![deltagraph stacked plots deltagraph stacked plots](https://vizzlo.com/img/vizzards/stacked-bar-chart.png)
Let's import a dataset and work with it instead. We work with data imported from larger datasets or pulled directly from databases. However, more typically, we don't work with simple, hand-made lists like this. The x list acts as our categorical variable list, while the y list acts as the numerical variable list. Here, we have two lists of values, x and y. Let's start out with the most basic form of populating data for a Line Plot, by providing a couple of lists for the X-axis and Y-axis to the lineplot() function: import matplotlib.pyplot as plt They can typically be used in much the same way Bar Plots can be used, though, they're more commonly used to keep track of changes over time. Line Plots display numerical values on one axis, and categorical values on the other.
#Deltagraph stacked plots how to#
In this tutorial, we'll take a look at how to plot a Line Plot in Seaborn - one of the most basic types of plots. It offers a simple, intuitive, yet highly customizable API for data visualization. Through the chain.Seaborn is one of the most widely used data visualization libraries in Python, as an extension to Matplotlib. You can also apply it on the ggplot object to make these changes permanent To be sure to reverse the alphabetical order, add as.character ggplot(df2, aes(x = Genotype, y = Freq, fill = Swelling)) +Īrrange_gg(Swelling, desc(as.character(Swelling))) + ggplot(df2, aes(x = Genotype, y = Freq, fill = Swelling)) + This will revert the existing order as defined alphabetically IF by is a character col, and the factor order otherwise. Geom_bar(position = "fill",stat = "identity") %>%Īrrange_gg(Genotype, desc(Freq), Swelling ="Swelling 1") %>%Īrrange_gg(Swelling, desc(Freq), Swelling !="Swelling 1") + so it will not reorder all values, just put Swelling 1 at the bottom. FALSE is put before TRUE when sorting, and first levels are on top. We can sort by the condition Swelling !="Swelling 1". Your additional request to get Swelling 1 at the bottom can be done in different ways yielding the same result here but not in the general case. Scale_y_continuous(labels = scales::percent) One cool thing about it is that for once the different operator precedence of + and %>% works for us and not against.Īrrange_gg(Genotype, desc(Freq), Swelling="Swelling 1") %>% I took a shot at it below, it should work with all geom_*(), stat_*(), and ggplot() calls. We could write a function to apply on the geom call to sort this type of issue as it's quite common and the way out is verbose and awkward. Theme(legend.title = element_text(size=16, face="bold")) Labels=c("No Swelling", "Slight swelling (L-axil)", "Strong swelling (L-axil)", "Swelling (hypocotyl)", "Crackings (L-axil)") ) + Scale_fill_brewer(palette="RdPu", name= my_legend_title, Scale_y_continuous(name= "Percentage of plants showing different swelling symptoms",labels = percent)+
![deltagraph stacked plots deltagraph stacked plots](http://i.stack.imgur.com/rq6r1.png)
Ggplot(aes(x = Genotype, y = pct, fill = SwellingComb)) + Mutate(freq.s1 = sum(SwellingComb="Swelling 1")) %>% I will be very happy to see what I'm doing wrong. Ggplot(aes(x = Genotype, y = pct, fill = Swelling)) +ĮxRCommTable 245×850 3.55 KB. Mutate(Swelling = factor(Swelling, levels=sort(levels(Swelling), decreasing=TRUE))) %>%
![deltagraph stacked plots deltagraph stacked plots](https://stackabuse.s3.amazonaws.com/media/matplotlib-change-scatter-plot-marker-size-4.png)
# set Swelling factor levels to decreasing order # Mutate(Genotype = factor(Genotype, levels=unique(Genotype))) %>% # Set Genotype factor order based on the sorting we just created Mutate(freq.s1 = sum(Swelling="Swelling 1")) %>% # Get frequency of "Swelling 1" within each level of Genotype So, here is a modification or my extension of Joels nice solution of your request: library(tidyverse) So just us the reordering-trick to reorder your Swelling levels. Same trick as Joels used before by reordering the Genotype levels. Scale_y_continuous(labels = scales::percent_format()) +Ĭreated on by the reprex package (v0.2.1) Ggplot(aes(x = reorder(Genotype, desc(Freq_1)), y = Freq, fill = Swelling)) + I'm sure it must be a more elegant solution but in the mean while this works df % Scale_y_continuous(labels = percent_format()) # to have percentage on y axis Geom_bar(position = "fill",stat = "identity") + Ggplot(df2, aes(x = Genotype, y = Freq, fill = Swelling)) + Here you can find my R data: df do not show when frequency is 0ĭf2<-ddply(df.(Swelling), function(x) with(x, ame(100*round(table(Genotype)/length(Genotype),2)))) The pictures show you what I have and what I want. It's mean that x axis has to be ordered like: Genotype 2, Genotype 3, Genotype 1 I want to order my variable depending on the frequency of the swelling 1.