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Idyll example post about kernel density.
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QUESTION
I am trying to use sns.histplot() instead of sns.distplot() since I got the following message in colab:
FutureWarning:
distplot
is a deprecated function and will be removed in a future version. Please adapt your code to use eitherdisplot
(a figure-level function with similar flexibility) orhistplot
(an axes-level function for histograms).
Code:
...ANSWER
Answered 2021-Jan-08 at 10:15From the documentation kde_kws=
is intended to pass arguments "that control the KDE computation, as in kdeplot()." It is not entirely explicit which arguments those are, but they seem to be the ones like bw_method=
and bw_adjust=
that change the way the KDE is computed, rather than displayed. If you want to change the appearance of the KDE plot, the you can use line_kws=
, but, as the name implies, the KDE is represented only by a line and therefore cannot be filled.
If you want both a histogram and a filled KDE, you need to combine histplot()
and kdeplot()
on the same axes
QUESTION
I am working on an application in GTK+ and C, and am wondering if there is a way to support dragging files onto the GUI (across File Explorers and Desktop Environments). I have been able to achieve dragging text (through gtk_drag_dest_set
and g_signal_connect
) but dragging files onto the GUI has no effect. I am wondering if this is something that varies by Distro and Desktop Environment or if there is a good way to do this universally. My code for dropping text is here and the Makefile here.
Surely there is a way to do this? I am able to drag files into apps like Firefox, Sublime Text, and VS Code...
EDIT (Clarification): I am using XFCE, but I would like to find a solution which supports other Desktops like Gnome and KDE.
...ANSWER
Answered 2021-Jun-06 at 01:19Change your target entries to this:
QUESTION
Say I have a file teams
with contents as follows:
ANSWER
Answered 2021-Jun-02 at 16:21You can try using sed
's -e
option (see 3.8 Multiple commands syntax):
QUESTION
ANSWER
Answered 2021-Jun-01 at 20:24You could add the medians manually, e.g. using .map_dataframe()
. Here is some example code using the penguins dataset:
QUESTION
When plotting histplot with default stats (density) and KDE flag set to True, the area under the curve is equal to 1. From the Seaborn documentation:
"The units on the density axis are a common source of confusion. While kernel density estimation produces a probability distribution, the height of the curve at each point gives a density, not a probability. A probability can be obtained only by integrating the density across a range. The curve is normalized so that the integral over all possible values is 1, meaning that the scale of the density axis depends on the data values."
Below is the example of density histplot with default KDE normalized to 1.
However, you can also plot a histogram with stats as count or probability. Plotting KDE on top of those will produce the below:
How is the KDE normalized? The area certainly is not equal to 1, but is has to be somehow normalized. I could not find this in the docs, the only explanation regards KDE plotted for density histogram. Any help appreciated here, thank you!
...ANSWER
Answered 2021-Jun-01 at 09:00As far as I understand it, the KDE (kernel density estimation) is simply smoothing the curve formed from the data points. What changes between the three representations is the values from which it is computed :
With density estimation, the total area under the KDE curve is 1 ; which means you can estimate the probability of finding a value between two bounding values with an integral computation. I think they smooth the data points with a curve, compute the area under the curve and divide all the values by the area so that the curve keeps the same look but the area becomes 1.
With probability estimation, the total area under the KDE curve does not matter : each category has a certain probability (e.g. P(x in [115; 125]) = 0.2) and the sum of the probabilities for each category is equal to 1. So instead of computing the area under the KDE curve, they would count all the samples and divide each bin's count by the total.
With the counting estimation, you get a standard bin/count distribution and the KDE is just smoothing the numbers so that you can estimate the distribution of values - so that you can estimate how your observations might look like if you take more measures or use more bins.
So all in all, the KDE curve stays the same : it is a smoothing of the sample data distribution. But there is a factor that is applied on the sample values based on what representation of the data you are interested in.
However, take what I am writing with a grain of salt : I think I am not far from the truth, from a mathematical point of view, but maybe someone could explain it with more precise terms - or correct me if I'm wrong.
Here is some reading about Kerneld density estimation : https://en.wikipedia.org/wiki/Kernel_density_estimation ; but for short, this is a smoothing method with some special methematical properties depending on the parameters used.
QUESTION
I have been asked to plot some histograms and KDEs using seaborn. We just want to focus on a range of the X axis, so I use ax.set_xlim(20_000, 42_460)
. In some cases most of the data is before 20.000 so the plot looks like this:
The full plot looks like this:
There is data, but since most of it is on the range (0,20.000) matplotlib adjusts the Y limit to it and in the range (20.000, 42.460) the data cannot be appreciated.
I would like to know a way to automatically adjust the Y limit so the data in the range (20.000, 42.460) is visible. I have been asked to not to plot just the range (20.000, 42.460), I have to plot the range (0, 42.460) and then zoom in the range (20.000, 42.460).
I have found Axes.relim()
that can take an argument visible_only=True
but it does not seem to work as I expected.
Other option could be to use a different library to calculate the histogram data, calculate then the Y limit and set it with ax.set_ylim(0, range_max)
but we are also plotting a seaborn KDE that has the same problem and that could be more complicated. Here it is an immage of a good plot:
EDIT:
To reproduce the plot use this data and this code:
...ANSWER
Answered 2021-May-30 at 21:29The fastest way to achieve what you want is to subset your DataFrame:
QUESTION
I want to plot histogram and kde line in the same plot with different color. I want to set green color for the histogram and blue color for the kde line. I managed to figure out using line_kws to change the kde line color but hist_kws is not working on the displot. I have tried using histplot but I am unable to put different color for the hist and the line.
...ANSWER
Answered 2021-May-30 at 11:36You can use line_kws={'color': ...}
to change the color of the kde line. And directly facecolor=...
to change the color of the histogram.
Here is an example:
QUESTION
I am learning C programming from "Learn c the hard way by Zed Shaw". He asks the learner to try and break their own code.
So I tried the following C code and thought printing more values that I gave argv will break it but it did not until later.
...ANSWER
Answered 2021-May-30 at 09:48A segmentation fault happens when the code try to access a memory region that is not available.
Accessing an array out of bounds doesn't means that the memory before or after the area occupied by the array is not available: The compiler or the runtime usually put all varibales or data in general in a given block of memory. If your array is the last item of such a memory block, the accessing it with a to big index will produce a Segmentaion Fault but is the array is in the middle of the memory block, you will just access memory used for other data, giving unexpected result and undefined behavior.
If the array (In may example, but valid for anything) is written, accessing available memory will not produce a segmentation fault but will overwrite something else. It may produce unexpected results or crash or segmentation fault later! This kind of bug is frequently very difficult to find because the unexpected result/behavior looks completely independent of the root cause.
QUESTION
Now I want to make a docker command run in frontend so that I could see the log output. Now I am using this command to run my docker container:
...ANSWER
Answered 2021-May-21 at 09:21Basically, you should get the point (based on your latest comment). Docker is based on some command, when it's done - it stops the container.
So to make it continuously running you should have command and run infinitely.
Also check this answer as well, there are more explanation Why docker exiting with code 0
One of the easiest solution is to tail some logs. Like,
QUESTION
I'm using Tcl 8.6.11, SQLite 3.35.5., and Manjaro Linux KDE.
I'm trying to take a verse in Hebrew and write it one word per row in a data table. This is one verse, for example.
בְּרֵאשִׁית בָּרָא אֱלֹהִים אֵת הַשּׁמַיִם וְאֵת הָאָֽרֶץ׃
The goal was to write the data to a list and then join the list as the values part of a SQL insert statement. As you can see, each [lindex $l n]
prints as expected but the [join $l ,]
starting at the second element places the Hebrew in the first position instead of the last, causing the SQL statement to fail.
How can I get each component of the [join $l ,]
to be ordered as they are in the [lindex $l n]
?
Thank you.
...ANSWER
Answered 2021-May-19 at 08:33As always with SQL, use parameters in a prepared statement instead of trying to add values directly into a query string at runtime. Something like:
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