我有一个数据框说df。 df有一列'Ages'
>>> df['Age']
我想分组这个年龄并创建一个类似这样的新列
If age >= 0 & age < 2 then AgeGroup = Infant
If age >= 2 & age < 4 then AgeGroup = Toddler
If age >= 4 & age < 13 then AgeGroup = Kid
If age >= 13 & age < 20 then AgeGroup = Teen
and so on .....
如何使用Pandas库实现此目的。
我尝试过这样的事情
X_train_data['AgeGroup'][ X_train_data.Age < 13 ] = 'Kid'
X_train_data['AgeGroup'][ X_train_data.Age < 3 ] = 'Toddler'
X_train_data['AgeGroup'][ X_train_data.Age < 1 ] = 'Infant'
但这样做我得到了这个警告
/Users/Anand/miniconda3/envs/learn/lib/python3.7/site-packages/ipykernel_launcher.py:3: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: /pandas-docs/stable/indexing.html#indexing-view-versus-copy
This is separate from the ipykernel package so we can avoid doing imports until
/Users/Anand/miniconda3/envs/learn/lib/python3.7/site-packages/ipykernel_launcher.py:4: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
如何避免此警告并以更好的方式执行此操作。
pandas的可能重复基于来自其他列的值创建新列
-1的预期输出是多少？
@jezrael可能是未知的
使用带参数right=False的pandas.cut不包括bin的最右边：
X_train_data = pd.DataFrame({'Age':[0,2,4,13,35,-1,54]})
bins= [0,2,4,13,20,110]
labels = ['Infant','Toddler','Kid','Teen','Adult']
X_train_data['AgeGroup'] = pd.cut(X_train_data['Age'], bins=bins, labels=labels, right=False)
print (X_train_data)
Age AgeGroup
0 0 Infant
1 2 Toddler
2 4 Kid
3 13 Teen
4 35 Adult
5 -1 NaN
6 54 Adult
最后替换缺失值使用add_categories和fillna：
X_train_data['AgeGroup'] = X_train_data['AgeGroup'].cat.add_categories('unknown')
.fillna('unknown')
print (X_train_data)
Age AgeGroup
0 0 Infant
1 2 Toddler
2 4 Kid
3 13 Teen
4 35 Adult
5 -1 unknown
6 54 Adult
bins= [-1,0,2,4,13,20, 110]
labels = ['unknown','Infant','Toddler','Kid','Teen', 'Adult']
X_train_data['AgeGroup'] = pd.cut(X_train_data['Age'], bins=bins, labels=labels, right=False)
print (X_train_data)
Age AgeGroup
0 0 Infant
1 2 Toddler
2 4 Kid
3 13 Teen
4 35 Adult
5 -1 unknown
6 54 Adult
请编辑以显示-1如何设置为Unknown @jezrael
@AnandSiddharth - 答案已被编辑。
我们可以将-1分配给bins并完成它
@AnandSiddharth - 是的，这是更好的解决方案;)
所以看起来像这样？bins= [-1, 0,2,4,13,20,110] labels = ['Unknown', 'Infant','Toddler','Kid','Teen','Adult']
@AnandSiddharth - 是的，exaclty，答案被编辑。
只需使用：
X_train_data.loc[(X_train_data.Age < 13), 'AgeGroup'] = 'Kid'
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