#1. Create a pandas excel writer instance and name the excel file
xlwriter = pd.ExcelWriter('Customer_Details.xlsx')
#NB: If you don't include a file path like 'C:\Users\Ron\Desktop\File_Name.xlsx'
# It will save to your default folder, that is,
#where the file you're reading from is located.
#2. Write each dataframe to a worksheet with a name
dfName.to_excel(xlwriter, sheet_name = 'Name', index = False)
dfAddress.to_excel(xlwriter, sheet_name = 'Address', index = False)
dfContact.to_excel(xlwriter, sheet_name = 'Contact', index = False)
#3. Close the instance
xlwriter.close()

# Create a Pandas Excel writer using XlsxWriter as the engine.
with pd.ExcelWriter('pandas_multiple.xlsx', engine='xlsxwriter') as writer: # Write each dataframe to a different worksheet. final_df.to_excel(writer, sheet_name='Sheet1') df_unigrams.to_excel(writer, sheet_name='Sheet2') df_bigrams.to_excel(writer, sheet_name='Sheet3')

# Write multiple DataFrames to Excel files
with pd.ExcelWriter('pandas_to_excel.xlsx') as writer: df.to_excel(writer, sheet_name='sheet1') df2.to_excel(writer, sheet_name='sheet2')
# Append to an existing Excel file
path = 'pandas_to_excel.xlsx'
with pd.ExcelWriter(path) as writer: writer.book = openpyxl.load_workbook(path) df.to_excel(writer, sheet_name='new_sheet1') df2.to_excel(writer, sheet_name='new_sheet2') 

with pd.ExcelWriter("Data 2016.xlsx") as writer: data.to_excel(writer, "Stock Prices") correlations.to_excel(writer, "Correlations") data.pct_change().mul(100).to_excel(writer, "Daily Changes")

import glob
all_data = pd.DataFrame()
path = 'C:\\Users\\Admin\\Desktop\\Notebook\\Week 38 Trip Data\\*.xlsx'
for f in glob.glob(path): df = pd.read_excel(f, sheet_name=None) cdf = pd.concat(df.values()) all_data = (all_data.append(cdf,ignore_index=True))