Question

假设我有这个结果

group1 = df.groupby(['first_column', 'second_column'], as_index=False).size()

first_column    second_column   
A               A1              1
                A2              2
B               B1              1
                B2              2
                B3              3

然后我希望它计算first_column的总大小并将其显示为类似

的内容

first_column    second_column       
A               A1              1           3
                A2              2
B               B1              1           6
                B2              2
                B3              3

根据总尺寸，我希望它排在前十大总尺寸之列。我该怎么做这样的事情？也可以为列命名。喜欢这个

first_column    second_column   size    total_size

更新1

数据框应该是这样的。

df.head()

    first_column    second_column
0   A               A1
1   A               A2
2   A               A2
3   B               B1
4   B               B2
5   B               B2
6   B               B3
7   B               B3
8   B               B3

Answer 1

代码注释应该是自我解释的。

# Sample data.
df = pd.DataFrame({'first_column': ['A']*3 + ['B']*6, 'second_column': ['A1'] + ['A2']*2 + ['B1'] + ['B2']*2 + ['B3']*3})

# Create initial groupby, rename column to 'size' and reset index.
gb = df.groupby(['first_column', 'second_column'], as_index=False).size()
gb.name = 'size'
gb = gb.reset_index()

>>> gb
  first_column second_column  size
0            A            A1     1
1            A            A2     2
2            B            B1     1
3            B            B2     2
4            B            B3     3

# Use transform to sum the `size` by the first column only.
gb['total_size'] = gb.groupby('first_column')['size'].transform('sum')

>>> gb
  first_column second_column  size  total_size
0            A            A1     1           3
1            A            A2     2           3
2            B            B1     1           6
3            B            B2     2           6
4            B            B3     3           6

熊猫：分组并按总大小排序

1 个答案: