之前使用的来源:
Pandas: Iterate through a list of DataFrames and export each to excel sheets
Splitting dataframe into multiple dataframes
我设法完成了所有这些:
# 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'
我已经成功完成了这项工作 - joe = df.loc[df.name=='joe']
并且它给出了我所寻找的确切结果。
作为使其适用于大量数据的解决方案,我发现了这种潜在的解决方案。
writer = pandas.ExcelWriter("MyData.xlsx", engine='xlsxwriter')
List = [Data , ByBrand]
for i in List:
i.to_excel(writer, sheet_name= i)
writer.save()
目前我有:
teacher_names = ['Teacher A', 'Teacher B', 'Teacher C']
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
如果我使用 - test = df.loc[df.Teacher_name=='Teacher A']
- 将收到确切的结果。
问题:如何优化它会自动将“测试”结果保存到(对于每个教师单独)excel文件(.to_excel(writer, sheet_name=Teacher_name
)与教师姓名,并将为所有现有的数据库老师?
答案 0 :(得分:0)
这对你有用。你几乎就在那里,你只需要迭代names
列表并每次都过滤你的数据帧。
names = df['name'].unique().tolist()
writer = pandas.ExcelWriter("MyData.xlsx", engine='xlsxwriter')
for myname in names:
mydf = df.loc[df.name==myname]
mydf.to_excel(writer, sheetname=myname)
writer.save()
答案 1 :(得分:0)
@jpp,将文本“ sheetname”替换为“ sheet_name”。同样,一旦将“名称”变量转换为列表,在运行for循环以基于唯一名称值创建多个工作表时,我将收到以下错误:
InvalidWorksheetName: Invalid Excel character '[]:*?/\' in sheetname '['.
基于列值(通过函数)创建多个工作表(在单个excel文件中)的替代方法:
def writesheet(g):
a=g['name'].tolist()[0]
g.to_excel(writer,sheet_name = str(a),index=False)
df.groupby('name').apply(writesheet)
writer.save()