Pandas - 按列值将数据框拆分为多个 Excel 工作簿

Question

I'm new to pandas. I have a large excel file, what I'm trying to do is split the data frame after manipulation into multiple excel workbooks. There is more or less 400 vendors and I would like each To have their own named workbook.

Example. SallyCreative.xlsx, JohnWorks.xlsx, AlexGraphics.xlsx

Answer 1

This is my approach to splitting dataframe into multiple excel workbooks by column values.

import pandas as pd
    
data = pd.read_excel('anyexcelfile.xlsx', engine='openpyxl') # creates a dataframe called 'data'; pick any spreadsheet you can add paths to 'x:/folder/subfolder/anyexcelfile.xlsx' to be explict. 

grouped = data.groupby("Column Header Name") # change "Column Header Name" to the name of the column needed to categorise or group the rows in the dataframe, 

keys = grouped.groups.keys() #create a dictionary list of the each group unique varibles in the specifed column of the dataframe.   

print(keys) #a cheeky debug to check it's working

for key in keys: #looping through each key 
        splitdf = grouped.get_group(key) # creating a temporary dataframe with only the values of the current key. 
        splitdf.to_excel(str(key)+".xlsx", engine='xlsxwriter') #write the temporary dataframe called 'splitdf' to an excel file named after the key. At the end of the loop the temporary dataframe 'splitdf' is overwritten for use with the next key. 

Answer 2

Try the below code, I hope it will help and provide you the required solution.

Consider I have data like this.

    displayName self    created id  field   fromString
0          A    A   2018-12-18  1   status  Backlog
1          B    B   2018-12-18  2   status  Funnel

Now i want to create different excel display name as A.xlsx and B.xlsx. We do so shown below:

import pandas as pd
data_df = pd.read_excel('./data_1.xlsx')
grouped_df = data_df.groupby('displayName')

for data in grouped_df.displayName:
    grouped_df.get_group(data[0]).to_excel(data[0]+".xlsx")

This will generate excels for you as per the number of display name in this case. But you can modify solution according to your need. Hope this would help.

As asked in the comment by @Kpittman

We can save in any directory by giving path to that directory.

import pandas as pd
data_df = pd.read_excel('./data_1.xlsx')
grouped_df = data_df.groupby('displayName')

for data in grouped_df.displayName:
    grouped_df.get_group(data[0]).to_excel("./IO/Files/"+data[0]+".xlsx")

So instead of this path ./IO/Files/ you can provide your custom path.

Hope it will help