在pandas数据帧上使用布尔过滤器时的KeyError

时间:2015-11-20 02:09:49

标签: python pandas boolean dataframe keyerror

当一个数据帧的日期时间对象在另一个数据帧的日期时间对象范围内时,尝试组合两个数据帧。

继续获取:KeyError:'不能使用单个bool索引到我发布的第二个块中的这行代码中的setitem'。

gametaxidf.loc[arrivemask, 'relevant'] = 1

我假设它会发生在下一行也有类似的命令。

这是给我带来麻烦的部分:

with open('/Users/benjaminprice/Desktop/TaxiCombined/Data/combinedtaxifiltered.csv', 'w') as csvfile: 
    fieldnames1 = ['index','pickup_datetime', 'dropoff_datetime', 'pickup_long', 'pickup_lat','dropoff_long','dropoff_lat','passenger_count','trip_distance','fare_amount','tip_amount','total_amount','stadium_code'] 
    writer = csv.DictWriter(csvfile, fieldnames=fieldnames1) 
    writer.writeheader()

for index, row in baseballdf.iterrows(): 
    gametimestart = row['Start.Time'] 
    gametimeend = row['End.Time'] 
    arrivemin = gametimestart - datetime.timedelta(minutes=120) 
    arrivemax = gametimeend - datetime.timedelta(minutes = 30) 
    departmin = gametimeend - datetime.timedelta(minutes = 60) 
    departmax = gametimeend + datetime.timedelta(minutes = 90)

    gametaxidf = combineddf[combineddf.DATE==row.DATE]
    gametaxidf['relevant']=0

    for index, row in gametaxidf.iterrows():
        arrivemask = (arrivemin < row['dropoff_datetime']) and (row['dropoff_datetime'] < arrivemax)
        departmask = (departmin < row['pickup_datetime']) and (row['pickup_datetime'] < departmax) 
        gametaxidf.loc[arrivemask, 'relevant'] = 1
        gametaxidf.loc[departmask, 'relevant'] = 1

        with open('/Users/benjaminprice/Desktop/TaxiCombined/Data/combinedtaxifiltered.csv','a') as combinedtaxi:
            gametaxidf.to_csv(combinedtaxi,header=None)
    print(str(index) + "done")

Gametaxidf.head(5):

   index     pickup_datetime    dropoff_datetime  pickup_long  pickup_lat  \
0    195 2014-04-01 00:08:13 2014-04-01 00:15:32   -73.922218   40.827557   
1    344 2014-04-01 00:16:30 2014-04-01 00:20:38   -73.846046   40.754566   
2    558 2014-04-01 00:28:59 2014-04-01 00:36:36   -73.921692   40.831394   
3    744 2014-04-01 00:42:00 2014-04-01 00:49:46   -73.938080   40.804646   
4    776 2014-04-01 00:43:54 2014-04-01 00:53:22   -73.952652   40.810577   

   dropoff_long  dropoff_lat  passenger_count  trip_distance  fare_amount  \
0    -73.900620    40.856174                1           2.30          9.0   
1    -73.890259    40.753246                1           0.56          4.5   
2    -73.942719    40.823257                1           1.53          7.0   
3    -73.928490    40.830433                1           2.96         11.0   
4    -73.924332    40.827320                1           2.28         10.5   

   tip_amount  total_amount  stadium_code       DATE  relevant  
0           0          10.0           1.1 2014-04-01         0  
1           0           5.5           2.1 2014-04-01         0  
2           0           8.0           1.1 2014-04-01         0  
3           0          12.0           1.0 2014-04-01         0  
4           0          11.5           1.0 2014-04-01         0 

同时收到此警告:正在尝试在DataFrame的切片副本上设置值。

Try using .loc[row_indexer,col_indexer] = value instead

但它让我继续通过......任何帮助都会很棒。

1 个答案:

答案 0 :(得分:3)

下面

gametaxidf.loc[arrivemask, 'relevant'] = 1

您正尝试按.loc运算符设置数据帧值。 Pandas docs for selecting rows说:

  

.loc主要是基于标签的,但也可以与布尔数组一起使用。当找不到项目时,.loc将引发KeyError。允许的输入是:

     
      
  • 单个标签,例如5或'a',(注意5被解释为索引的标签。这个用法不是索引的整数位置)
  •   
  • 标签列表或数组['a','b','c']
  •   
  • 带有标签'a':'f'的切片对象(请注意,与通常的python切片相反,包括开始和停止!)
  •   
  • 布尔数组
  •   

您正在尝试使用最后一种输入,但是

arrivemask = (arrivemin < row['dropoff_datetime']) and 
    (row['dropoff_datetime'] < arrivemax)

是标量布尔值,而不是数组。

您无需遍历数据框。熊猫为你做到了。只需使用:

gametaxidf.loc[
   (arrivemin < gametaxidf['dropoff_datetime'])
   &
   (gametaxidf['dropoff_datetime'] < arrivemax)
   , 'relevant'] = 1