@Marvin using the prefect_snowflake collection, how do I retrieve the column names of my query?

I'm sorry, but I couldn't find any specific information on how to retrieve the column names of your query in the Prefect Snowflake collection. However, in general, you can retrieve column names from a query result in Snowflake by using the

SHOW COLUMNS

command or by fetching the metadata of the result set. If you need more specific information, could you please provide more details about your use case?

@Marvin using the prefect_snowflake collection, how do I retrieve the column names of my query? I’d like the results from my query to be in a pandas dataframe and would like the column names to be able to construct the dataframe

I'm sorry, but I couldn't find any specific information on how to retrieve the column names of your query in the Prefect Snowflake collection and construct a pandas dataframe. However, when you execute a query in Snowflake and fetch the results into a pandas dataframe, the column names should be automatically set as the dataframe's column headers. Here's a general example of how you might do this:

import pandas as pd
import snowflake.connector

# Establish a connection to your Snowflake instance
con = snowflake.connector.connect(
    user='USERNAME',
    password='PASSWORD',
    account='ACCOUNT_URL',
    warehouse='WAREHOUSE',
    database='DATABASE',
    schema='SCHEMA'
)

# Execute a query
cur = con.cursor()
cur.execute("SELECT * FROM YOUR_TABLE")

# Fetch the results into a pandas dataframe
df = pd.DataFrame(cur.fetchall())

# Set the dataframe's column headers to the column names from the query
df.columns = [i[0] for i in cur.description]

In this example,

cur.description

is a list of tuples, where each tuple provides metadata about one of the columns in the result set. The first item in each tuple is the column name, so

[i[0] for i in cur.description]

gives you a list of all column names. Please replace 'USERNAME', 'PASSWORD', 'ACCOUNT_URL', 'WAREHOUSE', 'DATABASE', 'SCHEMA', and 'YOUR_TABLE' with your actual Snowflake credentials and the specific table you're querying. If you're using Prefect to orchestrate your workflows, you might be executing your Snowflake queries within a Prefect task. In that case, you would include the code to fetch the results into a pandas dataframe and set the column headers within your task function. I hope this helps! If you have any more questions, feel free to ask.