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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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Tableau 2 Top Books to Read

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In this post, I have given two top data visualization in Tableau books. These books helpful for your self-study.  


Tableau 2 Top Books to Read

Top Tableau Course Contents


  • Introduction to Tableau 
  • Connecting to data 
  • Visual analytics 
  • How to design dashboard 
  • Mapping 
  • Calculations 
  • How to publish and Manage with Tableau 
  • Security with Tableau .....Read more.

Two Best books on Tableau to Learn and Visualize the Data.


#1. Learning Tableau

  • Learn how to create effective data visualizations with Tableau and unlock a smarter approach to business analytics. 
  • It might just transform your organization About This Book
  • Create stylish visualizations and dashboards that explain complexity with clarity.
  • Learn effective data storytelling to transform how your business uses ideas and makes decisions
  • Explore all the new features in Tableau 10 and start to redefine what business. analytics means to your organization.

#2. How to create Data Visualization in Tableau 

  • Tableau Your Data! is a comprehensive guide to the effective use of the Tableau Software toolset for data visualization.
  • It covers the core feature set for data analytics, illustrating best practices for creating and sharing effective visualizations that support timely business decision-making.
  • The author also covers little-known as well as more advanced features and techniques, illustrating them using detailed, real-world case studies that the author has developed as part of his consulting and training.

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