Question

我试图为数据制作子总计和总计。但有些地方我卡住了，无法取得我应得的成果。你能帮忙吗？

data.groupby(['Column4', 'Column5'])['Column1'].count()

当前输出：

            Column4        Column5       
2018-05-19  Duplicate         220
            Informative         3
2018-05-20  Actionable          5
            Duplicate         270
            Informative       859
            Non-actionable      2
2018-05-21  Actionable          8
            Duplicate         295
            Informative        17
2018-05-22  Actionable         10
            Duplicate         424
            Informative        36
2018-05-23  Actionable          8
            Duplicate         157
            Informative         3
2018-05-24  Actionable          5
            Duplicate          78
            Informative         3
2018-05-25  Actionable          3
            Duplicate          80

预期产出：

            Row Labels Actionable   Duplicate   Informative Non-actionable  Grand Total
5/19/2018       219                 3           222
5/20/2018   5   270    859          2           1136
5/21/2018   8   295    17           320
5/22/2018   10  424    36           470
5/23/2018   8   157    3            168
5/24/2018   5   78     3            86
5/25/2018   3   80     83
Grand Total 39  1523   921          2           2485

这是一个示例数据。请问之前请你看一下。我得到的错误很少。可能是我没有给出正确的数据。请检查一次。 Column1 Column2 Column3 Column4 Column5 Column6 BI Account Subject1 2:12 PM 5/19/2018重复名称1 PI Account Subject2 1:58 PM 5/19/2018可操作名称2 AI Account Subject3 5:01 PM 5/19/2018 Non-Actionable Name3 BI Account Subject4 5:57 PM 5/19/2018信息名称4 PI Account Subject5下午6:59 5/19/2018重复名称5 AI Account Subject6 8:07 PM 5/19/2018 Actionable Name1

Answer 1

您可以使用pivot从当前输出获取所需的输出，然后sum计算所需的总数。

import pandas as pd

df = df.reset_index().pivot('index', values='Column5', columns='Column4')

# Add grand total columns, summing across all other columns
df['Grand Total'] = df.sum(axis=1)
df.columns.name = None
df.index.name = None

# Add the grand total row, summing all values in a column
df.loc['Grand Total', :] = df.sum()

df现在是：

             Actionable  Duplicate  Informative  Non-actionable  Grand Total
2018-05-19          NaN      220.0          3.0             NaN        223.0
2018-05-20          5.0      270.0        859.0             2.0       1136.0
2018-05-21          8.0      295.0         17.0             NaN        320.0
2018-05-22         10.0      424.0         36.0             NaN        470.0
2018-05-23          8.0      157.0          3.0             NaN        168.0
2018-05-24          5.0       78.0          3.0             NaN         86.0
2018-05-25          3.0       80.0          NaN             NaN         83.0
Grand Total        39.0     1524.0        921.0             2.0       2486.0

Answer 2

只需使用crosstab

pd.crosstab(df['Column4'], df['Column5'], margins = True, margins_name = 'Grand Total' )

Answer 3

看看这个： https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.pivot.html

你需要转动你的桌子：

df.reset_index().pivot(index='date', columns='Column4', values='Column5')

Python中的小计和总计

3 个答案: