trafficAudit.git

parent: 15c8035c | 补丁 | 提交 | ignore whitespace

feat(数据查看): 拆分表空列不显示、口径上移为筛选(接口加 periodType)、12 类表表头补齐单位

zhizhijie

9 天以前 30c490673b85720bd5447a0b577f3e989ba50ac4

feat(数据查看): 拆分表空列不显示、口径上移为筛选(接口加 periodType)、12 类表表头补齐单位

2个文件已修改

	traffic-audit-server/src/main/java/com/trafficaudit/dataimport/controller/DataViewController.java	168 ●●●●● 补丁 \| 查看 \| 原始文档 \| blame \| 历史
	traffic-audit-web/src/views/DataView.vue	26 ●●●●● 补丁 \| 查看 \| 原始文档 \| blame \| 历史

 traffic-audit-server/src/main/java/com/trafficaudit/dataimport/controller/DataViewController.java

@@ -105,6 +105,7 @@
    public Result<Map<String, Object>> list(@RequestParam("type") String type,
                                            @RequestParam(value = "period", required = false) String period,
                                            @RequestParam(value = "keyword", required = false) String keyword,
                                            @RequestParam(value = "periodType", required = false) String periodType,
                                            @RequestParam(value = "page", defaultValue = "1") long page,
                                            @RequestParam(value = "size", defaultValue = "20") long size) {
        String kw = keyword == null ? "" : keyword.trim();
@@ -154,6 +155,7 @@
            case "scaleSplit": {
                LambdaQueryWrapper<ScaleSplitTransport> w = new LambdaQueryWrapper<ScaleSplitTransport>()
                        .eq(notEmpty(period), ScaleSplitTransport::getReportPeriod, period)
                        .eq(notEmpty(periodType), ScaleSplitTransport::getPeriodType, periodType)
                        .like(!kw.isEmpty(), ScaleSplitTransport::getRegionName, kw)
                        .orderByDesc(ScaleSplitTransport::getId);
                Page<ScaleSplitTransport> p = new Page<>(safePage, safeSize);
@@ -540,26 +542,26 @@
        H2032_COLUMNS.add(col("enterpriseName", "企业名称", 220));
        H2032_COLUMNS.add(col("unifiedCreditCode", "统一社会信用代码", 180));
        H2032_COLUMNS.add(col("reportUnit", "填报单位", 160));
        H2032_COLUMNS.add(col("vehicleTotal", "车辆数合计", 110));
        H2032_COLUMNS.add(col("vehicleTotal", "车辆数合计(辆)", 130));
        H2032_COLUMNS.add(col("tonsTotal", "标记吨位数合计(吨)", 150));
        H2032_COLUMNS.add(col("vehicleTractor", "牵引车", 90));
        H2032_COLUMNS.add(col("vehicleTrailer", "挂车", 90));
        H2032_COLUMNS.add(col("tonsTrailer", "吨位-挂车", 110));
        H2032_COLUMNS.add(col("vehicleContainer", "集装箱车", 110));
        H2032_COLUMNS.add(col("tonsContainer", "吨位-集装箱", 120));
        H2032_COLUMNS.add(col("vehicleWhole", "整车", 90));
        H2032_COLUMNS.add(col("tonsWhole", "吨位-整车", 110));
        H2032_COLUMNS.add(col("vehicleTractor", "牵引车(辆)", 110));
        H2032_COLUMNS.add(col("vehicleTrailer", "挂车(辆)", 110));
        H2032_COLUMNS.add(col("tonsTrailer", "吨位-挂车(吨)", 130));
        H2032_COLUMNS.add(col("vehicleContainer", "集装箱车(辆)", 120));
        H2032_COLUMNS.add(col("tonsContainer", "吨位-集装箱(吨)", 140));
        H2032_COLUMNS.add(col("vehicleWhole", "整车(辆)", 110));
        H2032_COLUMNS.add(col("tonsWhole", "吨位-整车(吨)", 130));
        H2032_COLUMNS.add(col("freightTotal", "货运量合计(吨)", 130));
        H2032_COLUMNS.add(col("turnoverTotal", "周转量合计(吨公里)", 150));
        H2032_COLUMNS.add(col("freightContainer", "货运量-集装箱", 130));
        H2032_COLUMNS.add(col("freightCoal", "货运量-煤炭", 120));
        H2032_COLUMNS.add(col("freightOilGas", "货运量-油气", 120));
        H2032_COLUMNS.add(col("freightCrudeOil", "货运量-原油", 120));
        H2032_COLUMNS.add(col("freightMetalOre", "货运量-金属矿石", 140));
        H2032_COLUMNS.add(col("freightIronOre", "货运量-铁矿石", 130));
        H2032_COLUMNS.add(col("freightBuilding", "货运量-建材", 120));
        H2032_COLUMNS.add(col("freightGrain", "货运量-粮食", 120));
        H2032_COLUMNS.add(col("avgTonnage", "平均吨位", 100));
        H2032_COLUMNS.add(col("freightContainer", "货运量-集装箱(吨)", 140));
        H2032_COLUMNS.add(col("freightCoal", "货运量-煤炭(吨)", 140));
        H2032_COLUMNS.add(col("freightOilGas", "货运量-油气(吨)", 140));
        H2032_COLUMNS.add(col("freightCrudeOil", "货运量-原油(吨)", 140));
        H2032_COLUMNS.add(col("freightMetalOre", "货运量-金属矿石(吨)", 140));
        H2032_COLUMNS.add(col("freightIronOre", "货运量-铁矿石(吨)", 140));
        H2032_COLUMNS.add(col("freightBuilding", "货运量-建材(吨)", 140));
        H2032_COLUMNS.add(col("freightGrain", "货运量-粮食(吨)", 140));
        H2032_COLUMNS.add(col("avgTonnage", "平均吨位(吨)", 120));
        H2032_COLUMNS.add(col("avgDistance", "平均运距(公里)", 120));
        H2032_COLUMNS.add(col("unitLeader", "单位负责人", 110));
        H2032_COLUMNS.add(col("statsLeader", "统计负责人", 110));
@@ -571,46 +573,46 @@

        AUTH_COLUMNS.add(col("reportPeriod", "报表期", 100));
        AUTH_COLUMNS.add(col("enterpriseName", "企业名称", 240));
        AUTH_COLUMNS.add(col("tractorCount", "牵引车数", 100));
        AUTH_COLUMNS.add(col("trailerCount", "挂车数", 100));
        AUTH_COLUMNS.add(col("otherCount", "其他车数", 100));
        AUTH_COLUMNS.add(col("trailerTons", "挂车吨位", 110));
        AUTH_COLUMNS.add(col("otherTons", "其他吨位", 110));
        AUTH_COLUMNS.add(col("tractorCount", "牵引车数(辆)", 110));
        AUTH_COLUMNS.add(col("trailerCount", "挂车数(辆)", 110));
        AUTH_COLUMNS.add(col("otherCount", "其他车数(辆)", 110));
        AUTH_COLUMNS.add(col("trailerTons", "挂车吨位(吨)", 120));
        AUTH_COLUMNS.add(col("otherTons", "其他吨位(吨)", 120));

        TRACK_COLUMNS.add(col("reportPeriod", "报表期", 100));
        TRACK_COLUMNS.add(col("enterpriseName", "企业名称", 240));
        TRACK_COLUMNS.add(col("monthlyMileage", "月度里程", 120));
        TRACK_COLUMNS.add(col("trackedVehicles", "轨迹车辆数", 120));
        TRACK_COLUMNS.add(col("monthlyMileage", "月度里程(公里)", 130));
        TRACK_COLUMNS.add(col("trackedVehicles", "轨迹车辆数(辆)", 130));

        SPLIT_COLUMNS.add(col("reportPeriod", "报表期", 100));
        SPLIT_COLUMNS.add(col("periodType", "口径", 90));
        SPLIT_COLUMNS.add(col("regionName", "市州", 130));
        SPLIT_COLUMNS.add(col("aboveScaleFreight", "规上货运量(来源文件未提供该列)", 220));
        SPLIT_COLUMNS.add(col("aboveScaleFreight", "规上货运量(万吨)", 140));
        SPLIT_COLUMNS.add(col("aboveScaleTurnover", "规上周转量(万吨公里)", 170));
        SPLIT_COLUMNS.add(col("aboveScaleRank", "规上排名", 100));
        SPLIT_COLUMNS.add(col("aboveScaleYoy", "规上同比", 100));
        SPLIT_COLUMNS.add(col("belowScaleFreight", "规下货运量(来源文件未提供该列)", 220));
        SPLIT_COLUMNS.add(col("aboveScaleRank", "规上排名(名)", 110));
        SPLIT_COLUMNS.add(col("aboveScaleYoy", "规上同比(%)", 110));
        SPLIT_COLUMNS.add(col("belowScaleFreight", "规下货运量(万吨)", 140));
        SPLIT_COLUMNS.add(col("belowScaleTurnover", "规下周转量(万吨公里)", 170));
        SPLIT_COLUMNS.add(col("belowScaleRank", "规下排名", 100));
        SPLIT_COLUMNS.add(col("belowScaleYoy", "规下同比", 100));
        SPLIT_COLUMNS.add(col("totalFreight", "合计货运量(来源文件未提供该列)", 220));
        SPLIT_COLUMNS.add(col("belowScaleRank", "规下排名(名)", 110));
        SPLIT_COLUMNS.add(col("belowScaleYoy", "规下同比(%)", 110));
        SPLIT_COLUMNS.add(col("totalFreight", "合计货运量(万吨)", 140));
        SPLIT_COLUMNS.add(col("totalTurnover", "合计周转量(万吨公里)", 170));
        SPLIT_COLUMNS.add(col("totalRank", "合计排名", 100));
        SPLIT_COLUMNS.add(col("totalYoy", "合计同比", 100));
        SPLIT_COLUMNS.add(col("totalRank", "合计排名(名)", 110));
        SPLIT_COLUMNS.add(col("totalYoy", "合计同比(%)", 110));

        FREIGHT_COLUMNS.add(col("reportPeriod", "报表期", 100));
        FREIGHT_COLUMNS.add(col("regionName", "市州", 130));
        for (int m = 1; m <= 12; m++) {
            FREIGHT_COLUMNS.add(col(String.format("freightM%02d", m), "货运量" + m + "月", 110));
            FREIGHT_COLUMNS.add(col(String.format("freightM%02d", m), "货运量" + m + "月(万吨)", 140));
        }
        for (int m = 1; m <= 12; m++) {
            FREIGHT_COLUMNS.add(col(String.format("lastFreightM%02d", m), "去年货运量" + m + "月", 130));
            FREIGHT_COLUMNS.add(col(String.format("lastFreightM%02d", m), "去年货运量" + m + "月(万吨)", 160));
        }
        for (int m = 1; m <= 12; m++) {
            FREIGHT_COLUMNS.add(col(String.format("turnoverM%02d", m), "周转量" + m + "月", 120));
            FREIGHT_COLUMNS.add(col(String.format("turnoverM%02d", m), "周转量" + m + "月(万吨公里)", 160));
        }
        for (int m = 1; m <= 12; m++) {
            FREIGHT_COLUMNS.add(col(String.format("lastTurnoverM%02d", m), "去年周转量" + m + "月", 140));
            FREIGHT_COLUMNS.add(col(String.format("lastTurnoverM%02d", m), "去年周转量" + m + "月(万吨公里)", 180));
        }

        H2031_COLUMNS.add(col("reportPeriod", "报表期", 100));
@@ -620,37 +622,37 @@
        H2031_COLUMNS.add(col("enterpriseName", "企业名称", 220));
        H2031_COLUMNS.add(col("unifiedCreditCode", "统一社会信用代码", 180));
        H2031_COLUMNS.add(col("reportUnit", "填报单位", 160));
        H2031_COLUMNS.add(col("vehicleTotal", "客运车辆合计", 110));
        H2031_COLUMNS.add(col("seatTotal", "核定载客位合计", 130));
        H2031_COLUMNS.add(col("vehicleSchedule", "班线车辆数", 110));
        H2031_COLUMNS.add(col("seatSchedule", "班线载客位", 110));
        H2031_COLUMNS.add(col("vehicleCharter", "包车车辆数", 110));
        H2031_COLUMNS.add(col("seatCharter", "包车载客位", 110));
        H2031_COLUMNS.add(col("vehicleTotal", "客运车辆合计(辆)", 130));
        H2031_COLUMNS.add(col("seatTotal", "核定载客位合计(座)", 150));
        H2031_COLUMNS.add(col("vehicleSchedule", "班线车辆数(辆)", 130));
        H2031_COLUMNS.add(col("seatSchedule", "班线载客位(座)", 130));
        H2031_COLUMNS.add(col("vehicleCharter", "包车车辆数(辆)", 130));
        H2031_COLUMNS.add(col("seatCharter", "包车载客位(座)", 130));
        H2031_COLUMNS.add(col("passengerTotal", "客运量合计(人)", 130));
        H2031_COLUMNS.add(col("turnoverTotal", "周转量合计", 110));
        H2031_COLUMNS.add(col("passengerClass1", "客运量一类", 110));
        H2031_COLUMNS.add(col("passengerClass2", "客运量二类", 110));
        H2031_COLUMNS.add(col("passengerClass3", "客运量三类", 110));
        H2031_COLUMNS.add(col("passengerClass4", "客运量四类", 110));
        H2031_COLUMNS.add(col("passengerCharter", "客运量包车", 110));
        H2031_COLUMNS.add(col("turnoverClass1", "周转量一类", 110));
        H2031_COLUMNS.add(col("turnoverClass2", "周转量二类", 110));
        H2031_COLUMNS.add(col("turnoverClass3", "周转量三类", 110));
        H2031_COLUMNS.add(col("turnoverClass4", "周转量四类", 110));
        H2031_COLUMNS.add(col("turnoverCharter", "周转量包车", 110));
        H2031_COLUMNS.add(col("avgDistanceTotal", "平均运距合计", 120));
        H2031_COLUMNS.add(col("avgDistanceClass1", "一类平均运距", 120));
        H2031_COLUMNS.add(col("avgDistanceClass2", "二类平均运距", 120));
        H2031_COLUMNS.add(col("avgDistanceClass3", "三类平均运距", 120));
        H2031_COLUMNS.add(col("avgDistanceClass4", "四类平均运距", 120));
        H2031_COLUMNS.add(col("avgDistanceCharter", "包车平均运距", 120));
        H2031_COLUMNS.add(col("turnoverTotal", "周转量合计(人公里)", 140));
        H2031_COLUMNS.add(col("passengerClass1", "客运量一类(人)", 120));
        H2031_COLUMNS.add(col("passengerClass2", "客运量二类(人)", 120));
        H2031_COLUMNS.add(col("passengerClass3", "客运量三类(人)", 120));
        H2031_COLUMNS.add(col("passengerClass4", "客运量四类(人)", 120));
        H2031_COLUMNS.add(col("passengerCharter", "客运量包车(人)", 130));
        H2031_COLUMNS.add(col("turnoverClass1", "周转量一类(人公里)", 140));
        H2031_COLUMNS.add(col("turnoverClass2", "周转量二类(人公里)", 140));
        H2031_COLUMNS.add(col("turnoverClass3", "周转量三类(人公里)", 140));
        H2031_COLUMNS.add(col("turnoverClass4", "周转量四类(人公里)", 140));
        H2031_COLUMNS.add(col("turnoverCharter", "周转量包车(人公里)", 150));
        H2031_COLUMNS.add(col("avgDistanceTotal", "平均运距合计(公里)", 140));
        H2031_COLUMNS.add(col("avgDistanceClass1", "一类平均运距(公里)", 140));
        H2031_COLUMNS.add(col("avgDistanceClass2", "二类平均运距(公里)", 140));
        H2031_COLUMNS.add(col("avgDistanceClass3", "三类平均运距(公里)", 140));
        H2031_COLUMNS.add(col("avgDistanceClass4", "四类平均运距(公里)", 140));
        H2031_COLUMNS.add(col("avgDistanceCharter", "包车平均运距(公里)", 140));
        BUS_COLUMNS.add(col("reportPeriod", "报表期", 100));
        BUS_COLUMNS.add(col("regionCode", "所属地区", 100));
        BUS_COLUMNS.add(col("city", "市州", 110));
        BUS_COLUMNS.add(col("enterpriseName", "企业名称", 220));
        BUS_COLUMNS.add(col("opVehicles", "运营车数", 100));
        BUS_COLUMNS.add(col("stopTotal", "站点总个数", 110));
        BUS_COLUMNS.add(col("stopCity", "城市内站点", 110));
        BUS_COLUMNS.add(col("opVehicles", "运营车数(辆)", 120));
        BUS_COLUMNS.add(col("stopTotal", "站点总个数(个)", 130));
        BUS_COLUMNS.add(col("stopCity", "城市内站点(个)", 130));
        BUS_COLUMNS.add(col("passengerVolume", "客运量(万人次)", 120));
        BUS_COLUMNS.add(col("passengerCity", "城市内客运量(万人次)", 150));
        BUS_COLUMNS.add(col("turnover", "旅客周转量(万人公里)", 170));
@@ -672,16 +674,16 @@
        TAXI_COLUMNS.add(col("reportPeriod", "报表期", 100));
        TAXI_COLUMNS.add(col("regionCode", "所属地区", 100));
        TAXI_COLUMNS.add(col("city", "市州", 110));
        TAXI_COLUMNS.add(col("tripTotal", "载客车次总数", 120));
        TAXI_COLUMNS.add(col("tripCity", "载客车次_城市内", 130));
        TAXI_COLUMNS.add(col("tripTotal", "载客车次总数(车次)", 150));
        TAXI_COLUMNS.add(col("tripCity", "载客车次_城市内(车次)", 160));
        TAXI_COLUMNS.add(col("passengerVolume", "客运量(万人次)", 120));
        TAXI_COLUMNS.add(col("passengerCity", "城市内客运量(万人次)", 150));
        TAXI_COLUMNS.add(col("turnover", "旅客周转量(万人公里)", 170));
        TAXI_COLUMNS.add(col("turnoverCity", "城市内周转量(万人公里)", 180));
        TAXI_COLUMNS.add(col("opVehicles", "运营车辆数", 110));
        TAXI_COLUMNS.add(col("opVehicles", "运营车辆数(辆)", 130));
        TAXI_COLUMNS.add(col("avgDistance", "平均运距(公里)", 120));
        TAXI_COLUMNS.add(col("avgDistanceCity", "城市内平均运距(公里)", 150));
        TAXI_COLUMNS.add(col("passengersPerTrip", "单车次载客人数", 130));
        TAXI_COLUMNS.add(col("passengersPerTrip", "单车次载客人数(人/车次)", 170));
        TAXI_COLUMNS.add(col("rateTripMom", "载客车次环比", 110));
        TAXI_COLUMNS.add(col("rateTripYoy", "载客车次同比", 110));
        TAXI_COLUMNS.add(col("ratePassengerMom", "客运量环比", 100));
@@ -704,8 +706,8 @@
        PAUTH_COLUMNS.add(col("reportPeriod", "报表期", 100));
        PAUTH_COLUMNS.add(col("enterpriseCode", "企业代码", 130));
        PAUTH_COLUMNS.add(col("enterpriseName", "企业名称", 240));
        PAUTH_COLUMNS.add(col("vehicleCount", "车辆数", 100));
        PAUTH_COLUMNS.add(col("seatCount", "载客位数", 100));
        PAUTH_COLUMNS.add(col("vehicleCount", "车辆数(辆)", 110));
        PAUTH_COLUMNS.add(col("seatCount", "载客位数(座)", 120));
        INVEST_MONTHLY_COLUMNS.add(col("reportPeriod", "报表期", 100));
        INVEST_MONTHLY_COLUMNS.add(col("projectId", "项目ID", 80));
        INVEST_MONTHLY_COLUMNS.add(col("projectName", "项目名称", 280));
@@ -716,7 +718,7 @@
        INVEST_MONTHLY_COLUMNS.add(col("startCum", "自开始建设累计完成(万元)", 180));
        INVEST_MONTHLY_COLUMNS.add(col("progressStage", "建设阶段", 120));
        INVEST_MONTHLY_COLUMNS.add(col("progressDesc", "形象进度", 320));
        INVEST_MONTHLY_COLUMNS.add(col("buildingArea", "建筑面积", 110));
        INVEST_MONTHLY_COLUMNS.add(col("buildingArea", "建筑面积(平方米)", 140));
        INVEST_PROJECT_COLUMNS.add(col("projectName", "项目名称", 260));
        INVEST_PROJECT_COLUMNS.add(col("category", "类别", 100));
        INVEST_PROJECT_COLUMNS.add(col("city", "市州", 90));
@@ -726,7 +728,7 @@
        INVEST_PROJECT_COLUMNS.add(col("startTime", "开工年", 90));
        INVEST_PROJECT_COLUMNS.add(col("endTime", "完工年", 90));
        INVEST_PROJECT_COLUMNS.add(col("totalInvestment", "总投资(万元)", 130));
        INVEST_PROJECT_COLUMNS.add(col("buildingArea", "建筑面积", 110));
        INVEST_PROJECT_COLUMNS.add(col("buildingArea", "建筑面积(平方米)", 140));
        INVEST_PROJECT_COLUMNS.add(col("approvalGk", "工可或核准批复文号", 200));
        INVEST_PROJECT_COLUMNS.add(col("approvalCs", "初设或施工图批复文号", 200));
        INVEST_PROJECT_COLUMNS.add(col("source", "来源", 100));
@@ -745,34 +747,34 @@
        ENERGY_VEHICLE_COLUMNS.add(col("vehicleType", "车辆类型", 130));
        ENERGY_VEHICLE_COLUMNS.add(col("fuelType", "燃料类型", 110));
        ENERGY_VEHICLE_COLUMNS.add(col("manufactureYear", "出厂年份", 100));
        ENERGY_VEHICLE_COLUMNS.add(col("markedTonnage", "标记吨位", 100));
        ENERGY_VEHICLE_COLUMNS.add(col("markedTonnage", "标记吨位(吨)", 120));
        ENERGY_VEHICLE_COLUMNS.add(col("totalMileage", "总行驶里程(公里)", 150));
        ENERGY_VEHICLE_COLUMNS.add(col("loadedMileage", "重载里程(公里)", 140));
        ENERGY_VEHICLE_COLUMNS.add(col("emptyMileage", "空载里程(公里)", 140));
        ENERGY_VEHICLE_COLUMNS.add(col("freight", "货运量(吨)", 120));
        ENERGY_VEHICLE_COLUMNS.add(col("turnover", "周转量(吨公里)", 140));
        ENERGY_VEHICLE_COLUMNS.add(col("tripCount", "车次", 90));
        ENERGY_VEHICLE_COLUMNS.add(col("tripCount", "车次(次)", 100));
        ENERGY_VEHICLE_COLUMNS.add(col("fuelUnit", "燃料单位", 100));
        ENERGY_VEHICLE_COLUMNS.add(col("fuelConsumption", "燃料消耗量", 120));
        ENERGY_VEHICLE_COLUMNS.add(col("avgDistance", "平均运距", 110));
        ENERGY_VEHICLE_COLUMNS.add(col("avgLoadedTonnage", "平均载重吨位", 130));
        ENERGY_VEHICLE_COLUMNS.add(col("avgTripMileage", "平均车次里程", 130));
        ENERGY_VEHICLE_COLUMNS.add(col("fuelPer100km", "百公里油耗", 120));
        ENERGY_VEHICLE_COLUMNS.add(col("turnoverFuel", "周转量油耗", 120));
        ENERGY_VEHICLE_COLUMNS.add(col("fuelConsumption", "燃料消耗量(按燃料单位)", 170));
        ENERGY_VEHICLE_COLUMNS.add(col("avgDistance", "平均运距(公里)", 130));
        ENERGY_VEHICLE_COLUMNS.add(col("avgLoadedTonnage", "平均载重吨位(吨)", 150));
        ENERGY_VEHICLE_COLUMNS.add(col("avgTripMileage", "平均车次里程(公里)", 150));
        ENERGY_VEHICLE_COLUMNS.add(col("fuelPer100km", "百公里油耗(按燃料单位)", 170));
        ENERGY_VEHICLE_COLUMNS.add(col("turnoverFuel", "周转量油耗(按燃料单位)", 170));
        ENERGY_AUTH_COLUMNS.add(col("reportPeriod", "报表期", 100));
        ENERGY_AUTH_COLUMNS.add(col("plateNo", "车牌号", 110));
        ENERGY_AUTH_COLUMNS.add(col("vehicleType", "车辆类型", 130));
        ENERGY_AUTH_COLUMNS.add(col("fuelType", "燃料类型", 110));
        ENERGY_AUTH_COLUMNS.add(col("markedTonnage", "标记吨位", 100));
        ENERGY_AUTH_COLUMNS.add(col("tractionQuality", "牵引质量", 110));
        ENERGY_AUTH_COLUMNS.add(col("markedTonnage", "标记吨位(吨)", 120));
        ENERGY_AUTH_COLUMNS.add(col("tractionQuality", "牵引质量(吨)", 130));

        PAX_INDIVIDUAL_COLUMNS.add(col("reportPeriod", "报表期", 100));
        PAX_INDIVIDUAL_COLUMNS.add(col("regionCode", "所属地区", 110));
        PAX_INDIVIDUAL_COLUMNS.add(col("city", "市州", 110));
        PAX_INDIVIDUAL_COLUMNS.add(col("enterpriseCode", "企业代码", 130));
        PAX_INDIVIDUAL_COLUMNS.add(col("enterpriseName", "企业名称", 220));
        PAX_INDIVIDUAL_COLUMNS.add(col("passengerCount", "个体客运量", 130));
        PAX_INDIVIDUAL_COLUMNS.add(col("turnover", "个体旅客周转量", 150));
        PAX_INDIVIDUAL_COLUMNS.add(col("passengerCount", "个体客运量(人)", 140));
        PAX_INDIVIDUAL_COLUMNS.add(col("turnover", "个体旅客周转量(人公里)", 180));

        WYC_TOTAL_COLUMNS.add(col("reportPeriod", "报表期", 100));
        WYC_TOTAL_COLUMNS.add(col("pinK", "全省网约车客运量(万人次)", 210));

 traffic-audit-web/src/views/DataView.vue

@@ -27,6 +27,14 @@
              <el-option v-for="t in g.types" :key="t.value" :label="t.label" :value="t.value"></el-option>
            </el-option-group>
          </el-select>
          <template v-if="hasPeriodType">
            <span class="toolbar-label">口径</span>
            <el-select v-model="periodType" size="small" style="width:110px" @change="doQuery">
              <el-option label="全部" value=""></el-option>
              <el-option label="当月" value="MONTH"></el-option>
              <el-option label="累计" value="CUMULATIVE"></el-option>
            </el-select>
          </template>
          <el-input v-model="keyword" placeholder="企业/市州名称" clearable style="width:180px" @keyup.enter.native="doQuery"></el-input>
          <el-button type="primary" size="small" @click="doQuery">查询</el-button>
          <el-button size="small" icon="el-icon-full-screen" @click="toggleFullscreen">全屏查看</el-button>
@@ -99,6 +107,7 @@
      activeModule: 'freight',
      type: 'h2032',
      period: '',
      periodType: '',
      keyword: '',
      page: 1,
      size: 50,
@@ -110,6 +119,10 @@
    }
  },
  computed: {
    // 规上规下拆分等表有"口径"列（当月/累计），把它做成上方筛选而不是表格列
    hasPeriodType() {
      return (this.columns || []).some(c => c.prop === 'periodType')
    },
    currentTypeLabel() {
      for (const g of this.modules) {
        const t = g.types.find(x => x.value === this.type)
@@ -140,8 +153,10 @@
    // 数据查看统一列过滤：内部标识列不展示；报表期（由筛选条件体现）与所属地区（区划代码，已被市州列替代）不展示
    keepColumn(c) {
      if (!c) return false
      const hiddenProps = ['enterpriseCode', 'unifiedCreditCode', 'reportUnit', 'projectId', 'regionCode', 'reportPeriod']
      const hiddenLabels = ['企业代码', '统一社会信用代码', '填报单位', '项目ID', '所属地区', '报表期']
      // 口径列上移为筛选；拆分表货运量三列源文件未提供（全空）故不展示
      const hiddenProps = ['enterpriseCode', 'unifiedCreditCode', 'reportUnit', 'projectId', 'regionCode', 'reportPeriod',
        'periodType', 'aboveScaleFreight', 'belowScaleFreight', 'totalFreight']
      const hiddenLabels = ['企业代码', '统一社会信用代码', '填报单位', '项目ID', '所属地区', '报表期', '口径']
      if (hiddenProps.indexOf(c.prop) >= 0 || hiddenLabels.indexOf(c.label) >= 0) return false
      return true
    },
@@ -156,6 +171,7 @@
    onTypeSelect() {
      const g = this.modules.find(x => x.types.some(t => t.value === this.type))
      if (g) this.activeModule = g.key
      this.periodType = ''
      this.doQuery()
    },
    doQuery() {
@@ -171,13 +187,14 @@
          type: this.type,
          period: this.period || undefined,
          keyword: this.keyword || undefined,
          periodType: this.periodType || undefined,
          page: this.page,
          size: this.size
        }
      }).then(res => {
        const d = res.data || {}
        this.records = d.records || []
        this.columns = (d.columns || []).filter(c => ['enterpriseCode', 'unifiedCreditCode', 'reportUnit'].indexOf(c.prop) < 0 && ['企业代码', '统一社会信用代码', '填报单位'].indexOf(c.label) < 0)
        this.columns = d.columns || []
        this.total = d.total || 0
        if (this.page > 1 && this.records.length === 0) {
          this.page = 1
@@ -213,6 +230,7 @@
          type: this.type,
          period: this.period || undefined,
          keyword: this.keyword || undefined,
          periodType: this.periodType || undefined,
          page: nextPage,
          size: this.size
        }
@@ -226,7 +244,7 @@
        this.records = this.records.concat(addRows)
        this.page = nextPage
        if (d.total != null) this.total = d.total
        if (d.columns && d.columns.length) this.columns = d.columns.filter(c => ['enterpriseCode', 'unifiedCreditCode', 'reportUnit'].indexOf(c.prop) < 0 && ['企业代码', '统一社会信用代码', '填报单位'].indexOf(c.label) < 0)
        if (d.columns && d.columns.length) this.columns = d.columns
      }).catch(e => {
        if (e && e._toast) return
        this.$message.error('加载更多失败')

			@@ -105,6 +105,7 @@
			public Result<Map<String, Object>> list(@RequestParam("type") String type,
			@RequestParam(value = "period", required = false) String period,
			@RequestParam(value = "keyword", required = false) String keyword,
			@RequestParam(value = "periodType", required = false) String periodType,
			@RequestParam(value = "page", defaultValue = "1") long page,
			@RequestParam(value = "size", defaultValue = "20") long size) {
			String kw = keyword == null ? "" : keyword.trim();
			@@ -154,6 +155,7 @@
			case "scaleSplit": {
			LambdaQueryWrapper<ScaleSplitTransport> w = new LambdaQueryWrapper<ScaleSplitTransport>()
			.eq(notEmpty(period), ScaleSplitTransport::getReportPeriod, period)
			.eq(notEmpty(periodType), ScaleSplitTransport::getPeriodType, periodType)
			.like(!kw.isEmpty(), ScaleSplitTransport::getRegionName, kw)
			.orderByDesc(ScaleSplitTransport::getId);
			Page<ScaleSplitTransport> p = new Page<>(safePage, safeSize);
			@@ -540,26 +542,26 @@
			H2032_COLUMNS.add(col("enterpriseName", "企业名称", 220));
			H2032_COLUMNS.add(col("unifiedCreditCode", "统一社会信用代码", 180));
			H2032_COLUMNS.add(col("reportUnit", "填报单位", 160));
			H2032_COLUMNS.add(col("vehicleTotal", "车辆数合计", 110));
			H2032_COLUMNS.add(col("vehicleTotal", "车辆数合计(辆)", 130));
			H2032_COLUMNS.add(col("tonsTotal", "标记吨位数合计(吨)", 150));
			H2032_COLUMNS.add(col("vehicleTractor", "牵引车", 90));
			H2032_COLUMNS.add(col("vehicleTrailer", "挂车", 90));
			H2032_COLUMNS.add(col("tonsTrailer", "吨位-挂车", 110));
			H2032_COLUMNS.add(col("vehicleContainer", "集装箱车", 110));
			H2032_COLUMNS.add(col("tonsContainer", "吨位-集装箱", 120));
			H2032_COLUMNS.add(col("vehicleWhole", "整车", 90));
			H2032_COLUMNS.add(col("tonsWhole", "吨位-整车", 110));
			H2032_COLUMNS.add(col("vehicleTractor", "牵引车(辆)", 110));
			H2032_COLUMNS.add(col("vehicleTrailer", "挂车(辆)", 110));
			H2032_COLUMNS.add(col("tonsTrailer", "吨位-挂车(吨)", 130));
			H2032_COLUMNS.add(col("vehicleContainer", "集装箱车(辆)", 120));
			H2032_COLUMNS.add(col("tonsContainer", "吨位-集装箱(吨)", 140));
			H2032_COLUMNS.add(col("vehicleWhole", "整车(辆)", 110));
			H2032_COLUMNS.add(col("tonsWhole", "吨位-整车(吨)", 130));
			H2032_COLUMNS.add(col("freightTotal", "货运量合计(吨)", 130));
			H2032_COLUMNS.add(col("turnoverTotal", "周转量合计(吨公里)", 150));
			H2032_COLUMNS.add(col("freightContainer", "货运量-集装箱", 130));
			H2032_COLUMNS.add(col("freightCoal", "货运量-煤炭", 120));
			H2032_COLUMNS.add(col("freightOilGas", "货运量-油气", 120));
			H2032_COLUMNS.add(col("freightCrudeOil", "货运量-原油", 120));
			H2032_COLUMNS.add(col("freightMetalOre", "货运量-金属矿石", 140));
			H2032_COLUMNS.add(col("freightIronOre", "货运量-铁矿石", 130));
			H2032_COLUMNS.add(col("freightBuilding", "货运量-建材", 120));
			H2032_COLUMNS.add(col("freightGrain", "货运量-粮食", 120));
			H2032_COLUMNS.add(col("avgTonnage", "平均吨位", 100));
			H2032_COLUMNS.add(col("freightContainer", "货运量-集装箱(吨)", 140));
			H2032_COLUMNS.add(col("freightCoal", "货运量-煤炭(吨)", 140));
			H2032_COLUMNS.add(col("freightOilGas", "货运量-油气(吨)", 140));
			H2032_COLUMNS.add(col("freightCrudeOil", "货运量-原油(吨)", 140));
			H2032_COLUMNS.add(col("freightMetalOre", "货运量-金属矿石(吨)", 140));
			H2032_COLUMNS.add(col("freightIronOre", "货运量-铁矿石(吨)", 140));
			H2032_COLUMNS.add(col("freightBuilding", "货运量-建材(吨)", 140));
			H2032_COLUMNS.add(col("freightGrain", "货运量-粮食(吨)", 140));
			H2032_COLUMNS.add(col("avgTonnage", "平均吨位(吨)", 120));
			H2032_COLUMNS.add(col("avgDistance", "平均运距(公里)", 120));
			H2032_COLUMNS.add(col("unitLeader", "单位负责人", 110));
			H2032_COLUMNS.add(col("statsLeader", "统计负责人", 110));
			@@ -571,46 +573,46 @@

			AUTH_COLUMNS.add(col("reportPeriod", "报表期", 100));
			AUTH_COLUMNS.add(col("enterpriseName", "企业名称", 240));
			AUTH_COLUMNS.add(col("tractorCount", "牵引车数", 100));
			AUTH_COLUMNS.add(col("trailerCount", "挂车数", 100));
			AUTH_COLUMNS.add(col("otherCount", "其他车数", 100));
			AUTH_COLUMNS.add(col("trailerTons", "挂车吨位", 110));
			AUTH_COLUMNS.add(col("otherTons", "其他吨位", 110));
			AUTH_COLUMNS.add(col("tractorCount", "牵引车数(辆)", 110));
			AUTH_COLUMNS.add(col("trailerCount", "挂车数(辆)", 110));
			AUTH_COLUMNS.add(col("otherCount", "其他车数(辆)", 110));
			AUTH_COLUMNS.add(col("trailerTons", "挂车吨位(吨)", 120));
			AUTH_COLUMNS.add(col("otherTons", "其他吨位(吨)", 120));

			TRACK_COLUMNS.add(col("reportPeriod", "报表期", 100));
			TRACK_COLUMNS.add(col("enterpriseName", "企业名称", 240));
			TRACK_COLUMNS.add(col("monthlyMileage", "月度里程", 120));
			TRACK_COLUMNS.add(col("trackedVehicles", "轨迹车辆数", 120));
			TRACK_COLUMNS.add(col("monthlyMileage", "月度里程(公里)", 130));
			TRACK_COLUMNS.add(col("trackedVehicles", "轨迹车辆数(辆)", 130));

			SPLIT_COLUMNS.add(col("reportPeriod", "报表期", 100));
			SPLIT_COLUMNS.add(col("periodType", "口径", 90));
			SPLIT_COLUMNS.add(col("regionName", "市州", 130));
			SPLIT_COLUMNS.add(col("aboveScaleFreight", "规上货运量(来源文件未提供该列)", 220));
			SPLIT_COLUMNS.add(col("aboveScaleFreight", "规上货运量(万吨)", 140));
			SPLIT_COLUMNS.add(col("aboveScaleTurnover", "规上周转量(万吨公里)", 170));
			SPLIT_COLUMNS.add(col("aboveScaleRank", "规上排名", 100));
			SPLIT_COLUMNS.add(col("aboveScaleYoy", "规上同比", 100));
			SPLIT_COLUMNS.add(col("belowScaleFreight", "规下货运量(来源文件未提供该列)", 220));
			SPLIT_COLUMNS.add(col("aboveScaleRank", "规上排名(名)", 110));
			SPLIT_COLUMNS.add(col("aboveScaleYoy", "规上同比(%)", 110));
			SPLIT_COLUMNS.add(col("belowScaleFreight", "规下货运量(万吨)", 140));
			SPLIT_COLUMNS.add(col("belowScaleTurnover", "规下周转量(万吨公里)", 170));
			SPLIT_COLUMNS.add(col("belowScaleRank", "规下排名", 100));
			SPLIT_COLUMNS.add(col("belowScaleYoy", "规下同比", 100));
			SPLIT_COLUMNS.add(col("totalFreight", "合计货运量(来源文件未提供该列)", 220));
			SPLIT_COLUMNS.add(col("belowScaleRank", "规下排名(名)", 110));
			SPLIT_COLUMNS.add(col("belowScaleYoy", "规下同比(%)", 110));
			SPLIT_COLUMNS.add(col("totalFreight", "合计货运量(万吨)", 140));
			SPLIT_COLUMNS.add(col("totalTurnover", "合计周转量(万吨公里)", 170));
			SPLIT_COLUMNS.add(col("totalRank", "合计排名", 100));
			SPLIT_COLUMNS.add(col("totalYoy", "合计同比", 100));
			SPLIT_COLUMNS.add(col("totalRank", "合计排名(名)", 110));
			SPLIT_COLUMNS.add(col("totalYoy", "合计同比(%)", 110));

			FREIGHT_COLUMNS.add(col("reportPeriod", "报表期", 100));
			FREIGHT_COLUMNS.add(col("regionName", "市州", 130));
			for (int m = 1; m <= 12; m++) {
			FREIGHT_COLUMNS.add(col(String.format("freightM%02d", m), "货运量" + m + "月", 110));
			FREIGHT_COLUMNS.add(col(String.format("freightM%02d", m), "货运量" + m + "月(万吨)", 140));
			}
			for (int m = 1; m <= 12; m++) {
			FREIGHT_COLUMNS.add(col(String.format("lastFreightM%02d", m), "去年货运量" + m + "月", 130));
			FREIGHT_COLUMNS.add(col(String.format("lastFreightM%02d", m), "去年货运量" + m + "月(万吨)", 160));
			}
			for (int m = 1; m <= 12; m++) {
			FREIGHT_COLUMNS.add(col(String.format("turnoverM%02d", m), "周转量" + m + "月", 120));
			FREIGHT_COLUMNS.add(col(String.format("turnoverM%02d", m), "周转量" + m + "月(万吨公里)", 160));
			}
			for (int m = 1; m <= 12; m++) {
			FREIGHT_COLUMNS.add(col(String.format("lastTurnoverM%02d", m), "去年周转量" + m + "月", 140));
			FREIGHT_COLUMNS.add(col(String.format("lastTurnoverM%02d", m), "去年周转量" + m + "月(万吨公里)", 180));
			}

			H2031_COLUMNS.add(col("reportPeriod", "报表期", 100));
			@@ -620,37 +622,37 @@
			H2031_COLUMNS.add(col("enterpriseName", "企业名称", 220));
			H2031_COLUMNS.add(col("unifiedCreditCode", "统一社会信用代码", 180));
			H2031_COLUMNS.add(col("reportUnit", "填报单位", 160));
			H2031_COLUMNS.add(col("vehicleTotal", "客运车辆合计", 110));
			H2031_COLUMNS.add(col("seatTotal", "核定载客位合计", 130));
			H2031_COLUMNS.add(col("vehicleSchedule", "班线车辆数", 110));
			H2031_COLUMNS.add(col("seatSchedule", "班线载客位", 110));
			H2031_COLUMNS.add(col("vehicleCharter", "包车车辆数", 110));
			H2031_COLUMNS.add(col("seatCharter", "包车载客位", 110));
			H2031_COLUMNS.add(col("vehicleTotal", "客运车辆合计(辆)", 130));
			H2031_COLUMNS.add(col("seatTotal", "核定载客位合计(座)", 150));
			H2031_COLUMNS.add(col("vehicleSchedule", "班线车辆数(辆)", 130));
			H2031_COLUMNS.add(col("seatSchedule", "班线载客位(座)", 130));
			H2031_COLUMNS.add(col("vehicleCharter", "包车车辆数(辆)", 130));
			H2031_COLUMNS.add(col("seatCharter", "包车载客位(座)", 130));
			H2031_COLUMNS.add(col("passengerTotal", "客运量合计(人)", 130));
			H2031_COLUMNS.add(col("turnoverTotal", "周转量合计", 110));
			H2031_COLUMNS.add(col("passengerClass1", "客运量一类", 110));
			H2031_COLUMNS.add(col("passengerClass2", "客运量二类", 110));
			H2031_COLUMNS.add(col("passengerClass3", "客运量三类", 110));
			H2031_COLUMNS.add(col("passengerClass4", "客运量四类", 110));
			H2031_COLUMNS.add(col("passengerCharter", "客运量包车", 110));
			H2031_COLUMNS.add(col("turnoverClass1", "周转量一类", 110));
			H2031_COLUMNS.add(col("turnoverClass2", "周转量二类", 110));
			H2031_COLUMNS.add(col("turnoverClass3", "周转量三类", 110));
			H2031_COLUMNS.add(col("turnoverClass4", "周转量四类", 110));
			H2031_COLUMNS.add(col("turnoverCharter", "周转量包车", 110));
			H2031_COLUMNS.add(col("avgDistanceTotal", "平均运距合计", 120));
			H2031_COLUMNS.add(col("avgDistanceClass1", "一类平均运距", 120));
			H2031_COLUMNS.add(col("avgDistanceClass2", "二类平均运距", 120));
			H2031_COLUMNS.add(col("avgDistanceClass3", "三类平均运距", 120));
			H2031_COLUMNS.add(col("avgDistanceClass4", "四类平均运距", 120));
			H2031_COLUMNS.add(col("avgDistanceCharter", "包车平均运距", 120));
			H2031_COLUMNS.add(col("turnoverTotal", "周转量合计(人公里)", 140));
			H2031_COLUMNS.add(col("passengerClass1", "客运量一类(人)", 120));
			H2031_COLUMNS.add(col("passengerClass2", "客运量二类(人)", 120));
			H2031_COLUMNS.add(col("passengerClass3", "客运量三类(人)", 120));
			H2031_COLUMNS.add(col("passengerClass4", "客运量四类(人)", 120));
			H2031_COLUMNS.add(col("passengerCharter", "客运量包车(人)", 130));
			H2031_COLUMNS.add(col("turnoverClass1", "周转量一类(人公里)", 140));
			H2031_COLUMNS.add(col("turnoverClass2", "周转量二类(人公里)", 140));
			H2031_COLUMNS.add(col("turnoverClass3", "周转量三类(人公里)", 140));
			H2031_COLUMNS.add(col("turnoverClass4", "周转量四类(人公里)", 140));
			H2031_COLUMNS.add(col("turnoverCharter", "周转量包车(人公里)", 150));
			H2031_COLUMNS.add(col("avgDistanceTotal", "平均运距合计(公里)", 140));
			H2031_COLUMNS.add(col("avgDistanceClass1", "一类平均运距(公里)", 140));
			H2031_COLUMNS.add(col("avgDistanceClass2", "二类平均运距(公里)", 140));
			H2031_COLUMNS.add(col("avgDistanceClass3", "三类平均运距(公里)", 140));
			H2031_COLUMNS.add(col("avgDistanceClass4", "四类平均运距(公里)", 140));
			H2031_COLUMNS.add(col("avgDistanceCharter", "包车平均运距(公里)", 140));
			BUS_COLUMNS.add(col("reportPeriod", "报表期", 100));
			BUS_COLUMNS.add(col("regionCode", "所属地区", 100));
			BUS_COLUMNS.add(col("city", "市州", 110));
			BUS_COLUMNS.add(col("enterpriseName", "企业名称", 220));
			BUS_COLUMNS.add(col("opVehicles", "运营车数", 100));
			BUS_COLUMNS.add(col("stopTotal", "站点总个数", 110));
			BUS_COLUMNS.add(col("stopCity", "城市内站点", 110));
			BUS_COLUMNS.add(col("opVehicles", "运营车数(辆)", 120));
			BUS_COLUMNS.add(col("stopTotal", "站点总个数(个)", 130));
			BUS_COLUMNS.add(col("stopCity", "城市内站点(个)", 130));
			BUS_COLUMNS.add(col("passengerVolume", "客运量(万人次)", 120));
			BUS_COLUMNS.add(col("passengerCity", "城市内客运量(万人次)", 150));
			BUS_COLUMNS.add(col("turnover", "旅客周转量(万人公里)", 170));
			@@ -672,16 +674,16 @@
			TAXI_COLUMNS.add(col("reportPeriod", "报表期", 100));
			TAXI_COLUMNS.add(col("regionCode", "所属地区", 100));
			TAXI_COLUMNS.add(col("city", "市州", 110));
			TAXI_COLUMNS.add(col("tripTotal", "载客车次总数", 120));
			TAXI_COLUMNS.add(col("tripCity", "载客车次_城市内", 130));
			TAXI_COLUMNS.add(col("tripTotal", "载客车次总数(车次)", 150));
			TAXI_COLUMNS.add(col("tripCity", "载客车次_城市内(车次)", 160));
			TAXI_COLUMNS.add(col("passengerVolume", "客运量(万人次)", 120));
			TAXI_COLUMNS.add(col("passengerCity", "城市内客运量(万人次)", 150));
			TAXI_COLUMNS.add(col("turnover", "旅客周转量(万人公里)", 170));
			TAXI_COLUMNS.add(col("turnoverCity", "城市内周转量(万人公里)", 180));
			TAXI_COLUMNS.add(col("opVehicles", "运营车辆数", 110));
			TAXI_COLUMNS.add(col("opVehicles", "运营车辆数(辆)", 130));
			TAXI_COLUMNS.add(col("avgDistance", "平均运距(公里)", 120));
			TAXI_COLUMNS.add(col("avgDistanceCity", "城市内平均运距(公里)", 150));
			TAXI_COLUMNS.add(col("passengersPerTrip", "单车次载客人数", 130));
			TAXI_COLUMNS.add(col("passengersPerTrip", "单车次载客人数(人/车次)", 170));
			TAXI_COLUMNS.add(col("rateTripMom", "载客车次环比", 110));
			TAXI_COLUMNS.add(col("rateTripYoy", "载客车次同比", 110));
			TAXI_COLUMNS.add(col("ratePassengerMom", "客运量环比", 100));
			@@ -704,8 +706,8 @@
			PAUTH_COLUMNS.add(col("reportPeriod", "报表期", 100));
			PAUTH_COLUMNS.add(col("enterpriseCode", "企业代码", 130));
			PAUTH_COLUMNS.add(col("enterpriseName", "企业名称", 240));
			PAUTH_COLUMNS.add(col("vehicleCount", "车辆数", 100));
			PAUTH_COLUMNS.add(col("seatCount", "载客位数", 100));
			PAUTH_COLUMNS.add(col("vehicleCount", "车辆数(辆)", 110));
			PAUTH_COLUMNS.add(col("seatCount", "载客位数(座)", 120));
			INVEST_MONTHLY_COLUMNS.add(col("reportPeriod", "报表期", 100));
			INVEST_MONTHLY_COLUMNS.add(col("projectId", "项目ID", 80));
			INVEST_MONTHLY_COLUMNS.add(col("projectName", "项目名称", 280));
			@@ -716,7 +718,7 @@
			INVEST_MONTHLY_COLUMNS.add(col("startCum", "自开始建设累计完成(万元)", 180));
			INVEST_MONTHLY_COLUMNS.add(col("progressStage", "建设阶段", 120));
			INVEST_MONTHLY_COLUMNS.add(col("progressDesc", "形象进度", 320));
			INVEST_MONTHLY_COLUMNS.add(col("buildingArea", "建筑面积", 110));
			INVEST_MONTHLY_COLUMNS.add(col("buildingArea", "建筑面积(平方米)", 140));
			INVEST_PROJECT_COLUMNS.add(col("projectName", "项目名称", 260));
			INVEST_PROJECT_COLUMNS.add(col("category", "类别", 100));
			INVEST_PROJECT_COLUMNS.add(col("city", "市州", 90));
			@@ -726,7 +728,7 @@
			INVEST_PROJECT_COLUMNS.add(col("startTime", "开工年", 90));
			INVEST_PROJECT_COLUMNS.add(col("endTime", "完工年", 90));
			INVEST_PROJECT_COLUMNS.add(col("totalInvestment", "总投资(万元)", 130));
			INVEST_PROJECT_COLUMNS.add(col("buildingArea", "建筑面积", 110));
			INVEST_PROJECT_COLUMNS.add(col("buildingArea", "建筑面积(平方米)", 140));
			INVEST_PROJECT_COLUMNS.add(col("approvalGk", "工可或核准批复文号", 200));
			INVEST_PROJECT_COLUMNS.add(col("approvalCs", "初设或施工图批复文号", 200));
			INVEST_PROJECT_COLUMNS.add(col("source", "来源", 100));
			@@ -745,34 +747,34 @@
			ENERGY_VEHICLE_COLUMNS.add(col("vehicleType", "车辆类型", 130));
			ENERGY_VEHICLE_COLUMNS.add(col("fuelType", "燃料类型", 110));
			ENERGY_VEHICLE_COLUMNS.add(col("manufactureYear", "出厂年份", 100));
			ENERGY_VEHICLE_COLUMNS.add(col("markedTonnage", "标记吨位", 100));
			ENERGY_VEHICLE_COLUMNS.add(col("markedTonnage", "标记吨位(吨)", 120));
			ENERGY_VEHICLE_COLUMNS.add(col("totalMileage", "总行驶里程(公里)", 150));
			ENERGY_VEHICLE_COLUMNS.add(col("loadedMileage", "重载里程(公里)", 140));
			ENERGY_VEHICLE_COLUMNS.add(col("emptyMileage", "空载里程(公里)", 140));
			ENERGY_VEHICLE_COLUMNS.add(col("freight", "货运量(吨)", 120));
			ENERGY_VEHICLE_COLUMNS.add(col("turnover", "周转量(吨公里)", 140));
			ENERGY_VEHICLE_COLUMNS.add(col("tripCount", "车次", 90));
			ENERGY_VEHICLE_COLUMNS.add(col("tripCount", "车次(次)", 100));
			ENERGY_VEHICLE_COLUMNS.add(col("fuelUnit", "燃料单位", 100));
			ENERGY_VEHICLE_COLUMNS.add(col("fuelConsumption", "燃料消耗量", 120));
			ENERGY_VEHICLE_COLUMNS.add(col("avgDistance", "平均运距", 110));
			ENERGY_VEHICLE_COLUMNS.add(col("avgLoadedTonnage", "平均载重吨位", 130));
			ENERGY_VEHICLE_COLUMNS.add(col("avgTripMileage", "平均车次里程", 130));
			ENERGY_VEHICLE_COLUMNS.add(col("fuelPer100km", "百公里油耗", 120));
			ENERGY_VEHICLE_COLUMNS.add(col("turnoverFuel", "周转量油耗", 120));
			ENERGY_VEHICLE_COLUMNS.add(col("fuelConsumption", "燃料消耗量(按燃料单位)", 170));
			ENERGY_VEHICLE_COLUMNS.add(col("avgDistance", "平均运距(公里)", 130));
			ENERGY_VEHICLE_COLUMNS.add(col("avgLoadedTonnage", "平均载重吨位(吨)", 150));
			ENERGY_VEHICLE_COLUMNS.add(col("avgTripMileage", "平均车次里程(公里)", 150));
			ENERGY_VEHICLE_COLUMNS.add(col("fuelPer100km", "百公里油耗(按燃料单位)", 170));
			ENERGY_VEHICLE_COLUMNS.add(col("turnoverFuel", "周转量油耗(按燃料单位)", 170));
			ENERGY_AUTH_COLUMNS.add(col("reportPeriod", "报表期", 100));
			ENERGY_AUTH_COLUMNS.add(col("plateNo", "车牌号", 110));
			ENERGY_AUTH_COLUMNS.add(col("vehicleType", "车辆类型", 130));
			ENERGY_AUTH_COLUMNS.add(col("fuelType", "燃料类型", 110));
			ENERGY_AUTH_COLUMNS.add(col("markedTonnage", "标记吨位", 100));
			ENERGY_AUTH_COLUMNS.add(col("tractionQuality", "牵引质量", 110));
			ENERGY_AUTH_COLUMNS.add(col("markedTonnage", "标记吨位(吨)", 120));
			ENERGY_AUTH_COLUMNS.add(col("tractionQuality", "牵引质量(吨)", 130));

			PAX_INDIVIDUAL_COLUMNS.add(col("reportPeriod", "报表期", 100));
			PAX_INDIVIDUAL_COLUMNS.add(col("regionCode", "所属地区", 110));
			PAX_INDIVIDUAL_COLUMNS.add(col("city", "市州", 110));
			PAX_INDIVIDUAL_COLUMNS.add(col("enterpriseCode", "企业代码", 130));
			PAX_INDIVIDUAL_COLUMNS.add(col("enterpriseName", "企业名称", 220));
			PAX_INDIVIDUAL_COLUMNS.add(col("passengerCount", "个体客运量", 130));
			PAX_INDIVIDUAL_COLUMNS.add(col("turnover", "个体旅客周转量", 150));
			PAX_INDIVIDUAL_COLUMNS.add(col("passengerCount", "个体客运量(人)", 140));
			PAX_INDIVIDUAL_COLUMNS.add(col("turnover", "个体旅客周转量(人公里)", 180));

			WYC_TOTAL_COLUMNS.add(col("reportPeriod", "报表期", 100));
			WYC_TOTAL_COLUMNS.add(col("pinK", "全省网约车客运量(万人次)", 210));

			@@ -27,6 +27,14 @@
			<el-option v-for="t in g.types" :key="t.value" :label="t.label" :value="t.value"></el-option>
			</el-option-group>
			</el-select>
			<template v-if="hasPeriodType">
			<span class="toolbar-label">口径</span>
			<el-select v-model="periodType" size="small" style="width:110px" @change="doQuery">
			<el-option label="全部" value=""></el-option>
			<el-option label="当月" value="MONTH"></el-option>
			<el-option label="累计" value="CUMULATIVE"></el-option>
			</el-select>
			</template>
			<el-input v-model="keyword" placeholder="企业/市州名称" clearable style="width:180px" @keyup.enter.native="doQuery"></el-input>
			<el-button type="primary" size="small" @click="doQuery">查询</el-button>
			<el-button size="small" icon="el-icon-full-screen" @click="toggleFullscreen">全屏查看</el-button>
			@@ -99,6 +107,7 @@
			activeModule: 'freight',
			type: 'h2032',
			period: '',
			periodType: '',
			keyword: '',
			page: 1,
			size: 50,
			@@ -110,6 +119,10 @@
			}
			},
			computed: {
			// 规上规下拆分等表有"口径"列（当月/累计），把它做成上方筛选而不是表格列
			hasPeriodType() {
			return (this.columns \|\| []).some(c => c.prop === 'periodType')
			},
			currentTypeLabel() {
			for (const g of this.modules) {
			const t = g.types.find(x => x.value === this.type)
			@@ -140,8 +153,10 @@
			// 数据查看统一列过滤：内部标识列不展示；报表期（由筛选条件体现）与所属地区（区划代码，已被市州列替代）不展示
			keepColumn(c) {
			if (!c) return false
			const hiddenProps = ['enterpriseCode', 'unifiedCreditCode', 'reportUnit', 'projectId', 'regionCode', 'reportPeriod']
			const hiddenLabels = ['企业代码', '统一社会信用代码', '填报单位', '项目ID', '所属地区', '报表期']
			// 口径列上移为筛选；拆分表货运量三列源文件未提供（全空）故不展示
			const hiddenProps = ['enterpriseCode', 'unifiedCreditCode', 'reportUnit', 'projectId', 'regionCode', 'reportPeriod',
			'periodType', 'aboveScaleFreight', 'belowScaleFreight', 'totalFreight']
			const hiddenLabels = ['企业代码', '统一社会信用代码', '填报单位', '项目ID', '所属地区', '报表期', '口径']
			if (hiddenProps.indexOf(c.prop) >= 0 \|\| hiddenLabels.indexOf(c.label) >= 0) return false
			return true
			},
			@@ -156,6 +171,7 @@
			onTypeSelect() {
			const g = this.modules.find(x => x.types.some(t => t.value === this.type))
			if (g) this.activeModule = g.key
			this.periodType = ''
			this.doQuery()
			},
			doQuery() {
			@@ -171,13 +187,14 @@
			type: this.type,
			period: this.period \|\| undefined,
			keyword: this.keyword \|\| undefined,
			periodType: this.periodType \|\| undefined,
			page: this.page,
			size: this.size
			}
			}).then(res => {
			const d = res.data \|\| {}
			this.records = d.records \|\| []
			this.columns = (d.columns \|\| []).filter(c => ['enterpriseCode', 'unifiedCreditCode', 'reportUnit'].indexOf(c.prop) < 0 && ['企业代码', '统一社会信用代码', '填报单位'].indexOf(c.label) < 0)
			this.columns = d.columns \|\| []
			this.total = d.total \|\| 0
			if (this.page > 1 && this.records.length === 0) {
			this.page = 1
			@@ -213,6 +230,7 @@
			type: this.type,
			period: this.period \|\| undefined,
			keyword: this.keyword \|\| undefined,
			periodType: this.periodType \|\| undefined,
			page: nextPage,
			size: this.size
			}
			@@ -226,7 +244,7 @@
			this.records = this.records.concat(addRows)
			this.page = nextPage
			if (d.total != null) this.total = d.total
			if (d.columns && d.columns.length) this.columns = d.columns.filter(c => ['enterpriseCode', 'unifiedCreditCode', 'reportUnit'].indexOf(c.prop) < 0 && ['企业代码', '统一社会信用代码', '填报单位'].indexOf(c.label) < 0)
			if (d.columns && d.columns.length) this.columns = d.columns
			}).catch(e => {
			if (e && e._toast) return
			this.$message.error('加载更多失败')