创建一个新列以根据条件查找日期差异

时间:2018-12-16 15:55:57

标签: python pandas dataframe conditional multiple-columns

我有以下数据框:

df =

Date     Team1     Team2     
6/1      Boston    New York  
6/13     New York  Chicago   
6/27     Boston    New York  
6/28     Chicago   Boston   

我想创建一个新列,该列根据team1的条件查找日期差异。例如)当芝加哥是Team1时,我想知道自上次比赛以来的天数,无论他们在上一场比赛中是Team1还是Team2。

df =

Date     Team1     Team2      Days since Team1 played
6/1      Boston    New York   0
6/13     New York  Chicago    12
6/27     Boston    New York   26
6/28     Chicago   Boston     15

1 个答案:

答案 0 :(得分:3)

您的预期输出接近,但我会创建一个多索引

使用meltdiff然后使用pivot

# melt to get Teams as one columns
melt = df.melt('Date').sort_values('Date')

# groupby and find the difference
melt['diff'] = melt.groupby('value')['Date'].diff()

# pivot to go back to the original df format
melt.pivot('Date','variable') 

                  value              diff
variable     Team1    Team2     Team1     Team2
      Date              
2018-06-01  Boston   New York    NaT       NaT
2018-06-13  New York Chicago     12 days   NaT
2018-06-27  Boston   New York    26 days   14 days
2018-06-28  Chicago  Boston      15 days   1 days

更新

这是您的评论的更新:

# assume this df
    Date         Team1   Team2
0   2018-06-01  Boston    New York
1   2018-06-13  New York  Chicago
2   2018-06-27  Boston    New York
3   2018-06-28  Chicago   Boston
4   2018-06-28  New York  Detroit

代码:

# melt df (same as above example)
melt = df.melt('Date').sort_values('Date')

# find the difference
melt['diff'] = melt.groupby('value')['Date'].diff()

# use pivot_table not pivot
piv = melt.pivot_table(index=['Date', 'diff'], columns='variable', values='value', aggfunc=lambda x:x)

# reset index and dropna from team 1
piv.reset_index(level=1, inplace=True)
piv = piv[~piv['Team1'].isna()]

# merge your original df and your new one together
pd.merge(df, piv[piv.columns[:-1]], on=['Date','Team1'], how='outer').fillna(0)

         Date   Team1     Team2     diff
0   2018-06-01  Boston    New York  0 days
1   2018-06-13  New York  Chicago   12 days
2   2018-06-27  Boston    New York  26 days
3   2018-06-28  Chicago   Boston    15 days
4   2018-06-28  New York  Detroit   1 days

请注意,这次的区别只是与Team1上次比赛的时间不同