You would use the `read.csv` function; for example:

    dat = read.csv(&quot;spam.csv&quot;, header = TRUE)

You can also reference [this tutorial][1] for more details.

**Note:** make sure the `.csv` file to read is in your working directory (using  `getwd()`) or specify the right path to file. If you want, you can set the current directory using [`setwd`](https://www.rdocumentation.org/packages/base/versions/3.4.3/topics/getwd).


  [1]: http://www.cyclismo.org/tutorial/R/input.html#read

I have an old url (`www1.test.net`) and I would like to redirect it to `https://www1.test.net`&lt;br /&gt;
I have implemented and installed our SSL certificate on my site.&lt;br /&gt;
This is my old file `.htaccess`:

    RewriteEngine On
    RewriteRule !\.(js|gif|jpg|png|css|txt)$ public/index.php [L]
    RewriteCond %{REQUEST_URI} !^/public/
    RewriteRule ^(.*)$ public/$1 [L]


How can I configure my `.htaccess` file so that url auto redirect to `https`?&lt;br /&gt;
Thanks!

.htaccess redirect http to https

No, the answer to my second question is not the winter.

**Preface:**

I&#39;ve been doing a lot of research on Entity Framework recently and something that keeps bothering me is its performance when the queries are not warmed-up, so called cold queries. 

I went through the [performance considerations][1] article for Entity Framework 5.0. The authors introduced the concept of **Warm** and **Cold** queries and how they differ, which I also noticed myself without knowing of their existence. Here it&#39;s probably worth to mention I only have six months of experience behind my back.

Now I know what topics I can research into additionally if I want to understand the framework better in terms of performance. Unfortunately most of the information on the Internet is outdated or bloated with subjectivity, hence my inability to find any additional information on the *Warm* vs *Cold* queries topic.

Basically what I&#39;ve noticed so far is that whenever I have to recompile or the recycling hits, my initial queries are getting very slow. Any subsequent data read is fast (*subjective*), as expected.

We&#39;ll be migrating to Windows Server 2012, IIS8 and SQL Server 2012 and as a Junior I actually won myself the opportunity to test them before the rest. I&#39;m very happy they introduced a warming-up module that will get my application ready for that first request. However, I&#39;m not sure how to proceed with warming up my Entity Framework.

What I already know is worth doing:

 - Generate my Views in advance as suggested.
 - Eventually move my models into a separate assembly.

What I consider doing, by going with common sense, **probably wrong approach**:

 - Doing dummy data reads at Application Start in order to warm things
   up, generate and validate the models.

**Questions:** 

- What would be the best approach to have high availability on my Entity Framework at anytime?
- In what cases does the Entity Framework gets &quot;cold&quot; again? (Recompilation, Recycling, IIS Restart etc.)

  [1]: http://msdn.microsoft.com/en-us/data/hh949853.aspx

How to &quot;warm-up&quot; Entity Framework? When does it get &quot;cold&quot;?

I have a `.csv` file in my workstation. How can I open that file in R and do statistical calculation?

How do I import a CSV file in R?

<p>I have a <code>.csv</code> file in my workstation. How can I open that file in R and do statistical calculation?</p>


I have a `.txt` file that contains row names. However, R set the row names as the first column.

Specifying row names when reading in a file

I am aware that one can merge (join) two `data.table` with the `merge` function or the `[.data.table` function.  However, if I have say 10, `data.table`s and want to use `do.call` to merge them all together, is there a function that would do this? Currently I resort to `do.call(cbind, ...)` which works for only very special cases.

Merging multiple data.tables

From a dataframe like this

    test &lt;- data.frame(&#39;id&#39;= rep(1:5,2), &#39;string&#39;= LETTERS[1:10])
    test &lt;- test[order(test$id), ]
    rownames(test) &lt;- 1:10

    &gt; test
        id string
     1   1      A
     2   1      F
     3   2      B
     4   2      G
     5   3      C
     6   3      H
     7   4      D
     8   4      I
     9   5      E
     10  5      J

I want to create a new one with the first row of each id / string pair. If sqldf accepted R code within it, the query could look like this:

    res &lt;- sqldf(&quot;select id, min(rownames(test)), string 
                  from test 
                  group by id, string&quot;)

    &gt; res
        id string
     1   1      A
     3   2      B
     5   3      C
     7   4      D
     9   5      E

Is there a solution short of creating a new column like

    test$row &lt;- rownames(test)

and running the same sqldf query with min(row)?

Select the first row by group

When passing missing values to ggplot, it&#39;s very kind, and warns us that they are present. This is acceptable in an interactive session, but when writing reports, you do not the output get cluttered with warnings, especially if there&#39;s many of them. Below example has one label missing, which produces a warning.

    library(ggplot2)
    library(reshape2)
    mydf &lt;- data.frame(
      species = sample(c(&quot;A&quot;, &quot;B&quot;), 100, replace = TRUE), 
      lvl = factor(sample(1:3, 100, replace = TRUE))
    )
    labs &lt;- melt(with(mydf, table(species, lvl)))
    names(labs) &lt;- c(&quot;species&quot;, &quot;lvl&quot;, &quot;value&quot;)
    labs[3, &quot;value&quot;] &lt;- NA
    ggplot(mydf, aes(x = species)) + 
       stat_bin() + 
       geom_text(data = labs, aes(x = species, y = value, label = value, vjust = -0.5)) +
       facet_wrap(~ lvl)

![enter image description here][1]

If we wrap `suppressWarnings` around the last expression, we get a summary of how many warnings there were. For the sake of argument, let&#39;s say that this isn&#39;t acceptable (but is indeed very honest and correct). How to (completely) suppress warnings when printing a ggplot2 object?

  [1]: http://i.stack.imgur.com/l9AnH.png

How to suppress warnings when plotting with ggplot

I&#39;m using ggplot and have two graphs that I want to display on top of each other.  I used `grid.arrange` from gridExtra to stack them.  The problem is I want the left edges of the graphs to align as well as the right edges regardless of axis labels.  (the problem arises because the labels of one graph are short while the other is long).

**The Question:**   
How can I do this?  I am not married to grid.arrange but the ggplot2 is a must.  

**What I&#39;ve tried:**   
I tried playing with widths and heights as well as ncol and nrow to make a 2 x 2 grid and place the visuals in opposite corners and then play with the widths but I couldn&#39;t get the visuals in opposite corners.



    require(ggplot2);require(gridExtra)
    A &lt;- ggplot(CO2, aes(x=Plant)) + geom_bar() +coord_flip() 
    B &lt;- ggplot(CO2, aes(x=Type)) + geom_bar() +coord_flip() 
    grid.arrange(A, B, ncol=1)

![enter image description here][1]


  [1]: http://i.stack.imgur.com/gvnx5.png

Left align two graph edges (ggplot)

I have a CSV file, here is a sample of what it looks like:

    Year:  Dec: Jan:
    1      50   60
    2      25   50
    3      30   30
    4      40   20
    5      10   10

I know how to read the file in and print each column (for ex. - `[&#39;Year&#39;, &#39;1&#39;, &#39;2&#39;, &#39;3&#39;, etc]`). But what I actually want to do is read the rows, which would be like this `[&#39;Year&#39;, &#39;Dec&#39;, &#39;Jan&#39;]` and then `[&#39;1&#39;, &#39;50&#39;, &#39;60&#39;]` and so on. 

And then I would like to store those numbers `[&#39;1&#39;, &#39;50&#39;, &#39;60&#39;]` into variables so I can total them later for ex.:

`Year_1 = [&#39;50&#39;, &#39;60&#39;]`. Then I can do `sum(Year_1) = 110`.

How would I go about doing that in Python 3?

Reading rows from a CSV file in Python

I am new to Python. I need to write some data from my program to a spreadsheet. I&#39;ve searched online and there seem to be many packages available (xlwt, XlsXcessive, openpyxl). Others suggest to write to a .csv file (never used CSV and don&#39;t really understand what it is).

The program is very simple. I have two lists (float) and three variables (strings). I don&#39;t know the lengths of the two lists and they probably won&#39;t be the same length.

I want the layout to be as in the picture below:

![Layout sample][1]


  [1]: http://i.stack.imgur.com/Ih3fa.png

The pink column will have the values of the first list and the green column will have the values of the second list.

So what&#39;s the best way to do this?

P.S. I am running Windows 7 but I won&#39;t necessarily have Office installed on the computers running this program.


    import xlwt

    x=1
    y=2
    z=3

    list1=[2.34,4.346,4.234]

    book = xlwt.Workbook(encoding=&quot;utf-8&quot;)

    sheet1 = book.add_sheet(&quot;Sheet 1&quot;)

    sheet1.write(0, 0, &quot;Display&quot;)
    sheet1.write(1, 0, &quot;Dominance&quot;)
    sheet1.write(2, 0, &quot;Test&quot;)
    
    sheet1.write(0, 1, x)
    sheet1.write(1, 1, y)
    sheet1.write(2, 1, z)

    sheet1.write(4, 0, &quot;Stimulus Time&quot;)
    sheet1.write(4, 1, &quot;Reaction Time&quot;)

    i=4

    for n in list1:
        i = i+1
        sheet1.write(i, 0, n)
    


    book.save(&quot;trial.xls&quot;)

I wrote this using all your suggestions. It gets the job done but it can be slightly improved.

How do I format the cells created in the for loop (list1 values) as scientific or number?

I do not want to truncate the values. The actual values used in the program would have around 10 digits after the decimal.

Writing to an Excel spreadsheet

I would like to know the following;

1. Why the given non-working example doesn&#39;t work.
2. If there are any other cleaner methods than those given in working example.

*Non-working example*

    &gt; ids=(1 2 3 4);echo ${ids[*]// /|}
    1 2 3 4
    &gt; ids=(1 2 3 4);echo ${${ids[*]}// /|}
    -bash: ${${ids[*]}// /|}: bad substitution
    &gt; ids=(1 2 3 4);echo ${&quot;${ids[*]}&quot;// /|}
    -bash: ${&quot;${ids[*]}&quot;// /|}: bad substitution

*Working example*

    &gt; ids=(1 2 3 4);id=&quot;${ids[@]}&quot;;echo ${id// /|}
    1|2|3|4
    &gt; ids=(1 2 3 4); lst=$( IFS=&#39;|&#39;; echo &quot;${ids[*]}&quot; ); echo $lst
    1|2|3|4

In context, the delimited string to be used in a [sed][1] command for further parsing.


  [1]: https://www.gnu.org/software/sed/manual/sed.html

Converting a Bash array into a delimited string

My source data is in a TSV file, 6 columns and greater than 2 million rows.

Here&#39;s what I&#39;m trying to accomplish:

1. I need to read the data in 3 of the columns (3, 4, 5) in this source file
2. The fifth column is an integer. I need to use this integer value to duplicate a row entry with using the data in the third and fourth columns (by the number of integer times).
3. I want to write the output of #2 to an output file in CSV format.

Below is what I came up with.  

My question: is this an efficient way to do it?  It seems like it might be intensive when attempted on 2 million rows.

First, I made a sample tab separate file to work with, and called it &#39;sample.txt&#39;.  It&#39;s basic and only has four rows:

    Row1_Column1	Row1-Column2	Row1-Column3	Row1-Column4	2	Row1-Column6
    Row2_Column1	Row2-Column2	Row2-Column3	Row2-Column4	3	Row2-Column6
    Row3_Column1	Row3-Column2	Row3-Column3	Row3-Column4	1	Row3-Column6
    Row4_Column1	Row4-Column2	Row4-Column3	Row4-Column4	2	Row4-Column6

then I have this code:

    import csv 
    
    with open(&#39;sample.txt&#39;,&#39;r&#39;) as tsv:
        AoA = [line.strip().split(&#39;\t&#39;) for line in tsv]
    
    for a in AoA:
        count = int(a[4])
        while count &gt; 0:
            with open(&#39;sample_new.csv&#39;, &#39;a&#39;, newline=&#39;&#39;) as csvfile:
                csvwriter = csv.writer(csvfile, delimiter=&#39;,&#39;)
                csvwriter.writerow([a[2], a[3]])
            count = count - 1


reading and parsing a TSV file, then manipulating it for saving as CSV (*efficiently*)

I have a 350MB file named `text_file.txt` containing this tab delimited data:

    345868230	1646198120	1531283146	Keyword_1531283146	1.55	252910000
    745345566	1646198120	1539847239	another_1531276364	2.75	987831000
    ...

MySQL Database name: `Xml_Date`

Database table: `PerformanceReport`

I have already created the table with all the destination fields.

I want to import this text file data into a MySQL.  I googled and found some commands like `LOAD DATA INFILE` and quite confused on how to use it.

How can I import this text file data?

How to import data from text file to mysql database

I am importing some data of 20,000 rows from a CSV file into MySQL.

Columns in the CSV file are in a different order than MySQL tables&#39; columns. How can I automatically assign columns corresponding to MySQL table columns?

When I execute

    LOAD DATA INFILE &#39;abc.csv&#39; INTO TABLE abc

this query adds all data to the first column.

What is the auto syntax for importing data to MySQL?





Import data in MySQL from a CSV file using LOAD DATA INFILE

I&#39;ve been here:

* http://www.python.org/dev/peps/pep-0328/
* http://docs.python.org/2/tutorial/modules.html#packages
* https://stackoverflow.com/questions/10059002/python-packages-relative-imports
* https://stackoverflow.com/questions/9123062/python-relative-import-example-code-does-not-work
* https://stackoverflow.com/questions/8299270/ultimate-answer-to-relative-python-imports
* https://stackoverflow.com/questions/4175534/relative-imports-in-python
* https://stackoverflow.com/questions/13233931/python-disabling-relative-import?rq=1

and plenty of URLs that I did not copy, some on SO, some on other sites, back when I thought I&#39;d have the solution quickly.

The forever-recurring question is this: how do I solve this &quot;Attempted relative import in non-package&quot; message?

    ImportError: attempted relative import with no known parent package

I built an exact replica of the package on pep-0328:

    package/
        __init__.py
        subpackage1/
            __init__.py
            moduleX.py
            moduleY.py
        subpackage2/
            __init__.py
            moduleZ.py
        moduleA.py


The imports were done from the console.

I did make functions named spam and eggs in their appropriate modules.  Naturally, it didn&#39;t work.  The answer is apparently in the 4th URL I listed, but it&#39;s all alumni to me. There was this response on one of the URLs I visited:

&gt; Relative imports use a module&#39;s name attribute to determine that module&#39;s position in the package hierarchy. If the module&#39;s name does not contain any package information (e.g. it is set to &#39;main&#39;) then relative imports are resolved as if the module were a top level module, regardless of where the module is actually located on the file system.

The above response looks promising, but it&#39;s all hieroglyphs to me.  So my question, how do I make Python not return to me &quot;Attempted relative import in non-package&quot;? has an answer that involves -m, supposedly.

Can somebody please tell me why Python gives that error message, what it means by &quot;non-package&quot;, why and how do you define a &#39;package&#39;, and *the precise answer put in terms easy enough for a kindergartener to understand*. 


Relative imports for the billionth time

I have gone through many Python relative import questions but I can&#39;t understand the issue/get it to work.

My directory structure is:

    Driver.py

    A/
          Account.py
          __init__.py

    B/
          Test.py
          __init__.py

`Driver.py`

    from B import Test

`Account.py`

    class Account:
    def __init__(self):
        self.money = 0

`Test.py`

    from ..A import Account

When I try to run:

    python Driver.py

I get the error

    Traceback (most recent call last):

    from B import Test

    File &quot;B/Test.py&quot;, line 1, in &lt;module&gt; from ..A import Account

    ValueError: Attempted relative import beyond toplevel package

How to import a Python module from a sibling folder?

I&#39;m trying to create and use a custom package in Go. It&#39;s probably something very obvious but I cannot find much information about this. Basically, I have these two files in the same folder:

**mylib.go**

    package mylib
    
    type SomeType struct {
    	
    }

**main.go**

    package main
    
    import (
    	&quot;mylib&quot;
    )
    
    func main() {
    	
    }

When I try to `go run main.go`, I get this error:

    main.go:4:2: import &quot;mylib&quot;: cannot find package

I&#39;ve tried to run `go build mylib.go` first but it doesn&#39;t seem to be doing anything (no file generated, no error message). So any idea how I could do this?

Content Type	Original Author	Original Content on Stackoverflow
Question	Uselesssss	View Question on Stackoverflow
Solution 1 - R	Paul Hiemstra	View Answer on Stackoverflow

How do I import a CSV file in R?

R Problem Overview

R Solutions

Solution 1 - R

How to "warm-up" Entity Framework? When does it get "cold"?

.htaccess redirect http to https

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