> ## Documentation Index
> Fetch the complete documentation index at: https://docs.nekt.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Rename columns

> Standardize column names across sources — apply snake_case, remove prefixes, or align naming conventions.

## When to use this

Different data sources follow different naming conventions. A CRM might return `ContactFirstName`, an advertising platform might use `campaign-id`, and a database export might use `TOTAL AMT`. Before joining or analyzing data from multiple sources, renaming columns to a consistent convention (typically `snake_case`) makes everything easier to work with downstream.

***

## Sample input

A `hubspot_contacts` table in the **Raw** layer with mixed naming conventions:

| ContactId | FirstName | LastName | emailAddress                                  | Phone Number |
| --------- | --------- | -------- | --------------------------------------------- | ------------ |
| 101       | Alice     | Johnson  | [alice@acme.com](mailto:alice@acme.com)       | +1-555-0101  |
| 102       | Bob       | Smith    | [bob@globex.com](mailto:bob@globex.com)       | +1-555-0102  |
| 103       | Carol     | Lee      | [carol@initech.com](mailto:carol@initech.com) | +1-555-0103  |

We want to rename all columns to `snake_case`:

***

## Implementation

<Tabs>
  <Tab title="Nekt Express / BigQuery">
    BigQuery also uses column aliases. Use backticks for columns with spaces or special characters.

    ```sql theme={null}
    SELECT
      ContactId      AS contact_id,
      FirstName      AS first_name,
      LastName       AS last_name,
      emailAddress   AS email_address,
      `Phone Number` AS phone_number
    FROM `raw.hubspot_contacts`
    ```

    <Tip>
      BigQuery is case-insensitive for column names by default, but using explicit aliases ensures consistent naming for BI tools and downstream consumers.
    </Tip>
  </Tab>

  <Tab title="Athena SQL">
    In Athena, use column aliases in a `SELECT` statement to rename each column explicitly.

    ```sql theme={null}
    SELECT
      "ContactId"      AS contact_id,
      "FirstName"      AS first_name,
      "LastName"       AS last_name,
      "emailAddress"   AS email_address,
      "Phone Number"   AS phone_number
    FROM raw.hubspot_contacts
    ```

    <Tip>
      Athena requires double quotes around column names that contain spaces, special characters, or are case-sensitive. Once aliased, downstream queries can use the clean `snake_case` names.
    </Tip>
  </Tab>

  <Tab title="Python (Nekt SDK)">
    In PySpark, use `withColumnRenamed` for individual columns or `toDF` to rename all columns at once.

    ```python theme={null}
    import nekt

    df = nekt.load_table(layer_name="Raw", table_name="hubspot_contacts")

    renamed_df = (
        df
        .withColumnRenamed("ContactId", "contact_id")
        .withColumnRenamed("FirstName", "first_name")
        .withColumnRenamed("LastName", "last_name")
        .withColumnRenamed("emailAddress", "email_address")
        .withColumnRenamed("Phone Number", "phone_number")
    )

    nekt.save_table(
        df=renamed_df,
        layer_name="Trusted",
        table_name="hubspot_contacts_clean"
    )
    ```

    <Tip>
      For bulk renaming to `snake_case`, you can automate it with a helper that converts all column names at once:

      ```python theme={null}
      import re

      def to_snake_case(name):
          s = re.sub(r'([A-Z])', r'_\1', name).lower()
          s = re.sub(r'[\s\-]+', '_', s)
          return re.sub(r'_+', '_', s).strip('_')

      renamed_df = df.toDF(*[to_snake_case(c) for c in df.columns])
      ```
    </Tip>
  </Tab>
</Tabs>

***

## Expected output

| contact\_id | first\_name | last\_name | email\_address                                | phone\_number |
| ----------- | ----------- | ---------- | --------------------------------------------- | ------------- |
| 101         | Alice       | Johnson    | [alice@acme.com](mailto:alice@acme.com)       | +1-555-0101   |
| 102         | Bob         | Smith      | [bob@globex.com](mailto:bob@globex.com)       | +1-555-0102   |
| 103         | Carol       | Lee        | [carol@initech.com](mailto:carol@initech.com) | +1-555-0103   |

***

## Tips and gotchas

<Note>
  Renaming columns doesn't change the underlying data — it only affects how the column is referenced in the output. Always save the renamed table to a new layer (e.g., **Trusted**) so the raw data remains untouched.
</Note>

<Warning>
  Some BI tools are case-sensitive when referencing column names. Sticking to `snake_case` with all lowercase avoids surprises when connecting Looker Studio, Power BI, or Metabase to your data.
</Warning>