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Updated 3 years ago
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