How To Find Lowest Sale Month: SQL Interview Question Day 11/40
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YouTubeArt of Data
How To Find Lowest Sale Month: SQL Interview Question Day 11/40
In this video, we walk through a classic SQL interview challenge: finding the month with the lowest total sales over the past 12 months. It’s a great example of how to combine date functions, filtering windows, aggregation, and CTEs to answer real business questions. We start by breaking the sale date into a year and month using strftime ...
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Analyse sales data together part 7 # Extract year and month salesData['Year'] = salesData['Invoice Date'].dt.year salesData['Month'] = salesData['Invoice Date'].dt.month # Filter out the online sales onlineSales = salesData[salesData['Sales Method'] == 'Online'] # Group by year and month and sum the total sales monthlySales = onlineSales.groupby(['Year', 'Month'])['Total Sales'].sum().reset_index() # Pivot the data for line plot (years as columns, months as rows) pivotMonthlySales = monthlySales
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Analyse sales data together part 7 # Extract year and month salesData['Year'] = salesData['Invoice Date'].dt.year salesData['Month'] = salesData['Invoice Date'].dt.month # Filter out the online sales onlineSales = salesData[salesData['Sales Method'] == 'Online'] # Group by year and month and sum the total sales monthlySales = onlineSales.groupby(['Year', 'Month'])['Total Sales'].sum().reset_index() # Pivot the data for line plot (years as columns, months as rows) pivotMonthlySales = monthlySales
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Analyse sales data together part 7 # Extract year and month salesData['Year'] = salesData['Invoice Date'].dt.year salesData['Month'] = salesData['Invoice Date'].dt.month # Filter out the online sales onlineSales = salesData[salesData['Sales Method'] == 'Online'] # Group by year and month and sum the total sales monthlySales = onlineSales.groupby(['Year', 'Month'])['Total Sales'].sum().reset_index() # Pivot the data for line plot (years as columns, months as rows) pivotMonthlySales = monthlySales
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