Name: Electronic Card Transactions From 2017-2020
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Electronic Card Transactions From 2017-2020

Electronic Card Transactions from 2017-2020

Exploring Retail Spending Trends

By data.govt.nz [source]

About this dataset

This dataset contains valuable information about electronic card transactions from 2017-2020. The data is sourced from a trustable source and was last updated on 2020-08-10. It paints a comprehensive picture of electronic payments made during this period and includes important variables such as the series reference, period, data value, suppresed status, units magnitude, subject, group and five titles (series_title). This data is useful for exploring timely trends in electronic card spending activity over the 4 year period between 2017 to 2020 making it an invaluable asset for researchers looking to better understand purchasing habits in New Zealand. This dataset offers analysts unprecedented insight into consumer behavior allowing them to develop strategies aimed at increasing transaction volumes or customer loyalty initiatives

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How to use the dataset

This dataset contains information about electronic card transactions from 2017-2020. It includes data on the series reference, period, data value, suppressed status, units of measurement, magnitude, subject and group. Using this dataset can provide you with insightful information that can help you improve your business operations and make better decisions.

For example, you could use the data values to identify patterns and trends in sales over time. You could also use the period data to determine whether certain months have more sales than others. Finally, you could utilize the suppressed status to understand which transactions should or should not be included when making conclusions from your dataset.

In order to use this dataset effectively it would be helpful for you to be familiar with database software such as Microsoft Access or SQLite database manager which is free and open source software for managing a variety of databases. Once familiar with database software of your choice it is important to understand how different fields interact together in order create meaningful results from queries such as finding out what kind of expenditure is done during different times of year or discovering what kind of products contribute most revenue during certain periods etc..
It is also sensible for one become knowledgeable in some basic coding languages like Python - that have modules designed specifically for statistical analysis - so they are well equipped when it comes down crunching these kinds complex datasets into tangible insights!

Research Ideas

Visualizing changes in spending habits of consumers over time by analyzing the Data_value, UNITS and Magnitude columns.

Analyzing the correlation between areas with higher spending volumes and socioeconomic factors such as income level or population density by leveraging Subject and Group details.

Predicting future trends in electronic card transactions through machine learning algorithms that use historical data from the dataset to make predictions on changing patterns of consumer spending behaviors over time based on all columns in the dataset eg Series_title_1, STATUS etc.

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: electronic-card-transactions-feb-2018-csv-tables.csv

Column name	Description
Series_reference	Unique identifier for each series. (String)
Period	Date of the transaction. (Date)
Data_value	Value of the transaction. (Integer)
Suppressed	Boolean value indicating whether the data has been suppressed or not. (Boolean)
STATUS	Status of the transaction. (String)
UNITS	Units of the transaction. (String)
Magnitude	Magnitude of the transaction. (Integer)
Subject	Subject of the transaction. (String)
Group	Group of the transaction. (String)
Series_title_1	Title of the series. (String)
Series_title_2	Title of the series. (String)
Series_title_3	Title of the series. (String)
Series_title_4	Title of the series. (String)
Series_title_5	Title of the series. (String)

File: august-2019-ect-tables-69.csv

File: september-2018-ect-tables-3.csv

File: may-2019-ect-tables-28.csv

File: june-2018-ect-tables-16.csv

File: june-2019-ect-tables-14.csv

File: july-2019-ect-tables-17.csv

File: january-2019-ect-tables-45.csv

File: february-2018-ect-tables-7.csv

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit data.govt.nz.

Tables

April 2018 Ect Tables 6

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.april_2018_ect_tables_6

7.64 KB
21 rows
10 columns


CREATE TABLE april_2018_ect_tables_6 (
  "index" BIGINT,
  "electronic_card_transactions_april_2018" VARCHAR,
  "unnamed_1" VARCHAR,
  "unnamed_2" VARCHAR,
  "unnamed_3" VARCHAR,
  "unnamed_4" VARCHAR,
  "unnamed_5" VARCHAR,
  "unnamed_6" VARCHAR,
  "unnamed_7" VARCHAR,
  "unnamed_8" VARCHAR
);

April 2019 Ect Tables 15

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.april_2019_ect_tables_15

7.61 KB
22 rows
10 columns


CREATE TABLE april_2019_ect_tables_15 (
  "index" BIGINT,
  "electronic_card_transactions_april_2019" VARCHAR,
  "unnamed_1" VARCHAR,
  "unnamed_2" VARCHAR,
  "unnamed_3" VARCHAR,
  "unnamed_4" VARCHAR,
  "unnamed_5" VARCHAR,
  "unnamed_6" VARCHAR,
  "unnamed_7" VARCHAR,
  "unnamed_8" VARCHAR
);

April 2020 Ect Tables 67

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.april_2020_ect_tables_67

7.61 KB
22 rows
10 columns


CREATE TABLE april_2020_ect_tables_67 (
  "index" BIGINT,
  "electronic_card_transactions_april_2020" VARCHAR,
  "unnamed_1" VARCHAR,
  "unnamed_2" VARCHAR,
  "unnamed_3" VARCHAR,
  "unnamed_4" VARCHAR,
  "unnamed_5" VARCHAR,
  "unnamed_6" VARCHAR,
  "unnamed_7" VARCHAR,
  "unnamed_8" VARCHAR
);

August 2018 Ect Tables 70

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.august_2018_ect_tables_70

7.63 KB
22 rows
10 columns


CREATE TABLE august_2018_ect_tables_70 (
  "index" BIGINT,
  "electronic_card_transactions_august_2018" VARCHAR,
  "unnamed_1" VARCHAR,
  "unnamed_2" VARCHAR,
  "unnamed_3" VARCHAR,
  "unnamed_4" VARCHAR,
  "unnamed_5" VARCHAR,
  "unnamed_6" VARCHAR,
  "unnamed_7" VARCHAR,
  "unnamed_8" VARCHAR
);

August 2019 Ect Tables 69

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.august_2019_ect_tables_69

7.63 KB
22 rows
10 columns


CREATE TABLE august_2019_ect_tables_69 (
  "index" BIGINT,
  "electronic_card_transactions_august_2019" VARCHAR,
  "unnamed_1" VARCHAR,
  "unnamed_2" VARCHAR,
  "unnamed_3" VARCHAR,
  "unnamed_4" VARCHAR,
  "unnamed_5" VARCHAR,
  "unnamed_6" VARCHAR,
  "unnamed_7" VARCHAR,
  "unnamed_8" VARCHAR
);

December 2017 Ect Tables 8

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.december_2017_ect_tables_8

7.74 KB
25 rows
10 columns


CREATE TABLE december_2017_ect_tables_8 (
  "index" BIGINT,
  "electronic_card_transactions_december_2017" VARCHAR,
  "unnamed_1" VARCHAR,
  "unnamed_2" VARCHAR,
  "unnamed_3" VARCHAR,
  "unnamed_4" VARCHAR,
  "unnamed_5" VARCHAR,
  "unnamed_6" VARCHAR,
  "unnamed_7" VARCHAR,
  "unnamed_8" VARCHAR
);

December 2018 Ect Tables 35

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.december_2018_ect_tables_35

7.73 KB
25 rows
10 columns


CREATE TABLE december_2018_ect_tables_35 (
  "index" BIGINT,
  "electronic_card_transactions_december_2018" VARCHAR,
  "unnamed_1" VARCHAR,
  "unnamed_2" VARCHAR,
  "unnamed_3" VARCHAR,
  "unnamed_4" VARCHAR,
  "unnamed_5" VARCHAR,
  "unnamed_6" VARCHAR,
  "unnamed_7" VARCHAR,
  "unnamed_8" VARCHAR
);

December 2019 Ect Tables 34

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.december_2019_ect_tables_34

7.74 KB
25 rows
10 columns


CREATE TABLE december_2019_ect_tables_34 (
  "index" BIGINT,
  "electronic_card_transactions_december_2019" VARCHAR,
  "unnamed_1" VARCHAR,
  "unnamed_2" VARCHAR,
  "unnamed_3" VARCHAR,
  "unnamed_4" VARCHAR,
  "unnamed_5" VARCHAR,
  "unnamed_6" VARCHAR,
  "unnamed_7" VARCHAR,
  "unnamed_8" VARCHAR
);

Ect Apr2019 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.ect_apr2019_tables

181.68 KB
15969 rows
15 columns


CREATE TABLE ect_apr2019_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Ect Apr2020 Lower Level Data Release

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.ect_apr2020_lower_level_data_release

47.42 KB
3792 rows
15 columns


CREATE TABLE ect_apr2020_lower_level_data_release (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" VARCHAR,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Ect Aug2018 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.ect_aug2018_tables

175.11 KB
15357 rows
15 columns


CREATE TABLE ect_aug2018_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Ect Feb2019 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.ect_feb2019_tables

179.72 KB
15789 rows
15 columns


CREATE TABLE ect_feb2019_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Ect Jan2019 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.ect_jan2019_tables

179.23 KB
15732 rows
15 columns


CREATE TABLE ect_jan2019_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Ect Jul 2020 Lower Level Data Release

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.ect_jul_2020_lower_level_data_release

57.94 KB
4811 rows
15 columns


CREATE TABLE ect_jul_2020_lower_level_data_release (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Ect Mar2019 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.ect_mar2019_tables

181.17 KB
15916 rows
15 columns


CREATE TABLE ect_mar2019_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Ect May 2020 Lower Level Data Release

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.ect_may_2020_lower_level_data_release

47.76 KB
3816 rows
15 columns


CREATE TABLE ect_may_2020_lower_level_data_release (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" VARCHAR,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Ect Sep2017 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.ect_sep2017_tables

166.73 KB
14574 rows
15 columns


CREATE TABLE ect_sep2017_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Electronic Card Transaction May 2019 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.electronic_card_transaction_may_2019_tables

182.15 KB
16030 rows
15 columns


CREATE TABLE electronic_card_transaction_may_2019_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Electronic Card Transaction Nov 2018 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.electronic_card_transaction_nov_2018_tables

177.37 KB
15573 rows
15 columns


CREATE TABLE electronic_card_transaction_nov_2018_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Electronic Card Transaction Oct 2018 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.electronic_card_transaction_oct_2018_tables

176.73 KB
15516 rows
15 columns


CREATE TABLE electronic_card_transaction_oct_2018_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Electronic Card Transactions Apr 2018 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.electronic_card_transactions_apr_2018_tables

172.18 KB
15080 rows
15 columns


CREATE TABLE electronic_card_transactions_apr_2018_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Electronic Card Transactions April 2020 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.electronic_card_transactions_april_2020_tables

193.39 KB
16858 rows
15 columns


CREATE TABLE electronic_card_transactions_april_2020_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Electronic Card Transactions Aug2019 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.electronic_card_transactions_aug2019_tables

184.42 KB
16246 rows
15 columns


CREATE TABLE electronic_card_transactions_aug2019_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Electronic Card Transactions Dec 2017 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.electronic_card_transactions_dec_2017_tables

169.21 KB
14790 rows
15 columns


CREATE TABLE electronic_card_transactions_dec_2017_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);

Electronic Card Transactions Dec 2018 Tables

@kaggle.thedevastator_uncovering_insights_from_electronic_card_transac.electronic_card_transactions_dec_2018_tables

178.66 KB
15679 rows
15 columns


CREATE TABLE electronic_card_transactions_dec_2018_tables (
  "index" BIGINT,
  "series_reference" VARCHAR,
  "period" DOUBLE,
  "data_value" DOUBLE,
  "suppressed" VARCHAR,
  "status" VARCHAR,
  "units" VARCHAR,
  "magnitude" BIGINT,
  "subject" VARCHAR,
  "group" VARCHAR,
  "series_title_1" VARCHAR,
  "series_title_2" VARCHAR,
  "series_title_3" VARCHAR,
  "series_title_4" VARCHAR,
  "series_title_5" VARCHAR
);