Question

我在弄清楚我需要在jq中使用什么过滤器和方法以将json数据转换为我想要的内容时遇到问题。我尝试过的每种组合都根本无法使用，或者针对每个对象的每个子数组的每个值进行迭代。

我在此上花费了太长时间，并且没有取得更多进展。需要有人将另一只眼睛放在上面。我敢肯定，这比我想像的要简单得多，但我只是无法弄清楚！

这是我正在使用的json数据：

[
    {
        "location": "locationa",
        "services": [
            {
                "name": "serviceA",
                "version": "5.2.0.2",
                "updatedAt": "2018-04-17"
            },
            {
                "name": "serviceB",
                "version": "4.19.0.5",
                "updatedAt": "2018-04-17"
            }
        ]
    },
    {
        "location": "locationb",
        "services": [
            {
                "name": "serviceA",
                "version": "5.2.0.2",
                "updatedAt": "2018-04-17"
            },
            {
                "name": "serviceB",
                "version": "4.19.0.5",
                "updatedAt": "2018-04-17"
            },
            {
                "name": "serviceC",
                "version": "1.0.0.1",
                "updatedAt": "2018-04-17"
            }
        ]
    }
]

这是我尝试退出的格式：

locationa serviceA 5.2.0.2
locationa serviceB 4.19.0.5
locationb serviceA 5.2.0.2
locationb serviceB 4.19.0.5
locationb serviceC 1.0.0.1

Answer 1

您可以使用library(ggplot2) library(reshape2) library(scales) df<-data.frame(row.names=c("AcroMetrix","PV1_PV2","CHIPv2","TSACP","TSTP"),Germline=c(34,33,14,22,12),Somatic_5_15=c(341,331,281,249,147),Somatic_15_30=c(180,176,129,124,108)) df$name<-row.names(df) df_molten<-melt(df) df_molten$name<-factor(df_molten$name,levels=c('AcroMetrix','PV1_PV2','CHIPv2','TSACP','TSTP')) df_molten$Percent_targeted <- unlist(lapply(1:length(levels(df_molten$variable)), function(i){c(100,100,77,73,49)})) gg <- ggplot(df_molten,aes(x=name,y=value,fill=variable))+ geom_bar(stat='identity', width=.6)+ scale_fill_discrete(labels=c("Germline","Somatic 5-15% VAF","Somatic 15-30% VAF"))+ geom_text(aes(label=value),size=3,fontface='bold',position=position_stack(vjust=.5))+ xlab("Panel")+ylab("Counts")+ theme_bw()+ theme(panel.grid.major=element_blank(),panel.grid.minor=element_blank(),panel.background=element_blank(),axis.line=element_line(colour="black"),panel.border=element_blank(),legend.title=element_blank()) gg <- gg + scale_y_continuous(expand = expand_scale(mult=c(0, 0.0))) # get the sacle values of the current y-axis gb <- ggplot_build(gg) y.range <- gb$layout$panel_params[[1]]$y.range y2.range <- range(df_molten$Percent_targeted)# extendrange(, f=0.01) scale_factor <- (diff(y.range)/max(y2.range)) trans <- ~ ((. -y.range[1])/scale_factor) df_molten$Percent_targeted_scaled <- rescale(df_molten$Percent_targeted, y.range, c(0, y2.range[2])) df_molten$x <- which(levels(df_molten$name)%in%df_molten$name)-.3 gg <- gg + geom_segment(aes(x=x, xend=x, yend=Percent_targeted_scaled), y=0, size=2, data=df_molten) gg <- gg + geom_label(aes(label=paste0(Percent_targeted, '%'), x=x, y=Percent_targeted_scaled), fill='white', data=df_molten) gg <- gg + scale_y_continuous(expand=expand_scale(mult=c(.05, .05)), sec.axis = sec_axis(trans, name = "Percent targeted", labels = scales::percent(seq(0, 1, length.out = 5), scale=100))) gg运算符连接字符串：

Answer 2

通常，在尝试输出csv / tsv时，您将希望生成要输出的行的数组，然后传递到@csv或@tsv或利用join/1以以下格式输出您选择的。

jq -r '.[] | [.location] + (.services[] | [.name, .version]) | @tsv' input.json

Answer 3

作为替代方案，您可以考虑使用基于步行路径的Unix实用程序 jtc ：

bash $ <file.json jtc -x'<name>l:' -y'[-3][location]' -y' ' -y'[-1][version]' | xargs -L3
locationa serviceA 5.2.0.2
locationa serviceB 4.19.0.5
locationb serviceA 5.2.0.2
locationb serviceB 4.19.0.5
locationb serviceC 1.0.0.1
bash $

jq用对象的主值过滤子数组值

3 个答案: