Context of Data

Company - UK-based and registered non-store online retail

Products for selling - Mainly all-occasion gifts

Customers - Most are wholesalers (local or international)

Transactions Period - 1st Dec 2010 - 9th Dec 2011 (One year)

import pandas as pd 
import numpy as np 
import matplotlib.pyplot as plt
import seaborn as sns 

import warnings
# current version of seaborn generates a bunch of warnings that we'll ignore
warnings.filterwarnings('ignore')
sns.set_style('whitegrid')

#import missingno as msno # missing data visualization module for Python
#import pandas_profiling

import gc
import datetime

%matplotlib inline

df = pd.read_csv('Ecommerce _ UK_Retailer.csv')

df.head()

df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 541909 entries, 0 to 541908
Data columns (total 8 columns):
 #   Column       Non-Null Count   Dtype  
---  ------       --------------   -----  
 0   InvoiceNo    541909 non-null  object 
 1   StockCode    541909 non-null  object 
 2   Description  540455 non-null  object 
 3   Quantity     541909 non-null  int64  
 4   InvoiceDate  541909 non-null  object 
 5   UnitPrice    541909 non-null  float64
 6   CustomerID   406829 non-null  float64
 7   Country      541909 non-null  object 
dtypes: float64(2), int64(1), object(5)
memory usage: 33.1+ MB