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Top Questions People Ask About Pandas, NumPy, Matplotlib & Scikit-learn — Answered!

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 Whether you're a beginner or brushing up on your skills, these are the real-world questions Python learners ask most about key libraries in data science. Let’s dive in! 🐍 🐼 Pandas: Data Manipulation Made Easy 1. How do I handle missing data in a DataFrame? df.fillna( 0 ) # Replace NaNs with 0 df.dropna() # Remove rows with NaNs df.isna(). sum () # Count missing values per column 2. How can I merge or join two DataFrames? pd.merge(df1, df2, on= 'id' , how= 'inner' ) # inner, left, right, outer 3. What is the difference between loc[] and iloc[] ? loc[] uses labels (e.g., column names) iloc[] uses integer positions df.loc[ 0 , 'name' ] # label-based df.iloc[ 0 , 1 ] # index-based 4. How do I group data and perform aggregation? df.groupby( 'category' )[ 'sales' ]. sum () 5. How can I convert a column to datetime format? df[ 'date' ] = pd.to_datetime(df[ 'date' ]) ...

5 SQL Queries That Popularly Used in Data Analysis

 Here are five popular SQL queries frequently used in data analysis.


5 SQL Queries Popularly Used in Data Analytics




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 employees
GROUP BY department
HAVING SUM(salary) > 50000;

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