### 5 SQL Queries That Popularly Used in Data Analysis

Here are five popular SQL queries frequently used in data analysis. 1. SELECT with Aggregations Summarize data by calculating aggregates like counts, sums, averages, etc. SELECT department, COUNT(*) as employee_count, AVG(salary) as average_salary FROM employees GROUP BY department; 2. JOIN Operations  Combine data from multiple tables based on a related column. SELECT e.employee_id, e.name, d.department_name FROM employees e JOIN departments d ON e.department_id = d.department_id; 3. WHERE Clause for Filtering Filter records based on specified conditions. SELECT * FROM sales WHERE sale_date BETWEEN '2024-01-01' AND '2024-12-31'   AND amount > 1000; 4. ORDER BY Clause for Sorting Sort results in ascending or descending order based on one or more columns. SELECT product_name, price FROM products ORDER BY price DESC; 5. GROUP BY with HAVING Clause Group records and apply conditions to the aggregated results. SELECT department, SUM(salary) as total_salaries FROM employ

# Best Practices for Handling Duplicate Elements in Python Lists

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 unique_list containing only the distinct elements from the original_list. Keep in mind that the order of elements might not be preserved using the set approach as sets are unordered collections. The loop and list comprehension methods will maintain the order of the elements.

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