Pivot Table in Python (Pandas)

Question

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.**

Can you please provide some sample data as well as expected results? — ArchAngelPwn
– ArchAngelPwn, Commented Jun 29, 2022 at 3:45
@ArchAngelPwn: Just edited and provided sample. Appreciate your comment. It would mean so much if you could help. :) — Ashima
– Ashima, Commented Jun 29, 2022 at 3:53
@Ynjxsjmh: I think the problem was with my import data code df = pd.read_csv('df.csv', dtype=object). Once I removed dtype = object, the code worked. But I don't understand the logic. Can you explain why it worked after I removed the dtype = object? — Ashima
– Ashima, Commented Jun 29, 2022 at 4:10

Abhishek · Accepted Answer · 2022-06-29 04:03:54Z

1

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:

answered Jun 29, 2022 at 4:03

Abhishek

1,6252 gold badges15 silver badges16 bronze badges

Sign up to request clarification or add additional context in comments.

1 Comment

Ashima Over a year ago

Hi Abhishek, actually I figured out my error. Since my file had all mixed type data I imported using df = pd.read_csv('df.csv', dtype = object). Once I removed dtype=object, my code was successful. My code is same as yours. Thank you for your time. :)

Collectives™ on Stack Overflow

Pivot Table in Python (Pandas)

1 Answer 1

1 Comment

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

1 Comment

Your Answer

Sign up or log in

Post as a guest

Related