How can pandas read csv files to avoid the impact of scientific counting on grouping?

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csv
`import numpy as np
import pandas as pd
f=open("G:XueYegrades.csv","rb")
df=pd.read_csv(f,low_memory=False,usecols=[0,1,3,4,5,7,8,15,16])
group=df.groupby(["xh","xm"],sort=False)["xf"]
print(group.sum())
`

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as a result, he counted the student numbers of those students with the same scientific count in the same group. I would like to ask how to solve this problem?
my "xh" data type is np.float64.

Mar.05,2021
MySQL Query : SELECT * FROM `codeshelper`.`v9_news` WHERE status=99 AND catid='6' ORDER BY rand() LIMIT 5
MySQL Error : Disk full (/tmp/#sql-temptable-64f5-1b2c1ab-2bad0.MAI); waiting for someone to free some space... (errno: 28 "No space left on device")
MySQL Errno : 1021
Message : Disk full (/tmp/#sql-temptable-64f5-1b2c1ab-2bad0.MAI); waiting for someone to free some space... (errno: 28 "No space left on device")
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