Posts

Showing posts with the label DB2 NoSQL

Featured Post

Top Questions People Ask About Pandas, NumPy, Matplotlib & Scikit-learn — Answered!

Image
 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' ]) ...

The awesome points to learn from DB2 NoSQL GraphStore

Image
 #db2 graphstore: One best example, prior to understanding the RDF format for Graph data model -  If the graph data model is the model the semantic web uses to store data, RDF is the format in which it is written.  Related: Highly Demanding Web Designer Jobs Summary of DB2 Graph Store: DB2-RDF support is officially called "NoSQL Graph Support".   The API extends the Jena API (Graph layer).  Developers familiar with Jena TDB will have the Model layer capabilities they are accustomed to. Although the DB2-RDF functionality is being released with DB2 LUW 10.1, it is also compatible with DB2 9.7. Full supports for SPARQL 1.0 and a subset of SPARQL 1.1.  Full SPARQL 1.1 support (which is till a W3C working draft) will be forthcoming. While RDBMS implementations of RDF graphs have typically been non-performant, that is not the case here*.  Some very impressive and innovative work has been put into optimization capabilities.  Out-of-t...