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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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Switching Career Top Skills for Mainframe Programmers

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Read my part-1 post. Secondly, the programmers who are working on the mainframe have very good business knowledge. 

People who have the following skills are a valuable asset to any organization. Mainframe programmers if they learn other skills and try for new jobs they can earn more money.

Programmer Roles.

A programmer who can do analysis, create database structures, write clean code, create testing structures, and clearly communicate all that has been done is a very valuable asset.

Background of Mainframe.

The mainframe was leading in the market since 1950. All the big companies in the world are running their business in mainframes. 

Yes, many American universities now teaching mainframe technology in their education curriculum, since in the future possibility is there for mainframe skill shortage.

Skills You Need to Switch Career.

  1. It may become more important for IT professionals to gain experience working with analytics technology, as research firm Gartner predicted a surge in demand in this area in the next two years. According to CIO contributor Hamish Barwick, the big data trend alone is expected to create 4.4 million jobs worldwide.
  2. Analysts warned that only a third of those jobs are likely to be filled due to difficulties in recruiting analytics talent.
  3. An opportunity for every IT Professional: "Dark data is the data being collected, but going unused despite its value and leading organizations of the future will be distinguished by the quality of their predictive algorithms.

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