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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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Real thoughts on IBM power8 servers to use on analytics

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All About IBM Big data Server Models

IBM Servers

International Business Machines Corp, in its latest attempt at reviving demand for its hardware products, is launching high-end system servers that it says are 50 times faster than its closest competitor at analysing data. 

  • The POWER8 servers, the product of a $2.4 billion, three-year investment, are part of the company's decade-long shift to higher-value hardware technology.  
  • IBM said the machines are 50 times faster than the low-end x86-based servers it sold to Chinese PC maker Lenovo Group Ltd in January. 
  • The technology services provider said on Wednesday it hopes the servers, designed for large-scale computing, will appeal to clients looking to manage new types of social and mobile computing and mass amounts of data.
Last week, the company reported its lowest quarterly revenue in five years, weighed down by falling demand for its storage and server products.

IBM dominates the higher-end server market with 57 percent market share, according to research firm Canalys. "For IBM customers in particular the POWER8 represents a generational jump forward so far as overall performance and system capacity goes," said Charles King, an analyst at Pund-IT in California.

"POWER8 should help IBM move forward in this very cloud-centric, analytic path that it has been working on," he said. Read more

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