如何透视多个时间增量范围的表？

Question

1。我想Pivot_table将多个24小时时间增量范围放入一个表中，并对每个时间戳进行横截面分析。你能推荐一个有趣的算法来处理这些表吗

2.My每个趋势文件都是参数1分钟趋势的cross-tabular表：

Trend 1
Time, Parameter1, Parameter2,..
16:52:45, a,      b,   ...
15:53:45, c       d,   ...
...
Trend 2, Parameter1, Parameter2
07:41:16  e,      f,   ...
07:42:16  g,      h,   ...

frame = []
for raw_file_name in raw_files:
    input_raw_path = os.path.join(raw_path, raw_file_name, 'log.txt')
    if os.path.isfile (input_raw_path):
        with open(input_raw_path, encoding= "Latin-1") as f:
            ts = f.readline(19).split()[1]

            input_superecg_path = os.path.join(superecg_path, raw_file_name, 'Trend.csv')
            if os.path.isfile (input_superecg_path):
                df = pd.read_csv(input_superecg_path)
                df['File'] = raw_file_name
                df['Time'] = pd.timedelta_range(ts, freq='T', periods=df.shape[0], name='Time')
                df = pd.melt(df, id_vars = ['Time', 'File'], var_name = 'Parameter', value_name = 'Value')
                frame.append(df)

frame = pd.concat(frame, ignore_index=True)
frame = frame[frame.Value != '1.#INF'].astype({'Value': 'float64'})
frame = frame.set_index('Time')

Table = frame.pivot_table(values = ['Value'], index = ['Time'], 
columns = ['Parameter'], aggfunc = np.mean)

3.这会生成框架，但不会创建透视表。问题在{}行中，给出了不同的错误