问题

我想要填充'Outline_Level'列中的'N/A'值，使其等于下面单元格的值减1。例如，如果单元格中有一个'N/A'值，而下面的单元格的值为3，我希望'N/A'单元格的值为2。我尝试过bfill方法，它可以填充'N/A'值，但我无法弄清如何从这些值中减去1。

以下是您期望的数据框示例：

Ideal_data = [['1', 'Construction', '', '01/02/2022', '01/06/2022', '1', 'No'],
 ['2', 'Level Site', 'Construction', '01/02/2022', '01/02/2022', '2', 'No'],
 ['3', 'Foundation', '', '01/03/2023', '01/06/2023', '1', 'Yes'],
 ['2', 'Lay Foundation', 'Construction>Foundation', '01/03/2022', '01/04/2022', '3', 'No'],
 ['1', 'Prepare land for foundation', 'Construction>Foundation', '01/05/2022', '01/06/2022', '3', 'No'],
 ['2', 'Building Envelope', '', '01/07/2023', '01/16/2023', '1', 'No'],
 ['2', 'Install Footings', 'Building Envelope', '01/07/2022', '01/07/2022', '2', 'Yes'],
 ['2', 'Pouring', '', '01/08/202', '01/09/2023', '1', 'No'],
 ['1', 'Pour Foundation', 'Building Envelope>Pouring', '01/08/2022', '01/09/2022', '3', 'No'],
 ['2', 'Installation', '', '01/09/2022', '01/14/2022', '1', 'No']]

df2 = pd.DataFrame(Ideal_data, columns=['Outline_level', 'Activity', 'Parent', 'Start', 'Finish', 'WBS Level', 'Match'])

感谢任何帮助。

英文:

I have the below dataframe:

data = [[&#39;1&#39;, &#39;Construction&#39;, &#39;&#39;, &#39;01/02/2022&#39;, &#39;01/06/2022&#39;, &#39;1&#39;, &#39;No&#39;], [&#39;N/A&#39;, &#39;Level Site&#39;, &#39;Construction&#39;, &#39;01/02/2022&#39;, &#39;01/02/2022&#39;, &#39;2&#39;, &#39;No&#39;], [&#39;3&#39;, &#39;Foundation&#39;, &#39;&#39;, &#39;01/03/2023&#39;, &#39;01/06/2023&#39;, &#39;1&#39;, &#39;Yes&#39;],[&#39;2&#39;, &#39;Lay Foundation&#39;, &#39;Construction&gt;Foundation&#39;, &#39;01/03/2022&#39;, &#39;01/04/2022&#39;, &#39;3&#39;, &#39;No&#39;], [&#39;N/A&#39;, &#39;Prepare land for foundation&#39;, &#39;Construction&gt;Foundation&#39;, &#39;01/05/2022&#39;, &#39;01/06/2022&#39;, &#39;3&#39;, &#39;No&#39;],[&#39;2&#39;, &#39;Building Envelope&#39;, &#39;&#39;, &#39;01/07/2023&#39;, &#39;01/16/2023&#39;, &#39;1&#39;, &#39;No&#39;], [&#39;2&#39;, &#39;Install Footings&#39;, &#39;Building Envelope&#39;, &#39;01/07/2022&#39;, &#39;01/07/2022&#39;, &#39;2&#39;, &#39;Yes&#39;], [&#39;2&#39;, &#39;Pouring&#39;, &#39;&#39;, &#39;01/08/202&#39;, &#39;01/09/2023&#39;, &#39;1&#39;, &#39;No&#39;],[&#39;N/A&#39;, &#39;Pour Foundation&#39;, &#39;Building Envelope&gt;Pouring&#39;, &#39;01/08/2022&#39;, &#39;01/09/2022&#39;, &#39;3&#39;, &#39;No&#39;], [&#39;2&#39;, &#39;Installation&#39;, &#39;&#39;, &#39;01/09/2022&#39;, &#39;01/14/2022&#39;, &#39;1&#39;, &#39;No&#39;]]
df1 = pd.DataFrame(data, columns=[&#39;Outline_level&#39;,  &#39;Activity&#39;, &#39;Parent&#39;, &#39;Start&#39;, &#39;Finish&#39;, &#39;WBS Level&#39;, &#39;Match&#39;])

df1

I want to fill the N/A values in the 'Outline_Level' column with the value in the cell below it minus 1. For example, if the cell holds an 'N/A' value, and the cell below has a value of 3, I want the N/A cell to have the value of 2. I have tried the bfill method, which fills the N/A values but I can't figure out how to subtract one from those values.

Here is an example of my ideal dataframe:

Ideal_data = [[&#39;1&#39;, &#39;Construction&#39;, &#39;&#39;, &#39;01/02/2022&#39;, &#39;01/06/2022&#39;, &#39;1&#39;, &#39;No&#39;], [&#39;2&#39;, &#39;Level Site&#39;, &#39;Construction&#39;, &#39;01/02/2022&#39;, &#39;01/02/2022&#39;, &#39;2&#39;, &#39;No&#39;], [&#39;3&#39;, &#39;Foundation&#39;, &#39;&#39;, &#39;01/03/2023&#39;, &#39;01/06/2023&#39;, &#39;1&#39;, &#39;Yes&#39;],[&#39;2&#39;, &#39;Lay Foundation&#39;, &#39;Construction&gt;Foundation&#39;, &#39;01/03/2022&#39;, &#39;01/04/2022&#39;, &#39;3&#39;, &#39;No&#39;], [&#39;1&#39;, &#39;Prepare land for foundation&#39;, &#39;Construction&gt;Foundation&#39;, &#39;01/05/2022&#39;, &#39;01/06/2022&#39;, &#39;3&#39;, &#39;No&#39;],[&#39;2&#39;, &#39;Building Envelope&#39;, &#39;&#39;, &#39;01/07/2023&#39;, &#39;01/16/2023&#39;, &#39;1&#39;, &#39;No&#39;], [&#39;2&#39;, &#39;Install Footings&#39;, &#39;Building Envelope&#39;, &#39;01/07/2022&#39;, &#39;01/07/2022&#39;, &#39;2&#39;, &#39;Yes&#39;], [&#39;2&#39;, &#39;Pouring&#39;, &#39;&#39;, &#39;01/08/202&#39;, &#39;01/09/2023&#39;, &#39;1&#39;, &#39;No&#39;],[&#39;1&#39;, &#39;Pour Foundation&#39;, &#39;Building Envelope&gt;Pouring&#39;, &#39;01/08/2022&#39;, &#39;01/09/2022&#39;, &#39;3&#39;, &#39;No&#39;], [&#39;2&#39;, &#39;Installation&#39;, &#39;&#39;, &#39;01/09/2022&#39;, &#39;01/14/2022&#39;, &#39;1&#39;, &#39;No&#39;]]
df2 = pd.DataFrame(Ideal_data, columns=[&#39;Outline_level&#39;,  &#39;Activity&#39;, &#39;Parent&#39;, &#39;Start&#39;, &#39;Finish&#39;, &#39;WBS Level&#39;, &#39;Match&#39;])

df2

Thank you for any help

答案1

得分: 1

使用 pd.Series.shift 替换识别的索引处的值并移动值：

idx = df1[df1['Outline_level'].eq('N/A')].index
df1.loc[idx, 'Outline_level'] = df1['Outline_level'].shift(-1).iloc[idx].astype(int) - 1

      Outline_level                     Activity                     Parent  ...      Finish WBS Level Match
    0             1                 Construction                             ...  01/06/2022         1    No
    1             2                   Level Site               Construction  ...  01/02/2022         2    No
    2             3                   Foundation                             ...  01/06/2023         1   Yes
    3             2               Lay Foundation    Construction&gt;Foundation  ...  01/04/2022         3    No
    4             1  Prepare land for foundation    Construction&gt;Foundation  ...  01/06/2022         3    No
    5             2            Building Envelope                             ...  01/16/2023         1    No
    6             2             Install Footings          Building Envelope  ...  01/07/2022         2   Yes
    7             2                      Pouring                             ...  01/09/2023         1    No
    8             1              Pour Foundation  Building Envelope&gt;Pouring  ...  01/09/2022         3    No
    9             2                 Installation                             ...  01/14/2022         1    No
    
    [10 rows x 7 columns]

英文:

Replace values on recognized indices and shift values using pd.Series.shift:

idx = df1[df1[&#39;Outline_level&#39;].eq(&#39;N/A&#39;)].index
df1.loc[idx, &#39;Outline_level&#39;] = df1[&#39;Outline_level&#39;].shift(-1).iloc[idx].astype(int) - 1

  Outline_level                     Activity                     Parent  ...      Finish WBS Level Match
0             1                 Construction                             ...  01/06/2022         1    No
1             2                   Level Site               Construction  ...  01/02/2022         2    No
2             3                   Foundation                             ...  01/06/2023         1   Yes
3             2               Lay Foundation    Construction&gt;Foundation  ...  01/04/2022         3    No
4             1  Prepare land for foundation    Construction&gt;Foundation  ...  01/06/2022         3    No
5             2            Building Envelope                             ...  01/16/2023         1    No
6             2             Install Footings          Building Envelope  ...  01/07/2022         2   Yes
7             2                      Pouring                             ...  01/09/2023         1    No
8             1              Pour Foundation  Building Envelope&gt;Pouring  ...  01/09/2022         3    No
9             2                 Installation                             ...  01/14/2022         1    No

[10 rows x 7 columns]

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