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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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The best answer for 'Efficient Workbook' in Tableau

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There are several factors that define an “efficient” workbook. Some of these factors are technical and some more user-focused. An efficient workbook is:

  • A workbook that takes advantage of the “principles of visual analysis” to effectively communicate the message of the author and the data, possibly by engaging the user in an interactive experience.
  • A workbook that responds in a timely fashion. This can be a somewhat subjective measure, but in general we would want the workbook to provide an initial display of information and to respond to user interactions within a couple of (< 5) seconds. 
  • Tableau latest version is 9.1.2 as on writing this post
  • Tableau version 8 and Version 9 differences
  1. Individual Query time improved by 10x
  2. Dashboard Query times improved by 9x
  3. Query Fusion improving times by 2x
  4. And Query Caching improving times by 50x

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