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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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HBASE: Top Features in Storing Big data

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In this post explained top features added in HBase to handle the data. The Java implementation of Google's Big Table you can call it as HBASE.  In HBase, the data store as two parts.
hadoop hbase

Row Key : 00001 
Column : (Column Qualifier:Version:Value)

Features of HBASE

  • HBase data stores consist of one or more tables, which are indexed by row keys.
  • Data is stored in rows with columns, and rows can have multiple versions.
  • By default, data versioning for rows is implemented with time stamps.
  • Columns are grouped into column families, which must be defined upfront during table creation. Column families are stored together on disk, which is why HBase is referred to as a column-oriented datastore
New features of HBASE check now

In addition...

HBase is a distributed data store, which leverages a network-attached cluster of low-cost commodity servers to store and persist data.HBase architecture is a little trick to know.

Region Servers...

RegionServers are the software processes (often called daemons) you activate to store and retrieve data in HBase.

The big difference...

  • HABSE handles growing data or big data. HBase automatically scales as you add data to the system. A huge benefit compared to most database management systems, which require manual intervention to scale the overall system beyond a single server. 
  • With HBase, as long as you have in the rack another spare server that's configured, scaling is automatic.

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