Python 基于日期的 VLOOKUP - Pandas

Question

pandas df 有问题，试图根据日期获取 "Count" 列，代码应搜索 "date range' within the dates column, and if it is present the 'Count' should be copied into the "Posts" 列以获取相应的日期例如：date_range value = 16/02/2017 - 代码在 "Dates" 列中搜索 16/02/2017 并使 "Posts" 等于该日期的 "Count" 值 -如果 date_range 值未出现 - 帖子应 = 0.

数据示例：

Dates     Count date_range  Posts
0   07/02/2017  1   16/12/2016  (should = 5)   
1   01/03/2017  1   17/12/2016  
2   15/02/2017  1   18/12/2016  
3   23/01/2017  1   19/12/2016  
4   28/02/2017  1   20/12/2016  
5   09/02/2017  2   21/12/2016  
6   20/03/2017  2   22/12/2016  
7   16/12/2016  5

我的代码如下所示：

    DateList = df['Dates'].tolist()

    for date in df['date_range']:
        if str(date) in DateList:
            df['Posts'] = df['Count']
        else:
            dates_df['Posts'] = 0

然而，这会使数据将错误的值映射到 "Posts"

希望我解释正确！在此先感谢您的帮助！

Answer 1

您可以先为匹配值创建 dict，然后通过 date_range 列创建 map：

print (df)
        Dates  Count  date_range
0  07/02/2017      1  16/12/2016
1  01/03/2017      1  17/12/2016
2  15/02/2017      1  18/12/2016
3  23/01/2017      1  19/12/2016
4  28/02/2017      1  07/02/2017 <-change value for match
5  09/02/2017      2  21/12/2016
6  20/03/2017      2  22/12/2016
7  16/12/2016      5  22/12/2016

d = df[df['Dates'].isin(df.date_range)].set_index('Dates')['Count'].to_dict()
print (d)
{'16/12/2016': 5, '07/02/2017': 1}

df['Posts'] = df['date_range'].map(d).fillna(0).astype(int)
print (df)
        Dates  Count  date_range  Posts
0  07/02/2017      1  16/12/2016      5
1  01/03/2017      1  17/12/2016      0
2  15/02/2017      1  18/12/2016      0
3  23/01/2017      1  19/12/2016      0
4  28/02/2017      1  07/02/2017      1
5  09/02/2017      2  21/12/2016      0
6  20/03/2017      2  22/12/2016      0
7  16/12/2016      5  22/12/2016      0

Python 基于日期的 VLOOKUP - Pandas

Python VLOOKUP based on dates - Pandas

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