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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' ]) ...

Computer Science Vs Information Science Top Differences

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Here are the differences between Computer Science and Information Science. Computer Science Computer scientists are, in fact, scientists. They are focused on the theory of computational applications. That means they understand the “why” behind computer programs. Using algorithms and advanced mathematics, computer scientists invent new ways to manipulate and transfer information. Computer scientists are generally concerned with software, operating systems, and implementation. Like Neo in The Matrix, computer scientists can see and make sense of code. Computer science students will learn the fundamentals of different programming languages, linear and discrete mathematics, and software design and development. Computer scientists study the machine itself and understand how and why various computer processes operate the way they do.   Information Science To put it bluntly, computer engineers make computer parts work together. Computer engineers are responsible for the res...