用增量数字填充数据列值，Python 3.6

Question

我有 Dataframe contains columns + "Order" column，它有整数唯一数字，有些行是零。

我需要从 "Order" 值的最大值用增量数字更新零。

例如：

df['Order'] 的最大值 = 4 并且有 3 条记录 df['Order'] == 0 那么那些值为 0 的 3 行需要填充 5、6、7 .

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

给出错误，请帮助

Answer 1

SPy.

您可以遍历 DataFrame 以查找 Order = 0 的项目，然后将每个 Order 更新为 max_order + 1。试试这个：

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

希望对您有所帮助。

Answer 2

所以我们可以隔离零，然后用列表中的值填充它们，如果我理解正确的话。

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

用增量数字填充数据列值，Python 3.6

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