# 使用变量列表过滤数据 filter_condition <- c("age > 25") df_filtered <- df %>% filter(eval(parse(text = paste(filter_condition, collapse = " & "))) print(df_filtered) 变换列 代码语言:txt 复制 # 使用变量列表变换列 transform_columns <- c("salary") df_transformed <- df %>% mut...
group_by(column_name):根据 column_name 列的值对数据框进行分组。 filter(row_number() == 1):在每个分组内,只保留第一行(即唯一项)。 ungroup():取消分组,以便后续操作不受分组影响。 参考链接 dplyr 官方文档 R 语言数据框操作教程 通过这种方式,你可以使用 dplyr 包有条件地筛选出数据框中的唯一项。
select(iris, -starts_with("Petal")) select(iris, -ends_with("Width")) select(iris, -contains("etal")) select(iris, -matches(".t.")) select(iris, -Petal.Length, -Petal.Width) # Rename variables: # * select() keeps only the variables you specify select(iris, petal_length = Petal...
]# dplyr approach# note: you can use comma or ampersand to represent AND conditionfilter(flights,Month==1,DayofMonth==1)# use pipe for OR conditionfilter(flights,UniqueCarrier=="AA"|UniqueCarrier=="UA")# you can also use %in% operatorfilter(flights,UniqueCarrier%in%c("AA...
()operate on a subset of columns. These columuns are selected with either a character vector of columns names, a numeric vector of column positions, or a column specification withselect()semantics generated by the newcolumns()helper. In addition,summarise_if()andmutate_if()take a predicate ...
Consider this example of choosing columns a and b from the dataframe df # Without the %>% operator select(df, a, b) # By using the %>% operator df %>% select(a, b) Powered By Dataset used throughout this cheat sheet Throughout this cheat sheet, we will be using this example ...
case_when always tests the commands even the condition don't meet #6250 opened 5 days ago by seahearman Consider updating if_else() feature funs 😆 #6243 opened 7 days ago by hadley first(), last(), and nth() should have na.rm argument feature funs 😆 #6242 opened 7 days ...
select()Selecting columns (variables)SELECT filter()Filter (subset) rows.WHERE group_by()Group the dataGROUP BY summarise()Summarise (or aggregate) data- arrange()Sort the dataORDER BY join()Joining data frames (tables)JOIN mutate()Creating New VariablesCOLUMN ALIAS ...
语法:select(filter(df, condition, columns) 参数: df: dataframe对象 条件:过滤条件 columns:要打印的列名向量 filter() 的工作方式与上面给出的几乎相同,唯一的区别是我们在第二个参数中传递的列名向量。这仅打印在 select 函数中传递的列。这样我们就可以只打印选中的列了。
This is what we mean when we say the DT[i, j, by] form is consistent. Similarly in case (c), when we have if-else condition, we are able to express the logic "as-is" in both data.table and dplyr. However, if we would like to return just those rows where the i...