quora | Quora.com like project with Ruby on Rails | Application Framework library

Lately @MrWhite gave us another, better and simple solution - just add DirectoryIndex index.html to .htaccess file will do the same.

From the beginning I wrote that DirectoryIndex is working but NO! It seems it's working when you try prerender.io, but in reality it was showing website like this:

and I had to remove it. So it was not issue with .htaccess file, it was coming from the server.

What I did was I went into WHM->Apache Configurations->DirectoryIndex Priority and I saw this list

and yes that was it!

To fix I just moved index.html to the very top second comes index.html.var and after rest of them.

I don't know what index.html.var is for, but I did not risk just to remove it. Hope it helps someone who struggled as me.

Here is a solution with ggplot2:

1. Rownames to first column with tibble::rownames_to_column
2. fct_reorder from forcatspackage to order your data
3. plot with ggplot, change width as preferred etc....

We need to specify the column name as unquoted

The reason is that there are duplicate rows. So, we can create a group by row_number

The first argument to mutate must be a data.frame. You did not name your data.frame df, so the function df is passed to mutate.

tidyr::separate should do this for you (although it may warn about uneven numbers of elements in different rows)

What is the complexity of your algorithm of finding the longest increasing subsequence?

This article provides an algorithm with the complexity of O(n log n). Upd: doesn't work. You don't even need to modify the code, because in python comparison works for tuples: assert (1, 2) < (3, 4)

The answer is "usually you don't need a table whose size is a prime number, but there are some implementation reasons why you might want to do this."

Fundamentally, hash tables work best when hash codes are spread out as close to uniformly at random as possible. That prevents items from clustering in any one location within the table. At some level, provided that you have a good enough hash function to make this happen, the size of the table doesn't matter.

So why do folks say to pick tables whose size is a prime? There are two main reasons for this, and they're due to specific cases that don't arise in all hash tables.

One reason why you sometimes see prime-sized tables is due to a specific way of building hash functions. You can build reasonable hash functions by picking functions of the form h(x) = (ax + b) mod p, where a is a number in {1, 2, ..., p-1} and b is a number in the {0, 1, 2, ..., p-1}, assuming that p is a prime. If p isn't prime, hash functions of this form don't spread items out uniformly. As a result, if you're using a hash function like this one, then it makes sense to pick a table whose size is a prime number.

The second reason you see advice about prime-sized tables is if you're using an open-addressing strategy like quadratic probing or double hashing. These hashing strategies work by hashing items to some initial location k. If that slot is full, we look at slot (k + r) mod T, where T is the table size and r is some offset. If that slot is full, we then check (k + 2r) mod T, then (k + 3r) mod T, etc. If the table size is a prime number and r isn't zero, this has the nice, desirable property that these indices will cycle through all the different positions in the table without ever repeating, ensuring that items are nicely distributed over the table. With non-prime table sizes, it's possible that this strategy gets stuck cycling through a small number of slots, which gives less flexibility in positions and can cause insertions to fail well before the table fills up.

So assuming you aren't using double hashing or quadratic probing, and assuming you have a strong enough hash function, feel free to size your table however you'd like.

Getting your desired answer is pretty simple: