python - 如何分组并计算该组 Pandas 中的总数

Question

您好我有以下数据框：

# Import pandas library 
import pandas as pd
import numpy as np
from sklearn.linear_model import LogisticRegression
# initialize list of lists 
data = [['tom', 10,1], ['nick', 15,0], ['tom', 14,1], ['jason', 15,0], ['nick', 18,1], ['jason', 15,0], ['jason', 17,1]
       , ['tom', 14,0], ['nick',16 ,1], ['tom', 22,1]] 
  
# Create the pandas DataFrame 
df = pd.DataFrame(data, columns = ['Name', 'Attempts','Target']) 

# print dataframe. 
df 
Name    Attempts    Target
0   tom     10       1
1   nick    15       0
2   tom     14       1
3   jason   15       0
4   nick    18       1
5   jason   15       0
6   jason   17       1
7   tom     14       0
8   nick    16       1
9   tom     22       1

我希望简单地在每个名字旁边得到一个总数，这样它就变成了：

Name    Attempts    Target    totalentries
0   tom     10       1             4
1   nick    15       0             3
2   tom     14       1             4
3   jason   15       0             3
4   nick    18       1             3
5   jason   15       0             3
6   jason   17       1             3
7   tom     14       0             4
8   nick    16       1             3
9   tom     22       1             4

试过：

df['totalentries'] = df.groupby('Name').nunique()

但得到一个ValueError: Wrong number of items passed 8, placement implies 1

有任何想法吗？非常感谢！

标签： pythonpandas

Answer 1

与聚合函数GroupBy.transform后的指定列一起使用：groupby

df['totalentries'] = df.groupby('Name')['Target'].transform('nunique')

如果需要计算值：

df['totalentries'] = df.groupby('Name')['Target'].transform('size')