POST TEST MODULE 7

df.head()

transactions_df.head()

df.drop()

grouped_df.reset_index()

(["itemDescription", "Date"])["Member_number"]

(["Member_number", "Date"])["itemDescription"]

(["Member_number"; "itemDescription"])["Date"]

(["itemDescription"; "Date"])["Member_number"]

df.head()

transactions_df.head()

df.drop()

grouped_df.reset_index()

transactions_df = grouped_df.tolist()

transactions_df = grouped_df.reset_index()

transactions_list = transactions_df["itemDescription"].lists()

transactions_list = transactions_df["itemDescription"].tolist()

Display Top 10 results

Training the Eclat model on the dataset

Importing the data

Display the results

[1, 3]

[2, 3]

[1, 2]

[2, 2]

finding relationships between items in a dataset

transforms a given data set of transactions in the horizontal data into the vertical data

a measure that shows how much dominance an item/item set has over all transactions

a measure that shows the relationship between two items conditionally

Detect the Univariate Outlier

Group items and create a list of items for each group

Preparing Transaction Data

Defining ranges of parameter values

transforms a given data set of transactions in the horizontal data into the vertical data

finding relationships between items in a dataset

a measure that shows how much dominance an item/item set has over all transactions

a measure that shows the relationship between two items conditionally