If you haven't already installed DuckDB, you can do so by downloading the appropriate binary for your system from the DuckDB website or using pip if you're using Python:

```sh

pip install duckdb

```

You can start DuckDB using the command line or within a Python script. Here's how to do it in Python:

```python

import duckdb

‍

# This will create an in-memory database. To persist data, replace `:memory:` with a file path.

con = duckdb.connect(database=':memory:', read_only=False)

```

Before importing the CSV data, you need to create a table in DuckDB with the appropriate schema that matches the CSV file's structure.

```python

# Replace the column names and types with the ones that match your CSV file

con.execute("""

CREATE TABLE my_table (

column1 INTEGER,

column2 VARCHAR,

column3 FLOAT

)

""")

```

Now you can use DuckDB's `COPY` command to import the CSV file into the table you just created.

```python

# Replace 'my_table' with your table name and 'path/to/your/file.csv' with the path to your CSV file

con.execute("""

COPY my_table FROM 'path/to/your/file.csv' WITH (HEADER TRUE, DELIMITER ',');

""")

```

Make sure that the `HEADER` and `DELIMITER` options match the format of your CSV file. If your CSV file has a header row, set `HEADER` to `TRUE`. Adjust the `DELIMITER` option if your CSV uses a different character to separate fields.

After importing the data, you might want to verify that the data has been imported correctly.

```python

# This will fetch the first 10 rows from the table

result = con.execute("SELECT * FROM my_table LIMIT 10").fetchall()

print(result)

```

You can now perform SQL queries on your data in DuckDB.

```python

# Example query: Get the count of rows in the table

row_count = con.execute("SELECT COUNT(*) FROM my_table").fetchone()

print(f"Number of rows in the table: {row_count[0]}")

```

If you created a persistent database (not in-memory), you might want to commit changes and close the connection:

```python

# Commit changes if necessary (DuckDB usually auto-commits)

# con.commit()

‍

# Close the connection when done

con.close()

```

Additional Notes

- If your CSV file is very large, you might want to consider using the `COPY` command within DuckDB's CLI for better performance.

- Ensure that the data types in the `CREATE TABLE` statement match the corresponding fields in the CSV file to prevent data import errors.

- If your CSV contains special characters or different encodings, you may need to specify additional options in the `COPY` command to handle these correctly.

By following these steps, you should be able to move data from a CSV file into DuckDB without any third-party connectors or integrations, using DuckDB's own capabilities to handle CSV files.