percentile | Show percentile of input numbers
kandi X-RAY | percentile Summary
kandi X-RAY | percentile Summary
Show percentile of input numbers.
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
- percentile returns the percentage of the given reader .
- This is the main entry point for testing
- percentileN returns the nearest percentile of numbers
- printPercentileN prints a sorted list of numbers .
percentile Key Features
percentile Examples and Code Snippets
Community Discussions
Trending Discussions on percentile
QUESTION
I have a raster data and wants to make contour graph similar to the this question enter link description here. I got the code from here. But I want to highlight (colour) the regions which is above 75 percentile and remaining by the simple lines that are shown in picture below. I copied the code from the the above link
Code is folowing
...ANSWER
Answered 2022-Apr-09 at 16:05You can set the breaks of geom_contour_filled
to start at your 75th centile, and make the NA
value of scale_fill_manual
transparent. You also need to draw in the default contour lines:
QUESTION
I have a table like
...ANSWER
Answered 2022-Apr-03 at 17:44We convert to a logical vector (.x < quantile(.x, 0.30)
) and get the count with sum
- as TRUE
-> 1 and FALSE
-> 0
QUESTION
What would be the correct type hint for a function that accepts an one dimensional array-like object? More specifically, my function uses np.percentile
and I would like to 'match' np.percentile
's flexibility in terms of the kind of array it accepts (List, pandas Series, numpy array, etc.). Below illustrates what I'm looking for:
ANSWER
Answered 2022-Mar-16 at 15:01Use numpy.typing.ArrayLike
:
QUESTION
I have a dataframe with these names:
...ANSWER
Answered 2022-Feb-18 at 22:09You can do something like this, if I understand what you want
(First, a quick explanation of the pivot_longer()
options that I use)
cols
selects the columns you want to pivotnames_to
with multiple elements allows us to pivot into multiple columnsnames_prefix
allows us to remove a common prefix across the columns that we want to pivotname_sep
allows us to indicate how the multiple names innames_to
are broken up in the original columns
QUESTION
In these sample data, users place orders of certain random values at random dates in time. I've successfully implemented a method to calculate the percentile rank of each value regarding the last 180 days of orders of that same user.
However, for large values of n
the last groupby
line of code runs very slow (1M rows run in about 1m30s) Does anyone have a suggestion on how to improve computing time?
ANSWER
Answered 2022-Jan-17 at 20:36you can leverage the parameter raw=True
in the apply to pass a numpy array instead of Series. You need to slightly change your function to work with an array.
QUESTION
I am working with the R programming language. Suppose, I have the following data frame:
...ANSWER
Answered 2021-Dec-28 at 06:12This may be what you want
QUESTION
been wracking my head trying to replicate a solution to a sql exercise on pandas. the exercise contains creating 1 percentile bins using the NTILE function in order to calculate some metrics.
source Dset looks like this and the percentile i want to divide by is the measure_value column :
[source df]
this is what i want to get to (first create the "Ntile" equivalent and then group by it, agging with min max and count).
[destination df]
tried using qcut but encountered an error because of similar values.
code attempted :
...ANSWER
Answered 2021-Oct-06 at 17:37If the imgur you posted is truely your dataframe, then the problem is that you are performing qcut on a single-rowed dataframe. How can you split up a single row into 100 quantiles? Pandas is trying to create a bunch of bins of different quantile values, but since you only have one observation, all of those bins start and end in the same place. I can prove this is the case by recreating your error using a single row df:
QUESTION
I am doing some time series forecasting analysis with the fable
and fabletools
package and I am interested in comparing the accuracy of individual models and also a mixed model (consisting of the individual models I am using).
Here is some example code with a mock dataframe:-
...ANSWER
Answered 2021-Dec-07 at 11:04A couple of things to consider:
- While it's definitely desirable to quickly evaluate the performance of many combination models, it's pretty impractical. The best option would be to evaluate your models individually, and then create a more simple combination using, e.g. the 2 or 3 best ones
- As an example, consider that you can actually have weighted combinations - e.g.
0.75 * ets + 0.25 * arima
. The possibilities are now literally endless, so you start to see the limitations of the brute-force method (N.B. I don't thinkfable
actually supports these kind of combinations yet though).
That, said, here's one approach you could use to generate all the possible combinations. Note that this might take a prohibitively long time to run - but should give you what you're after.
QUESTION
suppose I have a number distribution like this.
...ANSWER
Answered 2021-Oct-29 at 23:07We may use findInterval
QUESTION
I have a string long string: its a teamcity buildLog
This is a buildLog from teamcity.
ANSWER
Answered 2021-Oct-15 at 17:05I can't check PowerShell 3.0 for you. But the following works in Windows PowerShell 5.1. I've got two solutions, one which includes the first info line as part of the match and one that does not.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install percentile
Support
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page