用Python 3.6用增量数填充数据列值

时间:2019-02-15 13:22:03

标签: python python-3.x dataframe

我有Dataframe包含列+“ Order”列,该列具有整数唯一数字,并且某些行为零。

我需要从“订单”值的最大值开始用增量数更新零。

例如:

df ['Order'] = 4的最大值,并且有3条记录df ['Order'] == 0,那么那3个具有0值的行需要用5、6、7填充。

我尝试了以下脚本:

Dimension_Items = {'Col1':['A', 'B', 'C', 'D', 'E', 'F'], 'Order':[0,2,3,4,0,0]}
Dimension_Items = pd.DataFrame.from_dict(Dimension_Items)

Max_Order = Dimension_Items['Order'].max()
Dimension_Items.loc[Dimension_Items['Order'] == 0, 'Order'] = range(Max_Order+1, len(Dimension_Items)+1)

错误:

Traceback (most recent call last):
    Dimension_Items.loc[Dimension_Items['Order'] == 0, 'Order'] = range(Max_Order+1, len(Dimension_Items)+1)
  File "C:\Python36\lib\site-packages\pandas\core\indexing.py", line 189, in __setitem__
    self._setitem_with_indexer(indexer, value)
  File "C:\Python36\lib\site-packages\pandas\core\indexing.py", line 606, in _setitem_with_indexer
    raise ValueError('Must have equal len keys and value '
ValueError: Must have equal len keys and value when setting with an iterable

出现错误,请对此提供帮助

2 个答案:

答案 0 :(得分:1)

间谍。

您可以遍历DataFrame来查找Order = 0的项目,然后使用max_order + 1更新每个Order。

import pandas as pd

data = {

    'Col1': ['A', 'B', 'C', 'D', 'E', 'F'], 
    'Order': [0, 2, 3, 4, 0, 0]

}

df = pd.DataFrame(data)

max_order = df['Order'].max()

for i in range(len(df)):

    if df.loc[i, 'Order'] == 0:
        df.loc[i, 'Order'] = max_order + 1
        max_order += 1

df.head()

输出:

    Order   Value
0      A        5
1      B        2
2      C        3
3      D        4
4      E        6

希望这会有所帮助。

答案 1 :(得分:1)

因此,如果我理解正确,我们可以隔离零,然后使用列表中的值填充零。

l = range(df.Order.max() + 1, df.Order.max() + df.loc[df.Order == 0, 'Order'].size + 1)

df.loc[df.Order == 0, 'Order'] = l

  Col1  Order
0    A      5
1    B      2
2    C      3
3    D      4
4    E      6
5    F      7