我从这样的输入数据开始
df1 = pandas.DataFrame( {
"Name" : ["Alice", "Bob", "Mallory", "Mallory", "Bob" , "Mallory"] ,
"City" : ["Seattle", "Seattle", "Portland", "Seattle", "Seattle", "Portland"] } )
打印出来的时候是这样的:
City Name
0 Seattle Alice
1 Seattle Bob
2 Portland Mallory
3 Seattle Mallory
4 Seattle Bob
5 Portland Mallory
分组很简单:
g1 = df1.groupby( [ "Name", "City"] ).count()
并且打印会产生一个 GroupBy
对象:
City Name
Name City
Alice Seattle 1 1
Bob Seattle 2 2
Mallory Portland 2 2
Seattle 1 1
但我最终想要的是另一个包含 GroupBy 对象中所有行的 DataFrame 对象。换句话说,我想得到以下结果:
City Name
Name City
Alice Seattle 1 1
Bob Seattle 2 2
Mallory Portland 2 2
Mallory Seattle 1 1
我不太明白如何在 pandas 文档中完成此操作。欢迎任何提示。
最佳答案
g1
这里是一个DataFrame。不过,它有一个分层索引:
In [19]: type(g1)
Out[19]: pandas.core.frame.DataFrame
In [20]: g1.index
Out[20]:
MultiIndex([('Alice', 'Seattle'), ('Bob', 'Seattle'), ('Mallory', 'Portland'),
('Mallory', 'Seattle')], dtype=object)
也许你想要这样的东西?
In [21]: g1.add_suffix('_Count').reset_index()
Out[21]:
Name City City_Count Name_Count
0 Alice Seattle 1 1
1 Bob Seattle 2 2
2 Mallory Portland 2 2
3 Mallory Seattle 1 1
或者类似的东西:
In [36]: DataFrame({'count' : df1.groupby( [ "Name", "City"] ).size()}).reset_index()
Out[36]:
Name City count
0 Alice Seattle 1
1 Bob Seattle 2
2 Mallory Portland 2
3 Mallory Seattle 1
关于python - 将 Pandas GroupBy 输出从 Series 转换为 DataFrame,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/10373660/