Select
基本格式：
counties %>%
select(字段)
可以用冒号来选择一个范围内的字段：
counties %>%
select(state, county, population, professional:production)
还可以用start_with, ends_with, contain 等等模糊匹配字段：
counties %>%
select(state, county, population, ends_with("work"))
Filter
基本格式：
counties %>%
filter(条件)
in的使用：
selected_names <- babynames %>%
filter(name %in% c("Steven", "Thomas", "Matthew"))
Arrange
按哪些字段排序，基本格式：
counties %>%
arrange(字段) ---默认为升序
arrange(desc(字段)) ---降序
Mutate
添加新字段，基本格式：
counties %>%
mutate(字段 = xxxxx)
Transmute
选择就字段且添加新字段，基本格式：
counties %>%
transmute(旧字段，新字段 = xxxxx)
Rename
字段重命名，基本格式：
counties %>%
rename(新字段名 = 旧字段名)
也可以在select里，选取的时候直接重命名：
counties %>%
select(字段......，新字段名 = 旧字段名)
混合使用示例
counties %>%
# Select the five columns
select(state, county, population, men, women) %>%
# Add the proportion_men variable
mutate(proportion_men = men/population) %>%
# Filter for population of at least 10,000
filter(population >= 10000) %>%
# Arrange proportion of men in descending order
arrange(desc(proportion_men))
下面开始聚合函数喽！
Count
按字段分组，数每个分组下的个数，基本格式：
counties_selected %>%
count(region, sort = TRUE)
可加入权重wt，按字段1分组，数每个分组下的字段2总数，基本格式：
counties_selected %>%
count(state, wt = citizens, sort = TRUE)
相当于：
counties_selected %>%
group_by(state) %>%
summarise(sum(citizens))
Group_by
按字段分组，基本格式：
counties_selected %>%
group_by(字段)
Ungroup
取消分组（一般是为了另外再进行其他的计算），基本格式：
counties_selected %>%
group_by(字段) %>%
计算1 %>%
ungroup() %>%
计算2
例子：
# Count the states with more people in Metro or Nonmetro areas
counties_selected %>%
group_by(state, metro) %>%
summarize(total_pop = sum(population)) %>%
top_n(1, total_pop) %>%
ungroup() %>%
count(metro)
# Find the year each name is most common
babynames %>%
group_by(year) %>%
mutate(year_total = sum(number)) %>%
ungroup() %>%
mutate(fraction = number / year_total) %>%
group_by(name) %>%
top_n(1, fraction)
Summarise
计算字段的聚合函数值，基本格式：
counties_selected %>%
summarize(新字段名1 = min(字段1)，新字段名2 = max(字段2)，…… )
例子：
# Add a density column, then sort in descending order
counties_selected %>%
group_by(state) %>%
summarize(total_area = sum(land_area),
total_population = sum(population)) %>%
mutate(density = total_population / total_area) %>%
arrange(desc(density))
# Calculate the average_pop and median_pop columns
counties_selected %>%
group_by(region, state) %>%
summarize(total_pop = sum(population)) %>%
summarize(average_pop = mean(total_pop),
median_pop = median(total_pop))
注意：上一行的计算结果可以马上给下一行计算哦！
Top_n
只按字段2取最高的n个值，常配合分组使用。基本格式：
counties_selected %>%
group_by(字段1) %>%
top_n(个数, 字段2)
例子：
counties_selected %>%
group_by(region, state) %>%
# Calculate average income
summarize(average_income = mean(income)) %>%
# Find the highest income state in each region
top_n(1, average_income)
