所以我一直在使用一个函数来合并时间序列数据，就在昨天我开始使用它时看到了这个折旧错误：
C:\Users\user\PycharmProjects\Hydrostats_tests\venv1\lib\site-
packages\dateutil\parser\__init__.py:46:
DeprecationWarning: _timelex is a
private class and may break without warning,
it will be moved and or renamed in future versions. warnings.warn(msg,
DeprecationWarning)
我正在运行的代码如下，我正在使用我制作的软件包。
import os
import hydrostats.data as hd
sim_dir = r'C:\Users\user\Documents\Data\interim_raw_data'
obs_dir = r'C:\Users\user\Documents\Data\recorded_raw_data'
sim_path = [os.path.join(sim_dir, d) for d in os.listdir(sim_dir)]
obs_path = [os.path.join(obs_dir, d) for d in os.listdir(obs_dir)]
visual_df = hd.merge_data(sim_path[0], obs_path[0])
这是合并数据功能：
def merge_data(predicted_file_path, recorded_file_path, interpolate=None, column_names=['Simulated', 'Observed'],
predicted_tz=None, recorded_tz=None, interp_type='pchip'):
if predicted_tz is None and recorded_tz:
print('Either Both Timezones are required or neither')
elif predicted_tz and recorded_tz is None:
print('Either Both Timezones are required or neither')
elif predicted_tz is None and recorded_tz is None and interpolate is None:
# Importing data into a data-frame
df_predicted = pd.read_csv(predicted_file_path, delimiter=",", header=None, names=[column_names[0]],
index_col=0, infer_datetime_format=True, skiprows=1)
df_recorded = pd.read_csv(recorded_file_path, delimiter=",", header=None, names=[column_names[1]],
index_col=0, infer_datetime_format=True, skiprows=1)
# Converting the index to datetime type
df_recorded.index = pd.to_datetime(df_recorded.index, infer_datetime_format=True)
df_predicted.index = pd.to_datetime(df_predicted.index, infer_datetime_format=True)
return pd.DataFrame.join(df_predicted, df_recorded).dropna()
错误发生在这两行
df_recorded.index = pd.to_datetime（df_recorded.index，infer_datetime_format =真） 的 df_predicted.index = pd.to_datetime（df_predicted.index，infer_datetime_format =真）
我正在阅读的csv数据如下所示：
Datetime,recorded streamflow (m^3/s)
1962-02-23,160.0
1962-02-24,163.0
1962-02-25,178.0
1962-02-26,169.0
1962-02-27,169.0
1962-02-28,169.0
1962-03-01,169.0
1962-03-02,163.0
1962-03-03,160.0
1962-03-04,158.0
1962-03-05,195.0
我在线查找了这个错误，并且我尝试使用调试器，但是我无法看到此错误的来源。我想有一个更新，但我不确定是什么更新导致此错误。
任何帮助将不胜感激，谢谢！