SnowPro Advanced Data Scientist

Question

A Data Scientist is working with two Snowpark DataFrames that each contain a column named id. The objective is to join these DataFrames using the id column.

new_df = df1.join(df2, df1["id"] == df2["id"])

After executing the following code:

new_df.select(col("id"), col("name"), col("country")).show()

The Scientist gets this error:

Error (1303): The reference to column 'ID' is ambiguous...

Which method should the Scientist use to resolve this error?

Explanation

A join that retains identically named columns requires column references to be qualified by their source DataFrame. Using df1.id and df2.country identifies the intended columns, and as_("df1_id") assigns the selected id column a distinct output name, eliminating the ambiguous ID reference.

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SnowPro Advanced Data Scientist

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Notes

Readiness

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