First, ensure you have Python installed on your machine. You will also need to install the `requests` library to interact with the CoinGecko API and `duckdb` to work with DuckDB. You can install these using pip:
```bash
pip install requests duckdb
```

Use Python's `requests` library to fetch data from CoinGecko's API. For example, to get the list of coins:
```python
import requests

response = requests.get('https://api.coingecko.com/api/v3/coins/list')
coins = response.json()
```

Once you have the raw data, parse it into a format suitable for DuckDB. Typically, this involves transforming the JSON data into a tabular format like a list of dictionaries or a Pandas DataFrame.
```python
import pandas as pd

df_coins = pd.DataFrame(coins)
```

Ensure DuckDB is installed and create a new database file or connect to an existing one. DuckDB can work in-memory or on-disk. Here, we demonstrate using an on-disk database:
```python
import duckdb

conn = duckdb.connect('coingecko_data.duckdb')
```

Define a table structure in DuckDB that matches the data format you are importing. You can do this using SQL commands through DuckDB's Python API:
```python
conn.execute('''
CREATE TABLE IF NOT EXISTS coins (
id VARCHAR,
symbol VARCHAR,
name VARCHAR
)
''')
```

Insert the structured data into your DuckDB table. If you are using Pandas, DuckDB can directly import DataFrames:
```python
conn.execute('INSERT INTO coins SELECT * FROM df_coins')
```

After insertion, verify that your data has been correctly imported. You can perform a simple query to check the number of records or some sample data:
```python
result = conn.execute('SELECT COUNT(*) FROM coins').fetchall()
print(f"Number of records in table: {result[0][0]}")
```

By following these steps, you can move data from CoinGecko to DuckDB without relying on third-party connectors, using only Python and direct API interactions.