You can use [`pandas.Dataframe.isin`](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.isin.html#pandas.DataFrame.isin).

`pandas.Dateframe.isin` will return boolean values depending on whether each element is inside the list `a` or not. You then invert this with the `~` to convert `True` to `False` and vice versa.

    import pandas as pd
    
    a = [&#39;2015-01-01&#39; , &#39;2015-02-01&#39;]
    
    df = pd.DataFrame(data={&#39;date&#39;:[&#39;2015-01-01&#39; , &#39;2015-02-01&#39;, &#39;2015-03-01&#39; , &#39;2015-04-01&#39;, &#39;2015-05-01&#39; , &#39;2015-06-01&#39;]})
    
    print(df)
    #         date
    #0  2015-01-01
    #1  2015-02-01
    #2  2015-03-01
    #3  2015-04-01
    #4  2015-05-01
    #5  2015-06-01
    
    df = df[~df[&#39;date&#39;].isin(a)]
    
    print(df)
    #         date
    #2  2015-03-01
    #3  2015-04-01
    #4  2015-05-01
    #5  2015-06-01

You can use [`Series.isin`][1]:

    df = df[~df.datecolumn.isin(a)]

While the error message suggests that ``all()`` or ``any()`` can be used, they are useful only when you want to reduce the result into a single Boolean value. That is however not what you are trying to do now, which is to test the membership of every values in the Series against the external list, and keep the results intact (i.e., a Boolean Series which will then be used to slice the original DataFrame).

You can read more about this in the [Gotchas][2].


  [1]: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.isin.html#pandas.Series.isin
  [2]: http://pandas.pydata.org/pandas-docs/stable/gotchas.html#using-if-truth-statements-with-pandas

I noticed that I can use either of `Closure` or `Callable` as type hint if we expected some callback function to run. For example:

    function callFunc1(Closure $closure) {
        $closure();
    }
    
    function callFunc2(Callable $callback) {
        $callback();
    }
    
    $function = function() {
        echo &#39;Hello, World!&#39;;
    };
    
    callFunc1($function); // Hello, World!
    callFunc2($function); // Hello, World!

Question:

What&#39;s the difference here ? In other words when to use `Closure` and when to use `Callable` OR they serve the same purpose ?

PHP: Type hinting - Difference between `Closure` and `Callable`

While installing pip and python I have ran into a that says:

&gt;The directory &#39;/Users/Parthenon/Library/Logs/pi&#39; or its parent directory is not owned by the current user and the debug log has been disabled. Please check the permissions and owner of that directory. If executing pip with sudo, you may want the -H flag.

because I now have to install using `sudo`.

I had python and a handful of libraries already installed on my Mac, I&#39;m running Yosemite. I recently had to do a clean wipe and then reinstall of the OS. Now I&#39;m getting this prompt and I&#39;m having trouble figuring out how to change it

Before my command line was `Parthenon$` now it&#39;s `Philips-MBP:~ Parthenon$`

I am the sole owner of this computer and this is the only account on it. This seems to be a problem when upgrading to python 3.4, nothing seems to be in the right place, virtualenv isn&#39;t going where I expect it to, etc.  

pip install: Please check the permissions and owner of that directory

I want to drop rows from a pandas dataframe when the value of the date column is in a list of dates. The following code doesn&#39;t work:

    a=[&#39;2015-01-01&#39; , &#39;2015-02-01&#39;]
    
    df=df[df.datecolumn not in a]


I get the following error:

&gt; ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().


dropping rows from dataframe based on a &quot;not in&quot; condition

I want to drop rows from a pandas dataframe when the value of the date column is in a list of dates. The following code doesn't work:
<pre><code class="hljs language-ini">a=['2015-01-01' , '2015-02-01']

df=df[df.datecolumn not in a]
</code></pre>
I get the following error:
> ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

I am writing a Python program in `TKinter` on Ubuntu to import and print
the name of files from particular folder in `Text` widget.
It is just adding filenames to the previous filnames in the `Text`
widget, but I want to clear it first, then add a fresh list of filenames.
But I am struggling to clear the `Text` widget&#39;s previous list of
filenames.

Can someone please explain how to clear a `Text` widget?

Screenshoot and coding is giving below:

[![screenshot showing text widget with contents][1]][1]

    import os
    from Tkinter import *

    def viewFile():
        path = os.path.expanduser(&quot;~/python&quot;)
        for f in os.listdir(path):
            tex.insert(END, f + &quot;\n&quot;)

    if __name__ == &#39;__main__&#39;:
        root = Tk()

        step= root.attributes(&#39;-fullscreen&#39;, True)
        step = LabelFrame(root, text=&quot;FILE MANAGER&quot;, font=&quot;Arial 20 bold italic&quot;)
        step.grid(row=0, columnspan=7, sticky=&#39;W&#39;, padx=100, pady=5, ipadx=130, ipady=25)

        Button(step, text=&quot;File View&quot;, font=&quot;Arial 8 bold italic&quot;, activebackground=
               &quot;turquoise&quot;, width=30, height=5, command=viewFile).grid(row=1, column=2)
        Button(step, text=&quot;Quit&quot;, font=&quot;Arial 8 bold italic&quot;, activebackground=
               &quot;turquoise&quot;, width=20, height=5, command=root.quit).grid(row=1, column=5)

        tex = Text(master=root)
        scr=Scrollbar(root, orient=VERTICAL, command=tex.yview)
        scr.grid(row=2, column=2, rowspan=15, columnspan=1, sticky=NS)
        tex.grid(row=2, column=1, sticky=W)
        tex.config(yscrollcommand=scr.set, font=(&#39;Arial&#39;, 8, &#39;bold&#39;, &#39;italic&#39;))

        root.mainloop()


  [1]: https://i.stack.imgur.com/B7ASq.png

How to clear/delete the contents of a Tkinter Text widget?

Assume we have a data frame in Python Pandas that looks like this:

    df = pd.DataFrame({&#39;vals&#39;: [1, 2, 3, 4], &#39;ids&#39;: [u&#39;aball&#39;, u&#39;bball&#39;, u&#39;cnut&#39;, u&#39;fball&#39;]})

Or, in table form:

&lt;!-- language: lang-none --&gt;

    ids    vals
    aball	1
    bball	2
    cnut	3
    fball	4

How do I filter rows which contain the key word &quot;ball?&quot; For example, the output should be:

&lt;!-- language: lang-none --&gt;

    ids    vals
    aball	1
    bball	2
    fball	4

How to filter rows containing a string pattern from a Pandas dataframe

I have a model &#39;MyModel&#39; with many fields and I would like to update a field &#39;status&#39; using PATCH method. I&#39;m using class based views. Is there any way to implement PATCH? 

How to PATCH a single field using Django Rest Framework?

I am writing scripts in Python2.6 with use of [pyVmomi](https://github.com/vmware/pyvmomi) and while using one of the connection methods:

    service_instance = connect.SmartConnect(host=args.ip,
                                            user=args.user,
                                            pwd=args.password)

I get the following warning:

    /usr/lib/python2.6/site-packages/requests/packages/urllib3/connectionpool.py:734: InsecureRequestWarning: Unverified HTTPS request is being made. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.org/en/latest/security.html
      InsecureRequestWarning)


What&#39;s interesting is that I do not have urllib3 installed with pip (but it&#39;s there in */usr/lib/python2.6/site-packages/requests/packages/urllib3/*).

I have tried as suggested [here](https://urllib3.readthedocs.org/en/latest/security.html)

    import urllib3
    ...
    urllib3.disable_warnings()

but that didn&#39;t change anything.



Suppress InsecureRequestWarning: Unverified HTTPS request is being made in Python2.6

I have a Python script that zips a file (`new.txt`):

    tofile =  &quot;/root/files/result/&quot;+file
    targetzipfile = new.zip # This is how I want my zip to look like
    zf = zipfile.ZipFile(targetzipfile, mode=&#39;w&#39;)
    try:
        #adding to archive
        zf.write(tofile)
    finally:
        zf.close()

When I do this I get the zip file.  But when I try to unzip the file I get the text file inside of a series of directories corresponding to the path of the file i.e I see a folder called `root` in the `result` directory and more directories within it, i.e. I have 

    /root/files/result/new.zip

and when I unzip `new.zip` I have a directory structure that looks like 

    /root/files/result/root/files/result/new.txt

Is there a way I can zip such that when I unzip I only get `new.txt`?

In other words I have `/root/files/result/new.zip` and when I unzip `new.zip`, it should look like 

    /root/files/results/new.txt

zip file and avoid directory structure

It&#39;s easy to turn a list of lists into a pandas dataframe:

    import pandas as pd
    df = pd.DataFrame([[1,2,3],[3,4,5]])

But how do I turn df back into a list of lists?

    lol = df.what_to_do_now?
    print lol
    # [[1,2,3],[3,4,5]]

Pandas DataFrame to List of Lists

I have a DataFrame `df` like the following (excerpt, &#39;Timestamp&#39; are the index):

    Timestamp              Value
    2012-06-01 00:00:00     100
    2012-06-01 00:15:00     150
    2012-06-01 00:30:00     120
    2012-06-01 01:00:00     220
    2012-06-01 01:15:00      80
    ...and so on.

I need a new column `df[&#39;weekday&#39;]` with the respective weekday/day-of-week of the timestamps.

How can I get this?


Get weekday/day-of-week for Datetime column of DataFrame

Here is a simple example of the code I am running, and I would like the results put into a pandas dataframe (unless there is a better option):

    for p in game.players.passing():
        print p, p.team, p.passing_att, p.passer_rating()

    R.Wilson SEA 29 55.7
    J.Ryan SEA 1 158.3
    A.Rodgers GB 34 55.8

Using this code:

    d = []
    for p in game.players.passing():
        d = [{&#39;Player&#39;: p, &#39;Team&#39;: p.team, &#39;Passer Rating&#39;:
            p.passer_rating()}]
    
    pd.DataFrame(d)

I can get:

    	Passer Rating	Player	    Team
      0	55.8	        A.Rodgers	GB

Which is a 1x3 dataframe, and I understand *why* it is only one row but I can&#39;t figure out how to make it multi-row with the columns in the correct order. Ideally the solution would be able to deal with *n* number of rows (based on p) and it would be wonderful (although not essential) if the number of columns would be set by the number of stats requested. Any suggestions? Thanks in advance!

How to build and fill pandas dataframe from for loop?

I&#39;m surely missing something simple here. Trying to merge two dataframes in pandas that have mostly the same column names, but the right dataframe has some columns that the left doesn&#39;t have, and vice versa. 

    &gt;df_may

      id  quantity  attr_1  attr_2
    0  1        20       0       1
    1  2        23       1       1
    2  3        19       1       1
    3  4        19       0       0

    &gt;df_jun

      id  quantity  attr_1  attr_3
    0  5         8       1       0
    1  6        13       0       1
    2  7        20       1       1
    3  8        25       1       1

I&#39;ve tried joining with an outer join:

    mayjundf = pd.DataFrame.merge(df_may, df_jun, how=&quot;outer&quot;)

But that yields:

    Left data columns not unique: Index([....

I&#39;ve also specified a single column to join on (`on = &quot;id&quot;`, e.g.), but that duplicates all columns except `id` like `attr_1_x`, `attr_1_y`, which is not ideal. I&#39;ve also passed the entire list of columns (there are many) to `on`:

    mayjundf = pd.DataFrame.merge(df_may, df_jun, how=&quot;outer&quot;, on=list(df_may.columns.values))

Which yields:

    ValueError: Buffer has wrong number of dimensions (expected 1, got 2)

What am I missing? I&#39;d like to get a df with all rows appended, and `attr_1`, `attr_2`, `attr_3` populated where possible, NaN where they don&#39;t show up. This seems like a pretty typical workflow for data munging, but I&#39;m stuck.

Thanks in advance.


Content Type	Original Author	Original Content on Stackoverflow
Question	gaurav gurnani	View Question on Stackoverflow
Solution 1 - Python	Ffisegydd	View Answer on Stackoverflow
Solution 2 - Python	YS-L	View Answer on Stackoverflow

dropping rows from dataframe based on a "not in" condition

Python Problem Overview

Python Solutions

Solution 1 - Python

Solution 2 - Python

pip install: Please check the permissions and owner of that directory

PHP: Type hinting - Difference between `Closure` and `Callable`

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