大熊貓 - 基於多部分邏輯覈查的日期時間

Question

我有一個數據幀，看起來像這樣添加列：

Num   First_Date  Last_Date 
20008526 7/3/2013 0:00 7/18/2013 0:00 
20008526 7/3/2013 0:00 7/18/2013 0:00 
20008526 7/3/2013 0:00 7/18/2013 0:00 
20008526 7/3/2013 0:00 7/18/2013 0:00 
20008526 7/3/2013 0:00 7/18/2013 0:00 
20008526 7/3/2013 0:00 7/18/2013 0:00 
20008526 7/3/2013 0:00 7/18/2013 0:00 
20008526 7/3/2013 0:00 7/18/2013 0:00 
20008526 7/3/2013 0:00 7/18/2013 0:00 
20008526 7/3/2013 0:00 7/18/2013 0:00 
20008526 7/3/2013 0:00 7/18/2013 0:00 
20008526 7/3/2013 0:00 7/18/2013 0:00 
20008526 7/3/2013 0:00 7/18/2013 0:00 
20008534 3/25/2014 0:00 5/5/2014 0:00 
20008534 3/25/2014 0:00 5/5/2014 0:00 
20008534 3/25/2014 0:00 5/5/2014 0:00 
20008534 3/25/2014 0:00 5/5/2014 0:00 
20008534 3/25/2014 0:00 5/5/2014 0:00 
20008534 3/25/2014 0:00 5/5/2014 0:00 
20008534 3/25/2014 0:00 5/5/2014 0:00 
20008534 3/25/2014 0:00 5/5/2014 0:00 
20008534 3/25/2014 0:00 5/5/2014 0:00 
20008534 3/25/2014 0:00 5/5/2014 0:00 
20008534 3/25/2014 0:00 5/5/2014 0:00 
20008534 3/25/2014 0:00 5/5/2014 0:00 
20008534 3/25/2014 0:00 5/5/2014 0:00 
20008636 7/15/2015 0:00 8/18/2015 0:00 
20008636 7/15/2015 0:00 8/18/2015 0:00 
20008636 7/15/2015 0:00 8/18/2015 0:00 

基本上，我想看看這兩個日期是我指定的時間內。

period_beg = datetime.datetime(2015, 7, 1, 0, 0) 
period_end = datetime.datetime(2015, 9, 30, 0, 0) 

這是我要去的地方，但這看起來很瘋狂和令人費解......哦，它不工作！大聲笑。

df['TimeCheck'] = df[(df['First_Date'] >= period_beg) and (df['Last_Date'] <= period_end)] 

這裏是我期待獲得：

Num   First_Date  Last_Date  TimeCheck 
20008526 7/3/2013 0:00 7/18/2013 0:00 TRUE 
20008526 7/3/2013 0:00 7/18/2013 0:00 TRUE 
20008526 7/3/2013 0:00 7/18/2013 0:00 TRUE 
20008526 7/3/2013 0:00 7/18/2013 0:00 TRUE 
20008526 7/3/2013 0:00 7/18/2013 0:00 TRUE 
20008526 7/3/2013 0:00 7/18/2013 0:00 TRUE 
20008526 7/3/2013 0:00 7/18/2013 0:00 TRUE 
20008526 7/3/2013 0:00 7/18/2013 0:00 TRUE 
20008526 7/3/2013 0:00 7/18/2013 0:00 TRUE 
20008526 7/3/2013 0:00 7/18/2013 0:00 TRUE 
20008526 7/3/2013 0:00 7/18/2013 0:00 TRUE 
20008526 7/3/2013 0:00 7/18/2013 0:00 TRUE 
20008526 7/3/2013 0:00 7/18/2013 0:00 TRUE 
20008534 3/25/2014 0:00 5/5/2014 0:00 FALSE 
20008534 3/25/2014 0:00 5/5/2014 0:00 FALSE 
20008534 3/25/2014 0:00 5/5/2014 0:00 FALSE 
20008534 3/25/2014 0:00 5/5/2014 0:00 FALSE 
20008534 3/25/2014 0:00 5/5/2014 0:00 FALSE 
20008534 3/25/2014 0:00 5/5/2014 0:00 FALSE 
20008534 3/25/2014 0:00 5/5/2014 0:00 FALSE 
20008534 3/25/2014 0:00 5/5/2014 0:00 FALSE 
20008534 3/25/2014 0:00 5/5/2014 0:00 FALSE 
20008534 3/25/2014 0:00 5/5/2014 0:00 FALSE 
20008534 3/25/2014 0:00 5/5/2014 0:00 FALSE 
20008534 3/25/2014 0:00 5/5/2014 0:00 FALSE 
20008534 3/25/2014 0:00 5/5/2014 0:00 FALSE 
20008636 7/15/2015 0:00 8/18/2015 0:00 TRUE 
20008636 7/15/2015 0:00 8/18/2015 0:00 TRUE 
20008636 7/15/2015 0:00 8/18/2015 0:00 TRUE 

上應如何做這樣的想法？另外 - 我應該這樣做這種方式（我不知道它的術語）還是應該遍歷行並逐個添加值？

Answer 1

你需要按位&而不是and使用：

In [7]: 
period_beg = dt.datetime(2015, 7, 1, 0, 0) 
period_end = dt.datetime(2015, 9, 30, 0, 0) 
df['TimeCheck'] = (df['First_Date'] >= period_beg) & (df['Last_Date'] <= period_end) 
df 

Out[7]: 
     Num First_Date Last_Date TimeCheck 
0 20008526 2013-07-03 2013-07-18  False 
1 20008526 2013-07-03 2013-07-18  False 
2 20008526 2013-07-03 2013-07-18  False 
3 20008526 2013-07-03 2013-07-18  False 
4 20008526 2013-07-03 2013-07-18  False 
5 20008526 2013-07-03 2013-07-18  False 
6 20008526 2013-07-03 2013-07-18  False 
7 20008526 2013-07-03 2013-07-18  False 
8 20008526 2013-07-03 2013-07-18  False 
9 20008526 2013-07-03 2013-07-18  False 
10 20008526 2013-07-03 2013-07-18  False 
11 20008526 2013-07-03 2013-07-18  False 
12 20008526 2013-07-03 2013-07-18  False 
13 20008534 2014-03-25 2014-05-05  False 
14 20008534 2014-03-25 2014-05-05  False 
15 20008534 2014-03-25 2014-05-05  False 
16 20008534 2014-03-25 2014-05-05  False 
17 20008534 2014-03-25 2014-05-05  False 
18 20008534 2014-03-25 2014-05-05  False 
19 20008534 2014-03-25 2014-05-05  False 
20 20008534 2014-03-25 2014-05-05  False 
21 20008534 2014-03-25 2014-05-05  False 
22 20008534 2014-03-25 2014-05-05  False 
23 20008534 2014-03-25 2014-05-05  False 
24 20008534 2014-03-25 2014-05-05  False 
25 20008534 2014-03-25 2014-05-05  False 
26 20008636 2015-07-15 2015-08-18  True 
27 20008636 2015-07-15 2015-08-18  True 
28 20008636 2015-07-15 2015-08-18  True 

這是因爲你比較陣列，而不是其and不理解了標值。

而且你試圖通過這樣做是爲了使用布爾面具從條件指數DF：

df['TimeCheck'] = df[(df['First_Date'] >= period_beg) and (df['Last_Date'] <= period_end)] 

其中由於and生成ValueError：

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

即使您在上面將and更改爲&，這將僅分配True值：

In [10]: 
df['TimeCheck'] = df[(df['First_Date'] >= period_beg) & (df['Last_Date'] <= period_end)] 
df 

Out[10]: 
     Num First_Date Last_Date TimeCheck 
0 20008526 2013-07-03 2013-07-18   NaN 
1 20008526 2013-07-03 2013-07-18   NaN 
2 20008526 2013-07-03 2013-07-18   NaN 
3 20008526 2013-07-03 2013-07-18   NaN 
4 20008526 2013-07-03 2013-07-18   NaN 
5 20008526 2013-07-03 2013-07-18   NaN 
6 20008526 2013-07-03 2013-07-18   NaN 
7 20008526 2013-07-03 2013-07-18   NaN 
8 20008526 2013-07-03 2013-07-18   NaN 
9 20008526 2013-07-03 2013-07-18   NaN 
10 20008526 2013-07-03 2013-07-18   NaN 
11 20008526 2013-07-03 2013-07-18   NaN 
12 20008526 2013-07-03 2013-07-18   NaN 
13 20008534 2014-03-25 2014-05-05   NaN 
14 20008534 2014-03-25 2014-05-05   NaN 
15 20008534 2014-03-25 2014-05-05   NaN 
16 20008534 2014-03-25 2014-05-05   NaN 
17 20008534 2014-03-25 2014-05-05   NaN 
18 20008534 2014-03-25 2014-05-05   NaN 
19 20008534 2014-03-25 2014-05-05   NaN 
20 20008534 2014-03-25 2014-05-05   NaN 
21 20008534 2014-03-25 2014-05-05   NaN 
22 20008534 2014-03-25 2014-05-05   NaN 
23 20008534 2014-03-25 2014-05-05   NaN 
24 20008534 2014-03-25 2014-05-05   NaN 
25 20008534 2014-03-25 2014-05-05   NaN 
26 20008636 2015-07-15 2015-08-18 2.00086e+07 
27 20008636 2015-07-15 2015-08-18 2.00086e+07 
28 20008636 2015-07-15 2015-08-18 2.00086e+07 

這是不是你想要的

而且只有最後3行滿足你的病情，不知道爲什麼你期望與最後日期值的行：7/18/2013 0:00也成爲True