如何通过使用 pandas 在工作表中覆盖来在现有 excel 中写入 json 数据？

Question

I have some sample json data in the below format:

{"VM": {"0": "v1", "1": "v2", "2": "v3", "3": "v4"},
 "Size in TB": {"0": "112", "1": "100", "2": "123", "3": "109"},
 "state": {"0": "ON", "1": "OFF", "2": "OFF", "3": "ON"}}

I want to store this data in an existing excel file by overwriting an existing sheet. I am aware of the long approach where I'll convert this json data to an excel sheet then I can copy the new excel to the existing sheet.

import pandas as pd

json_data = pd.read_json(r'C:\Users\XYZ\data.json')
datafrme = pd.DataFrame(json_data)
datafrme.to_excel('C:/Users/XYZ/OutputExcelFileWithoutIndex.xlsx',index=False)

Now this new excel file can be pasted into the existing one.

from openpyxl import load_workbook
wb = load_workbook(r'C:\Users\XYZ\OutputExcelFileWithoutIndex.xlsx',data_only=True)
wb2 =load_workbook(r'C:\Users\XYZ\output.xlsx')
sheet1=wb["Sheet1"]
sheet2=wb2["Sheet5"]

for i in range(1,sheet1.max_row+1):
    for j in range(1,sheet1.max_column+1):
        sheet2.cell(row=i,column=j).value=sheet1.cell(row=i,column=j).value

do we have any direct approach of directly copying json data in an existing excel?

Answer 1

To write the df directly to a sheet in an existing Excel file, you could write the following:

df_json = pd.read_json(r'C:\Users\XYZ\data.json')

# `mode='a' stands for "append', `if_sheet_exists='replace'` overwrites entire sheet,
# if sheet does not yet exist, it will be created
with pd.ExcelWriter(r'C:\Users\XYZ\output.xlsx', mode='a',
                    if_sheet_exists='replace', engine='openpyxl') as writer:
    df_json.to_excel(writer, sheet_name='Sheet1', index=None)

Result:

If you dislike the standard (index, and) header formatting, shift df.columns to the first row of your df , and add header=None . Like so:

with pd.ExcelWriter(r'C:\Users\XYZ\output.xlsx', mode='a', 
                    if_sheet_exists='replace', engine='openpyxl') as writer:
    df_json.T.reset_index().T.to_excel(writer, sheet_name='Sheet2', 
                                  index=None, header=None)

Result: