根据列值确定优先级并选择行 [英] Prioritize based on Column Value and select row

问题描述

我想为多列"赋予优先级，并根据优先级选择行

I want to give priority on Multiple columns and select row based on priority

我想在类别"列中选择具有RC优先级的ID，在状态"列中选择待处理优先级"，并相应地选择行"

I wanted to select ID's with RC priority in Category Column and Pending Priority in Status column and select Rows accordingly

示例:输入数据框

ID  Category      Status    Date
1   GC       Pending    01-03-2015
1   RC       Resolved   05-10-2016
1   GC       Resolved   06-03-2017
2   RC       Pending    09-08-2016
2   RC       Resolved   10-05-2014
3   GC       Resolved   10-08-2018
3   RC       Pending    13-05-2019
4   GC       Pending    10-06-2018
4   GC       Resolved   15-09-2014

输出数据框

ID  Category      Status    Date
1   RC       Resolved   05-10-2016
2   RC       Pending    09-08-2016
3   RC       Pending    13-05-2019
4   GC       Pending    10-06-2018

推荐答案

通过将列表传递给categories参数，然后按

Convert columns to ordered categoricals with set priority by passing list to categories parameter, then sorting by 3 columns by DataFrame.sort_values and last remove duplicates with DataFrame.drop_duplicates:

df['Category'] = pd.Categorical(df['Category'], ordered=True, categories=['GC','RC'])
df['Status'] = pd.Categorical(df['Status'], ordered=True, categories=['Resolved','Pending'])

df = df.sort_values(['ID','Category','Status']).drop_duplicates('ID', keep='last')
print (df)
   ID Category    Status        Date
1   1       RC  Resolved  05-10-2016
3   2       RC   Pending  09-08-2016
6   3       RC   Pending  13-05-2019
7   4       GC   Pending  10-06-2018

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