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Python | Working with Pandas and XlsxWriter | Set – 3

Last Updated : 28 Dec, 2018
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Prerequisite: : Python working with pandas and xlsxwriter | set-1

Python Pandas is a data analysis library. It can read, filter and re-arrange small and large datasets and output them in a range of formats including Excel.

Pandas writes Excel files using the XlsxWriter modules.

XlsxWriter is a Python module for writing files in the XLSX file format. It can be used to write text, numbers, and formulas to multiple worksheets. Also, it supports features such as formatting, images, charts, page setup, auto filters, conditional formatting and many others.

Code #1 : Plot a Column chart using Pandas and XlsxWriter.




# import pandas library as pd
import pandas as pd
  
# Create a Pandas dataframe from some data.
dataframe = pd.DataFrame({
                    'Subject': ["Math", "Physics", "Computer",
                                "Hindi", "English", "chemistry"],
                   'Mid Exam Score' :  [90, 78, 60, 80, 60, 90],
                   'End Exam Score' : [45, 39, 30, 40, 30, 60] })
  
# Create a Pandas Excel writer 
# object using XlsxWriter as the engine.
writer_object = pd.ExcelWriter('pandas_column_chart.xlsx',
                                     engine ='xlsxwriter')
  
# Write a dataframe to the worksheet.
dataframe.to_excel(writer_object, sheet_name ='Sheet1')
  
# Create xlsxwriter workbook object .
workbook_object = writer_object.book
  
# Create xlsxwriter worksheet object
worksheet_object = writer_object.sheets['Sheet1']
  
# set width of the B and C column
worksheet_object.set_column('B:C', 20)
  
# Create a chart object that can be added  
# to a worksheet using add_chart() method.  
    
# here we create a column chart object .
chart_object = workbook_object.add_chart({'type': 'column'})
  
# Add a data series to a chart  
# using add_series method.
  
# Configure the first series.  
# syntax to define ranges is : 
# [sheetname, first_row, first_col, last_row, last_col].
chart_object.add_series({
    'name':       ['Sheet1', 0, 2],  
    'categories': ['Sheet1', 1, 3, 6, 3],  
    'values':     ['Sheet1', 1, 2, 6, 2],  
    })
  
# Configure a second series.
chart_object.add_series({
    'name':       ['Sheet1', 0, 1],  
    'categories': ['Sheet1', 1, 3, 6, 3],  
    'values':     ['Sheet1', 1, 1, 6, 1],  
    })
  
# Add a chart title.
chart_object.set_title({'name': 'Exam Score Distribution'})
  
# Add x-axis label 
chart_object.set_x_axis({'name': 'Subjects'}) 
    
# Add y-axis label 
chart_object.set_y_axis({'name': 'Marks'})
  
# add chart to the worksheet with given
# offset values at the top-left corner of
# a chart is anchored to cell E2
worksheet_object.insert_chart('E2', chart_object, 
                {'x_offset': 20, 'y_offset': 5})
  
# Close the Pandas Excel writer 
# object and output the Excel file. 
writer_object.save()


Output :
Output-1
 
Code #2 : Plot a Line chart using Pandas and XlsxWriter.




# import pandas library as pd
import pandas as pd
  
# Create a Pandas dataframe from some data.
dataframe = pd.DataFrame({
                    'Subject': ["Math", "Physics", "Computer"
                                "Hindi", "English", "chemistry"],
                   'Mid Exam Score' :  [95, 78, 80, 80, 60, 95],
                   'End Exam Score' : [90, 67, 78, 70, 63, 90]
                    })
  
# Create a Pandas Excel writer 
# object using XlsxWriter as the engine.
writer_object = pd.ExcelWriter('pandas_line_chart.xlsx'
                                   engine ='xlsxwriter')
  
# Write a dataframe to the worksheet.
dataframe.to_excel(writer_object, sheet_name ='Sheet1')
  
# Create xlsxwriter workbook object .
workbook_object = writer_object.book
  
# Create xlsxwriter worksheet object
worksheet_object = writer_object.sheets['Sheet1']
  
# set width of the B and C column
worksheet_object.set_column('B:C', 20)
  
  
# Create a chart object that can be added  
# to a worksheet using add_chart() method.  
    
# here we create a line chart object .
chart_object = workbook_object.add_chart({'type': 'line'})
  
# Add a data series to a chart  
# using add_series method.
  
# Configure the first series.  
# syntax to define ranges is : 
# [sheetname, first_row, first_col, last_row, last_col].
chart_object.add_series({
    'name':       ['Sheet1', 0, 2],  
    'categories': ['Sheet1', 1, 3, 6, 3],  
    'values':     ['Sheet1', 1, 2, 6, 2],  
    })
  
# Configure a second series.
chart_object.add_series({
    'name':       ['Sheet1', 0, 1],  
    'categories': ['Sheet1', 1, 3, 6, 3],  
    'values':     ['Sheet1', 1, 1, 6, 1],  
    })
  
# Add a chart title.
chart_object.set_title({'name': 'Exam Score Distribution'})
  
# Add x-axis label 
chart_object.set_x_axis({'name': 'Subjects'}) 
    
# Add y-axis label 
chart_object.set_y_axis({'name': 'Marks'})
  
# add chart to the worksheet with given
# offset values at the top-left corner of
# a chart is anchored to cell E2
worksheet_object.insert_chart('E2', chart_object, 
                 {'x_offset': 20, 'y_offset': 5})
  
# Close the Pandas Excel writer 
# object and output the Excel file. 
writer_object.save()


Output :
Output-2
 
Code #3 : Plot a Scatter chart using Pandas and XlsxWriter.




# import pandas library as pd
import pandas as pd
  
# Create a Pandas dataframe from some data.
dataframe = pd.DataFrame({
                    'Subject': ["Math", "Physics", "Computer",
                             "Hindi", "English", "chemistry"],
                   'Mid Exam Score' :  [70, 80, 90, 40, 66, 98],
                   'End Exam Score' : [90, 60, 50, 80, 78, 96]
                    })
  
# Create a Pandas Excel writer 
# object using XlsxWriter as the engine.
writer_object = pd.ExcelWriter('pandas_Scatter_chart.xlsx',
                                      engine ='xlsxwriter')
  
# Write a dataframe to the worksheet.
dataframe.to_excel(writer_object, sheet_name ='Sheet1')
  
# Create xlsxwriter workbook object .
workbook_object = writer_object.book
  
# Create xlsxwriter worksheet object
worksheet_object = writer_object.sheets['Sheet1']
  
# set width of the B and C column
worksheet_object.set_column('B:C', 20)
  
  
# Create a chart object that can be added  
# to a worksheet using add_chart() method.  
    
# here we create a scatter chart object .
chart_object = workbook_object.add_chart({'type': 'scatter'})
  
# Add a data series to a chart  
# using add_series method.
  
# Configure the first series.  
# syntax to define ranges is : 
# [sheetname, first_row, first_col, last_row, last_col].
chart_object.add_series({
    'name':       ['Sheet1', 0, 2],  
    'categories': ['Sheet1', 1, 3, 6, 3],  
    'values':     ['Sheet1', 1, 2, 6, 2],  
    })
  
# Configure a second series.
chart_object.add_series({
    'name':       ['Sheet1', 0, 1],  
    'categories': ['Sheet1', 1, 3, 6, 3],  
    'values':     ['Sheet1', 1, 1, 6, 1],  
    })
  
# Add a chart title.
chart_object.set_title({'name': 'Exam Score Distribution'})
  
# Add x-axis label 
chart_object.set_x_axis({'name': 'Subjects'}) 
    
# Add y-axis label 
chart_object.set_y_axis({'name': 'Marks'})
  
# add chart to the worksheet with given
# offset values at the top-left corner of
# a chart is anchored to cell E2
worksheet_object.insert_chart('E2', chart_object, 
                {'x_offset': 20, 'y_offset': 5})
  
# Close the Pandas Excel writer 
# object and output the Excel file. 
writer_object.save()


Output :
Output-3



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