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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' ]) ...

The best career skills need for Social media platform

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#How-to-apply-social-media-analytics-for-all-it-developers Listening -  This one is still very much true, and perhaps even more so. The best social media pros listen the most actively and most aggressively. Pattern Recognition -  This is getting more and more critical as the data and complexity of social continues to ratchet up. Are these posts on our Facebook page a crisis in the making, or just noise? Where are the real-time marketing opportunities?  Instantly identifying patterns and being able to capitalize upon them  are some of the skills that separate good social practitioners from great ones. Visual Thinking -  This is perhaps the biggest change in the past year or two. Being a great writer was formerly a key characteristic of many social pros, as being able to coherently write in 140 characters isn’t as easy as it appears. Today, with every social network embracing visuals and multi-media,  being able to represent the brand visually is...