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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 Tips Helpful to Remove Python List and Dictionary Duplicates

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In this post, I have shared top ideas to remove duplicates from the list. Those are with Append and Dictionary. 1. How to Remove Duplicates with Append # Here is a list with duplicates list_with_duplicates = [1,2,3,12,1,2,3,4,5,6,1,2,3,7,8,9] It is simple if you follow the first-approach - brute force approach: list_without_duplicates = [] for pd in list_with_duplicates:   if pd not in list_without_duplicates:       list_without_duplicates.append(pd) print(list_without_duplicates) Result: [1, 2, 3, 12, 4, 5, 6, 7, 8, 9] This method has performance issues when the list is bigger in size.  Real-time. 2. How to Remove Duplicates with Dictionary # Here is you can convert a list to a dictionary dict_without_duplicates = dict(zip(list_with_duplicates, list_with_duplicates)) print(dictionary_without_duplicates) Result: {1: 1, 2: 2, 3: 3, 12: 12, 4: 4, 5: 5, 6: 6, 7: 7, 8: 8, 9: 9} Real-time. Once again, this works and has the advantage of taking less space than duplic...
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