Сергей

import numpy as np

def split(seq, num_chunks):
    lst = np.array_split(np.array(seq), num_chunks)
    return [x.tolist() for x in lst if len(x)]

from __future__ import division
import math

def split(seq, num_chunks):
    assert num_chunks
    pos = 0
    sz = len(seq)
    result = []
    while pos < sz:
        num_items = int(math.ceil((sz - pos) / num_chunks))
        result.append(seq[pos:pos + num_items])
        pos = pos + num_items
        num_chunks -= 1
    return result

split([1, 2, 3, 4, 5, 6, 7, 8, 9], X)

# X
# 1   [[1, 2, 3, 4, 5, 6, 7, 8, 9]]
# 2   [[1, 2, 3, 4, 5], [6, 7, 8, 9]]
# 3   [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
# 4   [[1, 2, 3], [4, 5], [6, 7], [8, 9]]
# 5   [[1, 2], [3, 4], [5, 6], [7, 8], [9]]
# 6   [[1, 2], [3, 4], [5, 6], [7], [8], [9]]
# 7   [[1, 2], [3, 4], [5], [6], [7], [8], [9]]
# 8   [[1, 2], [3], [4], [5], [6], [7], [8], [9]]
# 9   [[1], [2], [3], [4], [5], [6], [7], [8], [9]]
# 10  [[1], [2], [3], [4], [5], [6], [7], [8], [9]]

def split(seq, num_chunks):
    assert num_chunks
    pos = 0
    sz = len(seq)
    while pos < sz:
        num_items = int(math.ceil((sz - pos) / num_chunks))
        yield seq[pos:pos + num_items]
        pos = pos + num_items
        num_chunks -= 1

    for _ in range(num_chunks):
        yield []

list(split([1, 2, 3, 4, 5, 6, 7, 8, 9], X))

# X
# ...
# 9   [[1], [2], [3], [4], [5], [6], [7], [8], [9]]
# 10  [[1], [2], [3], [4], [5], [6], [7], [8], [9], []]
# 11  [[1], [2], [3], [4], [5], [6], [7], [8], [9], [], []]

df['col3'] = df.min(axis=1)
# или
import numpy as np
df['col3'] = np.minimum(df.col1, df.col2)

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)

...