python pandas：如果有条件，则删除 df 列
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python pandas: drop a df column if condition
提问by Boosted_d16
I would like to drop a given column from a pandas dataframe IF all the values in the column is "0%".
如果列中的所有值都是“0%”，我想从 Pandas 数据框中删除给定的列。
my df:
我的 df：
data = {'UK': ['11%', '16%', '7%', '52%', '2%', '5%', '3%', '3%'],
'US': ['0%', '0%', '0%', '0%', '0%', '0%', '0%', '0%'],
'DE': ['11%', '16%', '7%', '52%', '2%', '5%', '3%', '3%'],
'FR': ['11%', '16%', '7%', '52%', '2%', '5%', '3%', '3%']
}
dummy_df = pd.DataFrame(data,
index= ['cat1','cat2','cat3','cat4','cat5','cat6','cat7','cat8'],
columns=['UK', 'US', 'DE', 'FR'])
my code so far:
到目前为止我的代码：
dummy_df.drop(dummy_df == '0%',inplace=True)
I get a value error:
我收到一个值错误：
ValueError: labels ['UK' 'US' 'DE' 'FR'] not contained in axis
回答by joris
In [186]: dummy_df.loc[:, ~(dummy_df == '0%').all()]
Out[186]:
UK DE FR
cat1 11% 11% 11%
cat2 16% 16% 16%
cat3 7% 7% 7%
cat4 52% 52% 52%
cat5 2% 2% 2%
cat6 5% 5% 5%
cat7 3% 3% 3%
cat8 3% 3% 3%
Explanation:
解释：
The comparison with '0%' you already got, this gives the following dataframe:
与您已经获得的 '0%' 进行比较，这给出了以下数据框：
In [182]: dummy_df == '0%'
Out[182]:
UK US DE FR
cat1 False True False False
cat2 False True False False
cat3 False True False False
cat4 False True False False
cat5 False True False False
cat6 False True False False
cat7 False True False False
cat8 False True False False
Now we want to know which columns has all Trues:
现在我们想知道哪些列全True是 s：
In [183]: (dummy_df == '0%').all()
Out[183]:
UK False
US True
DE False
FR False
dtype: bool
And finally, we can index with these boolean values (but taking the opposite with ~as want don'twant to select where this is True): dummy_df.loc[:, ~(dummy_df == '0%').all()].
最后，我们可以用这些布尔值（但考虑以相反的指标~作为想不想要选择在那里，这是True）dummy_df.loc[:, ~(dummy_df == '0%').all()]。
Similarly, you can also do: dummy_df.loc[:, (dummy_df != '0%').any()](selects columns where at least one value is not equal to '0%')
同样，您也可以这样做：（dummy_df.loc[:, (dummy_df != '0%').any()]选择至少一个值不等于“0%”的列）
回答by Zero
First get the columns where all values != '0%'
首先获取所有值所在的列 != '0%'
In [163]: cols = (dummy_df != '0%').any()
In [164]: cols
Out[164]:
UK True
US False
DE True
FR True
dtype: bool
Then call only colscolumns which are True
然后只调用cols列True
In [165]: dummy_df[cols[cols].index]
Out[165]:
UK DE FR
cat1 11% 11% 11%
cat2 16% 16% 16%
cat3 7% 7% 7%
cat4 52% 52% 52%
cat5 2% 2% 2%
cat6 5% 5% 5%
cat7 3% 3% 3%
cat8 3% 3% 3%
