{
    "info": {
        "author": "JSong",
        "author_email": "gasongjian@126.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: BSD License",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: Implementation",
            "Topic :: Software Development :: Libraries"
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        "description": "reportgen\n===========\n\nRelease v0.1.8\n\n*reportgen* is a Python library for creating and updating analysis report.\n\nRelease History\n------------------\n0.1.8(2018-03-28)\n\n- Add subpackages metrics and preprocessing which contain entropy\u9286\u4e44OE\u9286\u4e68iscretization etc..\n- Add associate analysis(FP growth): frequent_itemsets and association_rules.\n- Add functions :ClassifierReport,type_of_var.\n- Fix the logic of package.\n- Fix some bugs.\n\n0.1.6(2017-12-06)\n\n- Add function rpt.plot().\n- Support drawing on the exist matplotlib figure and Report file\n- Fix some bugs.\n\n0.1.5(2017-11-29)\n\n- Add function AnalysisReport, it can plot the general data to pptx files.\n- Fix some bugs.\n\n0.1.0(2017-11-18)\n\n- Create.\n\n\nFeature Support\n------------------\n\n**reportgen** has the following capabilities, with many more on the roadmap:\n\n- get all the texts in the pptx file\n- get all the images in the pptx file\n- add one slide simply about charts/tables/images with pandas in a pptx file\n- add slides simply about charts/tables/images with pandas in a pptx file\n\nQuick Start\n------------\n\n1. Get texts or images in a pptx file.\n\n::\n\n  # import\n  import reportgen as rpt\n  # Open a pptx file\n  p=rpt.Report('analysis.pptx')\n  # We can get the texts and images simply.\n  result=p.get_texts()\n  print('\\n'.join(result))\n  # All the images will saved in folder '.\\\\images\\\\'.\n  p.get_images()\n\n2. Created a analysis report.\n\n::\n\n  #\n  import reportgen as rpt\n\timport pandas as pd\n\t# Open a pptx file\n\tp=rpt.Report('template.pptx')# The parameters can be defaulted\n\t# add a cover\n\tp.add_cover(title='A analysis report powered by reportgen')\n\t# add a chart slide\n\tdata=pd.DataFrame({'Jack':[90,80,100],'David':[100,70,85]},index=['Math','English','Physics'])\n\tp.add_slide(data={'data':data,'slide_type':'chart','type':'COLUMN_CLUSTERED'},\\\n\ttitle='the scores report',summary='Our class got excellent results',footnote='This is a footnote.')\n  # add a table slide\n\tdata=pd.DataFrame({'Jack':[90,80,100],'David':[100,70,85]},index=['Math','English','Physics'])\n\tp.add_slide(data={'data':data,'slide_type':'table'},title='the scores report',summary='Our class got excellent results',footnote='This is a footnote.')\n\t# add a textbox slide\n\tdata='This a paragraph. \\n'*4\n\tp.add_slide(data={'data':data,'slide_type':'textbox'},title='This is a textbox slide',summary='',footnote='')\n\t# add a picture slide\n\tdata='.\\\\images\\\\images.png'\n\tp.add_slide(data={'data':data,'slide_type':'picture'},title='This is a picture slide')\n  p.save('analysis report.pptx')\n\n\n\n\nIn general, I divide a slide of analysis report into four parts: title\u9286\u4e7bummary\u9286\u4e6bootnote and the body data. And the body are one or more charts/textboxs/tables/pictures.\n\nThe *add_slide* which is the most commonly used function  has the following parameters:\n\n::\n\n  add_slide(data=[{'data':,'slide_type':,'type':},],title='',summary='',footnote='',layouts='auto')\n\nFor example, we can draw a chart on the left side, and insert a picture on the right.\n\n::\n\n  import reportgen as rpt\n  import pandas as pd\n  p=rpt.Report()\n  scores=pd.DataFrame({'Jack':[90,80,100],'David':[100,70,85]},index=['Math','English','Physics'])\n  data=[{'data':scores,'slide_type':'chart','type':'COLUMN_CLUSTERED'},\\\n  {'data':'.\\\\images2.jpg','slide_type':'picture'}]\n  p.add_slide(data=data)\n  p.save('add_slide.pptx')\n\nAs a lazy person, I also provide a solution with less scripts.\n\n::\n\n  import reportgen as rpt\n  p=rpt.Report()\n  imgs=['.\\\\images\\\\'+img for img in os.listdir('.\\\\images\\\\')]\n  p.add_slides(data=imgs)\n  # more functions way\n  slides_data=[{'title':'ppt{}'.format(i),'data':data} for i in range(10)]\n  p.add.slides(slides_data)\n  p.save('add_slides.pptx')\n\n\nNow you can get a glance at any data.\n\n::\n\n  import pandas as pd\n  import reportgen as rpt\n\n  data=pd.read_excel('Scores.xlsx')\n  rpt.AnalysisReport(data,filename='Analysis Report of Scores.pptx');\n\nThe scripts will make a pptx file which analysis all the fields of the data in a visual way.\n\nTO DO\n-------\n\n- support export analysis report to html\n- make the chart_type recommend more intelligence\n\n\nContact\n--------\n\nIf 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.\n\n\n",
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