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How to Specify Data Format in Excel with Python

by Luca LiuJanuary 10th, 2024

Too Long; Didn't Read

This tutorial showcases the power of Python's xlsxwriter in saving and stylizing Excel sheets. From handling multiple data frames to formatting data types accurately, this step-by-step guide empowers you to master Excel with Python, enhancing your data management capabilities.

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featured image - How to Specify Data Format in Excel with Python

In this article, we will address the following:

How to use xlsxwriter to save Excel
How to save multiple data frames to worksheets using Python
How do use Python to stylize the Excel formatting
How to ensure that specific data types such as datetime, integer, string, and floating data are saved accurately when using Python and xlsxwriter to save a data frame to Excel

Question Description:

Imagine that you have the following 2 data frames and you want to save them into one Excel file with different sheets and stylize the Excel formatting.

Solution: Save Excel through xlsxwriter

1. Import xlsxwriter package and create Excel file

Use Workbook to create a new Excel file.

# import package
import xlsxwriter
# create excel file
workbook = xlsxwriter.Workbook("new_excel.xlsx")

2. Create two sheets

Use add_worksheet to create a sheet because we have two data frames that need to be saved, we have to create two sheets.

worksheet1 = workbook.add_worksheet('df1_sheet')
worksheet2 = workbook.add_worksheet('df2_sheet')

3. Set header format and save the header

First, we set the header format and use .write_row to save our header.

.write_row has four arguments, they are: worksheet.write_row(row, col, data, cell_format).

header_format = workbook.add_format({
 'valign': 'top',
 'fg_color': '#002060',
 'border': 1,
 'font_color': 'white'})
worksheet1.write_row(0, 0, df1.columns, header_format)
worksheet2.write_row(0, 0, df2.columns, header_format)

4. Create some format

format.set_num_format(): This method is used to define the numerical format of a number in Excel. It controls whether a number is displayed as an integer, a floating point number, a date, a currency value, or some other user-defined format.

The numerical format of a cell can be specified by using a format string or an index to one of Excel’s built-in formats, for more information you can check

For example: 14 represents m/dd/yyyy, so format.set_num_format(14) = format.set_num_format('m/dd/yyyy')

# set datetime format "m/d/yy"
format_datetime = workbook.add_format({'border': 1})
format_datetime.set_num_format(14) # based on above table, 14 means "m/d/yy"
format_datetime.set_font_size(12) # set font size

# set General format
format_general = workbook.add_format({'border': 1})
format_general.set_num_format(0) # 0 means general
format_general.set_font_size(12)

# set integer format "0"
format_integer = workbook.add_format({'border': 1})
format_integer.set_num_format(1)
format_integer.set_font_size(12)

# set float format "0.00"
format_float = workbook.add_format({'border':1})
format_float.set_num_format(2)
format_float.set_font_size(12)

# set integer format with thousands separators "#,##0"
format_integer_separator = workbook.add_format({'border': 1})
format_integer_separator.set_num_format(3)
format_integer_separator.set_font_size(12)

# set percent format "0.00%"
format_percent = workbook.add_format({'border':1})
format_percent.set_num_format(10)
format_percent.set_font_size(12)

5. Save the data into Excel with cell_format

The zero index row already saved our header, so we start from one index row(set the first argument to 1)

# .write_column(row, column, data, cell_format)

worksheet1.write_column(1, 0, df1.iloc[:, 0], format_datetime)
worksheet1.write_column(1, 1, df1.iloc[:, 1], format_integer)
worksheet1.write_column(1, 2, df1.iloc[:, 2], format_integer_separator)
worksheet1.write_column(1, 3, df1.iloc[:, 3], format_general)
worksheet1.write_column(1, 4, df1.iloc[:, 4], format_float)
worksheet1.write_column(1, 5, df1.iloc[:, 5], format_percent)
worksheet2.write_column(1, 0, df2.iloc[:, 0], format_datetime)
worksheet2.write_column(1, 1, df2.iloc[:, 1], format_integer)
worksheet2.write_column(1, 2, df2.iloc[:, 2], format_integer_separator)
worksheet2.write_column(1, 3, df2.iloc[:, 3], format_general)
worksheet2.write_column(1, 4, df2.iloc[:, 4], format_float)
worksheet2.write_column(1, 5, df2.iloc[:, 5], format_percent)

6. Set column width

For a better display of the data, we can also use .set_column to set the column width.

worksheet1.set_column('A:A', 15)
worksheet1.set_column('B:B', 15)
worksheet1.set_column('C:C', 15)
worksheet1.set_column('D:D', 15)
worksheet1.set_column('E:E', 15)
worksheet1.set_column('F:F', 15)
worksheet2.set_column('A:A', 15)
worksheet2.set_column('B:B', 15)
worksheet2.set_column('C:C', 15)
worksheet2.set_column('D:D', 15)
worksheet2.set_column('E:E', 15)
worksheet2.set_column('F:F', 15)

7. Finish

workbook.close()

Below is the full Python code that utilizes the xlsxwriter package to save two data frames into an Excel file with different sheets and stylized formatting. The code begins by importing the necessary pandas and xlsxwriter packages. Then, it defines the two data frames, df1 and df2. It proceeds to create a new Excel file and two sheets using xlsxwriter.Workbook and add_worksheet functions, respectively.

Following this, the code sets the header format, defines various cell formats for different data types, and writes the data into the Excel file with the specified cell formats. Finally, it sets the column widths, closes the workbook, and thus completes the process of saving the data frames into an Excel file.

# generate two dataframes 
import pandas as pd

df1 = pd.DataFrame(
    {'Date': ['2022/12/1', '2022/12/1', '2022/12/1', '2022/12/1'], 'Int': [116382, 227393, 3274984, 438164],
     'Int_with_seperator': [1845132, 298145, 336278, 443816], 'String': ['Tom', 'Grace', 'Luca', 'Tessa'],
     'Float': [98.45, 65.24, 30, 80.88], 'Percent': [0.8878, 0.9523, 0.4545, 0.9921]})
df2 = pd.DataFrame({'Date': ['2022/11/1', '2022/11/1', '2022/11/1', '2022/11/1'], 'Int': [233211, 24321, 35345, 23223],
                    'Int_with_seperator': [925478, 23484, 123249, 2345675],
                    'String': ['Apple', 'Huawei', 'Xiaomi', 'Oppo'], 'Float': [98.45, 65.24, 30, 80.88],
                    'Percent': [0.4234, 0.9434, 0.6512, 0.6133]})
print(df1)
print(df2)

# import package
import xlsxwriter
# create excel file
workbook = xlsxwriter.Workbook("new_excel.xlsx")

# create two sheets
worksheet1 = workbook.add_worksheet('df1_sheet')
worksheet2 = workbook.add_worksheet('df2_sheet')

# set header format and save the header
header_format = workbook.add_format({
 'valign': 'top',
 'fg_color': '#002060',
 'border': 1,
 'font_color': 'white'})
worksheet1.write_row(0, 0, df1.columns, header_format)
worksheet2.write_row(0, 0, df2.columns, header_format)

# set datetime format "m/d/yy"
format_datetime = workbook.add_format({'border': 1})
format_datetime.set_num_format(14) # based on above table, 14 means "m/d/yy"
format_datetime.set_font_size(12) # set font size

# set General format
format_general = workbook.add_format({'border': 1})
format_general.set_num_format(0) # 0 means general
format_general.set_font_size(12)

# set integer format "0"
format_integer = workbook.add_format({'border': 1})
format_integer.set_num_format(1)
format_integer.set_font_size(12)

# set float format "0.00"
format_float = workbook.add_format({'border':1})
format_float.set_num_format(2)
format_float.set_font_size(12)

# set integer format with thousands separators "#,##0"
format_integer_separator = workbook.add_format({'border': 1})
format_integer_separator.set_num_format(3)
format_integer_separator.set_font_size(12)

# set percent format "0.00%"
format_percent = workbook.add_format({'border':1})
format_percent.set_num_format(10)
format_percent.set_font_size(12)

worksheet1.write_column(1, 0, df1.iloc[:, 0], format_datetime)
worksheet1.write_column(1, 1, df1.iloc[:, 1], format_integer)
worksheet1.write_column(1, 2, df1.iloc[:, 2], format_integer_separator)
worksheet1.write_column(1, 3, df1.iloc[:, 3], format_general)
worksheet1.write_column(1, 4, df1.iloc[:, 4], format_float)
worksheet1.write_column(1, 5, df1.iloc[:, 5], format_percent)
worksheet2.write_column(1, 0, df2.iloc[:, 0], format_datetime)
worksheet2.write_column(1, 1, df2.iloc[:, 1], format_integer)
worksheet2.write_column(1, 2, df2.iloc[:, 2], format_integer_separator)
worksheet2.write_column(1, 3, df2.iloc[:, 3], format_general)
worksheet2.write_column(1, 4, df2.iloc[:, 4], format_float)
worksheet2.write_column(1, 5, df2.iloc[:, 5], format_percent)

worksheet1.set_column('A:A', 15)
worksheet1.set_column('B:B', 15)
worksheet1.set_column('C:C', 15)
worksheet1.set_column('D:D', 15)
worksheet1.set_column('E:E', 15)
worksheet1.set_column('F:F', 15)
worksheet2.set_column('A:A', 15)
worksheet2.set_column('B:B', 15)
worksheet2.set_column('C:C', 15)
worksheet2.set_column('D:D', 15)
worksheet2.set_column('E:E', 15)
worksheet2.set_column('F:F', 15)

workbook.close()

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