open')": {5: 0.0700000002980232, 6: 0.0649999976158142, 7: 0.0750000029802322, 8: 0.0649999976158142, 9: 0.0700000002980232},
"('7086', 'High')": {5: 0.0700000002980232, 6: 0.0750000029802322, 7: 0.0750000029802322, 8: 0.0750000029802322, 9: 0.0700000002980232},
"('7086', 'Low')": {5: 0.0700000002980232, 6: 0.0649999976158142, 7: 0.0750000029802322, 8: 0.0649999976158142, 9: 0.0700000002980232},
"('7086', 'Close')": {5: 0.0700000002980232, 6: 0.0750000029802322, 7: 0.0750000029802322, 8: 0.0750000029802322, 9: 0.0700000002980232},
"('7086', 'Adj Close')": {5: 0.0700000002980232, 6: 0.0750000029802322, 7: 0.0750000029802322, 8: 0.0750000029802322, 9: 0.0700000002980232},
"('7086', 'Volume')": {5: 0, 6: 3200, 7: 0, 8: 200800, 9: 260000},
"('03028', 'Open')": {5: 0.3600000143051147, 6: 0.3600000143051147, 7: 0.3600000143051147, 8: 0.3600000143051147, 9: 0.3600000143051147},
"('03028', 'High')": {5: 0.3600000143051147, 6: 0.3600000143051147, 7: 0.3600000143051147, 8: 0.3600000143051147, 9: 0.3600000143051147},
"('03028', 'Low')": {5: 0.3600000143051147, 6: 0.3600000143051147, 7: 0.3600000143051147, 8: 0.3600000143051147, 9: 0.3600000143051147},
"('03028', 'Close')": {5: 0.3600000143051147, 6: 0.3600000143051147, 7: 0.3600000143051147, 8: 0.3600000143051147, 9: 0.3600000143051147},
"('03028', 'Adj Close')": {5: 0.3509772419929504, 6: 0.3509772419929504, 7: 0.3509772419929504, 8: 0.3509772419929504, 9: 0.3509772419929504},
"('03028', 'Volume')": {5: 15500.0, 6: 0.0, 7: 0.0, 8: 0.0, 9: 0.0}}
df = pd.DataFrame(data)
('7086', 'Open') ... ('03028', 'Volume')
5 0.070 ... 15500.0
6 0.065 ... 0.0
7 0.075 ... 0.0
8 0.065 ... 0.0
9 0.070 ... 0.0
[5 rows x 12 columns]
现在,我希望执行的是当数字代码中的其中一列只有 1 个唯一数字时,删除具有相同数字代码的一组列:
df.nunique()
('7086', 'Open') 3
('7086', 'High') 2
('7086', 'Low') 3
('7086', 'Close') 2
('7086', 'Adj Close') 2
('7086', 'Volume') 4
('03028', 'Open') 1
('03028', 'High') 1
('03028', 'Low') 1
('03028', 'Close') 1
('03028', 'Adj Close') 1
('03028', 'Volume') 2
dtype: int64
如上,我们可以在数字代码03028
中看到,6 列中的 5 列只有 1 个唯一值。 因此,我希望根据这个事实删除所有具有相同数字代码的6列。 有什么想法我可以做到吗? 我正在考虑将它组合在一起并删除它。 但我不确定如何处理元组。 提前致谢。
我预期的 output 将是:
('7086', 'Open') ... ('7086', 'Volume')
5 0.070 ... 0
6 0.065 ... 3200
7 0.075 ... 0
8 0.065 ... 200800
9 0.070 ... 260000
[5 rows x 6 columns]
你可以做
out = df.loc[:,~df.columns.str.contains("'03028',")]
如果多个
out = df.loc[:,~df.columns.str.contains("'03028',|'00000',")]
尝试这样的事情
import ast
df.columns = pd.MultiIndex.from_tuples(map(ast.literal_eval, df.columns))
filter_ = (df.nunique()==1).groupby(level=0).any()
df.drop(filter_[filter_].index, axis=1, level=0)
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