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Showing posts with the label r-vs-sas

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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' ]) ...

5 Top R Vs SAS Differences

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Statistical analysis should know by every software engineer. R is an open source statistical programming language. SAS is licensed analysis suite for statistics. The two are very much popular in Machine learning and data analytics projects. SAS is an Analysis-suite software and R is a programming language. 1. R Language R supports both statistical analysis and Graphics R is an open source project. R is 18th most popular Language R packages are written in C, C++, Java, Python and.Net R is popular in Machine learning, data mining and Statistical analysis projects. a). R Advantages R is flexible since a lot of packages are available. R is best suited for data related projects and  Machine learning . Less cost since it is open source language. R Studio is the best tool to develop R programming modules. Ref: imartcus.org (read more advantages) b). R Disadvantages R language architecture model is out of date. So may not use it for critical applications. R is not suitable for S...