xlsxwriter formatting of dynamic header ranges

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I am working on a pandas dataframe with a varying number of columns. I want to parse it to Excel using xlsxWriter and create a worksheet table. Due to the varying number of columns I created a list comprehension for the column names when creating the table. (Here I just created a sample dataframe so dont get confused)

Can I somehow add additional optional parameters in that list comprehension to adjust the format of each header in the table? For instance, indent each header by 2 from the left? Or if possible add different formats to each column depending on the name of the header.

Below is the code I have so far:

writer = pd.ExcelWriter('pandas_table.xlsx', engine='xlsxwriter')

data = [
    ['Apples', 10000, 5000, 8000, 6000, 8000],
    ['Pears',   2000, 3000, 4000, 5000, 8000],
    ['Bananas', 6000, 6000, 6500, 600, 80000],
    ['Oranges',  500,  300,  200,  700, 8000],
]

#transform the list of values into a dataframe
df = pd.DataFrame(data = data, columns = ['Product', 'Quarter 1', 'Quarter 2', 'Quarter 3', 'Quarter 4', 'wtf' ])

#assign the dataframe to the worksheet Sheet1
df.to_excel(writer, sheet_name='Sheet1', startrow=1, header=False, index=False)

workbook = writer.book
worksheet = writer.sheets['Sheet1']

#define the length of the dataframe for the table format
(max_row, max_col) = df.shape
#list comprehension for the optional columns parameter in add_table
col_settings = [{'header': column} for column in df.columns]     

worksheet.add_table(0, 0, max_row, max_col - 1, {'columns' : col_settings})

To format single columns I did this little workaround but maybe you know also a smoother way to do that.

for i, col in enumerate(df.columns):
    if col == 'Quarter 2':
        worksheet.set_column(i, i, 18, currency_format)
    else:
        worksheet.set_column(i, i, 18)
pandas.excelwriter xlsxwriter python
1 Answers

For anything more complex than setting the column header names it is probably better to use a for loop instead of a list comprehension. Something like:

currency_format = workbook.add_format({'num_format': '$#,##0'})
col_settings = []

for column in df.columns:
    options = {'header': column}

    if column == 'Quarter 2':
        options['format'] = currency_format

    col_settings.append(options)

However, this won't actually format the column data since that has already been written by pandas. In order to get the data formatting to work you would also need to add the data to add_table():

worksheet.add_table(0, 0, max_row, max_col - 1, {'data': data, 'columns' : col_settings})

However, if you are doing that then there probably isn't a lot of value in using Panda's to_excel(). So if your workaround works I'd suggest to continue using it.

user_102380
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