Add time-series data
- About the dataset
  - note
Table details
Ingest the dataset
- Ingesting the dataset
  - note
Next steps

Add time-series data

To explore TimescaleDB’s features, you need some sample data. This tutorial provides real-time stock trade data, also known as tick data, from Twelve Data.

About the dataset

The dataset contains second-by-second stock-trade data for the top 100 most-traded symbols, in a hypertable named stocks_real_time. It also includes a separate table of company symbols and company names, in a regular PostgreSQL table named company.

The dataset is updated on a nightly basis and contains data from the last four weeks, typically ~8 million rows of data. Stock trades are recorded in real-time Monday through Friday, typically during normal trading hours of the New York Stock Exchange (9:30 AM - 4:00 PM EST).

note

In case you want to ingest real-time data, instead of sample data, read the tutorial Ingest real-time financial websocket data and ingest data directly from the Twelve Data financial API.

Table details

stocks_real_time: contains stock data. Includes stock price quotes at every second during trading hours.

Field	Type	Description
time	timestamptz	Timestamp column incrementing second by second
symbol	text	Symbols representing a company, mapped to company names in the `company` table
price	double precision	Stock quote price for a company at the given timestamp
day_volume	int	Number of shares traded each day, NULL values indicate the market is closed

company: contains a mapping for symbols to company names.

Field	Type	Description
symbol	text	the symbol representing a company name
name	text	Corresponding company name

Ingest the dataset

To ingest data into the tables that you created, you need to download the dataset and copy the data to your database.

Ingesting the dataset

Download the real_time_stock_data.zip file. The file contains two .csv files; one with company information, and one with real-time stock trades for the past month. Download:

real_time_stock_data.zip
In a new terminal window, run this command to unzip the .csv files:
```
unzip real_time_stock_data.zip
```
At the psql prompt, use the COPY command to transfer data into your TimescaleDB instance. If the .csv files aren’t in your current directory, specify the file paths in the following commands:
```
\COPY stocks_real_time from './tutorial_sample_tick.csv' DELIMITER ',' CSV HEADER;
\COPY company from './tutorial_sample_company.csv' DELIMITER ',' CSV HEADER;
```
Because there are millions of rows of data, the COPY process may take a few minutes depending on your internet connection and local client resources.

note

If you’re using a Docker container, add the data files to your container before copying them into your database.

To add files to your container:

docker cp tutorial_sample_tick.csv timescaledb:/tutorial_sample_tick.csv docker cp tutorial_sample_company.csv timescaledb:/tutorial_sample_company.csv

Next steps

Now that you have data in your TimescaleDB instance, learn how to query the data.