Mixing
Using Dplyr within a user-defined function to summarise data then plot it
I am trying to use dplyr within a function to create a user-defined function that I can pass multiple arguments to summarise data with dplyr then plot it with ggplot.
Here is some sample data and what I am trying to do with dplyr then plot
df <-data.frame(Year = c("2006", "2006", "2006", "2007", "2007", "2007", "2008", "2009", "2010", "2010", "2009", "2009"), JudicialOrientation = c("Defense", "Plaintiff", "Plaintiff", "Neutral", "Defense", "Plaintiff", "Defense", "Plaintiff", "Neutral", "Neutral", "Plaintiff","Defense"), Loss = c(100000, 100, 2500, 100000, 25000, 0, 7500, 5200, 900, 100, 0, 50))
df1 <- df %>%
group_by(Year, JudicialOrientation) %>%
summarise(MeanLoss =mean(Loss))
ggplot(df1, aes(x = JudicialOrientation, y = MeanLoss, color = Year, group =Year)) +
geom_line() +
geom_point()
I am now trying to replicate this into a user function so that I can pass different variables to get similar results.
Here is my attempt so far:
ConsistencyPlot <- function(df,var1,timevar,lossvar){
df1 <- df %>%
group_by_(df[timevar], df[var1]) %>%
summarise_(MeanLoss = mean(df[lossvar]))
ggplot(df1, aes(x = var1, y = MeanLoss, color = timevar, group = timevar)) +
geom_line() +
geom_point()
}
ConsistencyPlot(df,"JudicialOrientation","Year",'Loss')
I am replicating the same logic and passing in df as my dataframe, var1 as the JudicialOrientation, timevar as Year and lossvar as my vector of Loss values that I want averaged through summarise. I cannot get the same results however so I feel like I am missing something with how these functions are used within a closure.
r ggplot2 dplyr aggregate
edited Nov 21 '18 at 17:59
Tjebo
2,4311429
asked Nov 21 '18 at 14:30
Coldchain9Coldchain9
325
add a comment |
I am trying to use dplyr within a function to create a user-defined function that I can pass multiple arguments to summarise data with dplyr then plot it with ggplot.
Here is some sample data and what I am trying to do with dplyr then plot
df <-data.frame(Year = c("2006", "2006", "2006", "2007", "2007", "2007", "2008", "2009", "2010", "2010", "2009", "2009"), JudicialOrientation = c("Defense", "Plaintiff", "Plaintiff", "Neutral", "Defense", "Plaintiff", "Defense", "Plaintiff", "Neutral", "Neutral", "Plaintiff","Defense"), Loss = c(100000, 100, 2500, 100000, 25000, 0, 7500, 5200, 900, 100, 0, 50))
df1 <- df %>%
group_by(Year, JudicialOrientation) %>%
summarise(MeanLoss =mean(Loss))
ggplot(df1, aes(x = JudicialOrientation, y = MeanLoss, color = Year, group =Year)) +
geom_line() +
geom_point()
I am now trying to replicate this into a user function so that I can pass different variables to get similar results.
Here is my attempt so far:
ConsistencyPlot <- function(df,var1,timevar,lossvar){
df1 <- df %>%
group_by_(df[timevar], df[var1]) %>%
summarise_(MeanLoss = mean(df[lossvar]))
ggplot(df1, aes(x = var1, y = MeanLoss, color = timevar, group = timevar)) +
geom_line() +
geom_point()
}
ConsistencyPlot(df,"JudicialOrientation","Year",'Loss')
I am replicating the same logic and passing in df as my dataframe, var1 as the JudicialOrientation, timevar as Year and lossvar as my vector of Loss values that I want averaged through summarise. I cannot get the same results however so I feel like I am missing something with how these functions are used within a closure.
r ggplot2 dplyr aggregate
edited Nov 21 '18 at 17:59
Tjebo
2,4311429
asked Nov 21 '18 at 14:30
Coldchain9Coldchain9
325
add a comment |
I am trying to use dplyr within a function to create a user-defined function that I can pass multiple arguments to summarise data with dplyr then plot it with ggplot.
Here is some sample data and what I am trying to do with dplyr then plot
df <-data.frame(Year = c("2006", "2006", "2006", "2007", "2007", "2007", "2008", "2009", "2010", "2010", "2009", "2009"), JudicialOrientation = c("Defense", "Plaintiff", "Plaintiff", "Neutral", "Defense", "Plaintiff", "Defense", "Plaintiff", "Neutral", "Neutral", "Plaintiff","Defense"), Loss = c(100000, 100, 2500, 100000, 25000, 0, 7500, 5200, 900, 100, 0, 50))
df1 <- df %>%
group_by(Year, JudicialOrientation) %>%
summarise(MeanLoss =mean(Loss))
ggplot(df1, aes(x = JudicialOrientation, y = MeanLoss, color = Year, group =Year)) +
geom_line() +
geom_point()
I am now trying to replicate this into a user function so that I can pass different variables to get similar results.
Here is my attempt so far:
ConsistencyPlot <- function(df,var1,timevar,lossvar){
df1 <- df %>%
group_by_(df[timevar], df[var1]) %>%
summarise_(MeanLoss = mean(df[lossvar]))
ggplot(df1, aes(x = var1, y = MeanLoss, color = timevar, group = timevar)) +
geom_line() +
geom_point()
}
ConsistencyPlot(df,"JudicialOrientation","Year",'Loss')
I am replicating the same logic and passing in df as my dataframe, var1 as the JudicialOrientation, timevar as Year and lossvar as my vector of Loss values that I want averaged through summarise. I cannot get the same results however so I feel like I am missing something with how these functions are used within a closure.
r ggplot2 dplyr aggregate
edited Nov 21 '18 at 17:59
Tjebo
2,4311429
asked Nov 21 '18 at 14:30
Coldchain9Coldchain9
325
I am trying to use dplyr within a function to create a user-defined function that I can pass multiple arguments to summarise data with dplyr then plot it with ggplot.
Here is some sample data and what I am trying to do with dplyr then plot
df <-data.frame(Year = c("2006", "2006", "2006", "2007", "2007", "2007", "2008", "2009", "2010", "2010", "2009", "2009"), JudicialOrientation = c("Defense", "Plaintiff", "Plaintiff", "Neutral", "Defense", "Plaintiff", "Defense", "Plaintiff", "Neutral", "Neutral", "Plaintiff","Defense"), Loss = c(100000, 100, 2500, 100000, 25000, 0, 7500, 5200, 900, 100, 0, 50))
df1 <- df %>%
group_by(Year, JudicialOrientation) %>%
summarise(MeanLoss =mean(Loss))
ggplot(df1, aes(x = JudicialOrientation, y = MeanLoss, color = Year, group =Year)) +
geom_line() +
geom_point()
I am now trying to replicate this into a user function so that I can pass different variables to get similar results.
Here is my attempt so far:
ConsistencyPlot <- function(df,var1,timevar,lossvar){
df1 <- df %>%
group_by_(df[timevar], df[var1]) %>%
summarise_(MeanLoss = mean(df[lossvar]))
ggplot(df1, aes(x = var1, y = MeanLoss, color = timevar, group = timevar)) +
geom_line() +
geom_point()
}
ConsistencyPlot(df,"JudicialOrientation","Year",'Loss')
I am replicating the same logic and passing in df as my dataframe, var1 as the JudicialOrientation, timevar as Year and lossvar as my vector of Loss values that I want averaged through summarise. I cannot get the same results however so I feel like I am missing something with how these functions are used within a closure.
r ggplot2 dplyr aggregate
r ggplot2 dplyr aggregate
edited Nov 21 '18 at 17:59
Tjebo
2,4311429
asked Nov 21 '18 at 14:30
Coldchain9Coldchain9
325
edited Nov 21 '18 at 17:59
Tjebo
2,4311429
asked Nov 21 '18 at 14:30
Coldchain9Coldchain9
325
edited Nov 21 '18 at 17:59
Tjebo
2,4311429
edited Nov 21 '18 at 17:59
Tjebo
2,4311429
edited Nov 21 '18 at 17:59
Tjebo
2,4311429
2,4311429
asked Nov 21 '18 at 14:30
Coldchain9Coldchain9
325
asked Nov 21 '18 at 14:30
Coldchain9Coldchain9
325
asked Nov 21 '18 at 14:30
Coldchain9Coldchain9
325
325
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
First of all, inside dplyr functions you don't need to call variables indexing the dataframe like df[, timevar]. Use just the variable name. Besides that, when indexing a dataframe you have to specify if you are calling columns or rows, so df[timevar] is wrong.
About the function, it's a problem of evaluation.
This structure below is working:
ConsistencyPlot <- function(df, var1, timevar, lossvar){
var1 <- enquo(var1)
timevar <- enquo(timevar)
lossvar <- enquo(lossvar)
df1 <- df %>%
group_by(!!timevar, !!var1) %>%
summarise(MeanLoss = mean(!!lossvar))
ggplot(df1, aes(x = !!var1, y = MeanLoss, color = !!timevar, group = !!timevar)) +
geom_line() +
geom_point()
}
Look that the parameters were transformed with enquo() and then passed in the function using !!. So, you can pass the arguments without quoting them.
ConsistencyPlot(df, JudicialOrientation, Year, Loss)
I hope you find it useful.
answered Nov 21 '18 at 15:12
Bruno PinheiroBruno Pinheiro
402112
I realized I was referencing column names wrong right after I posted this question. Can you explain to me what !! is doing? This is exactly what I wanted. Thank you very much.
– Coldchain9
Nov 21 '18 at 15:19
It is an unquoting operator. See?"!!".
– Anonymous coward
Nov 21 '18 at 15:20
1
It's exactly what @Anonymouscoward said. For a deepier exaplanation, take a look here. Happy to help.
– Bruno Pinheiro
Nov 21 '18 at 15:29
I guess I am just trying to figure out why does the quoting-unquoting methodology work vs just sending the arguments in their unquoted form. It can't recognize the variables if I send them in so why does it work when they are enquoted then immediately unquoted with !!. I read ?enquo and if I understand correctly, the quosure maintains the original environment but !! just removes the quotes for evaluation purposes?
– Coldchain9
Nov 21 '18 at 16:12
2
@Coldchain9: see this for further explanation stackoverflow.com/questions/51738267/…
– Tung
Nov 21 '18 at 16:36
add a comment |
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1 Answer
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active
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1 Answer
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active
oldest
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oldest
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oldest
votes
First of all, inside dplyr functions you don't need to call variables indexing the dataframe like df[, timevar]. Use just the variable name. Besides that, when indexing a dataframe you have to specify if you are calling columns or rows, so df[timevar] is wrong.
About the function, it's a problem of evaluation.
This structure below is working:
ConsistencyPlot <- function(df, var1, timevar, lossvar){
var1 <- enquo(var1)
timevar <- enquo(timevar)
lossvar <- enquo(lossvar)
df1 <- df %>%
group_by(!!timevar, !!var1) %>%
summarise(MeanLoss = mean(!!lossvar))
ggplot(df1, aes(x = !!var1, y = MeanLoss, color = !!timevar, group = !!timevar)) +
geom_line() +
geom_point()
}
Look that the parameters were transformed with enquo() and then passed in the function using !!. So, you can pass the arguments without quoting them.
ConsistencyPlot(df, JudicialOrientation, Year, Loss)
I hope you find it useful.
answered Nov 21 '18 at 15:12
Bruno PinheiroBruno Pinheiro
402112
I realized I was referencing column names wrong right after I posted this question. Can you explain to me what !! is doing? This is exactly what I wanted. Thank you very much.
– Coldchain9
Nov 21 '18 at 15:19
It is an unquoting operator. See?"!!".
– Anonymous coward
Nov 21 '18 at 15:20
1
It's exactly what @Anonymouscoward said. For a deepier exaplanation, take a look here. Happy to help.
– Bruno Pinheiro
Nov 21 '18 at 15:29
I guess I am just trying to figure out why does the quoting-unquoting methodology work vs just sending the arguments in their unquoted form. It can't recognize the variables if I send them in so why does it work when they are enquoted then immediately unquoted with !!. I read ?enquo and if I understand correctly, the quosure maintains the original environment but !! just removes the quotes for evaluation purposes?
– Coldchain9
Nov 21 '18 at 16:12
2
@Coldchain9: see this for further explanation stackoverflow.com/questions/51738267/…
– Tung
Nov 21 '18 at 16:36
add a comment |
First of all, inside dplyr functions you don't need to call variables indexing the dataframe like df[, timevar]. Use just the variable name. Besides that, when indexing a dataframe you have to specify if you are calling columns or rows, so df[timevar] is wrong.
About the function, it's a problem of evaluation.
This structure below is working:
ConsistencyPlot <- function(df, var1, timevar, lossvar){
var1 <- enquo(var1)
timevar <- enquo(timevar)
lossvar <- enquo(lossvar)
df1 <- df %>%
group_by(!!timevar, !!var1) %>%
summarise(MeanLoss = mean(!!lossvar))
ggplot(df1, aes(x = !!var1, y = MeanLoss, color = !!timevar, group = !!timevar)) +
geom_line() +
geom_point()
}
Look that the parameters were transformed with enquo() and then passed in the function using !!. So, you can pass the arguments without quoting them.
ConsistencyPlot(df, JudicialOrientation, Year, Loss)
I hope you find it useful.
answered Nov 21 '18 at 15:12
Bruno PinheiroBruno Pinheiro
402112
I realized I was referencing column names wrong right after I posted this question. Can you explain to me what !! is doing? This is exactly what I wanted. Thank you very much.
– Coldchain9
Nov 21 '18 at 15:19
It is an unquoting operator. See?"!!".
– Anonymous coward
Nov 21 '18 at 15:20
1
It's exactly what @Anonymouscoward said. For a deepier exaplanation, take a look here. Happy to help.
– Bruno Pinheiro
Nov 21 '18 at 15:29
I guess I am just trying to figure out why does the quoting-unquoting methodology work vs just sending the arguments in their unquoted form. It can't recognize the variables if I send them in so why does it work when they are enquoted then immediately unquoted with !!. I read ?enquo and if I understand correctly, the quosure maintains the original environment but !! just removes the quotes for evaluation purposes?
– Coldchain9
Nov 21 '18 at 16:12
2
@Coldchain9: see this for further explanation stackoverflow.com/questions/51738267/…
– Tung
Nov 21 '18 at 16:36
add a comment |
First of all, inside dplyr functions you don't need to call variables indexing the dataframe like df[, timevar]. Use just the variable name. Besides that, when indexing a dataframe you have to specify if you are calling columns or rows, so df[timevar] is wrong.
About the function, it's a problem of evaluation.
This structure below is working:
ConsistencyPlot <- function(df, var1, timevar, lossvar){
var1 <- enquo(var1)
timevar <- enquo(timevar)
lossvar <- enquo(lossvar)
df1 <- df %>%
group_by(!!timevar, !!var1) %>%
summarise(MeanLoss = mean(!!lossvar))
ggplot(df1, aes(x = !!var1, y = MeanLoss, color = !!timevar, group = !!timevar)) +
geom_line() +
geom_point()
}
Look that the parameters were transformed with enquo() and then passed in the function using !!. So, you can pass the arguments without quoting them.
ConsistencyPlot(df, JudicialOrientation, Year, Loss)
I hope you find it useful.
answered Nov 21 '18 at 15:12
Bruno PinheiroBruno Pinheiro
402112
First of all, inside dplyr functions you don't need to call variables indexing the dataframe like df[, timevar]. Use just the variable name. Besides that, when indexing a dataframe you have to specify if you are calling columns or rows, so df[timevar] is wrong.
About the function, it's a problem of evaluation.
This structure below is working:
ConsistencyPlot <- function(df, var1, timevar, lossvar){
var1 <- enquo(var1)
timevar <- enquo(timevar)
lossvar <- enquo(lossvar)
df1 <- df %>%
group_by(!!timevar, !!var1) %>%
summarise(MeanLoss = mean(!!lossvar))
ggplot(df1, aes(x = !!var1, y = MeanLoss, color = !!timevar, group = !!timevar)) +
geom_line() +
geom_point()
}
Look that the parameters were transformed with enquo() and then passed in the function using !!. So, you can pass the arguments without quoting them.
ConsistencyPlot(df, JudicialOrientation, Year, Loss)
I hope you find it useful.
answered Nov 21 '18 at 15:12
Bruno PinheiroBruno Pinheiro
402112
edited Nov 21 '18 at 15:32
answered Nov 21 '18 at 15:12
Bruno PinheiroBruno Pinheiro
402112
answered Nov 21 '18 at 15:12
Bruno PinheiroBruno Pinheiro
402112
answered Nov 21 '18 at 15:12
Bruno PinheiroBruno Pinheiro
402112
402112
I realized I was referencing column names wrong right after I posted this question. Can you explain to me what !! is doing? This is exactly what I wanted. Thank you very much.
– Coldchain9
Nov 21 '18 at 15:19
It is an unquoting operator. See?"!!".
– Anonymous coward
Nov 21 '18 at 15:20
1
It's exactly what @Anonymouscoward said. For a deepier exaplanation, take a look here. Happy to help.
– Bruno Pinheiro
Nov 21 '18 at 15:29
I guess I am just trying to figure out why does the quoting-unquoting methodology work vs just sending the arguments in their unquoted form. It can't recognize the variables if I send them in so why does it work when they are enquoted then immediately unquoted with !!. I read ?enquo and if I understand correctly, the quosure maintains the original environment but !! just removes the quotes for evaluation purposes?
– Coldchain9
Nov 21 '18 at 16:12
2
@Coldchain9: see this for further explanation stackoverflow.com/questions/51738267/…
– Tung
Nov 21 '18 at 16:36
add a comment |
I realized I was referencing column names wrong right after I posted this question. Can you explain to me what !! is doing? This is exactly what I wanted. Thank you very much.
– Coldchain9
Nov 21 '18 at 15:19
It is an unquoting operator. See?"!!".
– Anonymous coward
Nov 21 '18 at 15:20
1
It's exactly what @Anonymouscoward said. For a deepier exaplanation, take a look here. Happy to help.
– Bruno Pinheiro
Nov 21 '18 at 15:29
I guess I am just trying to figure out why does the quoting-unquoting methodology work vs just sending the arguments in their unquoted form. It can't recognize the variables if I send them in so why does it work when they are enquoted then immediately unquoted with !!. I read ?enquo and if I understand correctly, the quosure maintains the original environment but !! just removes the quotes for evaluation purposes?
– Coldchain9
Nov 21 '18 at 16:12
2
@Coldchain9: see this for further explanation stackoverflow.com/questions/51738267/…
– Tung
Nov 21 '18 at 16:36
I realized I was referencing column names wrong right after I posted this question. Can you explain to me what !! is doing? This is exactly what I wanted. Thank you very much.
– Coldchain9
Nov 21 '18 at 15:19
I realized I was referencing column names wrong right after I posted this question. Can you explain to me what !! is doing? This is exactly what I wanted. Thank you very much.
– Coldchain9
Nov 21 '18 at 15:19
It is an unquoting operator. See
?"!!".– Anonymous coward
Nov 21 '18 at 15:20
It is an unquoting operator. See
?"!!".– Anonymous coward
Nov 21 '18 at 15:20
1
1
It's exactly what @Anonymouscoward said. For a deepier exaplanation, take a look here. Happy to help.
– Bruno Pinheiro
Nov 21 '18 at 15:29
It's exactly what @Anonymouscoward said. For a deepier exaplanation, take a look here. Happy to help.
– Bruno Pinheiro
Nov 21 '18 at 15:29
I guess I am just trying to figure out why does the quoting-unquoting methodology work vs just sending the arguments in their unquoted form. It can't recognize the variables if I send them in so why does it work when they are enquoted then immediately unquoted with !!. I read ?enquo and if I understand correctly, the quosure maintains the original environment but !! just removes the quotes for evaluation purposes?
– Coldchain9
Nov 21 '18 at 16:12
I guess I am just trying to figure out why does the quoting-unquoting methodology work vs just sending the arguments in their unquoted form. It can't recognize the variables if I send them in so why does it work when they are enquoted then immediately unquoted with !!. I read ?enquo and if I understand correctly, the quosure maintains the original environment but !! just removes the quotes for evaluation purposes?
– Coldchain9
Nov 21 '18 at 16:12
2
2
@Coldchain9: see this for further explanation stackoverflow.com/questions/51738267/…
– Tung
Nov 21 '18 at 16:36
@Coldchain9: see this for further explanation stackoverflow.com/questions/51738267/…
– Tung
Nov 21 '18 at 16:36
add a comment |
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