# 使用 pivot_longer 将宽格式数据转换为长格式 long_data <- wide_data %>% pivot_longer( cols = starts_with("var"), # 选择以 "var" 开头的列 names_to = "variable", # 新列名,存储原始列名 values_to = "value" # 新列名,存储原始值 ) print(long_data) 输出结果 代码语言:txt 复制 # ...
使用R中的pivot_longer()函数可以将数据从宽格式转换为长格式,同时将两个内部因子存储在一个变量中。 pivot_longer()函数是tidyverse包中的tidyr库提供的一个功能强大的函数,用于数据重塑和变换。它可以将宽格式的数据转换为长格式,使得数据更易于分析和可视化。 在使用pivot_longer()函数时,...
使用pivot_longer函数,从而实现宽表变长表,这已经是一个共识。注意函数使用细节则能够更加高效。 (1) 查看说明: # See vignette("pivot") for examples and explanation 结果: (2) 函数说明: pivot_longer( data, cols, ..., cols_vary = "fastest", names_to = "name", names_prefix = NULL, names_...
x <- x |> pivot_longer(cols = starts_with("kpu_"), names_prefix = "kpu_", names_to = "unit", values_to = "n_unit") |> pivot_longer(cols = starts_with("sf_"), names_prefix = "sf_", names_to = "unit2", values_to = "sf_unit") 还有另一个: x <- x |> pivot_...
pivot_longer,列上有多个时间变量您可以在pivot_longer的names_to参数中使用特殊的".value"来实现所需...
pivot_longer()"lengthens"数据,增加行数并减少列数。逆变换为pivot_wider() 在vignette("pivot")中了解更多信息。 用法 pivot_longer( data, cols,..., cols_vary ="fastest", names_to ="name", names_prefix =NULL, names_sep =NULL, names_pattern =NULL, ...
Using pivot_longer(), you can reshape this data into a more manageable format. Code: long_data_product <- pivot_longer(wide_data, cols = starts_with("Sales") | starts_with("Price"), names_to = c(".value", "Year"), names_pattern = "([A-Za-z]+)_(\\d+)") print(long_data...
survey_data_long <- pivot_longer(survey_data, cols = starts_with("Q"), names_to = "Question", values_to = "Response") In this example, the `starts_with` function is used to identify all columns starting with "Q," which are then melted using the pivot_longer function. The resulting...
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