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Showing posts with the label Algorithems

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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' ]) ...

Career Opportunities to Write Algorithms

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Many participants in the Analytics seminar expressed opportunity in preparing algorithms for predictive analytics. You Need Algorithms Why Using these algorithms, businesses can make better data-driven decisions by extracting actionable patterns and detailed statistics from large, often cumbersome data sets. Many business people small to big expecting some kind of algorithms. So that they can save their precious time in predictive analytics. As per IBM What are Good Benefits of Right  Algorithm Transform data into predictive insights to guide front-line decisions and interactions.  Predict what customers want and will do next to increase profitability and retention.  Maximize the productivity of your people, processes and assets.  Detect and prevent threats and fraud before they affect your organization.  Measure the social media impact of your products, services and marketing campaigns.  Perform statistical analysis including regression an...