Data Analytics with python/[Data Analysis]

[Pandas][DataFrame][MultiIndex]S4_04_Multi_indexing_operations1

보끔밥0130 2023. 1. 21. 20:44

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In [ ]:

import pandas as pd

In [ ]:

# Multi-index DataFrame
sales_df = pd.read_csv('Online Retail.csv', encoding = 'unicode_escape')
sales_df.set_index(keys=['Country','InvoiceDate'], inplace = True)
sales_df

Out[ ]:

		InvoiceNo	StockCode	Description	Quantity	UnitPrice	CustomerID
Country	InvoiceDate
United Kingdom	12/1/2010 8:26	536365	85123A	WHITE HANGING HEART T-LIGHT HOLDER	6	2.55	17850.0
	12/1/2010 8:26	536365	71053	WHITE METAL LANTERN	6	3.39	17850.0
	12/1/2010 8:26	536365	84406B	CREAM CUPID HEARTS COAT HANGER	8	2.75	17850.0
	12/1/2010 8:26	536365	84029G	KNITTED UNION FLAG HOT WATER BOTTLE	6	3.39	17850.0
	12/1/2010 8:26	536365	84029E	RED WOOLLY HOTTIE WHITE HEART.	6	3.39	17850.0
...	...	...	...	...	...	...	...
France	12/9/2011 12:50	581587	22613	PACK OF 20 SPACEBOY NAPKINS	12	0.85	12680.0
	12/9/2011 12:50	581587	22899	CHILDREN'S APRON DOLLY GIRL	6	2.10	12680.0
	12/9/2011 12:50	581587	23254	CHILDRENS CUTLERY DOLLY GIRL	4	4.15	12680.0
	12/9/2011 12:50	581587	23255	CHILDRENS CUTLERY CIRCUS PARADE	4	4.15	12680.0
	12/9/2011 12:50	581587	22138	BAKING SET 9 PIECE RETROSPOT	3	4.95	12680.0

541909 rows × 6 columns

In [ ]:

# the first level of indexing
sales_df.index.get_level_values(0)

Out[ ]:

Index(['United Kingdom', 'United Kingdom', 'United Kingdom', 'United Kingdom',
       'United Kingdom', 'United Kingdom', 'United Kingdom', 'United Kingdom',
       'United Kingdom', 'United Kingdom',
       ...
       'France', 'France', 'France', 'France', 'France', 'France', 'France',
       'France', 'France', 'France'],
      dtype='object', name='Country', length=541909)

In [53]:

# the second level of indexing
sales_df.index.get_level_values(1)

Out[53]:

Index(['12/1/2010 8:26', '12/1/2010 8:26', '12/1/2010 8:26', '12/1/2010 8:26',
       '12/1/2010 8:26', '12/1/2010 8:26', '12/1/2010 8:26', '12/1/2010 8:28',
       '12/1/2010 8:28', '12/1/2010 8:34',
       ...
       '12/9/2011 12:50', '12/9/2011 12:50', '12/9/2011 12:50',
       '12/9/2011 12:50', '12/9/2011 12:50', '12/9/2011 12:50',
       '12/9/2011 12:50', '12/9/2011 12:50', '12/9/2011 12:50',
       '12/9/2011 12:50'],
      dtype='object', name='InvoiceDate', length=541909)

In [54]:

# the name of the column/index
sales_df.index.get_level_values('InvoiceDate')

Out[54]:

Index(['12/1/2010 8:26', '12/1/2010 8:26', '12/1/2010 8:26', '12/1/2010 8:26',
       '12/1/2010 8:26', '12/1/2010 8:26', '12/1/2010 8:26', '12/1/2010 8:28',
       '12/1/2010 8:28', '12/1/2010 8:34',
       ...
       '12/9/2011 12:50', '12/9/2011 12:50', '12/9/2011 12:50',
       '12/9/2011 12:50', '12/9/2011 12:50', '12/9/2011 12:50',
       '12/9/2011 12:50', '12/9/2011 12:50', '12/9/2011 12:50',
       '12/9/2011 12:50'],
      dtype='object', name='InvoiceDate', length=541909)

In [56]:

# change the names of the DataFrmae
sales_df.index.set_names(names = ['Transaction Location','Transaction Date'], inplace=True)
sales_df.head()

Out[56]:

		InvoiceNo	StockCode	Description	Quantity	UnitPrice	CustomerID
Transaction Location	Transaction Date
United Kingdom	12/1/2010 8:26	536365	85123A	WHITE HANGING HEART T-LIGHT HOLDER	6	2.55	17850.0
	12/1/2010 8:26	536365	71053	WHITE METAL LANTERN	6	3.39	17850.0
	12/1/2010 8:26	536365	84406B	CREAM CUPID HEARTS COAT HANGER	8	2.75	17850.0
	12/1/2010 8:26	536365	84029G	KNITTED UNION FLAG HOT WATER BOTTLE	6	3.39	17850.0
	12/1/2010 8:26	536365	84029E	RED WOOLLY HOTTIE WHITE HEART.	6	3.39	17850.0

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