+-----+-------+--------+
| | Buyer | Sex |
+-----+-------+--------+
| 0 | 1 | Male |
| 1 | 1 | Female |
| 2 | 0 | Male |
| 3 | 1 | Female |
| ... | ... | ... |
+-----+-------+--------+
我想将上面的数据框求和并归入下面的数据框(表)。大熊猫有内置功能可以做到这一点吗?还是我必须手动进行迭代,求和和分组?
+---+---------+------+
| | Female | Male |
+---+---------+------+
| 0 | 81 | 392 |
| 1 | 539 | 233 |
+---+---------+------+
最佳答案
使用pivot_table
,将'count'
用作您的aggfunc。
另外,考虑到可能从未找到某些组合,请使用fillna
用0填充空白单元格:
In [28]:
df['V'] = 1
print df
Buyer Sex V
0 1 Male 1
1 1 Female 1
2 0 Male 1
3 1 Female 1
In [29]:
print df.pivot_table(index='Buyer', columns='Sex', values='V', aggfunc='count').fillna(0)
Sex Female Male
Buyer
0 0 1
1 2 1
关于python - 如何对数据框元素进行汇总和分组?,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/33921986/