TVL for each token by protocol

Description

This dataset provides a daily historical record of TVL (Total Value Locked) for each token within various DeFi protocols, aligned with the protocols mentioned in the previous datasets (TVL & fees per protocol, Top pools APY per protocol and Tokens OHCL price). It is structured in partitions, with each partition representing a different protocol. The columns within each partition are named after the tokens supported by that protocol, and a token is included only if it has historical data dating back to at least August 1, 2022. The dataset includes a date column for the daily data entries and focuses on the TVL of each token within a protocol, as opposed to the aggregate TVL of the entire protocol.

Collection method

The data for this dataset is collected from Defillama, a reputable source for DeFi data. The collection process involves:

Identifying protocols that have significant TVL and historical data presence.
Fetching daily TVL data for each token within these protocols.
Ensuring that tokens with data dating back to at least August 1, 2022, are included.
Organizing the data into partitions by protocol, with columns for each supported token.
Regularly updating the dataset to reflect the latest TVL figures.

This methodical approach ensures that the dataset is comprehensive and provides a granular view of the TVL across different tokens in the DeFi space.

Schema

partitions: Organized by protocol.
one_feature_per_supported_tokens: A different column for each of the tokens supported by the protocol. The column name will be the name of the token. Each row will represent the TVL of that protocol in that token.
date: Column indicating the date of each TVL entry.

The dataset only have date as the primary key.

Potential Use Cases

Detailed TVL Tracking: Examining the TVL distribution among various tokens within a protocol.
Trend Analysis: Identifying trends in token popularity and liquidity within protocols.
Comprehensive Market Analysis: Merging this dataset with earlier datasets for a holistic view of the DeFi ecosystem, spanning from overall protocol performance to individual token dynamics.

Use example

from giza.datasets import DatasetsLoader

# Usage example:
loader = DatasetsLoader()
df = loader.load('tvl-per-project-tokens/project=lido')

df.tail()

date	project	LUNC	MATIC	SOL	WETH	DOT	KSM
2024-01-18	1520883	null	1.0968e8	2.7014e7	2.2930e10	280550.86482	197307.26774
2024-01-19	1534167	null	1.0574e8	2.6493e7	2.3194e10	270533.57734	194061.91561
2024-01-20	1524093	null	1.1005e8	2.6495e7	2.3056e10	274119.44214	198321.44028
2024-01-21	1491960	null	1.1049e8	2.6054e7	2.3124e10	269747.9127	195756.44972
2024-01-22	1440121	null	1.0284e8	2.1498e7	2.1764e10	244719.75585	176726.65926

PreviousTop pools APY per protocol NextAave

Last updated 4 months ago

Description

Collection method

The data for this dataset is collected from Defillama, a reputable source for DeFi data. The collection process involves:

Identifying protocols that have significant TVL and historical data presence.

Fetching daily TVL data for each token within these protocols.

Ensuring that tokens with data dating back to at least August 1, 2022, are included.

Organizing the data into partitions by protocol, with columns for each supported token.

Regularly updating the dataset to reflect the latest TVL figures.

This methodical approach ensures that the dataset is comprehensive and provides a granular view of the TVL across different tokens in the DeFi space.

Schema

partitions: Organized by protocol.

one_feature_per_supported_tokens: A different column for each of the tokens supported by the protocol. The column name will be the name of the token. Each row will represent the TVL of that protocol in that token.

date: Column indicating the date of each TVL entry.

The dataset only have date as the primary key.

Potential Use Cases

Detailed TVL Tracking: Examining the TVL distribution among various tokens within a protocol.

Trend Analysis: Identifying trends in token popularity and liquidity within protocols.

Comprehensive Market Analysis: Merging this dataset with earlier datasets for a holistic view of the DeFi ecosystem, spanning from overall protocol performance to individual token dynamics.

Use example

from giza.datasets import DatasetsLoader

# Usage example:
loader = DatasetsLoader()
df = loader.load('tvl-per-project-tokens/project=lido')

df.tail()

date	project	LUNC	MATIC	SOL	WETH	DOT	KSM
2024-01-18	1520883	null	1.0968e8	2.7014e7	2.2930e10	280550.86482	197307.26774
2024-01-19	1534167	null	1.0574e8	2.6493e7	2.3194e10	270533.57734	194061.91561
2024-01-20	1524093	null	1.1005e8	2.6495e7	2.3056e10	274119.44214	198321.44028
2024-01-21	1491960	null	1.1049e8	2.6054e7	2.3124e10	269747.9127	195756.44972
2024-01-22	1440121	null	1.0284e8	2.1498e7	2.1764e10	244719.75585	176726.65926