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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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New Wave in Data Analytics in 2014

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 SrnimfJobs
Now that we’re in the swing of a new year, we’ve taken stock of the data analytics trends that are brewing and developed a list of the Top 5 trends we believe are going to dominate the industry this year. Even if some of them don’t realize their full potential in 2014, it promises to be an important year in which consumer trends and technology innovation will further shape a future in which companies make data-driven decisions.
1. Data Visualization Goes Mainstream
In the mid-90s, e-mail introduced the Internet to consumers, made it more accessible, and catalyzed user adoption. Similarly, data visualization will make data analytics more accessible in 2014. Visual analytics allows business users to ask interactive questions of their prepared data sets and get immediate visual responses, which makes the whole process engaging.
This trend will democratize access to data and foster a strong data analysis culture where business users will look for data and perform visual analysis before making decisions. The quick wins that data visualization provides will lead to a changed mindset that will allow for future forays into more advanced analytics that uses math, statistics, and complex data sets. In 2014, we could see some further innovation around collaboration of business users in answering business questions. Soon, the business utility and future of a dashboard could be determined by how many “likes,” “shares,” and comments it receives from business users.
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