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Analysing the content of an E-commerce database that contains list of purchases. Based on the analysis, I develop a model that allows to anticipate the purchases that will be made by a new customer, during the following year from its first purchase.

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jalajthanaki/Customer_segmentation

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Customer Segmentation

This notebook analyzing the content of an E-commerce database. Based on this analysis, We will predict segment for customer.

Dependencies

  • Python 2.7 or Python >3.4
  • pandas
  • numpy
  • scipy
  • scikit-learn
  • matplotlib
  • seaborn
  • nltk
  • wordcloud
  • jupyter notebook

Install dependencies

Pandas:           $ sudo pip install pandas
numpy:            $ sudo pip install numpy
scipy:            $ sudo pip install scipy
scikit-learn:     $ sudo pip install -U scikit-learn
matplotlib: 
                  $ sudo apt-get install libfreetype6-dev libpng-dev
                  $ sudo pip install matplotlib 
seaborn:          $ sudo pip install seaborn
jupyter notebook: $ sudo apt-get -y install ipython ipython-notebook
                  $ sudo -H pip install jupyter
nltk:              $ sudo pip install nltk
wordcloud:         $ sudo pip install wordcloud

Usage

  • Dataset path: ./input_data/
  • Run the code given in ipython notebook Cust_segmentation_online_retail.ipynb

Credit

Code credits for this code go to F. Daniel. I've merely created a wrapper and necessary changes to get people started.

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Analysing the content of an E-commerce database that contains list of purchases. Based on the analysis, I develop a model that allows to anticipate the purchases that will be made by a new customer, during the following year from its first purchase.

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