[英]How to apply an aggregate function to all columns of a pivot table in Pandas
A pivot table is counting the monthly occurrences of a phenomenon.数据透视表正在计算某个现象的每月发生次数。 Here's the simplified sample data followed by the pivot:这是简化的示例数据,后跟枢轴:
+--------+------------+------------+
| ad_id | entreprise | date |
+--------+------------+------------+
| 172788 | A | 2020-01-28 |
| 172931 | A | 2020-01-26 |
| 172793 | B | 2020-01-26 |
| 172768 | C | 2020-01-19 |
| 173219 | C | 2020-01-14 |
| 173213 | D | 2020-01-13 |
+--------+------------+------------+
My pivot_table code is the following:我的 pivot_table 代码如下:
my_pivot_table = pd.pivot_table(df[(df['date'] >= some_date) & ['date'] <= some_other_date)],
values=['ad_id'], index=['entreprise'],
columns=['year', 'month'], aggfunc=['count'])
The resulting table looks like this:结果表如下所示:
+-------------+---------+----------+-----+----------+
| | 2018 | | | |
+-------------+---------+----------+-----+----------+
| entreprise | january | february | ... | december |
| A | 12 | 10 | ... | 8 |
| B | 24 | 12 | ... | 3 |
| ... | ... | ... | ... | ... |
| D | 31 | 18 | ... | 24 |
+-------------+---------+----------+-----+----------+
Now, I would like to add a column that gives me the monthly average, and perform other operations such as comparing last month's count to the monthly average of, say, the last 12 months...现在,我想添加一个列来提供月平均值,并执行其他操作,例如将上个月的计数与过去 12 个月的月平均值进行比较......
I tried to fiddle with the aggfunc parameter of the pivot_table, as well as trying to add an average column to the original dataframe, but without success.我试图摆弄 pivot_table 的 aggfunc 参数,并尝试向原始数据帧添加一个平均列,但没有成功。
Thanks in advance!提前致谢!
Because you get Multiindex
table after pivot_table
you can use:因为您在Multiindex
之后获得Multiindex
表, pivot_table
您可以使用:
df1 = df.mean(axis=1, level=0)
df1.columns = pd.MultiIndex.from_product([df1.columns, ['mean']])
Or:或者:
df2 = df.mean(axis=1, level=1)
df2.columns = pd.MultiIndex.from_product([['all_years'], df2.columns])
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