`isnull` is an alias for `isna`. Literally in the [code source of pandas](https://github.com/pandas-dev/pandas/blob/0409521665bd436a10aea7e06336066bf07ff057/pandas/core/dtypes/missing.py#L109):

    isnull = isna

Indeed:

    &gt;&gt;&gt; pd.isnull
    &lt;function isna at 0x7fb4c5cefc80&gt;

So I would recommend using `isna`.

They both are same. As a best practice, always prefer to use `isna()` over `isnull()`. 

It is easy to remember what `isna()` is doing because when you look at numpy method `np.isnan()`, it checks `NaN` values. In pandas there are other similar method names like `dropna()`, `fillna()` that handles missing values and it always helps to remember easily.

The documentation for both is literally identical.

pandas.isna() : https://pandas.pydata.org/pandas-docs/stable/generated/pandas.isna.html#pandas.isna

pandas.isnull() : https://pandas.pydata.org/pandas-docs/stable/generated/pandas.isnull.html#pandas.isnull


In here, it even says DataFrame.isnull is an alias of isna in See also section.


pandas.DataFrame.isnull(): https://pandas-docs.github.io/pandas-docs-travis/generated/pandas.DataFrame.isnull.html#pandas.DataFrame.isnull

Therefore, they must be the same thing, like np.nan, np.NaN, np.NAN.

I am currently upgrading angular 4 to angular 6 code. I have installed &quot;rxjs&quot;: &quot;^6.3.2&quot; and un-installed rxjs-compact as I have migrated the code to use the new rxjs operators. I am still getting the following errors. Dont know the reason why
 
 
 

    ERROR in [at-loader] ./node_modules/rxjs/BehaviorSubject.d.ts:1:15
        TS2307: Cannot find module &#39;rxjs-compat/BehaviorSubject&#39;.
    
    ERROR in [at-loader] ./node_modules/rxjs/Observable.d.ts:1:15
        TS2307: Cannot find module &#39;rxjs-compat/Observable&#39;.
    
    ERROR in [at-loader] ./node_modules/rxjs/Observer.d.ts:1:15
        TS2307: Cannot find module &#39;rxjs-compat/Observer&#39;.
    
    ERROR in [at-loader] ./node_modules/rxjs/Operator.d.ts:1:15
        TS2307: Cannot find module &#39;rxjs-compat/Operator&#39;.
    
    ERROR in [at-loader] ./node_modules/rxjs/Subject.d.ts:1:15
        TS2307: Cannot find module &#39;rxjs-compat/Subject&#39;.
    
    ERROR in [at-loader] ./node_modules/rxjs/Subscription.d.ts:1:15
        TS2307: Cannot find module &#39;rxjs-compat/Subscription&#39;.

Cannot find module &#39;rxjs-compat/Observable&#39;

I am new to Android Studio and I don&#39;t get why my toolbar isn&#39;t shown as described by https://developer.android.com/training/appbar/setting-up
I know there are already some other questions like mine on stackoverflow but they don&#39;t work at my project. Therefore I would be very thankful for fixing this issue. Screenshot:

[![Screenshot][1]][1]



    java.lang.ClassNotFoundException: android.view.View$OnUnhandledKeyEventListener
	at org.jetbrains.android.uipreview.ModuleClassLoader.load(ModuleClassLoader.java:180)
	at com.android.tools.idea.rendering.RenderClassLoader.findClass(RenderClassLoader.java:61)
	at org.jetbrains.android.uipreview.ModuleClassLoader.findClass(ModuleClassLoader.java:118)
	at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
	at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
	at org.jetbrains.android.uipreview.ModuleClassLoader.loadClass(ModuleClassLoader.java:213)
	at android.support.v7.widget.ViewUtils.isLayoutRtl(ViewUtils.java:58)
	at android.support.v7.widget.Toolbar.onMeasure_Original(Toolbar.java:1578)
	at android.support.v7.widget.Toolbar.onMeasure(Toolbar.java)
	at android.view.View.measure_Original(View.java:22071)
	at android.view.View_Delegate.measure(View_Delegate.java:80)
	at android.view.View.measure(View.java:22035)
	at android.view.ViewGroup.measureChildWithMargins(ViewGroup.java:6602)
	at android.widget.FrameLayout.onMeasure(FrameLayout.java:185)
	at android.view.View.measure_Original(View.java:22071)
	at android.view.View_Delegate.measure(View_Delegate.java:80)
	at android.view.View.measure(View.java:22035)
	at android.widget.RelativeLayout.measureChildHorizontal(RelativeLayout.java:715)
	at android.widget.RelativeLayout.onMeasure(RelativeLayout.java:461)
	at android.view.View.measure_Original(View.java:22071)
	at android.view.View_Delegate.measure(View_Delegate.java:80)
	at android.view.View.measure(View.java:22035)
	at com.android.layoutlib.bridge.impl.RenderSessionImpl.measureView(RenderSessionImpl.java:590)
	at com.android.layoutlib.bridge.impl.RenderSessionImpl.inflate(RenderSessionImpl.java:343)
	at com.android.layoutlib.bridge.Bridge.createSession(Bridge.java:384)
	at com.android.tools.idea.layoutlib.LayoutLibrary.createSession(LayoutLibrary.java:193)
	at com.android.tools.idea.rendering.RenderTask.createRenderSession(RenderTask.java:544)
	at com.android.tools.idea.rendering.RenderTask.lambda$inflate$3(RenderTask.java:678)
	at java.util.concurrent.FutureTask.run(FutureTask.java:266)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)

toolbar.xml
=======

    &lt;?xml version=&quot;1.0&quot; encoding=&quot;utf-8&quot;?&gt;
    &lt;android.support.v7.widget.Toolbar xmlns:android=&quot;http://schemas.android.com/apk/res/android&quot;
        android:layout_width=&quot;match_parent&quot;
        android:layout_height=&quot;match_parent&quot;
        android:background=&quot;@color/colorPrimaryDark&quot;&gt;
    
    &lt;/android.support.v7.widget.Toolbar&gt;

build.gradle (app level)
=======

    apply plugin: &#39;com.android.application&#39;
    android {
		compileSdkVersion 28
		defaultConfig {
			applicationId &quot;com.example.david.gamebase&quot;
			minSdkVersion 21
			targetSdkVersion 28
			versionCode 1
			versionName &quot;1.0&quot;
			testInstrumentationRunner &quot;android.support.test.runner.AndroidJUnitRunner&quot;
		}
		buildTypes {
			release {
				minifyEnabled false
				proguardFiles getDefaultProguardFile(&#39;proguard-android.txt&#39;), &#39;proguard-rules.pro&#39;
			}
		}
	}

    dependencies {
		implementation fileTree(dir: &#39;libs&#39;, include: [&#39;*.jar&#39;])
		implementation &#39;com.android.support:appcompat-v7:28.0.0-rc01&#39;
		implementation &#39;com.android.support.constraint:constraint-layout:1.1.2&#39;
		implementation &#39;com.google.firebase:firebase-auth:11.6.0&#39;
		testImplementation &#39;junit:junit:4.12&#39;
		androidTestImplementation &#39;com.android.support.test:runner:1.0.2&#39;
		androidTestImplementation &#39;com.android.support.test.espresso:espresso-core:3.0.2&#39;
	}

    apply plugin: &#39;com.google.gms.google-services&#39;


style.xml:
---------

 

       &lt;resources&gt;
    
        &lt;!-- Base application theme. --&gt;
        &lt;style name=&quot;AppTheme&quot; parent=&quot;Base.Theme.AppCompat.Light.DarkActionBar&quot;&gt;
            &lt;!-- Customize your theme here. --&gt;
            &lt;item name=&quot;colorPrimary&quot;&gt;@color/colorPrimary&lt;/item&gt;
            &lt;item name=&quot;colorPrimaryDark&quot;&gt;@color/colorPrimaryDark&lt;/item&gt;
            &lt;item name=&quot;colorAccent&quot;&gt;@color/colorAccent&lt;/item&gt;
        &lt;/style&gt;
    
    &lt;/resources&gt;
    
    ## toolbar.xml ##
    
        &lt;?xml version=&quot;1.0&quot; encoding=&quot;utf-8&quot;?&gt;
    &lt;android.support.v7.widget.Toolbar xmlns:android=&quot;http://schemas.android.com/apk/res/android&quot;
        android:layout_width=&quot;match_parent&quot;
        android:layout_height=&quot;match_parent&quot;
        android:background=&quot;@color/colorPrimaryDark&quot;&gt;
    
    &lt;/android.support.v7.widget.Toolbar&gt;


  [1]: https://i.stack.imgur.com/kpx3o.png

android.view.View$OnUnhandledKeyEventListener

Pandas has both `isna()` and `isnull()`. I usually use `isnull()` to detect missing values and have never met the case so that I had to use other than that.
So, when to use `isna()`?

Pandas isna() and isnull(), what is the difference?

<p>Pandas has both <code>isna()</code> and <code>isnull()</code>. I usually use <code>isnull()</code> to detect missing values and have never met the case so that I had to use other than that.
So, when to use <code>isna()</code>?</p>


The problem originates when I start by cloning a git project that uses pipenv, so it has a Pipfile + Pipfile.lock. I want to use a virtual environment with the project so I run `pipenv shell`. I now have a virtual environment created and I am inside the virtual environment. The project obviously has a lot of dependencies (listed in the Pipfile). I don&#39;t want to have to go through the list in the Pipfile one by one and install them using `pipenv install &lt;package_name&gt;`. Is there a pipenv/pip command that installs all the packages from a Pipfile I already have? Or maybe I need to set up the environment differently than running `pipenv shell`?

How to install dependencies from a copied pipfile inside a virtual environment?

I have a pandas series with boolean entries.  I would like to get a list of indices where the values are `True`.

For example the input `pd.Series([True, False, True, True, False, False, False, True])`

should yield the output `[0,2,3,7]`.

I can do it with a list comprehension, but is there something cleaner or faster?

Getting a list of indices where pandas boolean series is True

I have a method inside a class that needs to do a lot of work in a loop, and I would like to spread the work over all of my cores.

I wrote the following code, which works if I use normal `map()`, but with `pool.map()` returns an error.

    import multiprocessing
    pool = multiprocessing.Pool(multiprocessing.cpu_count() - 1)
    
    class OtherClass:
      def run(sentence, graph):
        return False
    
    class SomeClass:
      def __init__(self):
        self.sentences = [[&quot;Some string&quot;]]
        self.graphs = [&quot;string&quot;]
    
      def some_method(self):
          other = OtherClass()
    
          def single(params):
              sentences, graph = params
              return [other.run(sentence, graph) for sentence in sentences]
    
          return list(pool.map(single, zip(self.sentences, self.graphs)))
    
    
    SomeClass().some_method()

### Error 1:

&gt; AttributeError: Can&#39;t pickle local object &#39;SomeClass.some_method.&lt;locals&gt;.single&#39;


Why can&#39;t it pickle `single()`? I even tried to move `single()` to the global module scope (not inside the class - makes it independent of the context):

    import multiprocessing
    pool = multiprocessing.Pool(multiprocessing.cpu_count() - 1)
    
    class OtherClass:
      def run(sentence, graph):
        return False
    
    
    def single(params):
        other = OtherClass()
        sentences, graph = params
        return [other.run(sentence, graph) for sentence in sentences]
    
    class SomeClass:
      def __init__(self):
        self.sentences = [[&quot;Some string&quot;]]
        self.graphs = [&quot;string&quot;]
    
      def some_method(self):
          return list(pool.map(single, zip(self.sentences, self.graphs)))
    
    
    SomeClass().some_method()

and I get the following ...
### Error 2:

&gt; AttributeError: Can&#39;t get attribute &#39;single&#39; on module &#39;__main__&#39; from &#39;.../test.py&#39;



Python multiprocessing.Pool: AttributeError

I have a Windows 10 PC and I want to install pyaudio to use it with my chatbot, powered by chatterbot.

I tried 2 different ways to install pyaudio.

The first way is doing this on the command prompt:

    python -m pip install PyAudio

This is the result:

       C:\Users\Waaberi&gt;python -m pip install PyAudio
    Collecting PyAudio
      Using cached https://files.pythonhosted.org/packages/ab/42/b4f04721c5c5bfc196ce156b3c768998ef8c0ae3654ed29ea5020c749a6b/PyAudio-0.2.11.tar.gz
    Installing collected packages: PyAudio
      Running setup.py install for PyAudio ... error
        Complete output from command C:\Users\Waaberi\AppData\Local\Programs\Python\Python37-32\python.exe -u -c &quot;import setuptools, tokenize;__file__=&#39;C:\\Users\\Waaberi\\AppData\\Local\\Temp\\pip-install-e5le61j0\\PyAudio\\setup.py&#39;;f=getattr(tokenize, &#39;open&#39;, open)(__file__);code=f.read().replace(&#39;\r\n&#39;, &#39;\n&#39;);f.close();exec(compile(code, __file__, &#39;exec&#39;))&quot; install --record C:\Users\Waaberi\AppData\Local\Temp\pip-record-adj3zivl\install-record.txt --single-version-externally-managed --compile:
        running install
        running build
        running build_py
        creating build
        creating build\lib.win32-3.7
        copying src\pyaudio.py -&gt; build\lib.win32-3.7
        running build_ext
        building &#39;_portaudio&#39; extension
        error: Microsoft Visual C++ 14.0 is required. Get it with &quot;Microsoft Visual C++ Build Tools&quot;: http://landinghub.visualstudio.com/visual-cpp-build-tools
    
        ----------------------------------------
    Command &quot;C:\Users\Waaberi\AppData\Local\Programs\Python\Python37-32\python.exe -u -c &quot;import setuptools, tokenize;__file__=&#39;C:\\Users\\Waaberi\\AppData\\Local\\Temp\\pip-install-e5le61j0\\PyAudio\\setup.py&#39;;f=getattr(tokenize, &#39;open&#39;, open)(__file__);code=f.read().replace(&#39;\r\n&#39;, &#39;\n&#39;);f.close();exec(compile(code, __file__, &#39;exec&#39;))&quot; install --record C:\Users\Waaberi\AppData\Local\Temp\pip-record-adj3zivl\install-record.txt --single-version-externally-managed --compile&quot; failed with error code 1 in C:\Users\Waaberi\AppData\Local\Temp\pip-install-e5le61j0\PyAudio\

The second way is entering this command:

    python pip install python-pyaudio

and it does nothing.




I can&#39;t install pyaudio on Windows? How to solve &quot;error: Microsoft Visual C++ 14.0 is required.&quot;?

    df = df[~df[&quot;column&quot;].str.contains(&quot;Total&quot;)]

    TypeError: bad operand type for unary ~: &#39;float&#39;

Why does `.str.contains()` return a float? What should I be doing here?

TypeError: bad operand type for unary ~: float

I have a dataframe ```df``` as follows:

    | name  | coverage |
    |-------|----------|
    | Jason | 25.1     |
I want to convert it to a dictionary.
I used the following command in ```pandas``` :

    dict=df.to_dict()
The output of ```dict``` gave me the following:

    {&#39;coverage&#39;: {0: 25.1}, &#39;name&#39;: {0: &#39;Jason&#39;}} 
I do not want the ```0``` in my output. I believe this is captured because of the column index in my dataframe ```df```.
What can I do to eliminate ```0``` in my output
( I do not want index to be captured.) expected output :

    {&#39;coverage&#39;: 25.1, &#39;name&#39;: &#39;Jason&#39;} 



How to convert dataframe to dictionary in pandas WITHOUT index

This may sound a noob question, but I&#39;m stuck with it as Python is not one of my best languages.

I have a html page with a table inside it, and I would like to show a pandas dataframe in it.
What is the best way to do it? Use pandasdataframe.to_html?

**py**

    from flask import Flask;
    import pandas as pd;
    from pandas import DataFrame, read_csv;
    
    file = r&#39;C:\Users\myuser\Desktop\Test.csv&#39;
    df = pd.read_csv(file)
    df.to_html(header=&quot;true&quot;, table_id=&quot;table&quot;)
    

**html**

    &lt;div class=&quot;table_entrances&quot; style=&quot;overflow-x: auto;&quot;&gt;
            
      &lt;table id=&quot;table&quot;&gt;
                
        &lt;thead&gt;&lt;/thead&gt; 
        &lt;tr&gt;&lt;/tr&gt;

      &lt;/table&gt;

    &lt;/div&gt;

How to show a pandas dataframe into a existing flask html table?

I am using Pandas dataframes and want to create a new column as a function of existing columns. I have not seen a good discussion of the speed difference between `df.apply()` and `np.vectorize()`, so I thought I would ask here. 

The Pandas `apply()` function is slow. From what I measured (shown below in some experiments), using `np.vectorize()` is 25x faster (or more) than using the DataFrame function `apply()` , at least on my 2016 MacBook Pro. **Is this an expected result, and why?** 

For example, suppose I have the following dataframe with `N` rows:

    N = 10
    A_list = np.random.randint(1, 100, N)
    B_list = np.random.randint(1, 100, N)
    df = pd.DataFrame({&#39;A&#39;: A_list, &#39;B&#39;: B_list})
    df.head()
    #     A   B
    # 0  78  50
    # 1  23  91
    # 2  55  62
    # 3  82  64
    # 4  99  80




Suppose further that I want to create a new column as a function of the two columns `A` and `B`. In the example below, I&#39;ll use a simple function `divide()`. To apply the function, I can use either `df.apply()` or `np.vectorize()`:


    def divide(a, b):
        if b == 0:
            return 0.0
        return float(a)/b
    
    df[&#39;result&#39;] = df.apply(lambda row: divide(row[&#39;A&#39;], row[&#39;B&#39;]), axis=1)
    
    df[&#39;result2&#39;] = np.vectorize(divide)(df[&#39;A&#39;], df[&#39;B&#39;])

    df.head()
    #     A   B    result   result2
    # 0  78  50  1.560000  1.560000
    # 1  23  91  0.252747  0.252747
    # 2  55  62  0.887097  0.887097
    # 3  82  64  1.281250  1.281250
    # 4  99  80  1.237500  1.237500


If I increase `N` to real-world sizes like 1 million or more, then I observe that `np.vectorize()` is 25x faster or more than `df.apply()`.

Below is some complete benchmarking code:

    import pandas as pd
    import numpy as np
    import time
    
    def divide(a, b):
        if b == 0:
            return 0.0
        return float(a)/b
    
    for N in [1000, 10000, 100000, 1000000, 10000000]:    
    
        print &#39;&#39;
        A_list = np.random.randint(1, 100, N)
        B_list = np.random.randint(1, 100, N)
        df = pd.DataFrame({&#39;A&#39;: A_list, &#39;B&#39;: B_list})
        
        start_epoch_sec = int(time.time())
        df[&#39;result&#39;] = df.apply(lambda row: divide(row[&#39;A&#39;], row[&#39;B&#39;]), axis=1)
        end_epoch_sec = int(time.time())
        result_apply = end_epoch_sec - start_epoch_sec
            
        start_epoch_sec = int(time.time())
        df[&#39;result2&#39;] = np.vectorize(divide)(df[&#39;A&#39;], df[&#39;B&#39;])
        end_epoch_sec = int(time.time())
        result_vectorize = end_epoch_sec - start_epoch_sec
    

        print &#39;N=%d, df.apply: %d sec, np.vectorize: %d sec&#39; % \
                (N, result_apply, result_vectorize)
        
        # Make sure results from df.apply and np.vectorize match.
        assert(df[&#39;result&#39;].equals(df[&#39;result2&#39;]))


The results are shown below:

    N=1000, df.apply: 0 sec, np.vectorize: 0 sec
    
    N=10000, df.apply: 1 sec, np.vectorize: 0 sec
    
    N=100000, df.apply: 2 sec, np.vectorize: 0 sec
    
    N=1000000, df.apply: 24 sec, np.vectorize: 1 sec
    
    N=10000000, df.apply: 262 sec, np.vectorize: 4 sec


If `np.vectorize()` is in general always faster than `df.apply()`, then why is `np.vectorize()` not mentioned more? I only ever see StackOverflow posts related to `df.apply()`, such as:

https://stackoverflow.com/questions/26886653/pandas-create-new-column-based-on-values-from-other-columns

https://stackoverflow.com/questions/16353729/how-do-i-use-pandas-apply-function-to-multiple-columns

https://stackoverflow.com/questions/13331698/how-to-apply-a-function-to-two-columns-of-pandas-dataframe

Content Type	Original Author	Original Content on Stackoverflow
Question	ipramusinto	View Question on Stackoverflow
Solution 1 - Python	qsantos	View Answer on Stackoverflow
Solution 2 - Python	Jyoti Prasad Pal	View Answer on Stackoverflow
Solution 3 - Python	Tam Le	View Answer on Stackoverflow

Pandas isna() and isnull(), what is the difference?

Python Problem Overview

Python Solutions

Solution 1 - Python

Solution 2 - Python

Solution 3 - Python

android.view.View$OnUnhandledKeyEventListener

Cannot find module 'rxjs-compat/Observable'

Attributions