Bug - Number summaries need to handle missing values better

[a-l-holmes]

Describe the bug

Namely in summarize_csv, if there are any missing values (e.g., NA, ., nan), then some of the summary statistics do not calculate correctly.

To Reproduce

Steps to reproduce the behavior:

1. Example command: summarize_csv -dd data/input/condition_INCLUDE_copy.csv -dt data/input/teamds_conditions_harmonized_2024-12-17.csv -m "" -e data/output/TEAM-DS_conditions_summary_2024_12_18.yaml where teamds_conditions_harmonized_2024-12-17.csv includes empty cells.
2. Example output with missing values:

Age At Condition or Measure Observation:
  Max: 6209.0
  Mean: .nan
  Median: .nan
  Min: 2192.0
  Q1: .nan
  Q3: .nan
  Total Count of Observations: 2990
  Total Missing Values(None): 2654

Expected behavior

Output for numeric handling should be able to compute all values by dropping empty cells from computation to provide a summary on the existing numbers.

Desktop (please complete the following information):

• OS: Windows
• Python Version: 3.12.2

Additional context

Review needed on statistics.quantiles, statistics.mean, min, and max in the summarize_csv.py script.