如何解决执行groupy后从数据中删除一些行
我有这个数据集:
df = pd.DataFrame({'scientist':["Wendelaar Bonga"," Sjoerd E.","Grätzel"," Michael","Willett","Walter C.","Kessler","Ronald C.","Witten,Edward","Wang,Zhong Lin"],'SubjectField': ["Biomedical Engineering","Inorganic & Nuclear Chemistry","Organic Chemistry","Biomedical Engineering","Developmental Biology","Mechanical Engineering & Transports","Microbiology","Cardiovascular System & Hematology","Biomedical Engineering"]})
我想计算每个学科领域的科学家人数,并从我的数据中删除少于 2 个科学家的学科领域。
x= df.groupby('SubjectField')['scientist'].count()
ans = x[x > 2]
解决方法
你已经在正确的轨道上,我刚刚添加了删除不满足条件的行的代码
import pandas as pd
df = pd.DataFrame({'scientist':["Wendelaar Bonga"," Sjoerd E.","Grätzel"," Michael","Willett","Walter C.","Kessler","Ronald C.","Witten,Edward","Wang,Zhong Lin"],'SubjectField': ["Biomedical Engineering","Inorganic & Nuclear Chemistry","Organic Chemistry","Biomedical Engineering","Developmental Biology","Mechanical Engineering & Transports","Microbiology","Cardiovascular System & Hematology","Biomedical Engineering"]})
x = df.groupby('SubjectField')['scientist'].count()
您可以使用带有参数 drop
的 index
删除不符合条件的行
波浪号 ~
用作否定以获取条件的反面
drop_idx = x[~(x > 2)].index.values
x = x.drop(index=drop_idx)
x
将只包含计数大于 2 的行
试试这个:
mask = df.groupby('SubjectField')['SubjectField'].transform('count') > 2
filtered = df[mask]
版权声明:本文内容由互联网用户自发贡献,该文观点与技术仅代表作者本人。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容, 请发送邮件至 dio@foxmail.com 举报,一经查实,本站将立刻删除。