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Group By Function | Pandas Data Analysis Tutorial #1 | Retail Example
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If you are data analyst, learning the Pandas groupby function is essential for you to segment and aggregate your data. Similar to a pivot table this allows you to group categories into different aggregations quickly to provide immediate insight.
In this example we will analyze an online retail dataset and answer business questions like:
1.Find out which customers placed the most and fewest orders.
2.Find out which countries placed the fewest orders.
3.Find out which customers spent the most money.
5.Find out which customer spent the most money on one item.
6.Find out which month had the most orders.
7. What is the most ordered product by country
Get the dataset here:
Don't hesitate to dive into the mini-case studies and questions and create your own answers using groupby. Learn by doing!
______________________________________________________________________
______________________________________________________________________
#DataAnalysis
# Pandas
#Python
In this example we will analyze an online retail dataset and answer business questions like:
1.Find out which customers placed the most and fewest orders.
2.Find out which countries placed the fewest orders.
3.Find out which customers spent the most money.
5.Find out which customer spent the most money on one item.
6.Find out which month had the most orders.
7. What is the most ordered product by country
Get the dataset here:
Don't hesitate to dive into the mini-case studies and questions and create your own answers using groupby. Learn by doing!
______________________________________________________________________
______________________________________________________________________
#DataAnalysis
# Pandas
#Python
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