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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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Here's to Know Data lake Vs Database

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In a data lake, data stored internally in a repository. You can call it a blob. The data in the lake a no-format data, but you need a schema for the database. 



Data lake Repository

Database

  • In the database, the Schema definition you need before you store data on it.
  • It should follow Codd's rules.
  • Here data is completely formatted.
  • The data stores here in Tables, so you need SQL language to read the records.
  • Poor performance in terms of scalability.



Data lake

  • It doesn't have any format - it's just a dump.
  • You can send this dump to the Hadoop repository for data analysis.
  • This repository can be incremental. You can build a database.
  • The data lake is a dump of data with no format. It needs a pre-format before it sends for analytics.
  • Data security and encryption: You need these before you send data to Hadoop.
  • In real-time, you need to pre-process data.
  • This data you need to send to the data warehouse to get insights.

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