Python 如何比较熊猫中的两列以制作第三列？
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how to compare two columns in pandas to make a third column ?
提问by Anurag Pandey
i have two columns age and sex in a pandas dataframe
我在熊猫数据框中有两列年龄和性别
sex = ['m', 'f' , 'm', 'f', 'f', 'f', 'f']
age = [16 , 15 , 14 , 9 , 8 , 2 , 56 ]
now i want to extract a third column : like this if age <=9 then output ' child' and if age >9 then output the respective gender
现在我想提取第三列：像这样，如果年龄 <=9 则输出“孩子”，如果年龄 >9 则输出相应的性别
sex = ['m', 'f' , 'm','f' ,'f' ,'f' , 'f']
age = [16 , 15 , 14 , 9 , 8 , 2 , 56 ]
yes = ['m', 'f' ,'m' ,'child','child','child','f' ]
please help ps . i am still working on it if i get anything i will immediately update
请帮忙ps。我还在努力，如果我得到任何东西我会立即更新
回答by root
Use numpy.where:
使用numpy.where：
df['col3'] = np.where(df['age'] <= 9, 'child', df['sex'])
The resulting output:
结果输出：
age sex col3
0 16 m m
1 15 f f
2 14 m m
3 9 f child
4 8 f child
5 2 f child
6 56 f f
Timings
时间安排
Using the following setup to get a larger sample DataFrame:
使用以下设置来获得更大的样本 DataFrame：
np.random.seed([3,1415])
n = 10**5
df = pd.DataFrame({'sex': np.random.choice(['m', 'f'], size=n), 'age': np.random.randint(0, 100, size=n)})
I get the following timings:
我得到以下时间：
%timeit np.where(df['age'] <= 9, 'child', df['sex'])
1000 loops, best of 3: 1.26 ms per loop
%timeit df['sex'].where(df['age'] > 9, 'child')
100 loops, best of 3: 3.25 ms per loop
%timeit df.apply(lambda x: 'child' if x['age'] <= 9 else x['sex'], axis=1)
100 loops, best of 3: 3.92 ms per loop
回答by Tim Fuchs
You could use pandas.DataFrame.where. For example
您可以使用pandas.DataFrame.where。例如
child.where(age<=9, sex)
回答by ragesz
df = pd.DataFrame({'sex':['m', 'f' , 'm', 'f', 'f', 'f', 'f'],
'age':[16, 15, 14, 9, 8, 2, 56]})
df['yes'] = df.apply(lambda x: 'child' if x['age'] <= 9 else x['sex'], axis=1)
Result:
结果：
age sex yes
0 16 m m
1 15 f f
2 14 m m
3 9 f child
4 8 f child
5 2 f child
6 56 f f
