Here's my dataframe "fulldays" (The column header Plastic refers to the second column of numbers, the first column is just a numbered list of the rows that R puts in that I didn't know how to remove):
Plastic Age Ones Zeros Nonzeros CellsCounted AllDaysAvail
1 2 10 2 5 5 10 TRUE
2 57 8 4 2 8 10 TRUE
3 3 9 2 4 6 10 TRUE
4 81 9 3 1 9 10 TRUE
5 131 20 8 1 9 10 TRUE
6 5 8 5 5 5 10 TRUE
7 26 10 4 4 6 10 TRUE
8 76 12 2 6 4 10 TRUE
9 9 9 8 2 8 10 TRUE
10 36 14 2 5 5 10 TRUE
11 64 12 3 4 6 10 TRUE
12 74 22 5 4 6 10 TRUE
13 10 10 1 4 6 10 TRUE
14 21 9 7 3 7 10 TRUE
15 16 9 5 3 7 10 TRUE
17 18 8 4 3 7 10 TRUE
18 23 22 6 4 6 10 TRUE
19 106 11 2 1 9 10 TRUE
20 113 9 1 4 6 10 TRUE
21 24 11 2 5 5 10 TRUE
22 29 9 3 2 8 10 TRUE
23 85 9 6 4 6 10 TRUE
24 403 19 1 6 4 10 TRUE
25 25 19 1 2 8 10 TRUE
26 27 10 3 3 7 10 TRUE
27 121 7 7 3 7 10 TRUE
29 35 12 1 4 6 10 TRUE
30 39 18 2 6 4 10 TRUE
31 37 8 5 1 9 10 TRUE
32 63 7 8 2 8 10 TRUE
33 122 11 3 2 8 10 TRUE
34 148 9 4 4 6 10 TRUE
37 42 13 2 3 7 10 TRUE
38 144 12 0 9 1 10 TRUE
39 43 12 1 2 8 10 TRUE
40 47 20 6 4 6 10 TRUE
41 90 12 2 5 5 10 TRUE
42 119 12 2 4 6 10 TRUE
43 138 7 7 3 7 10 TRUE
44 56 4 7 3 7 10 TRUE
45 58 12 2 5 5 10 TRUE
46 60 22 3 4 6 10 TRUE
47 71 9 2 5 5 10 TRUE
48 288 18 0 10 0 10 TRUE
49 66 22 1 5 5 10 TRUE
50 67 9 0 8 2 10 TRUE
51 149 12 0 5 5 10 TRUE
52 70 14 5 4 6 10 TRUE
53 72 12 1 4 6 10 TRUE
54 78 12 0 4 6 10 TRUE
59 79 12 4 3 7 10 TRUE
60 83 11 4 4 6 10 TRUE
61 87 8 6 4 6 10 TRUE
63 92 11 1 4 6 10 TRUE
64 96 8 0 5 5 10 TRUE
65 125 7 7 3 7 10 TRUE
66 98 9 3 4 6 10 TRUE
67 107 6 2 3 7 10 TRUE
68 102 11 5 3 7 10 TRUE
69 103 10 0 1 9 10 TRUE
72 108 12 3 3 7 10 TRUE
73 153 12 4 3 7 10 TRUE
74 109 12 3 4 6 10 TRUE
75 118 10 4 5 5 10 TRUE
77 133 12 0 4 6 10 TRUE
79 157 8 0 10 0 10 TRUE
81 318 14 2 5 5 10 TRUE
I have this code:
new_data <- fulldays %>%
group_by(Age) %>%
summarize(OnesMean=mean(Ones), ZerosMean=mean(Zeros), NonZeroMean=mean(Nonzeros))
This is the output "new_data" (again, Age starts on the second column, not the first):
Age OnesMean ZerosMean NonZeroMean
<int> <dbl> <dbl> <dbl>
1 4 7 3 7
2 6 2 3 7
3 7 7.25 2.75 7.25
4 8 3.43 4.29 5.71
5 9 3.67 3.67 6.33
6 10 2.33 3.67 6.33
7 11 2.83 3.17 6.83
8 12 1.75 4.31 5.69
9 13 2 3 7
10 14 3 4.67 5.33
11 18 1 8 2
12 19 1 4 6
13 20 7 2.5 7.5
14 22 3.75 4.25 5.75
I have three questions:
- Why is groupby creating a tibble and not a dataframe?
- Why when I click on "new_data" as an object in the "Data" section does it display the values with so many decimal places (see image below)? [1]: https://i.stack.imgur.com/724G9.png
- How can I add/bind a column to new_data that shows the sample size for each age? In other words, I want to know how many of each individual is contributing to the mean score for each column (ideally I would add this column between "Age" and "OnesMean")
Thank you so much, and please let me know if there are any questions!
CodePudding user response：
tidyverseworks withtibbles, which are stilldata.frames with a couple of differences. So when you usedplyrfunctions on adata.frame, it will become atibbledata.frame.- The
meanfunction doesn't round the result. If you want them to be rounded, you need to ask R to do that, withOnesMean = round(mean(Ones), 2), for example. - You add
n()as one of the arguments ofsummarise(). That is,summarise(OnesMean = mean(Ones), <...>, n()).