来源之前问：
Pandas: Iterate through a list of DataFrames and export each to excel sheets
Splitting dataframe into multiple dataframes的
我设法做到了这一切：

# sort the dataframe
df.sort(columns=['name'], inplace=True)
# set the index to be this and don't drop
df.set_index(keys=['name'], drop=False,inplace=True)
# get a list of names
names=df['name'].unique().tolist()
# now we can perform a lookup on a 'view' of the dataframe
joe = df.loc[df.name=='joe']
# now you can query all 'joes'

字符串
我已经设法使这个工作-joe = df.loc[df.name=='joe']和它给出了确切的结果，我正在寻找的。
作为解决方案，使其工作的大量数据，我发现这个潜在的解决方案。

writer = pandas.ExcelWriter("MyData.xlsx", engine='xlsxwriter')
List = [Data , ByBrand]
for i in List:
        i.to_excel(writer, sheet_name= i)
writer.save()

型
目前我有：

teacher_names = ['Teacher A', 'Teacher B', 'Teacher C']

型
DF =

ID   Teacher_name      Student_name
Teacher_name                                                         
Teacher A     1.0  Teacher A         Student 1 
Teacher A     NaN  Teacher A         Student 2  
Teacher B     0.0  Teacher B         Student 3 
Teacher C     2.0  Teacher C         Student 4

型
如果我使用-test = df.loc[df.Teacher_name=='Teacher A']-将收到准确的结果。

**问题：**如何优化，它会自动保存“测试”结果到（为每个教师单独的）excel文件（.to_excel(writer, sheet_name=Teacher_name）与教师的名字，并会做它为所有现有的数据库中的教师？