Plotting Multiple Lines in GGplot with Different lines corresponding to a different year

I am trying to use ggplot to plot multiple lines (categorized by years) for means for a categorical variable. I am stumped and have tried a variety of things but can't get exactly what I want. I have raw observations that have a year flag on each observation and a Loss value attached to them but here is a snapshot of me trying to group the mean losses by year/judicial orientation.

I want to aggregate all the Loss values by categorical variable level and then aggregate those further by the Year

My goal is this:

I want one graph that has a variable number of levels depending on variable (for JudicialOrientation I have 3 levels: Defense, Neutral, Plaintiff) so those would be the x values, I then want to have a line graph connecting the means between each 3 levels but I want multiple lines that represent 2006, 2007, 2008 etc.

So I would have different colored lines that correspond to a different year's MeanLoss value for that particular level. I hope this makes sense.

I am new to ggplot and I see some people use one line and others use multiple lines. I am ok with either approach.

An attempt so far:

ggplot() +geom_line(data=df1, aes(x=JudicialOrientation, y = MeanLoss, color=Year))

An example data frame with some dplyr code to obtain aggregate means:

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))

Let me know any tips you may have. Thanks!

edited Nov 20 '18 at 21:05

asked Nov 20 '18 at 20:51

Coldchain9

325

Please post the code you have tried so far?

– TeeKea
Nov 20 '18 at 20:54

I edited my post.This should give you a sample data frame you can work with. I want to aggregate the Loss column by JudicialOrientation and then plot a different line for each year in the data set to give aggregate meanLoss for each JudicialOrientation (on the x-axis preferably).

– Coldchain9
Nov 20 '18 at 21:01

add a comment |

I want to aggregate all the Loss values by categorical variable level and then aggregate those further by the Year

My goal is this:

So I would have different colored lines that correspond to a different year's MeanLoss value for that particular level. I hope this makes sense.

I am new to ggplot and I see some people use one line and others use multiple lines. I am ok with either approach.

An attempt so far:

ggplot() +geom_line(data=df1, aes(x=JudicialOrientation, y = MeanLoss, color=Year))

An example data frame with some dplyr code to obtain aggregate means:

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))

Let me know any tips you may have. Thanks!

edited Nov 20 '18 at 21:05

asked Nov 20 '18 at 20:51

Coldchain9

325

Please post the code you have tried so far?

– TeeKea
Nov 20 '18 at 20:54

I edited my post.This should give you a sample data frame you can work with. I want to aggregate the Loss column by JudicialOrientation and then plot a different line for each year in the data set to give aggregate meanLoss for each JudicialOrientation (on the x-axis preferably).

– Coldchain9
Nov 20 '18 at 21:01

add a comment |

I want to aggregate all the Loss values by categorical variable level and then aggregate those further by the Year

My goal is this:

So I would have different colored lines that correspond to a different year's MeanLoss value for that particular level. I hope this makes sense.

I am new to ggplot and I see some people use one line and others use multiple lines. I am ok with either approach.

An attempt so far:

ggplot() +geom_line(data=df1, aes(x=JudicialOrientation, y = MeanLoss, color=Year))

An example data frame with some dplyr code to obtain aggregate means:

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))

Let me know any tips you may have. Thanks!

edited Nov 20 '18 at 21:05

asked Nov 20 '18 at 20:51

Coldchain9

325

I want to aggregate all the Loss values by categorical variable level and then aggregate those further by the Year

My goal is this:

So I would have different colored lines that correspond to a different year's MeanLoss value for that particular level. I hope this makes sense.

I am new to ggplot and I see some people use one line and others use multiple lines. I am ok with either approach.

An attempt so far:

ggplot() +geom_line(data=df1, aes(x=JudicialOrientation, y = MeanLoss, color=Year))

An example data frame with some dplyr code to obtain aggregate means:

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))

Let me know any tips you may have. Thanks!

r ggplot2 aggregate

edited Nov 20 '18 at 21:05

asked Nov 20 '18 at 20:51

Coldchain9

325

edited Nov 20 '18 at 21:05

asked Nov 20 '18 at 20:51

Coldchain9

325

edited Nov 20 '18 at 21:05

asked Nov 20 '18 at 20:51

Coldchain9

325

asked Nov 20 '18 at 20:51

Coldchain9

325

asked Nov 20 '18 at 20:51

Coldchain9

325

Please post the code you have tried so far?

– TeeKea
Nov 20 '18 at 20:54

I edited my post.This should give you a sample data frame you can work with. I want to aggregate the Loss column by JudicialOrientation and then plot a different line for each year in the data set to give aggregate meanLoss for each JudicialOrientation (on the x-axis preferably).

– Coldchain9
Nov 20 '18 at 21:01

add a comment |

Please post the code you have tried so far?

– TeeKea
Nov 20 '18 at 20:54

I edited my post.This should give you a sample data frame you can work with. I want to aggregate the Loss column by JudicialOrientation and then plot a different line for each year in the data set to give aggregate meanLoss for each JudicialOrientation (on the x-axis preferably).

– Coldchain9
Nov 20 '18 at 21:01

Please post the code you have tried so far?

– TeeKea
Nov 20 '18 at 20:54

I edited my post.This should give you a sample data frame you can work with. I want to aggregate the Loss column by JudicialOrientation and then plot a different line for each year in the data set to give aggregate meanLoss for each JudicialOrientation (on the x-axis preferably).

– Coldchain9
Nov 20 '18 at 21:01

add a comment |

1 Answer
1

active

oldest

votes

I suppose your saw the message after you run your code.

geom_path: Each group consists of only one observation. Do you need to adjust the group aesthetic?

So adjusting the group aesthetic would give you this

ggplot(data = df1, aes(x = JudicialOrientation, y = MeanLoss, color=Year, group = Year)) +

  geom_line() +

  geom_point()

enter image description here

I added geom_point so you see that the values for e.g. 2008 are actually there. You wouldn't see them with only geom_line. Hope this helps.

You could even let stat_summary do the aggregation for you and use df directly.

Here is how

ggplot(df, aes(x = JudicialOrientation, y = Loss, color = Year, group = Year)) +

  stat_summary(geom = "line", fun.y = mean) +

  stat_summary(geom = "point", fun.y = mean)

edited Nov 20 '18 at 21:20

answered Nov 20 '18 at 21:14

markus

11.7k1233

1

This is very useful thanks. I did not know I needed a point when using categorical data to make it work properly.

– Coldchain9
Nov 20 '18 at 21:17

@Coldchain9 You don't need the points actually - you simply cannot draw a line for just one observation (that's what you brought you here, I guess).

– markus
Nov 20 '18 at 21:24

add a comment |

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1 Answer
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1 Answer
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I suppose your saw the message after you run your code.

geom_path: Each group consists of only one observation. Do you need to adjust the group aesthetic?

So adjusting the group aesthetic would give you this

ggplot(data = df1, aes(x = JudicialOrientation, y = MeanLoss, color=Year, group = Year)) +

  geom_line() +

  geom_point()

enter image description here

I added geom_point so you see that the values for e.g. 2008 are actually there. You wouldn't see them with only geom_line. Hope this helps.

You could even let stat_summary do the aggregation for you and use df directly.

Here is how

ggplot(df, aes(x = JudicialOrientation, y = Loss, color = Year, group = Year)) +

  stat_summary(geom = "line", fun.y = mean) +

  stat_summary(geom = "point", fun.y = mean)

edited Nov 20 '18 at 21:20

answered Nov 20 '18 at 21:14

markus

11.7k1233

1

This is very useful thanks. I did not know I needed a point when using categorical data to make it work properly.

– Coldchain9
Nov 20 '18 at 21:17

@Coldchain9 You don't need the points actually - you simply cannot draw a line for just one observation (that's what you brought you here, I guess).

– markus
Nov 20 '18 at 21:24

add a comment |

I suppose your saw the message after you run your code.

geom_path: Each group consists of only one observation. Do you need to adjust the group aesthetic?

So adjusting the group aesthetic would give you this

ggplot(data = df1, aes(x = JudicialOrientation, y = MeanLoss, color=Year, group = Year)) +

  geom_line() +

  geom_point()

enter image description here

I added geom_point so you see that the values for e.g. 2008 are actually there. You wouldn't see them with only geom_line. Hope this helps.

You could even let stat_summary do the aggregation for you and use df directly.

Here is how

ggplot(df, aes(x = JudicialOrientation, y = Loss, color = Year, group = Year)) +

  stat_summary(geom = "line", fun.y = mean) +

  stat_summary(geom = "point", fun.y = mean)

edited Nov 20 '18 at 21:20

answered Nov 20 '18 at 21:14

markus

11.7k1233

1

This is very useful thanks. I did not know I needed a point when using categorical data to make it work properly.

– Coldchain9
Nov 20 '18 at 21:17

@Coldchain9 You don't need the points actually - you simply cannot draw a line for just one observation (that's what you brought you here, I guess).

– markus
Nov 20 '18 at 21:24

add a comment |

I suppose your saw the message after you run your code.

geom_path: Each group consists of only one observation. Do you need to adjust the group aesthetic?

So adjusting the group aesthetic would give you this

ggplot(data = df1, aes(x = JudicialOrientation, y = MeanLoss, color=Year, group = Year)) +

  geom_line() +

  geom_point()

enter image description here

I added geom_point so you see that the values for e.g. 2008 are actually there. You wouldn't see them with only geom_line. Hope this helps.

You could even let stat_summary do the aggregation for you and use df directly.

Here is how

ggplot(df, aes(x = JudicialOrientation, y = Loss, color = Year, group = Year)) +

  stat_summary(geom = "line", fun.y = mean) +

  stat_summary(geom = "point", fun.y = mean)

edited Nov 20 '18 at 21:20

answered Nov 20 '18 at 21:14

markus

11.7k1233

I suppose your saw the message after you run your code.

geom_path: Each group consists of only one observation. Do you need to adjust the group aesthetic?

So adjusting the group aesthetic would give you this

ggplot(data = df1, aes(x = JudicialOrientation, y = MeanLoss, color=Year, group = Year)) +

  geom_line() +

  geom_point()

enter image description here

I added geom_point so you see that the values for e.g. 2008 are actually there. You wouldn't see them with only geom_line. Hope this helps.

You could even let stat_summary do the aggregation for you and use df directly.

Here is how

ggplot(df, aes(x = JudicialOrientation, y = Loss, color = Year, group = Year)) +

  stat_summary(geom = "line", fun.y = mean) +

  stat_summary(geom = "point", fun.y = mean)

edited Nov 20 '18 at 21:20

answered Nov 20 '18 at 21:14

markus

11.7k1233

edited Nov 20 '18 at 21:20

answered Nov 20 '18 at 21:14

markus

11.7k1233

answered Nov 20 '18 at 21:14

markus

11.7k1233

answered Nov 20 '18 at 21:14

markus

11.7k1233

1

This is very useful thanks. I did not know I needed a point when using categorical data to make it work properly.

– Coldchain9
Nov 20 '18 at 21:17

@Coldchain9 You don't need the points actually - you simply cannot draw a line for just one observation (that's what you brought you here, I guess).

– markus
Nov 20 '18 at 21:24

add a comment |

1

This is very useful thanks. I did not know I needed a point when using categorical data to make it work properly.

– Coldchain9
Nov 20 '18 at 21:17

@Coldchain9 You don't need the points actually - you simply cannot draw a line for just one observation (that's what you brought you here, I guess).

– markus
Nov 20 '18 at 21:24

This is very useful thanks. I did not know I needed a point when using categorical data to make it work properly.

– Coldchain9
Nov 20 '18 at 21:17

@Coldchain9 You don't need the points actually - you simply cannot draw a line for just one observation (that's what you brought you here, I guess).

– markus
Nov 20 '18 at 21:24

add a comment |

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