reportgen

Release v0.1.8

reportgen is a Python library for creating and updating analysis report.

Release History

0.1.8(2018-03-28)

• Add subpackages metrics and preprocessing which contain entropy,WOE,discretization etc..
• Add associate analysis(FP growth): frequent_itemsets and association_rules.
• Add functions :ClassifierReport,type_of_var.
• Fix the logic of package.
• Fix some bugs.

0.1.6(2017-12-06)

• Add function rpt.plot().
• Support drawing on the exist matplotlib figure and Report file
• Fix some bugs.

0.1.5(2017-11-29)

• Add function AnalysisReport, it can plot the general data to pptx files.
• Fix some bugs.

0.1.0(2017-11-18)

• Create.

Feature Support

reportgen has the following capabilities, with many more on the roadmap:

• get all the texts in the pptx file
• get all the images in the pptx file
• add one slide simply about charts/tables/images with pandas in a pptx file
• add slides simply about charts/tables/images with pandas in a pptx file

Quick Start

1. Get texts or images in a pptx file.

# import
import reportgen as rpt
# Open a pptx file
p=rpt.Report('analysis.pptx')
# We can get the texts and images simply.
result=p.get_texts()
print('\n'.join(result))
# All the images will saved in folder '.\\images\\'.
p.get_images()

2. Created a analysis report.

#
import reportgen as rpt
  import pandas as pd
  # Open a pptx file
  p=rpt.Report('template.pptx')# The parameters can be defaulted
  # add a cover
  p.add_cover(title='A analysis report powered by reportgen')
  # add a chart slide
  data=pd.DataFrame({'Jack':[90,80,100],'David':[100,70,85]},index=['Math','English','Physics'])
  p.add_slide(data={'data':data,'slide_type':'chart','type':'COLUMN_CLUSTERED'},\
  title='the scores report',summary='Our class got excellent results',footnote='This is a footnote.')
# add a table slide
  data=pd.DataFrame({'Jack':[90,80,100],'David':[100,70,85]},index=['Math','English','Physics'])
  p.add_slide(data={'data':data,'slide_type':'table'},title='the scores report',summary='Our class got excellent results',footnote='This is a footnote.')
  # add a textbox slide
  data='This a paragraph. \n'*4
  p.add_slide(data={'data':data,'slide_type':'textbox'},title='This is a textbox slide',summary='',footnote='')
  # add a picture slide
  data='.\\images\\images.png'
  p.add_slide(data={'data':data,'slide_type':'picture'},title='This is a picture slide')
p.save('analysis report.pptx')

In general, I divide a slide of analysis report into four parts: title、summary、footnote and the body data. And the body are one or more charts/textboxs/tables/pictures.

The add_slide which is the most commonly used function has the following parameters:

add_slide(data=[{'data':,'slide_type':,'type':},],title='',summary='',footnote='',layouts='auto')

For example, we can draw a chart on the left side, and insert a picture on the right.

import reportgen as rpt
import pandas as pd
p=rpt.Report()
scores=pd.DataFrame({'Jack':[90,80,100],'David':[100,70,85]},index=['Math','English','Physics'])
data=[{'data':scores,'slide_type':'chart','type':'COLUMN_CLUSTERED'},\
{'data':'.\\images2.jpg','slide_type':'picture'}]
p.add_slide(data=data)
p.save('add_slide.pptx')

As a lazy person, I also provide a solution with less scripts.

import reportgen as rpt
p=rpt.Report()
imgs=['.\\images\\'+img for img in os.listdir('.\\images\\')]
p.add_slides(data=imgs)
# more functions way
slides_data=[{'title':'ppt{}'.format(i),'data':data} for i in range(10)]
p.add.slides(slides_data)
p.save('add_slides.pptx')

Now you can get a glance at any data.

import pandas as pd
import reportgen as rpt

data=pd.read_excel('Scores.xlsx')
rpt.AnalysisReport(data,filename='Analysis Report of Scores.pptx');

The scripts will make a pptx file which analysis all the fields of the data in a visual way.

TO DO

• support export analysis report to html
• make the chart_type recommend more intelligence

Contact

If you have any question,you can email to gasongjian AT 126.com. And if you have a WeChat account,you can focus to my WeChat Official Account: gasongjian.