Python:如何在不聚合数据帧的情况下进行分组和计数
我的数据框如下所示: 现在我想按列['name','grade']分组,并执行count(),结果如下所示: df.groupby(['name','grade'],as_index=False).count() 但我想要的应该是这样的:Python:如何在不聚合数据帧的情况下进行分组和计数,python,pandas,dataframe,pandas-groupby,Python,Pandas,Dataframe,Pandas Groupby,我的数据框如下所示: 现在我想按列['name','grade']分组,并执行count(),结果如下所示: df.groupby(['name','grade'],as_index=False).count() 但我想要的应该是这样的: 尝试使用变换: dict = {"year": [2010, 2011, 2012, 2010, 2011], "name": ["kelly", "kelly", "kelly", "peter", "peter"], "grade": ["
尝试使用
变换
:
dict = {"year": [2010, 2011, 2012, 2010, 2011],
"name": ["kelly", "kelly", "kelly", "peter", "peter"],
"grade": ["A", "A", "C", "B", "B"] }
import pandas as pd
df = pd.DataFrame(dict)
print(df)
grp = df.groupby(['name', 'grade'], as_index=False)
print(grp.count())
df['count'] = grp['year'].transform('count')
print(df)
PS:credit to你能再给我们看一点源代码吗?year=[201201201201201201201201011],name=['kelly','kelly','peter','peter],grade=[A','A','C','B','B'],df=pd.DataFrame(数据={'year':year','name','grade':grade})