Aggregering

Marknadskorgsanalys i Python

Isaiah Hull

Visiting Associate Professor of Finance, BI Norwegian Business School

Utforska data

import pandas as pd

# Load novelty gift data.
gifts = pd.read_csv('datasets/novelty_gifts.csv')

# Preview data with head() method.
print(gifts.head())

  InvoiceNo                          Description
0    562583      IVORY STRING CURTAIN WITH POLE 
1    562583        PINK AND BLACK STRING CURTAIN
2    562583                PSYCHEDELIC TILE HOOK
3    562583                ENAMEL COLANDER CREAM
4    562583  SMALL FOLDING SCISSOR(POINTED EDGE)

Utforska data

# Print number of transactions.
print(len(gifts['InvoiceNo'].unique()))

# Print number of items.
print(len(gifts['Description'].unique()))

Beskärning och aggregering

Beskärning Diagrammet visar en lista med artiklar där vissa är överstrukna för att indikera att de har beskurits.

Aggregering Diagrammet visar en lista med artiklar som mappas till en kortare lista för att illustrera aggregering.

Aggregera data

# Load one-hot encoded data
onehot = pd.read_csv('datasets/online_retail_onehot.csv')

# Print preview of DataFrame
print(onehot.head(2))

    50'S CHRISTMAS GIFT BAG LARGE   DOLLY GIRL BEAKER ...  ZINC WILLIE WINKIE  CANDLE STICK
0                           False               False                               False
1                           False               False                               True

Aggregera data

# Select the column names for bags and boxes
bag_headers = [i for i in onehot.columns if i.lower().find('bag')>=0]
box_headers = [i for i in onehot.columns if i.lower().find('box')>=0]

# Identify column headers
bags = onehot[bag_headers]
boxes = onehot[box_headers]
print(bags)

       50'S CHRISTMAS GIFT BAG LARGE   RED SPOT GIFT BAG LARGE  
0                              False                     False   
1                              False                     False
...                             ...                      ...

Aggregera data

# Sum over columns
bags = (bags.sum(axis=1) > 0.0).values
boxes = (boxes.sum(axis=1) > 0.0).values
print(bags)

[False  True False ... False  True False]

Aggregera data

# Add results to DataFrame
aggregated = pd.DataFrame(np.vstack([bags, boxes]).T, columns = ['bags', 'boxes'])

print(aggregated.head())

    bags  boxes
0  False  False
1   True  False
2  False  False
3  False  False
4   True  False

Kundkorgsanalys med aggregering

Aggregeringsprocess:
- Artiklar -> Kategorier
- Beräkna mätvärden
- Identifiera regler

# Compute support
print(aggregated.mean())

bags     0.130075
boxes    0.071429

Nu kör vi en övning!

Marknadskorgsanalys i Python