blocks|key|1574966|text|这将计算stim_ending_t+(6)+x+modality+(3)+=+18组均值。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1574967|首先，我生成一些数据，比如您的analysis_v或analysis_a数据帧：|offset|length|style|CODE|1574968|library(dplyr)
library(tidyr)

analysis_v+<-+data.frame(stim_ending_t+=+rep(seq(1,+3.5,+0.5),+each+=+30),+
+++++++++++++++++++++++++visbility+=+rep(c(1,+0,+0),+60),+
+++++++++++++++++++++++++soundvolume+=+rep(c(0,+1,+0),+60),+
+++++++++++++++++++++++++key_resp_2.rt+=+runif(180,+1,+5))|code-block|syntax|javascript|1574969|然后我通过管道将对象放入代码块中：|1574970|analysis_v+%25>%25+
++group_by(stim_ending_t,+visbility,+soundvolume)+%25>%25+
++summarize(average+=+mean(key_resp_2.rt))+%25>%25+
++ungroup()+%25>%25+
++mutate(key+=+case_when(visbility+==+0+&+soundvolume+==+0+~+"blank",+
+++++++++++++++++++++++++visbility+==+0+&+soundvolume+==+1+~+"only_sound",+
+++++++++++++++++++++++++visbility+==+1+&+soundvolume+==+0+~+"only_images"))+%25>%25+
++select(-visbility,+-soundvolume)+%25>%25+
++spread(key,+average)|1574971|这将导致所请求的输出格式：|1574972|#+A+tibble:+6+x+4
++stim_ending_t+blank+only_images+only_sound
++++++++++<dbl>+<dbl>+++++++<dbl>++++++<dbl>
1+++++++++++1++++3.28++++++++3.55+++++++2.84
2+++++++++++1.5++2.64++++++++3.11+++++++2.32
3+++++++++++2++++3.27++++++++3.72+++++++2.42
4+++++++++++2.5++2.14++++++++3.01+++++++2.30
5+++++++++++3++++2.47++++++++3.03+++++++3.02
6+++++++++++3.5++2.93++++++++2.92+++++++2.78|1574973|您需要使用analysis_a重复代码块才能获得这些方法。|1574974|entityMap^0|0|F|A|Q|A|0|0|0|0|0|0|5|A|0^^$0|@$1|2|3|4|5|6|7|Y|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|Z|8|@$D|10|E|11|F|G]|$D|12|E|13|F|G]]|9|@]|A|$]]|$1|H|3|I|5|J|7|14|8|@]|9|@]|A|$K|L]]|$1|M|3|N|5|6|7|15|8|@]|9|@]|A|$]]|$1|O|3|P|5|J|7|16|8|@]|9|@]|A|$K|L]]|$1|Q|3|R|5|6|7|17|8|@]|9|@]|A|$]]|$1|S|3|T|5|J|7|18|8|@]|9|@]|A|$K|L]]|$1|U|3|V|5|6|7|19|8|@$D|1A|E|1B|F|G]]|9|@]|A|$]]|$1|W|3|-4|5|6|7|1C|8|@]|9|@]|A|$]]]|X|$]]

This will compute stim_ending_t (6) x modality (3) = 18 group means.

First I generate some data like your <code>analysis_v</code> or <code>analysis_a</code> data frames:

<pre><code>library(dplyr)
library(tidyr)

analysis_v &lt;- data.frame(stim_ending_t = rep(seq(1, 3.5, 0.5), each = 30), 
 visbility = rep(c(1, 0, 0), 60), 
 soundvolume = rep(c(0, 1, 0), 60), 
 key_resp_2.rt = runif(180, 1, 5))
</code></pre>

Then I pipe the object into the code block:

<pre><code>analysis_v %&gt;% 
 group_by(stim_ending_t, visbility, soundvolume) %&gt;% 
 summarize(average = mean(key_resp_2.rt)) %&gt;% 
 ungroup() %&gt;% 
 mutate(key = case_when(visbility == 0 &amp; soundvolume == 0 ~ "blank", 
 visbility == 0 &amp; soundvolume == 1 ~ "only_sound", 
 visbility == 1 &amp; soundvolume == 0 ~ "only_images")) %&gt;% 
 select(-visbility, -soundvolume) %&gt;% 
 spread(key, average)
</code></pre>

Which results in the requested output format:

<pre><code># A tibble: 6 x 4
 stim_ending_t blank only_images only_sound
 &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt;
1 1 3.28 3.55 2.84
2 1.5 2.64 3.11 2.32
3 2 3.27 3.72 2.42
4 2.5 2.14 3.01 2.30
5 3 2.47 3.03 3.02
6 3.5 2.93 2.92 2.78
</code></pre>

You would need to repeat the code block using <code>analysis_a</code> to get those means.

blocks|key|1790051|text|感谢您的帮助@Matthew+Schuelke，但是使用您的代码，我每次运行代码时都会得到不同的结果。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1790052|下面是我用下面的代码解决这个问题的方法：|1790053|name+of+the+new+data+=+(name+of+the+data+frame+without+the+parentheses)+%25>%25
++group_by(stim_ending_t,+visbility,+soundvolume,+Opening_text)+%25>%25
++summarize(m+=+mean(key_resp_2.rt),
++++++++++++sd+=+sd(key_resp_2.rt),
++++++++++++coefVar+=+cv(key_resp_2.rt))|code-block|syntax|javascript|1790054|得到了我想要的结果：|1790055|stim_ending_t+visbility+soundvolume+Opening_text+++++++++++++++m+++++sd+coefVar
++++++++++<dbl>+++++<dbl>+++++++<dbl>+<chr>++++++++++++++++++<dbl>++<dbl>+++<dbl>
1+++++++++++++1+++++++++0+++++++++++0+Now+focus+on+the+Image++1.70++1.14++++0.670
2+++++++++++++1+++++++++0+++++++++++0+Now+focus+on+the+Sound++1.57++0.794+++0.504
3+++++++++++++1+++++++++0+++++++++++1+Now+focus+on+the+Image++1.62++1.25++++0.772
4+++++++++++++1+++++++++0+++++++++++1+Now+focus+on+the+Sound++1.84++1.17++++0.637
5+++++++++++++1+++++++++1+++++++++++0+Now+focus+on+the+Image++3.19+17.2+++++5.38+
6+++++++++++++1+++++++++1+++++++++++0+Now+focus+on+the+Sound++1.59++0.706+++0.444|1790056|entityMap^0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|P|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|Q|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|R|8|@]|9|@]|A|$]]|$1|K|3|L|5|F|7|S|8|@]|9|@]|A|$G|H]]|$1|M|3|-4|5|6|7|T|8|@]|9|@]|A|$]]]|N|$]]

Thank you for your help @Matthew Schuelke, but with your code I was getting different results every time I run the code. 

Here is how I solved the problem with this code:

<pre><code>name of the new data = (name of the data frame without the parentheses) %&gt;%
 group_by(stim_ending_t, visbility, soundvolume, Opening_text) %&gt;%
 summarize(m = mean(key_resp_2.rt),
 sd = sd(key_resp_2.rt),
 coefVar = cv(key_resp_2.rt))
</code></pre>

The result as I wanted: 

<pre><code>stim_ending_t visbility soundvolume Opening_text m sd coefVar
 &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;chr&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt;
1 1 0 0 Now focus on the Image 1.70 1.14 0.670
2 1 0 0 Now focus on the Sound 1.57 0.794 0.504
3 1 0 1 Now focus on the Image 1.62 1.25 0.772
4 1 0 1 Now focus on the Sound 1.84 1.17 0.637
5 1 1 0 Now focus on the Image 3.19 17.2 5.38 
6 1 1 0 Now focus on the Sound 1.59 0.706 0.444
</code></pre>

I am trying to calculate the means of this data frame and group them in a tale! I know how to do that using averageifs in excel but because I want to eventually get the standard deviation and coefficient of variation (CV) I need to learn that in R. 

For now I just need the mean. Here are my conditions: 

I need a table where the "stim_ending_t" which is my time intervals are arranged from 1.0 to 3.5 in a rows. For time intervals I need these three conditions to be met while calculating the mean which is "key_resp_2.rt"

only image Visibility and soundvolume(V=1 &amp; s=0) 

Only Sound (V=0 &amp; s=1)

Blank (V=0 &amp; s=0)

<a href="https://i.stack.imgur.com/Ext55.png" rel="nofollow noreferrer">The data frame</a>

<a href="https://i.stack.imgur.com/vIZeH.png" rel="nofollow noreferrer">Expected out come</a>

How to calculate the mean in R with several conditions

我正在尝试计算这个数据帧的均值，并将它们分组到一个故事中！我知道如何在excel中使用averageifs，但因为我想最终得到标准差和变异系数(CV)，所以我需要在R中学习。现在我只需要中庸之道。以下是我的条件：我需要一个表，其中的"stim_ending_t“，即我的时间间隔是从1.0到3.5排成一行的。对于时间间隔...

问如何在几个条件下计算R中的平均值
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