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The Quick and Easy Way to Analyze Numpy Arrays

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The quickest and easiest way to analyze NumPy arrays is by using the numpy.array() method. This method allows you to quickly and easily analyze the values contained in a numpy array. This method can also be used to find the sum, mean, standard deviation, max, min, and other useful analysis of the value contained within a numpy array. Sum You can find the sum of Numpy arrays using the np.sum() function.  For example:  import numpy as np  a = np.array([1,2,3,4,5])  b = np.array([6,7,8,9,10])  result = np.sum([a,b])  print(result)  # Output will be 55 Mean You can find the mean of a Numpy array using the np.mean() function. This function takes in an array as an argument and returns the mean of all the values in the array.  For example, the mean of a Numpy array of [1,2,3,4,5] would be  result = np.mean([1,2,3,4,5])  print(result)  #Output: 3.0 Standard Deviation To find the standard deviation of a Numpy array, you can use the NumPy std() function. This function takes in an array as a par

Top Hive interview Questions for quick read (1 of 2)

The selected interview questions on HIVE. Hive is a technology being used in Hadoop eco system.

1) What are major activities in Hadoop eco system?
Within the Hadoop ecosystem, HDFS can load and store massive quantities of data in an efficient and reliable manner. It can also serve that same data back up to client applications, such as MapReduce jobs, for processing and data analysis.
2)What is the role of HIVE in HADOOP Eco system?
Hive, often considered the Hadoop data warehouse platform, got its start at Facebook as their analyst struggled to deal with the massive quantities of data produced by the social network. Requiring analysts to learn and write MapReduce jobs was neither productive nor practical.
Hive Questions
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3)What is Hive in Hadoop?
Facebook developed a data warehouse-like layer of abstraction that would be based on tables. The tables function merely as metadata, and the table schema is projected onto the data, instead of actually moving potentially massive sets of data. 

This new capability allowed their analyst to use a SQL-like language called Hive Query Language (HQL) to query massive data sets stored with HDFS and to perform both simple and sophisticated summarizations and data analysis.

4)What is the requirement for HIVE learning?
If you are familiar with basic T-SQL data definition language (DDL) commands, you already have a good head start in working with Hive tables.

5)What is CREATE Table in HIVE?
CREATE EXTERNAL TABLE iislogtest (
       date STRING,
       time STRING,
       username STRING,
       ip STRING,
       port INT,
       method STRING,
       uristem STRING,
       uriquery STRING,
       timetaken INT,
       useragent STRING,
       referrer STRING
)
ROW FORMAT DELIMITED FIELDS TERMINATED BY ',';

6) What is SELECT statement in Query?
SELECT *
FROM iislogtest; 
This simple query, simply returns all rows found in the iislogtest table.

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