Learn how to analyze customer personality data using Python and various libraries like NumPy, Pandas, and Matplotlib. This blog explores a dataset containing 29 variables and 2240 observations about different customers, and includes data cleaning and preparation steps. Get started with the Zero to Pandas course and download the dataset from Kaggle.
The Customer Personality data Analysis is one of the best analysis to collect a information from the customer and in which data maximum information is given. We analysis some informations to get important data like customer in which product to money investing. This data set collecting from kaggle.com, and in this data to analysis with the help of some python program, numpy, pandas, matplotlib, piechart performing in Jupyternotebook. We learn data analysis from Zero to Panda is one of the best platform to learn data analysis course Data Analysis with Python: Zero to Pandas, and we learn how to analysis data with the help of pandas numeric calculation numpy visualization etc.
This dataset contains 29 variables and 2240 observations about different customers.
Here's a brief version of the data description file.
ID: Customer's unique identifier
Year_Birth: Customer's birth year
Education: Customer's education level
Marital_Status: Customer's marital status
Income: Customer's yearly household income
Kidhome: Number of children in customer's household
Teenhome: Number of teenagers in customer's household
Dt_Customer: Date of customer's enrollment with the company
Recency: Number of days since customer's last purchase
Complain: 1 if customer complained in the last 2 years, 0 otherwise
MntWines: Amount spent on wine in last 2 years
MntFruits: Amount spent on fruits in last 2 years
MntMeatProducts: Amount spent on meat in last 2 years
MntFishProducts: Amount spent on fish in last 2 years
MntSweetProducts: Amount spent on sweets in last 2 years
MntGoldProds: Amount spent on gold in last 2 years
NumDealsPurchases: Number of purchases made with a discount
AcceptedCmp1: 1 if customer accepted the offer in the 1st campaign, 0 otherwise
AcceptedCmp2: 1 if customer accepted the offer in the 2nd campaign, 0 otherwise
AcceptedCmp3: 1 if customer accepted the offer in the 3rd campaign, 0 otherwise
AcceptedCmp4: 1 if customer accepted the offer in the 4th campaign, 0 otherwise
AcceptedCmp5: 1 if customer accepted the offer in the 5th campaign, 0 otherwise
Response: 1 if customer accepted the offer in the last campaign, 0 otherwise
NumWebPurchases: Number of purchases made through the company’s web site
NumCatalogPurchases: Number of purchases made using a catalogue
NumStorePurchases: Number of purchases made directly in stores
NumWebVisitsMonth: Number of visits to company’s web site in the last month
!pip install jovian opendatasets --upgrade --quiet
Let's begin by downloading the data, and listing the files within the dataset.
# Change this dataset_url = 'https://www.kaggle.com/imakash3011/customer-personality-analysis'
import opendatasets as od od.download(dataset_url)
Please provide your Kaggle credentials to download this dataset. Learn more: http://bit.ly/kaggle-creds Your Kaggle username: mdzee888 Your Kaggle Key: ········ Downloading customer-personality-analysis.zip to ./customer-personality-analysis
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