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Showing posts with the label retail analytics

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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' ]) ...

Data Science in Retail Marketing and Opportunities

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Data Science and Analytics started by all big companies including Shoppers top and Wal-mart. Data Science in Retail Shoppers Stop started big data analytics to study customers behavior. Started with one of the easiest programs. Where they studied customer loyalty program. Some Insights Studied patterns Studied customer buying styles Some people buy shirt-only and some people buy both Shirt and Trouser Studied buying patterns of Women buyers Read more at Live Mint

Retail Analytics Solution from Leader in Data Science SAS

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Retail market is changed now. So many companies now open shops across the world. Every business owner tries to increase sales. This is possible with analytics. Retail Analytics The study also includes an in-depth look at how best-in-class retailers use analytics, as well as the business analytics software vendor landscape. Walmart started retail business in India. So the real use of data analytics started now. References Download here