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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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These Lovely Skills You Need to Enter as Data Architect

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We can analyze data quickly now. The data can be any size. The basic skills you need are R language skills and Machine learning for analyzing the data.

MapReduce Techniques

The MapReduce techniques and parallel processing in Hadoop allow us to cheaply and efficiently implement MapReduce on Internet scale problems. We use SQL like tools Pig and Hive.

NoSQL

We analyze so-called NoSQL storage solutions exemplified by HBase for their critical features: speed of reads and writes, data consistency, and ability to scale to extreme volumes.

Data Architect Requirements

  1. Data architects develop, analyze and administer data for businesses, schools and other organizations.
  2. They need sophisticated design and development skills to collect data and translate it for use in computer applications and systems. Most data architects have a bachelor's degree in information technology (IT), as well as years of experience in the IT field.
  3. Experience with programs such as Microsoft Excel, Access, SQL, Business Objects software, XML, SOA, ETL, BI, ERP and Agile; computer programming and data modeling skills*
  4. Degree in Engineering/Computer Science is desirable. Read more.

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