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Showing posts with the label Flash storage

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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' ]) ...

Oracle fFlash Storage and its Top Features

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ORACLE flash storage is faster than other storage systems. This post tells why flash storage you need and the special features of flash storage from oracle. Customers today are facing a triad of issues requiring higher performance from their storage systems such as More server and application virtualization, Faster servers and scale-out applications and Latency-sensitive applications. Flash storage is seen as the solution to these issues because it delivers the desired higher performance.  But does all of your data need flash media?  What if there were “a smart and self-optimizing” storage system that automatically moves data across different media depending not only on frequency of usage, but also on the application’s performance requirements, media cost, and business value? Introducing Oracle FS1 Flash Storage System. How is Oracle FS1 Flash Storage System Different? Oracle FS1 intelligently delivers flash performance when you need it and reduces costs by mov...