Python and Excel

Create excel charts with xlsxwriter

import xlsxwriter

# sample data
chart_data = [
    {'name': 'Lorem', 'value': 23},
    {'name': 'Ipsum', 'value': 48},
    {'name': 'Dolor', 'value': 15},
    {'name': 'Sit', 'value': 8},
    {'name': 'Amet', 'value': 32}
]

# excel file path
xls_file = 'chart.xlsx'

# the workbook
workbook = xlsxwriter.Workbook(xls_file)

# add worksheet to workbook
worksheet = workbook.add_worksheet()

row_ = 0
col_ = 0

# write headers
worksheet.write(row_, col_, 'NAME')
col_ += 1
worksheet.write(row_, col_, 'VALUE')
row_ += 1

# write sample data 
for item in chart_data:
    col_ = 0
    worksheet.write(row_, col_, item['name'])
    col_ += 1
    worksheet.write(row_, col_, item['value'])
    row_ += 1

# create pie chart
pie_chart = workbook.add_chart({'type': 'pie'})

# add series to pie chart
pie_chart.add_series({
    'name': 'Series Name',
    'categories': '=Sheet1!$A$3:$A$%s' % row_,
    'values': '=Sheet1!$B$3:$B$%s' % row_,
    'marker': {'type': 'circle'}
})
# insert pie chart
worksheet.insert_chart('D2', pie_chart)

# create column chart
column_chart = workbook.add_chart({'type': 'column'})

# add serie to column chart
column_chart.add_series({
    'name': 'Series Name',
    'categories': '=Sheet1!$A$3:$A$%s' % row_,
    'values': '=Sheet1!$B$3:$B$%s' % row_,
    'marker': {'type': 'circle'}
})
# insert column chart
worksheet.insert_chart('D20', column_chart)

workbook.close()

Result:

enter image description here

Format Excel files with xlsxwriter

import xlsxwriter

# create a new file 
workbook = xlsxwriter.Workbook('your_file.xlsx')

# add some new formats to be used by the workbook 
percent_format = workbook.add_format({'num_format': '0%'})
percent_with_decimal = workbook.add_format({'num_format': '0.0%'})
bold = workbook.add_format({'bold': True})
red_font = workbook.add_format({'font_color': 'red'})
remove_format = workbook.add_format()

# add a new sheet 
worksheet = workbook.add_worksheet() 

# set the width of column A 
worksheet.set_column('A:A', 30, )

# set column B to 20 and include the percent format we created earlier 
worksheet.set_column('B:B', 20, percent_format)

# remove formatting from the first row (change in height=None) 
worksheet.set_row('0:0', None, remove_format)

workbook.close()

OpenPyXL

OpenPyXL is a module for manipulating and creating xlsx/xlsm/xltx/xltm workbooks in memory.

Manipulating and reading an existing workbook:

import openpyxl as opx
#To change an existing wookbook we located it by referencing its path
workbook = opx.load_workbook(workbook_path)

load_workbook() contains the parameter read_only, setting this to True will load the workbook as read_only, this is helpful when reading larger xlsx files:

workbook = opx.load_workbook(workbook_path, read_only=True)

Once you have loaded the workbook into memory, you can access the individual sheets using workbook.sheets

first_sheet = workbook.worksheets[0]

If you want to specify the name of an available sheets, you can use workbook.get_sheet_names().

sheet = workbook.get_sheet_by_name('Sheet Name')

Finally, the rows of the sheet can be accessed using sheet.rows. To iterate over the rows in a sheet, use:

for row in sheet.rows:
    print row[0].value

Since each row in rows is a list of Cells, use Cell.value to get the contents of the Cell.

Creating a new Workbook in memory:

#Calling the Workbook() function creates a new book in memory
wb = opx.Workbook()

#We can then create a new sheet in the wb
ws = wb.create_sheet('Sheet Name', 0) #0 refers to the index of the sheet order in the wb

Several tab properties may be changed through openpyxl, for example the tabColor:

ws.sheet_properties.tabColor = 'FFC0CB'

To save our created workbook we finish with:

wb.save('filename.xlsx')

Put list data into a Excel's file.

import os, sys
from openpyxl import Workbook
from datetime import datetime

dt = datetime.now()
list_values = [["01/01/2016", "05:00:00", 3], \
               ["01/02/2016", "06:00:00", 4], \
               ["01/03/2016", "07:00:00", 5], \
               ["01/04/2016", "08:00:00", 6], \
               ["01/05/2016", "09:00:00", 7]]

# Create a Workbook on Excel:
wb = Workbook()
sheet = wb.active
sheet.title = 'data'

# Print the titles into Excel Workbook:
row = 1
sheet['A'+str(row)] = 'Date'
sheet['B'+str(row)] = 'Hour'
sheet['C'+str(row)] = 'Value'

# Populate with data
for item in list_values:
    row += 1
    sheet['A'+str(row)] = item[0]
    sheet['B'+str(row)] = item[1]
    sheet['C'+str(row)] = item[2]

# Save a file by date:
filename = 'data_' + dt.strftime("%Y%m%d_%I%M%S") + '.xlsx'
wb.save(filename)

# Open the file for the user:
os.chdir(sys.path[0])
os.system('start excel.exe "%s\\%s"' % (sys.path[0], filename, ))

Read the excel data using xlrd module

Python xlrd library is to extract data from Microsoft Excel (tm) spreadsheet files.

Installation:-

pip install xlrd

Or you can use setup.py file from pypi

https://pypi.python.org/pypi/xlrd

Reading an excel sheet:- Import xlrd module and open excel file using open_workbook() method.

import xlrd
book=xlrd.open_workbook('sample.xlsx')

Check number of sheets in the excel

print book.nsheets

Print the sheet names

print book.sheet_names()

Get the sheet based on index

sheet=book.sheet_by_index(1)

Read the contents of a cell

cell = sheet.cell(row,col) #where row=row number and col=column number
print cell.value #to print the cell contents

Get number of rows and number of columns in an excel sheet

num_rows=sheet.nrows
num_col=sheet.ncols

Get excel sheet by name

sheets = book.sheet_names()
cur_sheet = book.sheet_by_name(sheets[0])