docs: use head() to get top n results, not to preview results (#190)

head() requires ordering. Just peeking at the whole DataFrame or Series is actually more efficient since it doesn't require ordering and still only downloads a fraction of the results. Thank you for opening a Pull Request! Before submitting your PR, there are a few things you can do to make sure it goes smoothly: - [ ] Make sure to open an issue as a [bug/issue](https://togithub.com/googleapis/python-bigquery-dataframes/issues/new/choose) before writing your code! That way we can discuss the change, evaluate designs, and agree on the general idea - [ ] Ensure the tests and linter pass - [ ] Code coverage does not decrease (if any source code was changed) - [ ] Appropriate docs were updated (if necessary) Fixes #<issue_number_goes_here> 🦕

Author: tswast

samples/snippets/pandas_methods_test.py

@@ -22,13 +22,20 @@ def test_bigquery_dataframes_pandas_methods():
  bq_df = bpd.read_gbq(query_or_table)
 
  # Inspect one of the columns (or series) of the DataFrame:
- bq_df["body_mass_g"].head(10)
+ bq_df["body_mass_g"]
 
  # Compute the mean of this series:
  average_body_mass = bq_df["body_mass_g"].mean()
  print(f"average_body_mass: {average_body_mass}")
 
- # Calculate the mean body_mass_g by species using the groupby operation:
- bq_df["body_mass_g"].groupby(by=bq_df["species"]).mean().head()
+ # Find the heaviest species using the groupby operation to calculate the
+ # mean body_mass_g:
+ (
+ bq_df["body_mass_g"]
+ .groupby(by=bq_df["species"])
+ .mean()
+ .sort_values(ascending=False)
+ .head(10)
+ )
  # [END bigquery_dataframes_pandas_methods]
  assert average_body_mass is not None