1.53
4.45
4.00
现在来做一个改进,按照div来抽取。
grep "em class=\"vs\"" *e|awk -F"score-text\">" '{print $2}'|awk -F"<" '{print $1}' > vs.lst
grep -A4 "div class=\"selection\"" *e|grep -A3 "FMW" |awk '{ if($2~/no-sale/) {print "\"num\">0< \n \"num\">0< \n \"num\">0< \n" } else {print $5$6}}'|awk -F"num\">" '{print $2}'|awk -F"<" '{print $1}' |awk -v RS= '{print $1" " $2" " $3}' > fmw.lst
grep -A9 "div class=\"selection\"" *e|grep -A3 "FHMW" |awk '{ if($2~/no-sale/) {print "\"num\">0< \n \"num\">0< \n \"num\">0< \n" } else {print $5$6}}'|awk -F"num\">" '{print $2}'|awk -F"<" '{print $1}' |awk -v RS= '{print $1" " $2" " $3}' > hfmw.lst
抽取后的数据就会很自然的显示出来,我们把“未开售”的记录设置为0
数据抽取过滤后,结果就会如下所示,数据就不会乱了。
1,3.40,3.35,1.88,1.71,3.65,3.70
2,0,0,0,2.85,4.20,1.85
1,4.90,3.95,1.50,2.24,3.60,2.47
1,7.10,4.80,1.29,2.95,3.75,1.91
1,5.30,3.85,1.48,2.26,3.35,2.58
1,5.00,4.00,1.49,2.25,3.55,2.48
1,3.20,3.40,1.93,1.68,3.75,3.75
来自 “ ITPUB博客 ” ,链接:https://blog.itpub.net/29900508/viewspace-1276064/
,如需转载,请注明出处,否则将追究法律责任。