Pandas 给出 datetime.date' 被强制为 datetime

Question

Im trying to compare two date values. My data contains a datecolumn.

    dateCols = ['Document Date']
    data = pd.read_excel(os.path.join(delivery_file_path, f), parse_dates=dateCols,
                                   dayfirst=True, sheet_name='Refined',skiprows=1)

    data['Document Date'] = pd.to_datetime(data['Document Date'])
    df = pd.DataFrame(columns=['Document Date'], data=data['Document Date'])
    print(df.dtypes)  <-- prints **datetime64[ns]**
    if (df['Document Date'] >= start) and (df['Document Date'] <= end):
.....

I get following error;

datetime.date' is coerced to a datetime. In the future pandas will
not coerce, and a TypeError will be raised. To retain the current
behavior, convert the 'datetime.date' to a datetime with
'pd.Timestamp'.
  if (df['Document Date'] >= start) and (df['Document Date'] <= end):
...
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

What is wrong with my above date comparison?

Answer 1

I sorted out like adding.any()

if ((df['Document Date'] >= start) & (df['Document Date'] <= end)).any():

My requirement was, the file i process contain a monthly worth records or not. It is for data quality check. So using any() would be fine.