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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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Oracle 12C 'Bitmap Index' benefits over B-tree Index

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#Oracle 12C 'Bitmap Index' benefits over B-tree Index: A bitmap index has a significantly different structure from a B-tree index in the leaf node of the index. It stores one string of bits for each possible value (the cardinality) of the column being indexed. Note: One string of BITs means -Each tupple of possible value it assigns '1' bit in a string.So, all the BITs become a string ( This is an example, on which column you created BIT map index) The length of the string of bits is the same as the number of rows in the table being indexed. In addition to saving a tremendous amount of space compared to traditional indexes, a bitmap index can provide dramatic improvements in response time because Oracle can quickly remove potential rows from a query containing multiple WHERE clauses long before the table itself needs to be accessed. Multiple bitmaps can use logical AND and OR operations to determine which rows to access from the table. Although you ca...
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