murder | Large scale server deploys using BitTorrent | Runtime Evironment library
kandi X-RAY | murder Summary
kandi X-RAY | murder Summary
Murder is a method of using Bittorrent to distribute files to a large amount of servers within a production environment. This allows for scaleable and fast deploys in environments of hundreds to tens of thousands of servers where centralized distribution systems wouldn't otherwise function. A "Murder" is normally used to refer to a flock of crows, which in this case applies to a bunch of servers doing something. For an intro video, see: Twitter - Murder Bittorrent Deploy System.
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QUESTION
I cannot pass Story #5: "When I click a .nav-link button in the nav element, I am taken to the corresponding section of the landing page." I have all of my href
attributes set to the corresponding id
attributes and when i click on them they take me to the correct section of the page, but I am still failing this test... What am I Doing Wrong???
The code I wrote is below:
...ANSWER
Answered 2021-May-28 at 01:41The error reads
QUESTION
I have a dataframe like:
...ANSWER
Answered 2021-May-25 at 21:58We could use across
in filter
looping over the names
of 'l', created the logical expression by subsetting the 'l' using the key from column name (cur_column()
) and negate (!
). Note that cur_column()
works currently only with across
and not if_all/if_any
(dplyr
-1.0.6
on R 4.1.0
)
QUESTION
I have a table in Excel that show which weapon where used to commit murder per year.
I want to read the data and plot it as a line plot with multiple lines:
However my code only gives me a gibberish graph:
This is my code:
...ANSWER
Answered 2021-May-25 at 17:06You need to convert your variable column from factor
to date
. See below;
QUESTION
I have a Excel spread sheet with which looks at the relationship between victim and offender in murders. Either the murderer know the victim or not.
I want to plot it in a barplot, but I need to group each year. I am a bit green in R graphing so I did a paint image of what I want to have in my report:
I have the following code:
...ANSWER
Answered 2021-May-14 at 12:20I did this:
QUESTION
The Q3+1.5*IQR
portion of the box plot does not match the actual calculation and trying to figure out why. I show that it should be 10.24 but the plot shows about 8.5. Wondering if I am missing something obvious or something else is going on. I deliberately put whis=1.5
as an argument.
ANSWER
Answered 2021-Apr-27 at 03:40This is because seaborn flags 10.3 as an outlier. With whis=1.5
, this is the outlier threshold:
QUESTION
Hello!
Task: 3 people got murdered while staying at 3 different hotels. The murders did not happen on the same day. You have 3 lists from each hotel, with the names of people staying there. If you find matching names list them as suspects.
...ANSWER
Answered 2021-Apr-22 at 11:50You receive the error because the last index of listBox1
or listBox3
is smaller than n2. You actually are comparing only the Items of the same index for each list.
I would addRange()
all three lists, distinct()
them to receive all possible names. Loop through those names to check if they appear in all three lists.
QUESTION
import requests
from bs4 import BeautifulSoup
def getPage(url):
try:
req = requests.get(url)
except requests.exceptions.RequestException:
return None
return BeautifulSoup(req.text, 'html.parser')
bs = getPage('https://www.reuters.com/world/us/us-launch-probe-minneapolis-police-after-george-floyd-murder'
'-report-2021-04-21/')
bs.select_one('div.ArticleHeader__container___3rO4Ad h1')
...ANSWER
Answered 2021-Apr-22 at 03:59In BS you can use find('span').next_sibling
QUESTION
I have a large table with a comments column (contains large strings of text) and a date column on which the comment was posted. I created a separate vector of keywords (we'll call this key) and I want to count how many matches there are for each day. This gets me close, however it counts matches across the entire dataset, where I need it broken down by each day. The code:
...ANSWER
Answered 2021-Apr-21 at 18:50As pointed out in the comments, you can use group_by
from dplyr
to accomplish this.
First, you can extract keywords for each comment/sentence. Then unnest
so each keyword is in a separate row with a date.
Then, use group_by
with both date and comment included (to get frequency for combination of date and keyword together). The use of summarise
with n()
will give number of mentions.
Here's a complete example:
QUESTION
I'd like to know how to do 2 execution plans: "traditional" execution plan joins (A with B) and then C. The "new" plan joins (A with B) then (A with C) and then joins the result of those joins so there would be 3 joins. How would I code the traditional and new plan in Oracle SQLPlus given the code below? I also need to measure the time complexity of both methods to show that the new plan takes less time, which I believe I just do with set timer on; The joins can be on whatever attributes work. Same with select statements. I made a artist, b album, c track, and d played.
Here's the database:
...ANSWER
Answered 2021-Apr-18 at 06:13Your question doesn't make a lot of sense, because it's imposing bizarre restrictions that we can't really assess, but I don't mind telling you how to join two joins
You already know how to join three tables in the normal/traditional/sensible sense. Here's how to join them as you ask:
QUESTION
I have created some code to generate histograms using apply on the state.x77 dataset.
...ANSWER
Answered 2021-Apr-11 at 14:02I found the answer
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