Сергей

Можно просто разделить таблицу на несколько независимых датафреймов. Читать CSV несколько раз нет необходимости.

Например, так:

import pandas as pd
import numpy as np


def get_df(filename, parse_dates=None):
    """Build :class:`DataFrame` list from CSV file.

    Expected CSV file format::

        Timestamp0; Value0 ; Timestamp1; Value1; ...TimestampN; ValueN;

    Args:
        filename: CSV filename.
        parse_dates: List of columns with dates.

    Returns:
        List of DataFrames with 'Timestamp' as index and 'Value' as value
        column.

    Notes:
        :attr:`DataFrame._name` contains name extracted
        from 'TimestampX' column.
    """

    df_all = pd.read_csv(filename, sep=';', decimal=',',
                         parse_dates=parse_dates, header=0)

    assert len(df_all.columns) % 2 == 0

    lst = []
    columns = ['time', 'value']

    # Create lsit of 2-items chunks.
    col_list = np.split(df_all.columns, len(df_all.columns) / 2)

    for cols in col_list:
        df = df_all[cols]                   # split 2-column DataFrame.
        df._name = cols[0].split(',')[0]    # attach name to data frame.
        df.columns = columns                # change columns names.
        df = df.set_index('time')           # set index to timestamps.
        lst.append(df)

    return lst


df_list = get_df('GAS.csv', parse_dates=[0, 2, 4])
df = df_list[0]
print(df.index)
print(df._name)

...