学习小组Day6-微冷凉了三分情

主要内容

Day6-学习R包.png

实际操作

1. 打开R自带数据集

library(dplyr)
airquality=tbl_df(airquality) #airquality为R自带数据集
df <- tbl_df(airquality)
df
# A tibble: 153 x 6
   Ozone Solar.R  Wind  Temp Month   Day
   <int>   <int> <dbl> <int> <int> <int>
 1    41     190  7.40    67     5     1
 2    36     118  8.00    72     5     2
 3    12     149 12.6     74     5     3
 4    18     313 11.5     62     5     4
 5    NA      NA 14.3     56     5     5
 6    28      NA 14.9     66     5     6
 7    23     299  8.60    65     5     7
 8    19      99 13.8     59     5     8
 9     8      19 20.1     61     5     9
10    NA     194  8.60    69     5    10
# ... with 143 more rows

2. muture变形

mutate(airquality,Temp_C = (Temp - 30) / 1.5)
# A tibble: 153 x 7
   Ozone Solar.R  Wind  Temp Month   Day Temp_C
   <int>   <int> <dbl> <int> <int> <int>  <dbl>
 1    41     190   7.4    67     5     1   24.7
 2    36     118   8      72     5     2   28  
 3    12     149  12.6    74     5     3   29.3
 4    18     313  11.5    62     5     4   21.3
 5    NA      NA  14.3    56     5     5   17.3
 6    28      NA  14.9    66     5     6   24  
 7    23     299   8.6    65     5     7   23.3
 8    19      99  13.8    59     5     8   19.3
 9     8      19  20.1    61     5     9   20.7
10    NA     194   8.6    69     5    10   26  
# ... with 143 more rows

3. select选择

select(df,1)
# A tibble: 153 x 1
   Ozone
   <int>
 1    41
 2    36
 3    12
 4    18
 5    NA
 6    28
 7    23
 8    19
 9     8
10    NA
# ... with 143 more rows

4. filter筛选

filter(df,Temp < 60 & Wind > 15)
filter(df,Temp > 60)

5. arrange排列

arrange(df,Wind,Temp_C)
arrange(df,desc(Wind))

6. 管道操作

airquality %>% 
+     group_by(Month) %>% 
+     summarise(mean_temp=mean(Temp)) %>% 
+     arrange(mean_temp)