The `T` doesn&#39;t really stand for anything. It is just the *separator* that the [ISO 8601 combined date-time format](http://en.wikipedia.org/wiki/ISO_8601#Combined_date_and_time_representations) requires. You can read it as an abbreviation for *Time*.

The `Z` stands for the *Zero* timezone, as it is offset by 0 from the [Coordinated Universal Time (UTC)](http://en.wikipedia.org/wiki/Time_zone#UTC).

Both characters are just static letters in the format, which is why they are not documented by the `datetime.strftime()` method. You could have used `Q` or `M` or `Monty Python` and the method would have returned them unchanged as well; the method only looks for patterns starting with `%` to replace those with information from the `datetime` object.

I learned from my colleague that one can write and execute a C program without writing a `main()` function. It can be done like this:

`my_main.c`

    /* Compile this with gcc -nostartfiles */
    
    #include &lt;stdlib.h&gt;
    
    void _start() {
      int ret = my_main();
      exit(ret); 
    }
 
    int my_main() {
      puts(&quot;This is a program without a main() function!&quot;);
      return 0; 
    }

Compile it with this command:

    gcc -o my_main my_main.c –nostartfiles

Run it with this command:
 
    ./my_main

When would one need to do this kind of thing? Is there any real world scenario where this would be useful?

What is the use of _start() in C?

I have by pure chance discovered that the C# compiler turns this method:

    static bool IsNotNull(object obj)
    {
        return obj != null;
    }

…into this [CIL][1]:

    .method private hidebysig static bool IsNotNull(object obj) cil managed
    {
        ldarg.0   // obj
        ldnull
        cgt.un
        ret
    }

…or, if you prefer looking at decompiled C# code:

    static bool IsNotNull(object obj)
    {
        return obj &gt; null;   // (note: this is not a valid C# expression)
    }

How come that the `!=` gets translated as a &quot;`&gt;`&quot;?

  [1]: http://en.wikipedia.org/wiki/Common_Intermediate_Language



Why does the C# compiler translate this != comparison as if it were a &gt; comparison?

I have this timestamp value being return by a web service `&quot;2014-09-12T19:34:29Z&quot;`

I know that it means timezone, but what exactly does it mean? 

And I am trying to mock this web service, so is there a way to generate this timestamp using `strftime` in python?

Sorry if this is painfully obvious, but Google was not very helpful and neither was the `strftime()` reference page. 

I am currently using this :

    x.strftime(&quot;%Y-%m-%dT%H:%M:%S%Z&quot;)
    &#39;2015-03-26T10:58:51&#39;



What exactly does the T and Z mean in timestamp?

I have this timestamp value being return by a web service <code>"2014-09-12T19:34:29Z"</code>
I know that it means timezone, but what exactly does it mean?
And I am trying to mock this web service, so is there a way to generate this timestamp using <code>strftime</code> in python?
Sorry if this is painfully obvious, but Google was not very helpful and neither was the <code>strftime()</code> reference page.
I am currently using this :
<pre><code class="hljs language-perl">x.strftime("%Y-%m-%dT%H:%M:%S%Z")
'2015-03-26T10:58:51'
</code></pre>

When using the Anacoda Python distribution, what is the best way to install a PyPi package that isn&#39;t available directly through Anaconda?  For now I&#39;m using:

    conda pipbuild [pypi_name]
    conda install --use-local [package_spec]

But I&#39;m unclear if this is the best way and if `conda update --all` will update these packages when updates are made available.  I&#39;m also unclear what the point of binstar is when PyPi already exists.

How to install PyPi packages using anaconda conda command

How can I read in a .csv file (with no headers) and when I only want a subset of the columns (say 4th and 7th out of a total of 20 columns), using pandas? I cannot seem to be able to do `usecols`

Pandas read in table without headers

Can anyone amend [namedtuple][1] or provide an alternative class so that it works for mutable objects?

Primarily for readability, I would like something similar to namedtuple that does this:

    from Camelot import namedgroup
    
    Point = namedgroup(&#39;Point&#39;, [&#39;x&#39;, &#39;y&#39;])
    p = Point(0, 0)
    p.x = 10
    
    &gt;&gt;&gt; p
    Point(x=10, y=0)

    &gt;&gt;&gt; p.x *= 10
    Point(x=100, y=0)

It must be possible to pickle the resulting object.  And per the characteristics of named tuple, the ordering of the output when represented must match the order of the parameter list when constructing the object.


  [1]: http://code.activestate.com/recipes/500261/

Existence of mutable named tuple in Python?

When I use the command:

    pyinstaller.exe --icon=test.ico -F --noconsole test.py

All icons do not change to test.ico. Some icons remain as the pyinstaller&#39;s default icon.

Why?


All icon change in 
- windows 7 32bit
- windows 7 64bit (make an exe file OS)

Some remain default
- windows 7 64bit (other PC)

Pyinstaller setting icons don&#39;t change

I have a huge data set and prior to machine learning modeling it is always suggested that first you should remove highly correlated descriptors(columns) how can i calculate the column wice correlation and remove the column with a threshold value say remove all the columns or descriptors having  &gt;0.8 correlation.  also it should retained the headers in reduce data.. 

Example data set 

     GA      PN       PC     MBP      GR     AP   
    0.033   6.652   6.681   0.194   0.874   3.177    
    0.034   9.039   6.224   0.194   1.137   3.4      
    0.035   10.936  10.304  1.015   0.911   4.9      
    0.022   10.11   9.603   1.374   0.848   4.566    
    0.035   2.963   17.156  0.599   0.823   9.406    
    0.033   10.872  10.244  1.015   0.574   4.871     
    0.035   21.694  22.389  1.015   0.859   9.259     
    0.035   10.936  10.304  1.015   0.911   4.5       
    

Please help.... 

How to calculate correlation between all columns and remove highly correlated ones using pandas?

How can I convert `Gregorian date` to `Persian date` and vice-versa in `Python`?

[All I found][1] was some widgets and stuffs which will create Persian Calendar. I don&#39;t want a Persian calendar. I just want to convert dates to each other.
So how can I do that?


  [1]: https://github.com/behzadi/persianDatepicker

Convert Gregorian (Christian) date to Persian date and vice-versa in Python

I would like to get the current time in Python and assign them into variables like `year`, `month`, `day`, `hour`, `minute`. How can this be done in Python 2.7?

How to get current time in python and break up into year, month, day, hour, minute?

How should I transform from `datetime` to `string`? My attempt:

    dates = p.to_datetime(p.Series([&#39;20010101&#39;, &#39;20010331&#39;]), format = &#39;%Y%m%d&#39;)
    dates.str

datetime to string with series in pandas

Create a day-of-week column in a Pandas dataframe using Python

I’d like to read a csv file into a pandas dataframe, parse a column of dates from string format to a date object, and then generate a new column that indicates the day of the week.

This is what I’m trying:


What I’d like to do is something like:

    import pandas as pd

    import csv

    df = pd.read_csv(&#39;data.csv&#39;, parse_dates=[&#39;date&#39;]))

    df[&#39;day-of-week&#39;] = df[&#39;date&#39;].weekday()


    AttributeError: &#39;Series&#39; object has no attribute &#39;weekday&#39;

________
Thank you for your help.
James


Create a day-of-week column in a Pandas dataframe using Python

I import a dataframe via `read_csv`, but for some reason can&#39;t extract the year or month from the series `df[&#39;date&#39;]`, trying that gives `AttributeError: &#39;Series&#39; object has no attribute &#39;year&#39;`:

    date	Count
    6/30/2010	525
    7/30/2010	136
    8/31/2010	125
    9/30/2010	84
    10/29/2010	4469

    df = pd.read_csv(&#39;sample_data.csv&#39;, parse_dates=True)

    df[&#39;date&#39;] = pd.to_datetime(df[&#39;date&#39;])

    df[&#39;year&#39;] = df[&#39;date&#39;].year
    df[&#39;month&#39;] = df[&#39;date&#39;].month

UPDATE:
and when I try solutions with `df[&#39;date&#39;].dt` on my pandas version 0.14.1, I get   &quot;AttributeError: &#39;Series&#39; object has no attribute &#39;dt&#39; &quot;:

    df = pd.read_csv(&#39;sample_data.csv&#39;,parse_dates=True)

    df[&#39;date&#39;] = pd.to_datetime(df[&#39;date&#39;])

    df[&#39;year&#39;] = df[&#39;date&#39;].dt.year
    df[&#39;month&#39;] = df[&#39;date&#39;].dt.month

Sorry for this question that seems repetitive - I expect the answer will make me feel like a bonehead... but I have not had any luck using answers to the similar questions on SO.

---

FOLLOWUP: I can&#39;t seem to update my pandas 0.14.1 to a newer release in my Anaconda environment, each of the attempts below generates an invalid syntax error. I&#39;m using Python 3.4.1 64bit.

    conda update pandas

    conda install pandas==0.15.2

    conda install -f pandas


Any ideas?

python pandas extract year from datetime: df[&#39;year&#39;] = df[&#39;date&#39;].year is not working

I have Spark DataFrame with take(5) top rows as follows:

	[Row(date=datetime.datetime(1984, 1, 1, 0, 0), hour=1, value=638.55),
	 Row(date=datetime.datetime(1984, 1, 1, 0, 0), hour=2, value=638.55),
	 Row(date=datetime.datetime(1984, 1, 1, 0, 0), hour=3, value=638.55),
	 Row(date=datetime.datetime(1984, 1, 1, 0, 0), hour=4, value=638.55),
	 Row(date=datetime.datetime(1984, 1, 1, 0, 0), hour=5, value=638.55)]

It&#39;s schema is defined as:

	elevDF.printSchema()

	root
	 |-- date: timestamp (nullable = true)
	 |-- hour: long (nullable = true)
	 |-- value: double (nullable = true)

How do I get the Year, Month, Day values from the &#39;date&#39; field?




Spark DataFrame TimestampType - how to get Year, Month, Day values from field?

I have a string representing the current time: `2015-11-24T19:40:00`. How do I parse this string in Javascript to get a Date represented by this string as the **LOCAL TIME**?  **Due to some restriction, I cannot use the library `moment`, but jquery is allowed. I know that someone has asked this question before, but the answer used `moment`**

For example, if I run the script in California, then this string would represent 7PM pacific time, but if I run the script in NY then this string would represent Eastern Time?

I tried the following but Chrome and Firefox give me different results:

    var str = &quot;2015-11-24T19:40:00&quot;;
    var date = new Date(str);

Chrome consumes it as **UTC** time (`Tue Nov 24 2015 11:40:00 GMT-0800 (Pacific Standard Time)`), 

but Firefox consumes it as my local **PACIFIC** time (`Tue Nov 24 2015 19:40:00 GMT-0800 (Pacific Standard Time)`)

I tried adding &quot;Z&quot; to `str`, like this `var date = new Date(str+&quot;Z&quot;);`, then both browsers give me UTC time. Is there any similar letter to `&quot;Z&quot;` which tells all browsers (at least chrome, Firefox and Safari) to parse the string as local time zone?

Javascript: parse a string to Date as LOCAL time zone

I have a pandas column of Timestamp data

    In [27]: train[&quot;Original_Quote_Date&quot;][6] 
    Out[27]: Timestamp(&#39;2013-12-25 00:00:00&#39;)

How can check equivalence of these objects to `datetime.date` objects of the type

    datetime.date(2013, 12, 25)

Pandas: Convert Timestamp to datetime.date

I&#39;m trying to convert a ``timestamp`` to a date format using Angular pipes. I wrote this in the HTML template:
```HTML
{{myTimestamp | date}}
```
Where `myTimestamp` is of type number.

I get unexpected results, for example, the timestamp `1468251287` (Which matches Nov 7, 2016) is displayed as `Jan 18, 1970`.

I would like to know how I can fix this issue.



Convert timestamp to date using Angular 2 pipes

I have a DataFrame with some (hundreds of) million of rows. And I want to convert datetime to timestamp effectively. How can I do it?

My sample `df`:

    df = pd.DataFrame(index=pd.DatetimeIndex(start=dt.datetime(2016,1,1,0,0,1),
        end=dt.datetime(2016,1,2,0,0,1), freq=&#39;H&#39;))\
        .reset_index().rename(columns={&#39;index&#39;:&#39;datetime&#39;})

which looks like:

                 datetime
    0 2016-01-01 00:00:01
    1 2016-01-01 01:00:01
    2 2016-01-01 02:00:01
    3 2016-01-01 03:00:01
    4 2016-01-01 04:00:01

Now I convert datetime to timestamp value-by-value with `.apply()` but it takes a very long time (some hours) if I have some (hundreds of) million rows:

    df[&#39;ts&#39;] = df[[&#39;datetime&#39;]].apply(lambda x: x[0].timestamp(), axis=1).astype(int)

Output:

                 datetime          ts
    0 2016-01-01 00:00:01  1451602801
    1 2016-01-01 01:00:01  1451606401
    2 2016-01-01 02:00:01  1451610001
    3 2016-01-01 03:00:01  1451613601
    4 2016-01-01 04:00:01  1451617201

The above result is what I want.

If I try to use the `.dt` accessor of `pandas.Series` then I get error message:

    df[&#39;ts&#39;] = df[&#39;datetime&#39;].dt.timestamp

&gt; AttributeError: &#39;DatetimeProperties&#39; object has no attribute
&gt; &#39;timestamp&#39;

If I try to create eg. the date parts of datetimes with the `.dt` accessor then it is much faster then using `.apply()`:

    df[&#39;date&#39;] = df[&#39;datetime&#39;].dt.date

Output:

                 datetime          ts        date
    0 2016-01-01 00:00:01  1451602801  2016-01-01
    1 2016-01-01 01:00:01  1451606401  2016-01-01
    2 2016-01-01 02:00:01  1451610001  2016-01-01
    3 2016-01-01 03:00:01  1451613601  2016-01-01
    4 2016-01-01 04:00:01  1451617201  2016-01-01

I want something similar with timestamps...

But I don&#39;t really understand the official documentation: it talks about &quot;[Converting to Timestamps][1]&quot; but I don&#39;t see any timestamps there; it just talks about converting to datetime with `pd.to_datetime()` but not to timestamp...

`pandas.Timestamp` constructor also doesn&#39;t work (returns with the below error):

    df[&#39;ts2&#39;] = pd.Timestamp(df[&#39;datetime&#39;])

&gt; TypeError: Cannot convert input to Timestamp

[`pandas.Series.to_timestamp`][2] also makes something totally different from what I want:

    df[&#39;ts3&#39;] = df[&#39;datetime&#39;].to_timestamp

Output:

                 datetime          ts                                                ts3
    0 2016-01-01 00:00:01  1451602801  &lt;bound method Series.to_timestamp of 0    2016...
    1 2016-01-01 01:00:01  1451606401  &lt;bound method Series.to_timestamp of 0    2016...
    2 2016-01-01 02:00:01  1451610001  &lt;bound method Series.to_timestamp of 0    2016...
    3 2016-01-01 03:00:01  1451613601  &lt;bound method Series.to_timestamp of 0    2016...
    4 2016-01-01 04:00:01  1451617201  &lt;bound method Series.to_timestamp of 0    2016...



  [1]: http://pandas.pydata.org/pandas-docs/stable/timeseries.html#converting-to-timestamps
  [2]: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.to_timestamp.html

Python pandas convert datetime to timestamp effectively through dt accessor

My dataframe has a `DOB` column (example format **`1/1/2016`**) which by default gets converted to Pandas dtype &#39;object&#39;.

Converting this to date format with `df[&#39;DOB&#39;] = pd.to_datetime(df[&#39;DOB&#39;])`, the date gets converted to: **`2016-01-26`** and its `dtype` is: `datetime64[ns]`.

Now I want to convert this date format to **`01/26/2016` or any other general date format**. How do I do it?

(Whatever the method I try, it always shows the date in `2016-01-26` format.)

Content Type	Original Author	Original Content on Stackoverflow
Question	roymustang86	View Question on Stackoverflow
Solution 1 - Python	Martijn Pieters	View Answer on Stackoverflow

What exactly does the T and Z mean in timestamp?

Python Problem Overview

Python Solutions

Solution 1 - Python

Why does the C# compiler translate this != comparison as if it were a > comparison?

What is the use of _start() in C?

Attributions