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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

Skills needed for NoSQL Data engineer

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The following Skills are needed to become successful NoSQL data engineer. NoSQL Skills Skills You Need to Become NoSQL Developer 3 + years of practical experience with distributed data analysis systems using parallel processes such as Hadoop. Experience working with batch processing/ real-time systems using various open source technologies like Solr, Hadoop, NoSQL, Spark, Hive, etc. Knowledgeable about data modeling, data access, and data storage techniques Experience in Linux or similar system is preferred Experience on MySQL, NoSQL and storage software is a plus Check here... NoSQL jobs skills and experience required Related:   NoSQL Interview Questions