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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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7 Amazing Ideas to Make Resume for First Job

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Resume writing is a skill. Out of a thousand applications, only a few would shortlist for the next process. Here are my ideas to provide in your resume before you send it out.


7 Top Resume Ideas Worth to Read

Resume format

How to make resume format
  • Give Mobile number and E-mail on the top of your resume.
  • Use MS-word to format it.
  • Organize information using bullets wherever the need.
  • Check Spell and Grammar.
  • Two pages are ideal for any type of job.

7 Amazing ideas

Detailed resume ideas
  1. Provide genuine-experience.
  2. Transferable skills such as Public-speaking, Customer-communication - good to mention.
  3. Provide previous experience in reverse order - last-in-first.
  4. Keep educational qualification after the experience.
  5. No need to mention weaknesses.
  6. Add awards you received during your employment.
  7. Not required salary details.

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