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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 5 Skills You need to Start Data Analytics Career

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Data analytics is the job role hot in demand in each organization. Digital skills such as Mobile development, Full-stack development, Data Science, and Cloud computing are successful because they are very user-friendly to the end-users.


skills in-demand

Digital devices enabled digital technologies to cause to generate more data. You need different kinds of tools to analyze data in different formats.

You need the right tools. Else you cannot predict the user's mind. User search data is the source of big retail markets. Based on these search words, they start selling the products.

The motto behind data analytics is to get the benefit all stakeholders. Let us take cloud computing the main advantage is cost-effectiveness and scalability.

5 Skills you need for data analyst job

  1. R Programming
  2. SAS
  3. Excel
  4. Tableau
  5. QlikView

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