### Install pdp CLI Tool

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/README.md

Installs the `pdp` command-line interface tool for managing Paradigm Data Portal datasets. This tool allows users to list, download, and manage various crypto datasets.

```bash
pip install paradigm-data-portal
```

--------------------------------

### Get Help for pdp download command

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/datasets/ethereum_native_transfers/README.md

This command displays the help message for the 'pdp download' command, providing information on available options and usage for downloading datasets.

```bash
pdp download -h
```

--------------------------------

### pdp CLI Tool Usage Examples

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/README.md

Demonstrates common commands for the `pdp` CLI tool, including listing datasets, listing files within a dataset, and downloading a dataset. Detailed help for each command is available using the `-h` flag.

```bash
pdp ls
pdp ls <dataset_name>
pdp download <dataset_name>
pdp <command> -h
```

--------------------------------

### Download Ethereum Slots using pdp CLI

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/datasets/ethereum_slots/README.md

This command downloads the entire Ethereum Slots dataset using the 'pdp' command-line interface tool. Ensure the 'pdp' tool is installed and configured.

```bash
pdp download ethereum_slots
```

--------------------------------

### Contract Deployment Information (DAI Example)

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Retrieves deployment details for a specific contract address (DAI in this example). It converts the address to binary, filters the data, and then converts binary columns back to hex format.

```python
DAI = '0x6b175474e89094c44da98b954eedeac495271d0f'
```

```python
binary_address = ctc.binary_convert(DAI, 'binary')

result = (
    pl.scan_parquet(data_path)
    .filter(pl.col('contract_address') == binary_address)
    .collect(streaming=True)
)
pl_utils.binary_columns_to_prefix_hex(result)
```

--------------------------------

### Download Ethereum Contracts using pdp CLI

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/datasets/ethereum_contracts/README.md

This snippet demonstrates how to download the entire Ethereum Contracts dataset using the `pdp` command-line interface tool. It assumes the `pdp` tool is installed and configured.

```bash
pdp download ethereum_contracts

# For more options, see:
pdp download -h
```

--------------------------------

### Get Unique Column Count

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

A utility function to calculate the number of unique values in a specified column of the scanned Parquet data. It uses Polars for efficient, streaming data processing.

```python
def get_unique_column_count(column):
    result = pl.scan_parquet(data_path).select(
        pl.col(column).n_unique(),
    ).collect(streaming=True)
    return result[column][0]
```

--------------------------------

### Get Top N Entities by Count

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

A function to retrieve the top N most frequent entities (like deployers, factories, etc.) from a specified column. It counts value occurrences, sorts them, and returns the top N.

```python
def get_top_n(column, n):
    col = '0x' + (pl.col(column).struct.field(column).bin.encode('hex'))
    return (
        pl.scan_parquet(data_path)
        .select(pl.col(column).value_counts())
        .select([col.alias(column), pl.col(column).struct.field('counts')])
        .sort('counts', descending=True)
        .head(n)
        .collect(streaming=True)
    )
```

--------------------------------

### Set Up Environment and Data Path

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Configures the display width for Polars columns and sets the data path for the Ethereum contracts Parquet files, expanding the user directory.

```python
# set up env

pl_utils.set_column_display_width()

data_path = '~/pdp/ethereum_contracts/ethereum_contracts__v1_0_0__*.parquet'
data_path = os.path.expanduser(data_path)
```

--------------------------------

### Dataset Versioning Explained

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/README.md

Details the versioning scheme for datasets in the Paradigm Data Portal, following a `<major>.<minor>.<patch>` format. Explains how schema changes, data modifications, and new block additions impact version increments.

```APIDOC
Dataset Versioning:
  Format: <major>.<minor>.<patch>
  - Major version increase: Schema updates.
  - Minor version increase: Rows added, removed, or modified.
  - Patch version increase: Rows added due to new blocks.

Example: 1.2.8
```

--------------------------------

### Download Ethereum Native Transfers using pdp CLI

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/datasets/ethereum_native_transfers/README.md

This command downloads the entire Ethereum Native Transfers dataset using the 'pdp' command-line interface tool. It's a convenient way to acquire the full dataset for analysis.

```bash
pdp download ethereum_native_transfers
```

--------------------------------

### Ethereum Contracts Dataset Schema

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/datasets/ethereum_contracts/README.md

This documentation outlines the schema for the `contracts` table in the Ethereum Contracts Dataset. Each row represents a contract creation trace with details like block number, transaction hash, contract address, deployer, and bytecode.

```APIDOC
contracts table:
  Each row corresponds to a contract create trace.

  Columns:
    block_number (INTEGER): Block number when contract was created.
    create_index (INTEGER): Increased by 1 for each contract created in block.
    transaction_hash (BINARY): Hash of transaction that created contract.
    contract_address (BINARY): Address of deployed contract.
    deployer (BINARY): EOA that deployed the contract.
    factory (BINARY): The `from` field in the creation trace.
    init_code (BINARY): Initialization bytecode of contract.
    code (BINARY): Bytecode of contract.
    init_code_hash (BINARY): Keccak hash of contract initialization code.
    code_hash (BINARY): Keccak hash of contract bytecode.
```

--------------------------------

### Download Ethereum Slots Dataset via URLs

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/datasets/ethereum_slots/README.md

Provides direct URLs to download individual parquet files that constitute the Ethereum Slots Dataset. The dataset is split into multiple files based on contract address ranges.

```url
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0x00_to_0x0f.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0x10_to_0x1f.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0x20_to_0x2f.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0x30_to_0x3f.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0x40_to_0x4f.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0x50_to_0x5f.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0x60_to_0x6f.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0x70_to_0x7f.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0x80_to_0x8f.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0x90_to_0x9f.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0xa0_to_0xaf.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0xb0_to_0xbf.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0xc0_to_0xcf.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0xd0_to_0xdf.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0xe0_to_0xef.parquet
https://datasets.paradigm.xyz/datasets/ethereum_slots/ethereum_slots__v1.0.0__0xf0_to_0xff.parquet
```

--------------------------------

### Calculate Percentage of Contracts by Top 10 Deployers

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Calculates and prints the percentage of all Ethereum contracts deployed by the top 10 EOAs.

```python
top_10_deployer_percent = toolstr.format(
    top_10_deployers['counts'].sum() / n_deployments,
    percentage=True,
    decimals=1,
)

print('The top 10 deployers have deployed', top_10_deployer_percent, 'of all contracts on Ethereum')
```

--------------------------------

### Import Libraries for Ethereum Contracts Analysis

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Imports necessary libraries including math, os, shutil, subprocess, ctc, polars, matplotlib, toolplot, numpy, and toolstr for data manipulation, plotting, and utility functions.

```python
import math
import os
import shutil
import subprocess

import ctc
import ctc.rpc
from ctc.toolbox import pl_utils
import polars as pl
import matplotlib.pyplot as plt
import toolplot
import numpy as np
import toolstr
```

--------------------------------

### Calculate Percentage of Contracts by Top 10 Factories

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Calculates and displays the percentage of all Ethereum contracts deployed by the top 10 factories.

```python
top_10_factory_percent = toolstr.format(
    top_10_factories['counts'].sum() / n_deployments,
    percentage=True,
    decimals=1,
)

print('The top 10 factories have deployed', top_10_factory_percent, 'of all contracts on Ethereum')
```

--------------------------------

### Python Script for Collecting Ethereum Slots

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/datasets/ethereum_slots/README.md

This snippet references a Python script used for collecting Ethereum slot data. The script is hosted on GitHub and is the source for generating the dataset.

```python
https://github.com/paradigmxyz/paradigm-data-portal/blob/main/pdp/datasets/slots/slots_collect.py
```

--------------------------------

### Count Total Contract Deployments

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Calculates the total number of contract deployments by counting the entries in the 'create_index' column of the dataset.

```python
result = pl.scan_parquet(data_path).select(pl.col('create_index').count()).collect()
n_deployments = result['create_index'][0]

n_deployments
```

--------------------------------

### Identify Top 10 Common Bytecodes

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Finds the 10 most common contract bytecodes (identified by `code_hash`) using the `get_top_n` function.

```python
top_10_bytecodes = get_top_n("code_hash", 10)

top_10_bytecodes
```

--------------------------------

### Download Ethereum Native Transfers Data (Parquet)

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/datasets/ethereum_native_transfers/README.md

Provides direct download links for Parquet files containing Ethereum native transfer data. The data is segmented into files based on block ranges, allowing for efficient downloading of specific data subsets. Each link points to a .parquet file.

```parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__00000000_to_00199999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__00200000_to_00399999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__00400000_to_00599999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__00600000_to_00799999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__00800000_to_00999999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__01000000_to_01199999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__01200000_to_01399999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__01400000_to_01599999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__01600000_to_01799999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__01800000_to_01999999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__02000000_to_02199999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__02200000_to_02399999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__02400000_to_02599999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__02600000_to_02799999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__02800000_to_02999999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__03000000_to_03199999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__03200000_to_03399999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__03400000_to_03599999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__03600000_to_03799999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__03800000_to_03999999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__04000000_to_04199999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__04200000_to_04399999.parquet
https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__04400000_to_04599999.parquet
```

--------------------------------

### Calculate Percentage of Contracts by Top 10 Bytecodes

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Calculates and presents the percentage of all Ethereum contracts that utilize the top 10 most common bytecodes.

```python
top_10_bytecode_percent = toolstr.format(
    top_10_bytecodes['counts'].sum() / n_deployments,
    percentage=True,
    decimals=1,
)

print('The top 10 bytecodes represent', top_10_bytecode_percent, 'of all contracts on Ethereum')
```

--------------------------------

### Calculate Percentage of Re-deployed Addresses

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Calculates and prints the percentage of contract addresses that have been deployed more than once, using the previously computed counts.

```python
more_than_once_percent = toolstr.format(
    n_deployed_more_than_once / n_unique_contract_addresses,
    percentage=True,
    decimals=2,
)
print(more_than_once_percent, 'of contract addresses have been deployed more than once')
```

--------------------------------

### Download Ethereum Contracts Data (v1.0.0)

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/datasets/ethereum_contracts/README.md

Provides direct URLs to download Parquet files containing Ethereum contract data. The data is versioned as v1.0.0 and segmented into files based on block number ranges, from 00000000 to 16799999. These files are useful for large-scale data analysis and historical blockchain research.

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__00000000_to_00999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__01000000_to_01999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__02000000_to_02999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__03000000_to_03999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__04000000_to_04999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__05000000_to_05999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__06000000_to_06999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__07000000_to_07999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__08000000_to_08999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__09000000_to_09999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__10000000_to_10999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__11000000_to_11999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__12000000_to_12999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__13000000_to_13999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__14000000_to_14999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__15000000_to_15999999.parquet
```

```URL
https://datasets.paradigm.xyz/datasets/ethereum_contracts/ethereum_contracts__v1_0_0__16000000_to_16799999.parquet
```

--------------------------------

### Ethereum Native Transfers Data Files

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/datasets/ethereum_native_transfers/README.md

This section lists the available Parquet files containing Ethereum native transfer data. Each file represents a specific range of block numbers and is provided for download. The data is partitioned to manage large datasets efficiently.

```parquet
ethereum_native_transfers__v1_0_0__09200000_to_09399999.parquet
ethereum_native_transfers__v1_0_0__09400000_to_09599999.parquet	hereum_native_transfers__v1_0_0__09600000_to_09799999.parquet
ethereum_native_transfers__v1_0_0__09800000_to_09999999.parquet
ethereum_native_transfers__v1_0_0__10000000_to_10199999.parquet
ethereum_native_transfers__v1_0_0__10200000_to_10399999.parquet
ethereum_native_transfers__v1_0_0__10400000_to_10599999.parquet
ethereum_native_transfers__v1_0_0__10600000_to_10799999.parquet
ethereum_native_transfers__v1_0_0__10800000_to_10999999.parquet
ethereum_native_transfers__v1_0_0__11000000_to_11199999.parquet
ethereum_native_transfers__v1_0_0__11200000_to_11399999.parquet
ethereum_native_transfers__v1_0_0__11400000_to_11599999.parquet
ethereum_native_transfers__v1_0_0__11600000_to_11799999.parquet
ethereum_native_transfers__v1_0_0__11800000_to_11999999.parquet
ethereum_native_transfers__v1_0_0__12000000_to_12199999.parquet
ethereum_native_transfers__v1_0_0__12200000_to_12399999.parquet
ethereum_native_transfers__v1_0_0__12400000_to_12599999.parquet
ethereum_native_transfers__v1_0_0__12600000_to_12799999.parquet
ethereum_native_transfers__v1_0_0__12800000_to_12999999.parquet
ethereum_native_transfers__v1_0_0__13000000_to_13199999.parquet
ethereum_native_transfers__v1_0_0__13200000_to_13399999.parquet
ethereum_native_transfers__v1_0_0__13400000_to_13599999.parquet
ethereum_native_transfers__v1_0_0__13600000_to_13799999.parquet
```

--------------------------------

### Identify Top 10 Deployers

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Uses the `get_top_n` function to find the 10 Externally Owned Accounts (EOAs) that have deployed the most contracts.

```python
top_10_deployers = get_top_n('deployer', 10)

top_10_deployers
```

--------------------------------

### Ethereum Native Transfers v1.0.0 Parquet Files

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/datasets/ethereum_native_transfers/README.md

This section details the available Parquet files for Ethereum native transfers, version 1.0.0. Each file represents a contiguous range of Ethereum block numbers and is provided for download. The data is partitioned into segments of approximately 200,000 blocks each.

```parquet
ethereum_native_transfers__v1_0_0__04600000_to_04799999.parquet
ethereum_native_transfers__v1_0_0__04800000_to_04999999.parquet ethereum_native_transfers__v1_0_0__05000000_to_05199999.parquet ethereum_native_transfers__v1_0_0__05200000_to_05399999.parquet ethereum_native_transfers__v1_0_0__05400000_to_05599999.parquet ethereum_native_transfers__v1_0_0__05600000_to_05799999.parquet ethereum_native_transfers__v1_0_0__05800000_to_05999999.parquet ethereum_native_transfers__v1_0_0__06000000_to_06199999.parquet ethereum_native_transfers__v1_0_0__06200000_to_06399999.parquet ethereum_native_transfers__v1_0_0__06400000_to_06599999.parquet ethereum_native_transfers__v1_0_0__06600000_to_06799999.parquet ethereum_native_transfers__v1_0_0__06800000_to_06999999.parquet ethereum_native_transfers__v1_0_0__07000000_to_07199999.parquet ethereum_native_transfers__v1_0_0__07200000_to_07399999.parquet ethereum_native_transfers__v1_0_0__07400000_to_07599999.parquet ethereum_native_transfers__v1_0_0__07600000_to_07799999.parquet ethereum_native_transfers__v1_0_0__07800000_to_07999999.parquetethereum_native_transfers__v1_0_0__08000000_to_08199999.parquetethereum_native_transfers__v1_0_0__08200000_to_08399999.parquetethereum_native_transfers__v1_0_0__08400000_to_08599999.parquetethereum_native_transfers__v1_0_0__08600000_to_08799999.parquetethereum_native_transfers__v1_0_0__08800000_to_08999999.parquetethereum_native_transfers__v1_0_0__09000000_to_09199999.parquet
```

--------------------------------

### Find Uniswap V2 Pools by Code Hash

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Identifies deployed Uniswap V2 pools by fetching the bytecode of a known pool, calculating its code hash, and then filtering the dataset for contracts with the same code hash. It returns results with binary columns converted to hex.

```python
example_pool = '0xb4e16d0168e52d35cacd2c6185b44281ec28c9dc'
```

```python
example_bytecode = await ctc.rpc.async_eth_get_code(example_pool)
example_code_hash = ctc.keccak(example_bytecode, output_format='binary')

result = (
    pl.scan_parquet(data_path)
    .filter(pl.col('code_hash') == example_code_hash)
    .collect(streaming=True)
)
pl_utils.binary_columns_to_prefix_hex(result)
```

--------------------------------

### Count Unique Factories Used

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Calculates the number of unique factories used for contract creation by querying the 'factory' column.

```python
get_unique_column_count('factory')
```

--------------------------------

### Identify Top 10 Factories

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Identifies the 10 factories responsible for the highest number of contract deployments using the `get_top_n` function.

```python
top_10_factories = get_top_n('factory', 10)

top_10_factories
```

--------------------------------

### Count Unique Contract Bytecodes

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Determines the number of unique contract bytecodes deployed by analyzing the 'code_hash' column.

```python
get_unique_column_count('code_hash')
```

--------------------------------

### Ethereum Native Transfers Data Files

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/datasets/ethereum_native_transfers/README.md

This section lists the available Parquet files for Ethereum native transfers. Each file corresponds to a specific range of Ethereum block numbers and is provided in Parquet format. These files are essential for accessing and analyzing historical Ethereum transaction data.

```parquet
[ethereum_native_transfers__v1_0_0__13800000_to_13999999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__13800000_to_13999999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__14000000_to_14199999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__14000000_to_14199999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__14200000_to_14399999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__14200000_to_14399999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__14400000_to_14599999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__14400000_to_14599999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__14600000_to_14799999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__14600000_to_14799999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__14800000_to_14999999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__14800000_to_14999999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__15000000_to_15199999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__15000000_to_15199999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__15200000_to_15399999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__15200000_to_15399999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__15400000_to_15599999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__15400000_to_15599999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__15600000_to_15799999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__15600000_to_15799999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__15800000_to_15999999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__15800000_to_15999999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__16000000_to_16199999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__16000000_to_16199999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__16200000_to_16399999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__16200000_to_16399999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__16400000_to_16599999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__16400000_to_16599999.parquet)
```

```parquet
[ethereum_native_transfers__v1_0_0__16600000_to_16799999.parquet](https://datasets.paradigm.xyz/datasets/ethereum_native_transfers/ethereum_native_transfers__v1_0_0__16600000_to_16799999.parquet)
```

--------------------------------

### Identify Most Frequently Deployed Contract Addresses

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Identifies the top 10 contract addresses that have been deployed the most number of times, using the `get_top_n` function.

```python
top_10_contract_addresses = get_top_n('contract_address', 10)

top_10_contract_addresses
```

--------------------------------

### Count EOAs Deploying Contracts

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Counts the number of unique Externally Owned Accounts (EOAs) that have deployed contracts, using the 'deployer' column.

```python
get_unique_column_count('deployer')
```

--------------------------------

### Count Contract Addresses Deployed More Than Once

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Identifies and counts the number of contract addresses that have been deployed multiple times. It groups by 'contract_address', counts occurrences, and filters for counts greater than 1.

```python
n_deployed_more_than_once = (
    pl.scan_parquet(data_path)
    .groupby(pl.col("contract_address"))
    .agg(pl.count())
    .filter(pl.col('count') > 1)
    .select(pl.count())
    .collect(streaming=True)
).rows()[0][0]

n_deployed_more_than_once
```

--------------------------------

### Ethereum Slots Dataset Schema

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/datasets/ethereum_slots/README.md

Defines the schema for the 'slots' table in the Ethereum Slots Dataset. Each row represents a slot of a contract, detailing its address, last known value, and update history.

```parquet
contract_address | BINARY | contract of slot
slot | BINARY | address of slot
value | BINARY | last data stored in slot
first_updated_block | INTEGER | first block where slot was used
last_updated_block | INTEGER | last block where slot was updated
n_tx_updates | INTEGER | number of transactions that updated slot
```

--------------------------------

### Count Unique Contract Addresses

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Determines the number of unique contract addresses deployed by using the `get_unique_column_count` function on the 'contract_address' column.

```python
n_unique_contract_addresses = get_unique_column_count('contract_address')

n_unique_contract_addresses
```

--------------------------------

### Top 10 Transactions by Deployed Contracts

Source: https://github.com/paradigmxyz/paradigm-data-portal/blob/main/notebooks/explore_ethereum_contracts.ipynb

Retrieves the top 10 transactions that deployed the most contracts. This function likely queries a data source for transaction information and ranks them.

```python
top_10_transactions = get_top_n('transaction_hash', 10)

top_10_transactions
```