python的枢轴表（熊猫）

发布于 2025-02-11 11:22:47 字数 1854 浏览 2 评论 0原文

我是Python（使用Pandas）的新手。请帮助。

我的数据框中有两个列 - 权重转换（float）和sales_units（int）。 我只想按（sum）通过wigath_conversion进行sales_units。

示例数据

weight_conversion   sales_units
0.1                   1
0.1                   2
50                    100
50                    200
96.1                  20
314.4                  2
500                   100
500                   200

我尝试了两种方法：

by in pandas：complat by in pandas：

df.groupby（['stoge_conversion']）['sales_unit']。sum（）

df.groupby（[[ 'df.pivot_table（index ='stroge_conversion'，values ='sales_unit'， aggfunc ='sum'）

必需的输出：我需要一个简单的枢轴表，其中我的行作为weight_conversion以及销售单元的总和。

我在python pandas中获得的输出如下（很奇怪）： weight_conversion

0       3300000000000000000000000000034000000000000000...
0.1     0000100001000000000000001000000020050000000000...
0.2     0000000000000000000000000000001000000001100000...
0.3                           000000000000000000000300000
0.4     0000000000100000000000000000000000000000000001...
                            ...                        
90                                        000000000102009
92      0000200011000000000000010001000000000000000020...
92.1                            0000001000000000000000003
96      2000000000000000000000000000000000001100000000...
96.1    0000000000000000000000000000000000000000000000...

名称：sales_unit，长度：96，dtype：对象

样本输出

weight_conversion   sales_units
0.1                   3
50                    300
96.1                  20
314.4                  2
500                   300

请帮助。**

原文

I'm very new to python (using pandas). Kindly help.

There are two columns in my dataframe - weight conversion (float) and sales_units (int). I simply want to group by (sum) the sales_units by weight_conversion.

Sample Data

weight_conversion   sales_units
0.1                   1
0.1                   2
50                    100
50                    200
96.1                  20
314.4                  2
500                   100
500                   200

I have tried two ways:

GROUP BY IN PANDAS :

df.groupby(['weight_conversion'])['Sales_Unit'].sum()

PIVOT TABLE IN PANDAS:
df.pivot_table(index = 'weight_conversion', values='Sales_Unit',
aggfunc ='sum')

Required Output: I need a simple pivot table where I have rows as weight_conversion along with sum of sales units.

The output I'm getting in Python Pandas is as follows (so weird):
weight_conversion

0       3300000000000000000000000000034000000000000000...
0.1     0000100001000000000000001000000020050000000000...
0.2     0000000000000000000000000000001000000001100000...
0.3                           000000000000000000000300000
0.4     0000000000100000000000000000000000000000000001...
                            ...                        
90                                        000000000102009
92      0000200011000000000000010001000000000000000020...
92.1                            0000001000000000000000003
96      2000000000000000000000000000000000001100000000...
96.1    0000000000000000000000000000000000000000000000...

Name: Sales_Unit, Length: 96, dtype: object

sample output

weight_conversion   sales_units
0.1                   3
50                    300
96.1                  20
314.4                  2
500                   300

Please help.**

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另类 2025-02-18 11:22:47

我认为您不需要枢轴表才能获得所提供的样本输出。以下是您提到的所需输出的工作

df = pd.DataFrame({"weight_conversion":[0.1,0.1,50,50,96.1,314.4,500,500],
              "sales_units":[1,2,100,200,20,2,100,200]})
              
df.groupby('weight_conversion').agg({'sales_units':'sum'}).reset_index()

Output:

I dont think you need PIVOT table for the sample output you have given. Below worked as for the required output you mentioned

df = pd.DataFrame({"weight_conversion":[0.1,0.1,50,50,96.1,314.4,500,500],
              "sales_units":[1,2,100,200,20,2,100,200]})
              
df.groupby('weight_conversion').agg({'sales_units':'sum'}).reset_index()

Output:

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