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Showing posts with the label SQL VIEWS

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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' ]) ...
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3 SQL Query Examples to Create Views Quickly

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There are three kinds of Views in SQL. The three views are Read-only, Force, and Updatable. Views real usage is to hide data. And you need to ensure base tables are present before you create a View. You can call views as logical tables. The advantage of Views is you can show only some of the fields of base tables. What is a View in SQL A view can be constructed with another view so it is called a nested view. You can create or replace an existing view A view can be created without having base tables. This is possible with the FORCE option. #1: Read-Only Views The standard syntax for the view is as follows: CREATE OR replace VIEW invoice_summary AS SELECT vendor_name count(*) AS invoice_count, SUM(invoice_total) AS invoice_total_sum FROM vendor JOIN invoices ON vendors.vendor_id*invoices.vendor_id GROUP BY vendor_name; Notes: You cannot update Read-only Views #2: Force Views CREATE FORCE VIEW products_list AS SELECT product_description, product_price FROM products;...
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