data = data[(data['mon_day']>=1210) | (data['mon_day']<=430)].copy() data['Year_new'] = np.where(data['mon_day']<=430,data['Year']-1,data['Year']) out_dw = pd.DataFrame(columns={'年'}) for iyear in range(styr,edyr+1): wka = data[data['Year_new']==iyear].copy() diff_max = 0 stdate = 0 for i in range(0,len(wka)-2): t_1 = wka.iloc[i]['TEM_Min'] t_2 = wka.iloc[i+1]['TEM_Min'] t_3 = wka.iloc[i+2]['TEM_Min'] diff = max(t_1-t_2,t_1-t_3,t_2-t_3) if diff > diff_max: diff_max = diff stdate = wka.iloc[i]['date'] out_dw = out_dw.append({'年':wka.iloc[0]['Year_new'],'stdate':stdate,'diff':diff_max},ignore_index=True)转成R代码

时间: 2023-06-15 12:07:07 浏览: 47
data <- data[(data$mon_day>=1210) | (data$mon_day<=430),] data$Year_new <- ifelse(data$mon_day<=430, data$Year-1, data$Year) out_dw <- data.frame(matrix(ncol = 2, nrow = 0)) colnames(out_dw) <- c("年", "stdate") for (iyear in styr:edyr) { wka <- data[data$Year_new == iyear,] diff_max <- 0 stdate <- 0 for (i in 1:(nrow(wka)-2)) { t_1 <- wka[i, "TEM_Min"] t_2 <- wka[i+1, "TEM_Min"] t_3 <- wka[i+2, "TEM_Min"] diff <- max(t_1-t_2, t_1-t_3, t_2-t_3) if (diff > diff_max) { diff_max <- diff stdate <- wka[i, "date"] } } out_dw <- rbind(out_dw, c(iyear, stdate)) } colnames(out_dw) <- c("年", "stdate", "diff") # 如果需要 diff 列，可以添加该行代码
相关问题

<body> <eqp_id></eqp_id> <sub_eqp_id></sub_eqp_id> <trace_data_list> <trace_data> <data_item></data_item> <data_value></data_value> </trace_data> <trace_data> <data_item></data_item> <data_value></data_value> </trace_data> </trace_data_list> </body> 设计实体类

根据您提供的XML，可以设计以下Java实体类： ```java import java.util.List; public class Body { private String eqpId; private String subEqpId; private List<TraceData> traceDataList; public String getEqpId() { return eqpId; } public void setEqpId(String eqpId) { this.eqpId = eqpId; } public String getSubEqpId() { return subEqpId; } public void setSubEqpId(String subEqpId) { this.subEqpId = subEqpId; } public List<TraceData> getTraceDataList() { return traceDataList; } public void setTraceDataList(List<TraceData> traceDataList) { this.traceDataList = traceDataList; } } public class TraceData { private String dataItem; private String dataValue; public String getDataItem() { return dataItem; } public void setDataItem(String dataItem) { this.dataItem = dataItem; } public String getDataValue() { return dataValue; } public void setDataValue(String dataValue) { this.dataValue = dataValue; } } ``` 在`Body`类中，我们使用了`eqpId`和`subEqpId`字段来表示`eqp_id`和`sub_eqp_id`元素的值。`traceDataList`字段是一个`List`类型，其中包含多个`TraceData`对象，每个`TraceData`对象表示一个`trace_data`元素。在`TraceData`类中，我们使用了`dataItem`和`dataValue`字段来表示`data_item`和`data_value`元素的值。

data <- data[(data$mon_day>=1210) | (data$mon_day<=430),] data$Year_new <- ifelse(data$mon_day<=430, data$Year-1, data$Year) out_dw <- data.frame(matrix(ncol = 2, nrow = 0)) colnames(out_dw) <- c("年", "stdate")这段代码什么意思

这段代码的作用是对一个数据框进行操作，具体解释如下： 1. 第一行代码是筛选数据的操作，将数据框中mon_day列大于等于1210或者小于等于430的行保留下来，其余行删除。 2. 第二行代码是根据mon_day列的值来对数据进行分类，如果mon_day列的值小于等于430，那么将Year列的值减1，并将结果赋值给Year_new列；否则将Year列的值赋值给Year_new列。 3. 第三行代码是创建一个空的数据框out_dw，包含两列，列名为“年”和“stdate”。 这段代码的作用是对时间数据进行处理，将数据根据mon_day列的值分类，并将处理后的结果保存到新的数据框中。

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