# 1. 报告的初始化 region_data = RegionData() report = Report(title=report_title,author=report_author) for i in range(len(vars)): var = vars[i] restvar = list(vars) del restvar[i] # 生成章节 report.createSection(var) period = region_data.databases['citystatiscs'].period(var) for year in period: # 生成分支章节 report.createSubSection(year) mdata = region_data.query(region=['t'],year=[year],variable=[var]) mdata = mdata['data'] invars = mdata.columns[1:] cse = CrossSectionRegionDataExplorer(mdata) tdata = cse.describe().applymap(lambda x:'{0:.2f}'.format(x)) tdata = dataframe2list(tdata) print(var,year) report.addTable(tdata['data'],tdata['nrow'],tdata['ncol']) report.flush() report.generate_pdf(save_file)
var = [var] for v in var: if not (self._data[v]>0).all(): return False return True # 储存图像 def _save(self,savepath='E:/Report/'): x = str(int(datetime.now().timestamp()*1000)) filename = savepath + 'graph/' + x + '.pdf' plt.savefig(filename) if __name__ == '__main__': rdata = RegionData() mdata = rdata.query(region=['t'],year=[2010],variable=[u'地区生产总值',u'年末总人口'],scale=u'全市') mdata = mdata['data'] csdexplorer = CrossSectionRegionDataExplorer(mdata) #dframe = csdexplorer.perVar(pop=mdata[u'年末总人口'],var=[u'地区生产总值',u'年末总人口']) #print(dframe) ''' dframe = csdexplorer.lgVar() dframe2 = csdexplorer.describe().applymap(lambda x:'{0:.2f}'.format(x)) print(dframe2) csdexplorer.hist(var=u'地区生产总值',save=True) csdexplorer.scatter(y=u'地区生产总值',x=u'年末总人口',kind='kde') csdexplorer.pair(vars=[u'地区生产总值',u'年末总人口'])''' csdexplorer.ols(y=u'地区生产总值',x=u'年末总人口') #print(csdexplorer.corr())
# coding=UTF-8 import matplotlib.pyplot as plt import seaborn as sns from application.DataWarehouse.data.class_regiondata import RegionData from application.DataWarehouse.toolkit.class_crosssectiondataexplorer import CrossSectionRegionDataExplorer sns.set(style="white", palette="muted", color_codes=True) # 载入数据 rdata = RegionData() mdata = rdata.query(region=["t"], year=[2010], variable=[u"地区生产总值", u"年末总人口"], scale=u"全市") mdata = mdata["data"] csdexplorer = CrossSectionRegionDataExplorer(mdata) """ plt.style.use('ggplot') mdata = mdata[u'地区生产总值'] mdata.plot(kind='hist') plt.show() """ print(sns.axes_style()) sns.set_style( "white", {"font.sans-serif": ["Microsoft YaHei", "Arial", "Liberation Sans", "Bitstream Vera Sans", "sans-serif"]} ) mdata = mdata[u"地区生产总值"] sns.distplot(mdata, kde=False) plt.show()