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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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Top sub-modules in Cloud Computing Technology Architecture

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Top sub-modules in Cloud Computing Technology Architecture
#Top sub-modules in Cloud Computing Technology Architecture:
The main architectural characteristics of a cloud computing environment. One fundamental architectural aspect of a cloud is heterogeneity. A cloud must support the aggregation of heterogeneous hardware and software resources, as it happens with scientific experiments. The concept of virtualization is also a key aspect for clouds.

Through virtualization, many users may benefit from the same infrastructure using independent instances. Virtualization enables the first security level in the clouds, since it allows the isolation of environments. In clouds, each user has unique access to its individual virtualized environment.

Cloud Architecture
  1. Virtualization
  2. Heterogeneity
  3. Security
  4. Resource sharing
  5. Scalability
  6. Monitoring
Resource sharing is provided by clouds, since each resource is represented as a single artifact, giving the impression of a single dedicated resource. Scalability is mainly defined by increasing the number of working nodes. By definition, clouds offer the automatic resizing of virtualized hardware resources. Monitoring refers to the ability of watching the current status of virtual machines or services provided.

Each one of those architectural characteristics is standardized by specific standards (which are in another class of the taxonomy). Besides that, some architectural characteristics are important to scientific experiments, such as scalability and monitoring to control the execution.

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