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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 top IT Skills every new IT Professionals learn to progress in software career

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What are the skills needed by the new IT professionals or job seekers who help the  organisation  transition to IT-as-a-Service.  In order  to lead their  organisations  to the cloud, IT professionals must focus on three fundamental areas: Core  Virtualisation  Skill Sets IT professionals must think and operate in the virtual world. No longer can they be tied to the old paradigm of physical assets dedicated to specific users or applications. They must think in terms of “services” riding on top of a fully virtualized infrastructure, and how applications will take advantage of shared resources with both servers and storage. This requires comprehensive skills in both server and storage virtualization technology, and enough experience as a practitioner to understand the intricacies and critical elements of managing virtual platforms. Rules of Old IT and New IT Cross-training Competency Leaders of IT innovation cannot be completely siloed...
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