Pandas 中的 Pivot 表具有两列（索引和值）

Question

I have a CSV file with obj and VS column. I need to sum VS values for each obj and have output like below

Input:

+-----+------+
| obj |  VS  |
+-----+------+
| B   | 2048 |
| A   | 1024 |
| B   |   10 |
| A   | 1024 |
| B   | 1025 |
| A   | 1026 |
| B   | 1027 |
+-----+------+

Output:

+---+------+
| A | 3074 |
+---+------+
| B | 4110 |
+---+------+

I have tried below code,As I have just two column to apply I added value column with unique value to have pivot(pivot table need Index,Column and Value).Then Value column is just to help. However out put is sum thing weird!!!

import pandas as pd 
import numpy as np 

filename='1test.csv'
df = pd.read_csv(filename, dtype='str')
df["value"]=1
pd.pivot_table(df, values="VS", index="obj", columns="value", aggfunc=np.sum)

output of my code :

+-------+----------------+
| value |       1        |
+-------+----------------+
| obj   |                |
| A     |   102410241026 |
| B     | 20481010251027 |
+-------+----------------+

Answer 1

Just consider that as you read from CSV, values are string, you need to convert them to int by df['VS']=pd.to_numeric(df['VS']) print(df.dtypes) show the type of column in df

import pandas as pd 
import numpy as np 

filename='1test.csv'
df = pd.read_csv(filename, dtype='str')
df["value"]=1
print(df.dtypes)
df['VS']=pd.to_numeric(df['VS'])
print(df.dtypes)
pd.pivot_table(df, values="VS", index="obj", columns="value", aggfunc=np.sum)