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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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Python Regex: The 5 Exclusive Examples

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 Regular expressions (regex) are powerful tools for pattern matching and text manipulation in Python. Here are five Python regex examples with explanations: 01 Matching a Simple Pattern import re text = "Hello, World!" pattern = r"Hello" result = re.search(pattern, text) if result:     print("Pattern found:", result.group()) Output: Output: Pattern found: Hello This example searches for the pattern "Hello" in the text and prints it when found. 02 Matching Multiple Patterns import re text = "The quick brown fox jumps over the lazy dog." patterns = [r"fox", r"dog"] for pattern in patterns:     if re.search(pattern, text):         print(f"Pattern '{pattern}' found.") Output: Pattern 'fox' found. Pattern 'dog' found. It searches for both "fox" and "dog" patterns in the text and prints when they are found. 03 Matching Any Digit   import re text = "The price of the...
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