df.to_excel(r'C:\Users\Ron\Desktop\File_Name.xlsx', index = False)
#if you omit the file path (must also omit 'r') and
#enter only file_name.xlsx, it will save to your default file location,
# that is, where the file you're reading from is located.# Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter('LTD Report Data.xlsx', engine='xlsxwriter')
# Write each dataframe to a different worksheet.
seg_2019.to_excel(writer, sheet_name='Seg 2019', index = False)
seg_2020.to_excel(writer, sheet_name='Seg 2020', index = False)
seg_2021.to_excel(writer, sheet_name='Seg 2021', index = False)
seg_2022.to_excel(writer, sheet_name='Seg 2022', index = False)
# Close the Pandas Excel writer and output the Excel file.
writer.save()import pandas as pd
import numpy as np
path = r"C:\Users\fedel\Desktop\excelData\PhD_data.xlsx"
x1 = np.random.randn(100, 2)
df1 = pd.DataFrame(x1)
x2 = np.random.randn(100, 2)
df2 = pd.DataFrame(x2)
writer = pd.ExcelWriter(path, engine = 'xlsxwriter')
df1.to_excel(writer, sheet_name = 'x1')
df2.to_excel(writer, sheet_name = 'x2')
writer.save()
writer.close()