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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' ]) ...

Information Architect Key Responsibilities

Gartner defines "enterprise information architecture" as that part of the enterprise architecture process. It is a set of requirements , principles and models — the current state, future state, and guidance necessary to flexibly share and exchange information assets to achieve effective enterprise change.  Enterprise information Architect also called EIA. Information Architecture  The transition from information that is isolated within applications to a flexible, comprehensive enterprise information architecture will require changes in technology, process, organizational structure and orientation.  In particular, EA practitioners comfortable with technical architecture must now devote time to understanding this emerging discipline.  Gartner projects that, EA teams will be forced by the business to spend as much time on information architecture as they currently spend on technical architecture.  Changes will also impact a range of disciplines across the organiza...