How to create a scatter plot legend with only one symbol for each label? - matplotlib

How can I create a scatter plot legend without two symbols showing up each time? I can understand why you'd want this when you're joining symbols by lines, but for a pure scatter plot, all I want in the legend is one example of the symbol. This plot from a previous stackoverflow post shows the kind of thing I mean:

In the legend command you can use the scatterpoints option:
ax.legend(loc=0, scatterpoints = 1)
For a normal plot, it is the option numpoints.
Here you can find more information about the keyword arguments for the legend: http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.legend

Related

Turn off x-axis marginal distribution axes on jointplot using seaborn package

There is a similar question here, however I fail to adapt the provided solutions to my case.
I want to have a jointplot with kind=hex while removing the marginal plot of the x-axis as it contains no information. In the linked question the suggestion is to use JointGrid directly, however Seaborn then seems to to be unable to draw the hexbin plot.
joint_kws = dict(gridsize=70)
g = sns.jointplot(data=all_data, x="Minute of Hour", y="Frequency", kind="hex", joint_kws=joint_kws)
plt.ylim([49.9, 50.1])
plt.xlim([0, 60])
g.ax_joint.axvline(x=30,ymin=49, ymax=51)
plt.show()
plt.close()
How to remove the margin plot over the x-axis?
Why is the vertical line not drawn?
Also is there a way to exchange the right margin to a plot which more clearly resembles the density?
edit: Here is a sample of the dataset (33kB). Read it with pd.read_pickle("./data.pickle")
I've been fiddling with an analog problem (using a scatterplot instead of the hexbin). In the end, the solution to your first point is awkwardly simple. Just add this line :
g.ax_marg_x.remove()
Regarding your second point, I've no clue as to why no line is plotted. But a workaround seems to be to use vlines instead :
g.ax_joint.vlines(x=30, ymin=49, ymax=51)
Concerning your last point, I'm afraid I haven't understood it. If you mean increasing/reducing the margin between the subplots, you can use the space argument stated in the doc.

TramineR legend position and axis

I'm working with TraMineR and I don't know how to arrange my plot. So basically what i would like to have the legend under the plot and to remove the space between the x and y axis. Any help is welcomed.
The plot:
Sample code:
seqdplot(Activities.seq, with.legend=FALSE)
legend("bottom", legend=attr(Activities.seq, "labels"),
fill=attr(Activities.seq, "cpal"),
inset=-.1, bty="o", xpd=NA, cex=.75,ncol=3)
The family of seqplot functions offers a series of arguments to control the legend as well as the axes. Look at the help page of seqplot (and of plot.stslist.statd for specific seqdplot parameters).
For instance, you can suppress the x-axis with axes=FALSE, and the y-axis with yaxis=FALSE.
To print the legend you can let seqdplot display it automatically using the default with.legend=TRUE option and control it with for examples cex.legend for the font size, ltext for the text. You can also use the ncol argument to set the number of columns in the legend.
The seqplot functions use by default layout to organize the graphic area between the plots and the legend. If you need more fine tuning (e.g. to change the default par(mar=c(5.1,4.1,4.1,2.1)) margins around the plot and the legend), you should create separately the plot(s) and the legend and then organize them yourself using e.g. layout or par(mfrow=...). In that case, the separate graphics should be created by setting with.legend=FALSE, which prevents the display of the legend and disables the automatic use of layout.
The color legend is easiest obtained with seqlegend.
I illustrate with the mvad data that ships with TraMineR. First the default plot with the legend. Note the use of border=NA to suppress the too many vertical black lines.
library(TraMineR)
data(mvad)
mvad.scode <- c("EM", "FE", "HE", "JL", "SC", "TR")
mvad.seq <- seqdef(mvad, 17:86,
states = mvad.scode,
xtstep = 6)
# Default plot with the legend,
seqdplot(mvad.seq, border=NA)
Now, we suppress the x and y axes and modify the display of the legend
seqdplot(mvad.seq, border=NA,
axes=FALSE, yaxis=FALSE, ylab="",
cex.legend=1.3, ncol=6, legend.prop=.11)
Here is how you can control the space between the plot and the x and y axes
seqdplot(mvad.seq, border=NA, yaxis=FALSE, xaxis=FALSE, with.legend=FALSE)
axis(2, line=-1)
axis(1, line=0)
Creating the legend separately and reducing the left, top, and right margins around the legend
op <- par(mar=c(5.1,0.1,0.1,0.1))
seqlegend(mvad.seq, ncol=2, cex=2)
par(op)

Matplotlib stacked bar chart not showing all bars

I will make a stacked bar chart in matplotlib. Somehow it doesnt include all the bar chart that i gave him (there should be like 50 bar charts stacked on each other)
The code:
N=45 #numbers of columns
max_el=50
ind=np.arrange(N)
for bar in range(0,max_el):
y=[dic[value][bar] for value in dic]
plt.bar(ind,y,)
plt.show()
note: I used the similar code and same data and made a stacked bar chart with plotly (which worked)
With plotly
With matplotlib
Some of the values of variables are zeros or 0.1. Could that be the problem ?
As described in the comments, you need to add a bottoms array that keeps track of how much each should be moved up from the 0 line. Otherwise, they all start plotting a 0 and overplot one another, with the tallest one sticking up to its values and each one hiding those that were plotted before.

How to remove duplicate legends from the plot in matplotlib

Here is the code snippet I'm using to plot the graph:
plt.figure(figsize=(15,6))
plt.xticks(rotation='vertical')
for frame in top20s:
plt.plot(frame['name'][:20], frame['pb'][:20], label=frame.league)
plt.legend()
plt.show()
And below is what I get:
How would I remove all the duplicates in the legend, and have one for each plots?
The problem is that you are labeling your lines with an entire dataframe column.
Instead you would want to only use one of the column's entries as label.
I.e. instead of plt.plot(..., label=frame.league) use
plt.plot(..., label=frame.league[0])

Generating subplots of heatmaps in Julia-lang

I am trying to produce a figure/plot with more than a single heatmap (matrix with color shading according to the cell value). At the moment using Plots;
pyplot() and heatmap(mat) is enough to produce a heatmap.
It is not clear to me how to produce a single figure with more though. After looking at this page example subplots for how to use the layout, and then the example histogram, I cannot seem to produce working examples for the two together.
The question is how to produce a figure with two different matrices displayed via heatmap or some other function to do the same?
(as an extra side, could you also explain the context of the 'using' statement and how it relates to the 'backend'?)
The easiest way is to make a Vector of heatmaps, then plot those
using Plots
hms = [heatmap(randn(10,10)) for i in 1:16];
plot(hms..., layout = (4,4), colorbar = false)
The using statement calls the Plots library. The "backend" is another package, loaded by Plots, that does the actual plotting. Plots itself has no plotting capabilities - it translates the plot call to a plot call for the backend package.
Explanation of the code above:
Plotting with Plots is a two-step process. 1: plot generates a Plot object with all the information for the plot; 2: when a Plot object is returned to the console, it automatically calls julia´s display function, which then generates the plot. But you can do other things with the Plot object first, like put it in an array.
The heatmap call is a short form of plot(randn(10,10), seriestype = :heatmap), so it just creates a Plot object. 16 Plot objects are stored in the vector.
Passing a number of Plot objects to plot creates a new, larger Plot, with each of the incoming Plot objects as subplots. The splat operator ... simply passes each element of the Array{Plot} to plot as an individual argument.