Use csv DictReader and DictWriter to read, and write a csv files, dropping rows with missing data.

gistfile1.txt

import csv

IN_PATH = "values.csv"
OUT_PATH = "values_cleaned.csv"

def is_number(s: str) -> bool:
    try:
        float(s)
        return True
    except ValueError:
        return False

kept = 0
dropped = 0

with open(IN_PATH, newline="", encoding="utf-8") as src, open(OUT_PATH, "w", newline="", encoding="utf-8") as dst:
    reader = csv.DictReader(src)
    fieldnames = reader.fieldnames or ["date", "min", "max"]
    writer = csv.DictWriter(dst, fieldnames=fieldnames)
    writer.writeheader()

    for row in reader:
        min_val = (row.get("min") or "").strip()
        max_val = (row.get("max") or "").strip()
        if is_number(min_val) and is_number(max_val):
            # preserve trimmed strings for date/min/max
            out_row = {k: (row.get(k) or "").strip() for k in fieldnames}
            writer.writerow(out_row)
            kept += 1
        else:
            dropped += 1

print(f"Wrote {kept} rows to `{OUT_PATH}`; dropped {dropped} invalid rows.")