usl | Analyze system scalability with the Universal Scalability | Blockchain library
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Analyze system scalability with the Universal Scalability Law
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QUESTION
I was tasked to write a program to write some websites on a text file and extract those who have the same top level domains and write it to a separate text file. This is my code:
...ANSWER
Answered 2021-Mar-08 at 13:55The way you are opening the files for writing always truncates the output files. If you call the FileWriter
constructor with just the file name, then that file will be opened for writing and truncated.
In order to append to the file, you should use the constructor that takes a boolean argument that specifies whether you want to append or not:
QUESTION
I'm new in python and pandas. I'm trying to convert a pandas dataframe to a json with format:
...ANSWER
Answered 2021-Jan-20 at 17:24Try this:
QUESTION
I'm trying make a comment section for my Q&A project.I made the model for comment , the form part in question_detail.html an , also the QuestionCommentForm() in form.py .
model.py
...ANSWER
Answered 2021-Jan-02 at 15:26You never save the model object (not by the form, nor by the view). Furthermore the name of the method is 'POST'
, not 'Post'
:
QUESTION
I am trying to add some sibling tags after 10
tag
My XML looks like:
...ANSWER
Answered 2020-Dec-31 at 21:19You can find position of VIDPOM
in list of children of SLUCH
QUESTION
I am developing some data sheet to check process control limits. I've could develop the system as required. But I like to increase the performance in there. Part of the data sheet that I've developed will described below.
LSL & USL Limits are as mention in above the table for ID. First I've extract the data into Help Col 01(Col V) which are within limits using below formula.
...ANSWER
Answered 2020-Dec-08 at 05:28In V4
, formula copied down :
QUESTION
I have a dataframe which has columns -
...ANSWER
Answered 2020-Nov-01 at 15:14I would first create a dictionary with the averages and then convert it into a DataFrame
QUESTION
I have a python list of about 300 items in a pandas correlation matrix and for each item, I would like to programmatically group the corresponding 10 least correlated items with it and store it in a dictionary.
I'm not sure how to do that since the correlations run from 1 to -1. If I take the smallest number, I'll take the most negatively correlated items.
I'm sure this is some sort of iterator but I'm not sure how. Here is a smaller correlation matrix example with 10.
...ANSWER
Answered 2020-Oct-04 at 10:39You can use abs
+ nsmallest
inside a dict
comprehension:
QUESTION
Here are the codes that I use:
...ANSWER
Answered 2020-Jun-05 at 05:28Try adding some sleep time (say 3 seconds) every n
number of tickers.
QUESTION
I have two dataframes, one that is a very large, wide dataset with hundreds of parameters and another with 3 columns that identify the parameters in the larger dataframe with specification limits and two columns for the lower and upper limits. What I want to do is to be able to reduce the wide dataframe to just the columns that are in the limits dataframe. I feel like this is incredibly basic but I cannot get it to work
See below for an example and output that I would like.
df
...ANSWER
Answered 2020-May-01 at 15:14Just subset df
column names by values %in%
the parameter
column of limits
QUESTION
Two questions:
I like to store and process the output of ss.study.ca() in same way as I do with ggplot:
...
ANSWER
Answered 2020-Apr-13 at 15:27Thank you for your questions Luc.
- ss.study.ca() does not produce a ggplot but a grid plot (with ggplots inside). Nonetheless, as ggplot internally also uses the grid system, you can merge SixSigma and ggplot2 plots with the grid and gridExtra packages. This is a reproducible example that works for me:
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