Need the achieve this programmatically from a dataframe:
https://docs.microsoft.com/en-us/power-bi/service-admin-troubleshoot-excel-workbook-data
To write to multiple sheets it is necessary to create an ExcelWriter object with a target file name, and specify a sheet in the file to write to. Multiple sheets may be written to by specifying unique sheet_name . With all data written to the file it is necessary to save the changes.
Usage. In Jupyter Notebook, just select the 'Excel Spreadsheet (. xlsx)' option under 'Download As' in the File menu. This should output ExcelTest.
Tasks such as data cleaning, data normalization, visualization, and statistical analysis can be performed on both Excel and Pandas.
I created a package to write properly formatted excel tables from pandas: pandas-xlsx-tables
from pandas_xlsx_tables import df_to_xlsx_table
import pandas as pd
data = [10, 20, 30, 40, 50, 60, 70, 80]
df = pd.DataFrame({'Rank': data,
'Country': data,
'Population': data,
'Strings': [f"n{n}" for n in data],
'Datetimes': [pd.Timestamp.now() for _ in range(len(data))]})
df_to_xlsx_table(df, "my_table", index=False, header_orientation="diagonal")
You can also do the reverse with xlsx_table_to_df
Here is one way to do it using XlsxWriter:
import pandas as pd
# Create a Pandas dataframe from some data.
data = [10, 20, 30, 40, 50, 60, 70, 80]
df = pd.DataFrame({'Rank': data,
'Country': data,
'Population': data,
'Data1': data,
'Data2': data})
# Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter("pandas_table.xlsx", engine='xlsxwriter')
# Convert the dataframe to an XlsxWriter Excel object. Turn off the default
# header and index and skip one row to allow us to insert a user defined
# header.
df.to_excel(writer, sheet_name='Sheet1', startrow=1, header=False, index=False)
# Get the xlsxwriter workbook and worksheet objects.
workbook = writer.book
worksheet = writer.sheets['Sheet1']
# Get the dimensions of the dataframe.
(max_row, max_col) = df.shape
# Create a list of column headers, to use in add_table().
column_settings = []
for header in df.columns:
column_settings.append({'header': header})
# Add the table.
worksheet.add_table(0, 0, max_row, max_col - 1, {'columns': column_settings})
# Make the columns wider for clarity.
worksheet.set_column(0, max_col - 1, 12)
# Close the Pandas Excel writer and output the Excel file.
writer.save()
Output:
Update: I've added a similar example to the XlsxWriter docs: Example: Pandas Excel output with a worksheet table
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