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export multiple python pandas dataframe to single excel file

#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:UsersRonDesktopFile_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()
Comment

write multiple df to excel pandas

# 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')
Comment

Write multiple DataFrames to Excel files

# 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')    
Comment

python export multiple dataframes to excel

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")
Comment

Multiple excel files to single df

import glob

all_data = pd.DataFrame()
path = 'C:UsersAdminDesktopNotebookWeek 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))
Comment

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