Release v0.1.8
reportgen is a Python library for creating and updating analysis report.
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.
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
- 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()
- 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.
- support export analysis report to html
- make the chart_type recommend more intelligence
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.