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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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11 Top PIG Interview Questions

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Here are the top PIG interview questions. These are useful for your project and interviews. 1). What is PIG? PIG is a platform for analyzing large data sets that consist of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs.  PIG’s infrastructure layer consists of a compiler that produces a sequence of MapReduce Programs. 2). What is the difference between logical and physical plans? Pig undergoes some steps when a Pig Latin Script is converted into MapReduce jobs. After performing the basic parsing and semantic checking, it produces a logical plan.  The logical plan describes the logical operators that have to be executed by Pig during execution. After this, Pig produces a physical plan. The physical plan describes the physical operators that are needed to execute the script. 3). Does ‘ILLUSTRATE’ run MR job? No, illustrate will not pull any MR, it will pull the internal data. On the console, illustr...
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