Question

我有两个DataFrame：

Person_df

Name  Emplid  Country

    0  DK     123    India

    1  JS     456    India

    2  RM     789    China

    3  MS     111    China

    4  SR     222    China

Target_df

Country Category    Target

    0   India   Marketing   Reduce spend by $xy.

    1   India   R&D         Increase spend by $dd.

    2   India   Infra       Reduce spend by $kn.

    3   China   Marketing   Increase spend by $eg.

    4   China   R&D         Increase spend by $cb.

    5   China   Infra       Reduce spend by $mn.

我的目标是根据每个人的国家/地区创建第三个DataFrame，如下所示：

Individual_df

TargetID    Category    Target

    DK12301     Marketing   Reduce spend by $xy.

    DK12302     R&D         Increase spend by $dd.

    DK12303     Infra       Reduce spend by $kn.

    JS45601     Marketing   Reduce spend by $xy.

    JS45602     R&D         Increase spend by $dd.

    JS45603     Infra       Reduce spend by $kn.

    RM78901     Marketing   Increase spend by $eg.

    RM78902     R&D         Increase spend by $cb.

    RM78903     Infra       Reduce spend by $mn.

    MS11101     Marketing   Increase spend by $eg.

    MS11102     R&D         Increase spend by $cb.

    MS11103     Infra       Reduce spend by $mn.

    SR22201     Marketing   Increase spend by $eg.

    SR22202     R&D         Increase spend by $cb.

    SR22203     Infra       Reduce spend by $mn.

基本上我必须从Person_df中取一个人，将他/她的国家与Target_df中提到的国家匹配，然后将每个目标分配给此人（并存储在Individual_df中）。

问题是，我是python的新手，无法真正弄清楚如何进行这种国家比较。

我写了下面的代码：

for index, row in Person_df.iterrows():

     

        for index1, row1 in Goals_df.iterrows():

            If Person_df['country'] == Person_df['country'] : #I know this is incorrect

                data = [] 

                #populate data[] with selected values for one person.

                #append data[] to Individual_df

我在这里需要几点帮助：

1）我如何才能在这里对每个人的国家进行比较。

2）即使我知道如何比较，我写的代码效率也不高，因为我在这里做了大量不必要的迭代。任何指示如何改善这一点？

谢谢！

Answer 1

试试这个，

Write-Output "Begin a lengthy process..."
$i = 0
while ($i -le 100)
{
  Start-Sleep 1
  Write-Output "Inner code executed"
  $i += 10
}
Write-Output "Completed."

输出：

Individual_df = pd.merge(Person_df, Target_df2, on=['Country'], how='left')
Individual_df['TargetID'] = Individual_df['Name'] + df3['Emplid'].astype(str) + ((df3.groupby('Emplid').cumcount() + 1).astype(str).str.zfill(2))
Individual_df = Individual_df[['TargetID', 'Category', 'Target']]
print Individual_df

说明：

使用Person_df和Target_df执行左连接
然后根据名称和员工ID以及cumcount为emp id
提取所需的列

当用户请求通过for循环获取行时：

   TargetID   Category                  Target
0   DK12301  Marketing    Reduce spend by $xy.
1   DK12302        R&D  Increase spend by $dd.
2   DK12303      Infra    Reduce spend by $kn.
3   JS45601  Marketing    Reduce spend by $xy.
4   JS45602        R&D  Increase spend by $dd.
5   JS45603      Infra    Reduce spend by $kn.
6   RM78901  Marketing  Increase spend by $eg.
7   RM78902        R&D  Increase spend by $cb.
8   RM78903      Infra    Reduce spend by $mn.
9   MS11101  Marketing  Increase spend by $eg.
10  MS11102        R&D  Increase spend by $cb.
11  MS11103      Infra    Reduce spend by $mn.
12  SR22201  Marketing  Increase spend by $eg.
13  SR22202        R&D  Increase spend by $cb.
14  SR22203      Infra    Reduce spend by $mn.

说明：

找到Person_df的唯一元素
迭代Individual_df至for循环
检查国家/地区是否存在独特元素（国家/地区）如果存在，则执行所需的操作。

如何在Python中比较两个不同DataFrame的单元格值？

1 个答案: