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Best Practices for Handling Duplicate Elements in Python Lists

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Here are three awesome ways that you can use to remove duplicates in a list. These are helpful in resolving your data analytics solutions.  01. Using a Set Convert the list into a set , which automatically removes duplicates due to its unique element nature, and then convert the set back to a list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = list(set(original_list)) 02. Using a Loop Iterate through the original list and append elements to a new list only if they haven't been added before. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] for item in original_list:     if item not in unique_list:         unique_list.append(item) 03. Using List Comprehension Create a new list using a list comprehension that includes only the elements not already present in the new list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] [unique_list.append(item) for item in original_list if item not in unique_list] All three methods will result in uni
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5 Essential IT Skills for Data Engineers

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Data engineers need the following skills. These skills help you get nice job in any analytics company.
Data engineer skills
Photo Credit: Srini

Five Top Skills Need

Skill-1

Experience working with big data tools such as MapReduce, Pig, Spark, Kafka and NoSQL data stores such as MongoDB, Cassandra, HBase, etc.

Skill-2

Expertise in multi-structured data modeling, reporting on NoSQL & structured database technologies such as HBase and Cassandra, SQL.

Skill-3

Experience with languages such as Python, Perl, Ruby, Java, Scala, R etc.

Skill-4

Strong data & visual presentation skills and ability to explain insights using tools like tableau, D3 charts or other tools.

Skill-5

Basic knowledge and experience of statistical analysis tools such as R.

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