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How to Check Column Nulls and Replace: Pandas

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Here is a post that shows how to count Nulls and replace them with the value you want in the Pandas Dataframe. We have explained the process in two steps - Counting and Replacing the Null values. Count null values (column-wise) in Pandas ## count null values column-wise null_counts = df.isnull(). sum() print(null_counts) ``` Output: ``` Column1    1 Column2    1 Column3    5 dtype: int64 ``` In the above code, we first create a sample Pandas DataFrame `df` with some null values. Then, we use the `isnull()` function to create a DataFrame of the same shape as `df`, where each element is a boolean value indicating whether that element is null or not. Finally, we use the `sum()` function to count the number of null values in each column of the resulting DataFrame. The output shows the count of null values column-wise. to count null values column-wise: ``` df.isnull().sum() ``` ##Code snippet to count null values row-wise: ``` df.isnull().sum(axis=1) ``` In the above code, `df` is the Panda
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Scala: Unique features you need to know

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scala features

Let us start it in layman terms...

Why you need Scala...

The name Scala stands for “scalable language.” The language is so named because it was designed to grow with the demands of its users.

Where Scala can be applied...

You can apply Scala to a wide range of programming tasks, from writing small scripts to
building large systems. 

The real use of Scala...

  • Scala is easy to get into. It runs on the standard Java platform and interoperates seamlessly with all Java libraries. It’s quite a good language for writing scripts that pull together Java components.
  • But it can apply its strengths even more when used for building large systems and frameworks of reusable components.
Technically, Scala is a blend of object-oriented and functional programming
concepts in a statically typed language.
The fusion of object-oriented and functional programming shows up in many different aspects of Scala;
It is probably more pervasive than in any other widely used language. The two programming styles have complementary strengths when it comes to scalability.

Also read: The real Quiz on Scala for developers 

What are the Scala unique strengths...
  • Scala’s functional programming constructs make it easy to build interesting things quickly from simple parts.
  • Its object-oriented constructs make it easy to structure larger systems and to adapt them to new demands.
The combination of both styles in Scala makes it possible to express new kinds of programming patterns and component abstractions. It also leads to a legible and concise programming style. And because it is so malleable, programming in Scala can be a lot of fun. 

The sample Scala program...

Scala program:

var capital = Map("US" -> "Washington", "France" -> "Paris")
capital += ("Japan" -> "Tokyo")
println(capital("France"))

This program sets up a map from countries to their capitals, modifies the map by adding a new binding ("Japan" -> "Tokyo"), and prints the capital associated with the country France.

The notation in this example is high-level, to the point, and not cluttered with extraneous semicolons or type annotations.

Indeed, the feel is that of a modern “scripting” language like Perl, Python, or Ruby.

One common characteristic of these languages, which is relevant for the example above, is that they each support an “associative map” construct in the syntax of the language

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