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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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Cloud Storage as a Service Basics(1 of 3)

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Cloud storage is a model of networked enterprise storage where data is stored in virtualized pools of storage which are generally hosted by third parties. Hosting companies operate large data centers, and customers that require their data to be hosted buy or lease storage capacity from these hosting companies.

The data center operators virtualize the resources according to customer requirements and expose them as storage pools, which the customers can use to store data. Physically, the resource may span multiple servers and multiple locations. The safety of the data depends upon the hosting companies and on the applications that leverage the cloud storage.

Cloud storage is based on highly virtualized infrastructure and has the same characteristics as cloud computing in terms of agility, scalability, elasticity, and multi-tenancy. It is available both off-premises and on-premises. 

While it is difficult to declare a canonical definition of cloud storage architecture, object storage is reasonably analogous. Cloud storage software such as OpenStack Cinder, cloud storage products like EMC Atmos® and Hitachi Content Platform, and distributed storage research projects like OceanStore or VISION Cloud are examples of object storage and infer the following guidelines.

Cloud storage is:

  • Made up of many distributed resources but still acts as one; often referred to as federated storage clouds. 
  • Highly fault tolerant through redundancy and distribution of data. 
  • Highly durable through the creation of versioned copies. 
  • Typically eventually consistent with regard to data replicas. 


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