Calculating absolute, relative, and cumulative frequencies in R









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1
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I have two variables, X and Y:



x <- c(1.18,1.42,0.69,0.88,1.69,1.09,1.53,1.02,1.19,1.32)
y <- c(1.72,1.42,1.69,0.79,1.79,0.77,1.44,1.29,1.96,0.99)


I would like to create a table of the absolute, relative and cumulative frequencies of both X and Y in R



 plot(table(x)/length(x), type ="h", ylab = "Relative Frequency", xlim = c(0.6,1.8))
plot(table(y)/length(y), type ="h", ylab = "Relative Frequency", xlim = c(0.6,1.8))


I did a sample of the relative frequency but it came out like this: plot of the relative frequency. I think it is wrong. What do you think? Also, how can I use hist(x)$counts to obtain the absolute and cumulative frequencies?










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  • Are x and y individual observations or are they variables? Also, please do not use links to questions since users cannot download or manipulate them.
    – Harro Cyranka
    Nov 11 at 19:57














up vote
1
down vote

favorite












I have two variables, X and Y:



x <- c(1.18,1.42,0.69,0.88,1.69,1.09,1.53,1.02,1.19,1.32)
y <- c(1.72,1.42,1.69,0.79,1.79,0.77,1.44,1.29,1.96,0.99)


I would like to create a table of the absolute, relative and cumulative frequencies of both X and Y in R



 plot(table(x)/length(x), type ="h", ylab = "Relative Frequency", xlim = c(0.6,1.8))
plot(table(y)/length(y), type ="h", ylab = "Relative Frequency", xlim = c(0.6,1.8))


I did a sample of the relative frequency but it came out like this: plot of the relative frequency. I think it is wrong. What do you think? Also, how can I use hist(x)$counts to obtain the absolute and cumulative frequencies?










share|improve this question























  • Are x and y individual observations or are they variables? Also, please do not use links to questions since users cannot download or manipulate them.
    – Harro Cyranka
    Nov 11 at 19:57












up vote
1
down vote

favorite









up vote
1
down vote

favorite











I have two variables, X and Y:



x <- c(1.18,1.42,0.69,0.88,1.69,1.09,1.53,1.02,1.19,1.32)
y <- c(1.72,1.42,1.69,0.79,1.79,0.77,1.44,1.29,1.96,0.99)


I would like to create a table of the absolute, relative and cumulative frequencies of both X and Y in R



 plot(table(x)/length(x), type ="h", ylab = "Relative Frequency", xlim = c(0.6,1.8))
plot(table(y)/length(y), type ="h", ylab = "Relative Frequency", xlim = c(0.6,1.8))


I did a sample of the relative frequency but it came out like this: plot of the relative frequency. I think it is wrong. What do you think? Also, how can I use hist(x)$counts to obtain the absolute and cumulative frequencies?










share|improve this question















I have two variables, X and Y:



x <- c(1.18,1.42,0.69,0.88,1.69,1.09,1.53,1.02,1.19,1.32)
y <- c(1.72,1.42,1.69,0.79,1.79,0.77,1.44,1.29,1.96,0.99)


I would like to create a table of the absolute, relative and cumulative frequencies of both X and Y in R



 plot(table(x)/length(x), type ="h", ylab = "Relative Frequency", xlim = c(0.6,1.8))
plot(table(y)/length(y), type ="h", ylab = "Relative Frequency", xlim = c(0.6,1.8))


I did a sample of the relative frequency but it came out like this: plot of the relative frequency. I think it is wrong. What do you think? Also, how can I use hist(x)$counts to obtain the absolute and cumulative frequencies?







r statistics






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edited Nov 11 at 20:18









Adam Liss

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40.4k1193130










asked Nov 11 at 19:18









A_1960

102




102











  • Are x and y individual observations or are they variables? Also, please do not use links to questions since users cannot download or manipulate them.
    – Harro Cyranka
    Nov 11 at 19:57
















  • Are x and y individual observations or are they variables? Also, please do not use links to questions since users cannot download or manipulate them.
    – Harro Cyranka
    Nov 11 at 19:57















Are x and y individual observations or are they variables? Also, please do not use links to questions since users cannot download or manipulate them.
– Harro Cyranka
Nov 11 at 19:57




Are x and y individual observations or are they variables? Also, please do not use links to questions since users cannot download or manipulate them.
– Harro Cyranka
Nov 11 at 19:57












1 Answer
1






active

oldest

votes

















up vote
1
down vote



accepted










I'm not sure why you wish to use hist(x). Everything can be obtained using table:



# Absolute frequencies
table(x)
# x
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 1 1 1 1 1 1 1 1 1 1

# Relative frequencies
table(x) / length(x)
# x
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

# Cumulative frequencies
cumsum(table(x))
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 1 2 3 4 5 6 7 8 9 10


and the same for y. As to put them together,



rbind(Absolute = table(x), 
Relative = table(x) / length(x),
Cumulative = cumsum(table(x)))
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# Absolute 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
# Relative 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
# Cumulative 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0


The results are correct, although indeed somewhat boring. If you have more data, with repetitions, it will look better.






share|improve this answer




















  • is it normal to get 1 for all the absolute frequencies !! and hist(x)$counts it's an extra for me to capture the difference between x, y which i wanna ask you but I wanna send my plot but I'm new to SOF so no clue
    – A_1960
    Nov 11 at 20:31






  • 1




    As I said, yes, 1 for all the absolute frequencies is correct in this case. A frequency is simply the number of times this value appears in your data. Since all your values are distinct, their frequencies are all 1. Now histogram doesn't show absolute frequencies. It selects bins: in the case of x, six bins of width 0.2, from 0.6 to 1.8. Then it computes absolute frequencies with respect to those bins. That may also be useful to you, but the answer to your original question is in my post.
    – Julius Vainora
    Nov 11 at 20:36











  • thanks.- but what can be the difference between the two histograms of x and y doing "hist(x)$counts" "hist(y)$counts" if I should give an opinion about it ?
    – A_1960
    Nov 11 at 20:40










  • I guess that's not what you mean, but if you wanted to literally look at their difference, you could do c(hist(x)$counts,0) - hist(y)$counts. I added a zero to x's histogram because it has one bin less (with no values there). This shows you differences of absolute differences of those discretized values (i.e., with respect to bins). Also you may plot those two histograms together and compare. You have little data, so it's hard to say something. In any case, knowing what x and y are is important. Anyway, that's not what you initial question is about.
    – Julius Vainora
    Nov 11 at 20:47










  • ...If you want more help regarding interpretation of your results, I suggest to ask another question on stats.stackexchange.com
    – Julius Vainora
    Nov 11 at 20:47











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1 Answer
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active

oldest

votes








1 Answer
1






active

oldest

votes









active

oldest

votes






active

oldest

votes








up vote
1
down vote



accepted










I'm not sure why you wish to use hist(x). Everything can be obtained using table:



# Absolute frequencies
table(x)
# x
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 1 1 1 1 1 1 1 1 1 1

# Relative frequencies
table(x) / length(x)
# x
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

# Cumulative frequencies
cumsum(table(x))
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 1 2 3 4 5 6 7 8 9 10


and the same for y. As to put them together,



rbind(Absolute = table(x), 
Relative = table(x) / length(x),
Cumulative = cumsum(table(x)))
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# Absolute 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
# Relative 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
# Cumulative 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0


The results are correct, although indeed somewhat boring. If you have more data, with repetitions, it will look better.






share|improve this answer




















  • is it normal to get 1 for all the absolute frequencies !! and hist(x)$counts it's an extra for me to capture the difference between x, y which i wanna ask you but I wanna send my plot but I'm new to SOF so no clue
    – A_1960
    Nov 11 at 20:31






  • 1




    As I said, yes, 1 for all the absolute frequencies is correct in this case. A frequency is simply the number of times this value appears in your data. Since all your values are distinct, their frequencies are all 1. Now histogram doesn't show absolute frequencies. It selects bins: in the case of x, six bins of width 0.2, from 0.6 to 1.8. Then it computes absolute frequencies with respect to those bins. That may also be useful to you, but the answer to your original question is in my post.
    – Julius Vainora
    Nov 11 at 20:36











  • thanks.- but what can be the difference between the two histograms of x and y doing "hist(x)$counts" "hist(y)$counts" if I should give an opinion about it ?
    – A_1960
    Nov 11 at 20:40










  • I guess that's not what you mean, but if you wanted to literally look at their difference, you could do c(hist(x)$counts,0) - hist(y)$counts. I added a zero to x's histogram because it has one bin less (with no values there). This shows you differences of absolute differences of those discretized values (i.e., with respect to bins). Also you may plot those two histograms together and compare. You have little data, so it's hard to say something. In any case, knowing what x and y are is important. Anyway, that's not what you initial question is about.
    – Julius Vainora
    Nov 11 at 20:47










  • ...If you want more help regarding interpretation of your results, I suggest to ask another question on stats.stackexchange.com
    – Julius Vainora
    Nov 11 at 20:47















up vote
1
down vote



accepted










I'm not sure why you wish to use hist(x). Everything can be obtained using table:



# Absolute frequencies
table(x)
# x
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 1 1 1 1 1 1 1 1 1 1

# Relative frequencies
table(x) / length(x)
# x
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

# Cumulative frequencies
cumsum(table(x))
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 1 2 3 4 5 6 7 8 9 10


and the same for y. As to put them together,



rbind(Absolute = table(x), 
Relative = table(x) / length(x),
Cumulative = cumsum(table(x)))
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# Absolute 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
# Relative 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
# Cumulative 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0


The results are correct, although indeed somewhat boring. If you have more data, with repetitions, it will look better.






share|improve this answer




















  • is it normal to get 1 for all the absolute frequencies !! and hist(x)$counts it's an extra for me to capture the difference between x, y which i wanna ask you but I wanna send my plot but I'm new to SOF so no clue
    – A_1960
    Nov 11 at 20:31






  • 1




    As I said, yes, 1 for all the absolute frequencies is correct in this case. A frequency is simply the number of times this value appears in your data. Since all your values are distinct, their frequencies are all 1. Now histogram doesn't show absolute frequencies. It selects bins: in the case of x, six bins of width 0.2, from 0.6 to 1.8. Then it computes absolute frequencies with respect to those bins. That may also be useful to you, but the answer to your original question is in my post.
    – Julius Vainora
    Nov 11 at 20:36











  • thanks.- but what can be the difference between the two histograms of x and y doing "hist(x)$counts" "hist(y)$counts" if I should give an opinion about it ?
    – A_1960
    Nov 11 at 20:40










  • I guess that's not what you mean, but if you wanted to literally look at their difference, you could do c(hist(x)$counts,0) - hist(y)$counts. I added a zero to x's histogram because it has one bin less (with no values there). This shows you differences of absolute differences of those discretized values (i.e., with respect to bins). Also you may plot those two histograms together and compare. You have little data, so it's hard to say something. In any case, knowing what x and y are is important. Anyway, that's not what you initial question is about.
    – Julius Vainora
    Nov 11 at 20:47










  • ...If you want more help regarding interpretation of your results, I suggest to ask another question on stats.stackexchange.com
    – Julius Vainora
    Nov 11 at 20:47













up vote
1
down vote



accepted







up vote
1
down vote



accepted






I'm not sure why you wish to use hist(x). Everything can be obtained using table:



# Absolute frequencies
table(x)
# x
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 1 1 1 1 1 1 1 1 1 1

# Relative frequencies
table(x) / length(x)
# x
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

# Cumulative frequencies
cumsum(table(x))
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 1 2 3 4 5 6 7 8 9 10


and the same for y. As to put them together,



rbind(Absolute = table(x), 
Relative = table(x) / length(x),
Cumulative = cumsum(table(x)))
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# Absolute 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
# Relative 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
# Cumulative 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0


The results are correct, although indeed somewhat boring. If you have more data, with repetitions, it will look better.






share|improve this answer












I'm not sure why you wish to use hist(x). Everything can be obtained using table:



# Absolute frequencies
table(x)
# x
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 1 1 1 1 1 1 1 1 1 1

# Relative frequencies
table(x) / length(x)
# x
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

# Cumulative frequencies
cumsum(table(x))
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# 1 2 3 4 5 6 7 8 9 10


and the same for y. As to put them together,



rbind(Absolute = table(x), 
Relative = table(x) / length(x),
Cumulative = cumsum(table(x)))
# 0.69 0.88 1.02 1.09 1.18 1.19 1.32 1.42 1.53 1.69
# Absolute 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
# Relative 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
# Cumulative 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0


The results are correct, although indeed somewhat boring. If you have more data, with repetitions, it will look better.







share|improve this answer












share|improve this answer



share|improve this answer










answered Nov 11 at 20:24









Julius Vainora

29.5k75878




29.5k75878











  • is it normal to get 1 for all the absolute frequencies !! and hist(x)$counts it's an extra for me to capture the difference between x, y which i wanna ask you but I wanna send my plot but I'm new to SOF so no clue
    – A_1960
    Nov 11 at 20:31






  • 1




    As I said, yes, 1 for all the absolute frequencies is correct in this case. A frequency is simply the number of times this value appears in your data. Since all your values are distinct, their frequencies are all 1. Now histogram doesn't show absolute frequencies. It selects bins: in the case of x, six bins of width 0.2, from 0.6 to 1.8. Then it computes absolute frequencies with respect to those bins. That may also be useful to you, but the answer to your original question is in my post.
    – Julius Vainora
    Nov 11 at 20:36











  • thanks.- but what can be the difference between the two histograms of x and y doing "hist(x)$counts" "hist(y)$counts" if I should give an opinion about it ?
    – A_1960
    Nov 11 at 20:40










  • I guess that's not what you mean, but if you wanted to literally look at their difference, you could do c(hist(x)$counts,0) - hist(y)$counts. I added a zero to x's histogram because it has one bin less (with no values there). This shows you differences of absolute differences of those discretized values (i.e., with respect to bins). Also you may plot those two histograms together and compare. You have little data, so it's hard to say something. In any case, knowing what x and y are is important. Anyway, that's not what you initial question is about.
    – Julius Vainora
    Nov 11 at 20:47










  • ...If you want more help regarding interpretation of your results, I suggest to ask another question on stats.stackexchange.com
    – Julius Vainora
    Nov 11 at 20:47

















  • is it normal to get 1 for all the absolute frequencies !! and hist(x)$counts it's an extra for me to capture the difference between x, y which i wanna ask you but I wanna send my plot but I'm new to SOF so no clue
    – A_1960
    Nov 11 at 20:31






  • 1




    As I said, yes, 1 for all the absolute frequencies is correct in this case. A frequency is simply the number of times this value appears in your data. Since all your values are distinct, their frequencies are all 1. Now histogram doesn't show absolute frequencies. It selects bins: in the case of x, six bins of width 0.2, from 0.6 to 1.8. Then it computes absolute frequencies with respect to those bins. That may also be useful to you, but the answer to your original question is in my post.
    – Julius Vainora
    Nov 11 at 20:36











  • thanks.- but what can be the difference between the two histograms of x and y doing "hist(x)$counts" "hist(y)$counts" if I should give an opinion about it ?
    – A_1960
    Nov 11 at 20:40










  • I guess that's not what you mean, but if you wanted to literally look at their difference, you could do c(hist(x)$counts,0) - hist(y)$counts. I added a zero to x's histogram because it has one bin less (with no values there). This shows you differences of absolute differences of those discretized values (i.e., with respect to bins). Also you may plot those two histograms together and compare. You have little data, so it's hard to say something. In any case, knowing what x and y are is important. Anyway, that's not what you initial question is about.
    – Julius Vainora
    Nov 11 at 20:47










  • ...If you want more help regarding interpretation of your results, I suggest to ask another question on stats.stackexchange.com
    – Julius Vainora
    Nov 11 at 20:47
















is it normal to get 1 for all the absolute frequencies !! and hist(x)$counts it's an extra for me to capture the difference between x, y which i wanna ask you but I wanna send my plot but I'm new to SOF so no clue
– A_1960
Nov 11 at 20:31




is it normal to get 1 for all the absolute frequencies !! and hist(x)$counts it's an extra for me to capture the difference between x, y which i wanna ask you but I wanna send my plot but I'm new to SOF so no clue
– A_1960
Nov 11 at 20:31




1




1




As I said, yes, 1 for all the absolute frequencies is correct in this case. A frequency is simply the number of times this value appears in your data. Since all your values are distinct, their frequencies are all 1. Now histogram doesn't show absolute frequencies. It selects bins: in the case of x, six bins of width 0.2, from 0.6 to 1.8. Then it computes absolute frequencies with respect to those bins. That may also be useful to you, but the answer to your original question is in my post.
– Julius Vainora
Nov 11 at 20:36





As I said, yes, 1 for all the absolute frequencies is correct in this case. A frequency is simply the number of times this value appears in your data. Since all your values are distinct, their frequencies are all 1. Now histogram doesn't show absolute frequencies. It selects bins: in the case of x, six bins of width 0.2, from 0.6 to 1.8. Then it computes absolute frequencies with respect to those bins. That may also be useful to you, but the answer to your original question is in my post.
– Julius Vainora
Nov 11 at 20:36













thanks.- but what can be the difference between the two histograms of x and y doing "hist(x)$counts" "hist(y)$counts" if I should give an opinion about it ?
– A_1960
Nov 11 at 20:40




thanks.- but what can be the difference between the two histograms of x and y doing "hist(x)$counts" "hist(y)$counts" if I should give an opinion about it ?
– A_1960
Nov 11 at 20:40












I guess that's not what you mean, but if you wanted to literally look at their difference, you could do c(hist(x)$counts,0) - hist(y)$counts. I added a zero to x's histogram because it has one bin less (with no values there). This shows you differences of absolute differences of those discretized values (i.e., with respect to bins). Also you may plot those two histograms together and compare. You have little data, so it's hard to say something. In any case, knowing what x and y are is important. Anyway, that's not what you initial question is about.
– Julius Vainora
Nov 11 at 20:47




I guess that's not what you mean, but if you wanted to literally look at their difference, you could do c(hist(x)$counts,0) - hist(y)$counts. I added a zero to x's histogram because it has one bin less (with no values there). This shows you differences of absolute differences of those discretized values (i.e., with respect to bins). Also you may plot those two histograms together and compare. You have little data, so it's hard to say something. In any case, knowing what x and y are is important. Anyway, that's not what you initial question is about.
– Julius Vainora
Nov 11 at 20:47












...If you want more help regarding interpretation of your results, I suggest to ask another question on stats.stackexchange.com
– Julius Vainora
Nov 11 at 20:47





...If you want more help regarding interpretation of your results, I suggest to ask another question on stats.stackexchange.com
– Julius Vainora
Nov 11 at 20:47


















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