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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

Apache HIVE Top Features

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Apache Hive aids the examination of great datasets kept in Hadoop’s HDFS and harmonious file setups such as the Amazon S3 filesystem. It delivers an SQL-like lingo named when keeping complete aid aimed at map/reduce. To accelerate requests, it delivers guides, containing bitmap guides. By preset, Hive stores metadata in an implanted Apache Derby database, and different client/server databases like MySQL may optionally be applied. Currently, there are 4 file setups maintained in Hive, which are TEXTFILE, SEQUENCE FILE, ORC, and RCFILE. Other attributes of Hive include: Indexing to supply quickening, directory sort containing compacting, and Bitmap directory as of 0.10, further directory kinds are designed. Different depository kinds such as simple written material, RCFile, HBase, ORC, and other ones. Metadata depository in an RDBMS, notably decreasing the time to accomplish verbal examines throughout request implementation. Operating on compressed information kept into the H