问题描述
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，尝试合并两个数据帧.
Trying to combine two data frames when a datetime object from one dataframe is within a datetime object range in the other.
在我发布的第二个代码块中的这行代码中，不断出现:KeyError: 'cannot use a single bool to index into setitem'.
Keep getting: KeyError: 'cannot use a single bool to index into setitem' on this line of code in the second chunk I posted.
gametaxidf.loc[arrivemask, 'relevant'] = 1
我假设它也会在下一行使用类似的命令发生.
I'm assuming it would happen on the following line with a similar command as well.
这是给我带来麻烦的部分:
This is the part giving me trouble:
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):
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
还收到此警告:正在尝试在 DataFrame 中的切片副本上设置值.
Also getting this warning: A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
但它让我继续经历……任何帮助都会很棒.
But it's letting me continue through that... any help would be great.
推荐答案
这里
gametaxidf.loc[arrivemask, 'relevant'] = 1
您正在尝试通过 .loc 运算符设置数据帧值.用于选择行的 Pandas 文档 说:
you're trying to set dataframe values by .loc operator. Pandas docs for selecting rows says:
.loc 主要是基于标签的，但也可以与布尔数组一起使用..loc 将在未找到项目时引发 KeyError.允许的输入是:
.loc is primarily label based, but may also be used with a boolean array. .loc will raise KeyError when the items are not found. Allowed inputs are:
- 单个标签，例如5 或 'a'，(注意 5 被解释为索引的标签.此用法不是沿索引的整数位置)
- 标签列表或数组 ['a', 'b', 'c']
- 带有标签'a':'f'的切片对象，(注意与通常的python切片相反，开始和结束都包括在内！)
- 一个布尔数组
您正在尝试使用最后一种类型的输入，但是这个
You're trying to use the last type of input, but this
arrivemask = (arrivemin < row['dropoff_datetime']) and
(row['dropoff_datetime'] < arrivemax)
是标量布尔值，而不是数组.
is scalar boolean, not array.
您无需遍历数据框.熊猫为你做这件事.只需使用:
You need not to iterate through dataframe. Pandas does it for you. Just use:
gametaxidf.loc[
(arrivemin < gametaxidf['dropoff_datetime'])
&
(gametaxidf['dropoff_datetime'] < arrivemax)
, 'relevant'] = 1
这篇关于在 Pandas 数据帧上使用布尔过滤器时出现 KeyError的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持跟版网！