Overview

Dataset statistics

Number of variables17
Number of observations94
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.8 KiB
Average record size in memory139.4 B

Variable types

Categorical12
Text3
Numeric2

Dataset

Description서비스구분,서비스ID,대분류명,소분류명,서비스상태,서비스명,결제방법,장소명,서비스대상,바로가기URL,장소X좌표,장소Y좌표,서비스개시시작일시,서비스개시종료일시,접수시작일시,접수종료일시,지역명
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-2274/S/1/datasetView.do

Alerts

서비스구분 has constant value ""Constant
서비스개시시작일시 is highly overall correlated with 대분류명 and 9 other fieldsHigh correlation
대분류명 is highly overall correlated with 장소Y좌표 and 8 other fieldsHigh correlation
소분류명 is highly overall correlated with 대분류명 and 9 other fieldsHigh correlation
접수종료일시 is highly overall correlated with 장소X좌표 and 11 other fieldsHigh correlation
서비스개시종료일시 is highly overall correlated with 대분류명 and 7 other fieldsHigh correlation
장소명 is highly overall correlated with 장소X좌표 and 9 other fieldsHigh correlation
결제방법 is highly overall correlated with 소분류명 and 4 other fieldsHigh correlation
접수시작일시 is highly overall correlated with 장소X좌표 and 11 other fieldsHigh correlation
지역명 is highly overall correlated with 장소X좌표 and 10 other fieldsHigh correlation
서비스대상 is highly overall correlated with 대분류명 and 6 other fieldsHigh correlation
장소X좌표 is highly overall correlated with 장소명 and 3 other fieldsHigh correlation
장소Y좌표 is highly overall correlated with 대분류명 and 4 other fieldsHigh correlation
서비스상태 is highly overall correlated with 소분류명 and 4 other fieldsHigh correlation
서비스상태 is highly imbalanced (50.3%)Imbalance
결제방법 is highly imbalanced (61.8%)Imbalance
서비스대상 is highly imbalanced (87.3%)Imbalance
서비스개시종료일시 is highly imbalanced (55.1%)Imbalance
서비스ID has unique valuesUnique
바로가기URL has unique valuesUnique

Reproduction

Analysis started2024-05-11 04:01:02.822120
Analysis finished2024-05-11 04:01:08.198345
Duration5.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

서비스구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
Current System
94 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCurrent System
2nd rowCurrent System
3rd rowCurrent System
4th rowCurrent System
5th rowCurrent System

Common Values

ValueCountFrequency (%)
Current System 94
100.0%

Length

2024-05-11T04:01:08.384503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:01:08.642628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
current 94
50.0%
system 94
50.0%

서비스ID
Text

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-05-11T04:01:09.131732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1786
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)100.0%

Sample

1st rowS240430105734069402
2nd rowS240508102718888983
3rd rowS240508102250869149
4th rowS240424162327007428
5th rowS240325084139631405
ValueCountFrequency (%)
s240430105734069402 1
 
1.1%
s231108104359716676 1
 
1.1%
s231102163210275611 1
 
1.1%
s231030153120733548 1
 
1.1%
s231030151708150434 1
 
1.1%
s231127180612701976 1
 
1.1%
s231127180318293666 1
 
1.1%
s231127175843091098 1
 
1.1%
s231127174944025714 1
 
1.1%
s231127174523276322 1
 
1.1%
Other values (84) 84
89.4%
2024-05-11T04:01:10.030879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 325
18.2%
1 301
16.9%
0 214
12.0%
3 195
10.9%
4 137
7.7%
8 136
7.6%
5 115
 
6.4%
7 95
 
5.3%
S 94
 
5.3%
9 93
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1692
94.7%
Uppercase Letter 94
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 325
19.2%
1 301
17.8%
0 214
12.6%
3 195
11.5%
4 137
8.1%
8 136
8.0%
5 115
 
6.8%
7 95
 
5.6%
9 93
 
5.5%
6 81
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
S 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1692
94.7%
Latin 94
 
5.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 325
19.2%
1 301
17.8%
0 214
12.6%
3 195
11.5%
4 137
8.1%
8 136
8.0%
5 115
 
6.8%
7 95
 
5.6%
9 93
 
5.5%
6 81
 
4.8%
Latin
ValueCountFrequency (%)
S 94
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1786
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 325
18.2%
1 301
16.9%
0 214
12.0%
3 195
10.9%
4 137
7.7%
8 136
7.6%
5 115
 
6.4%
7 95
 
5.3%
S 94
 
5.3%
9 93
 
5.2%

대분류명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size884.0 B
Gyms
58 
<NA>
32 
Cultural Events
 
4

Length

Max length15
Median length4
Mean length4.4680851
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGyms
2nd rowGyms
3rd rowGyms
4th rowCultural Events
5th rowGyms

Common Values

ValueCountFrequency (%)
Gyms 58
61.7%
<NA> 32
34.0%
Cultural Events 4
 
4.3%

Length

2024-05-11T04:01:10.463465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:01:10.770776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
gyms 58
59.2%
na 32
32.7%
cultural 4
 
4.1%
events 4
 
4.1%

소분류명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size884.0 B
Recording/Filming
32 
Tennis court
14 
Basketball court
13 
Futsal field
12 
Foot Volleyball court
9 
Other values (5)
14 

Length

Max length21
Median length17
Mean length15.542553
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFutsal field
2nd rowFutsal field
3rd rowFutsal field
4th rowEvent
5th rowFutsal field

Common Values

ValueCountFrequency (%)
Recording/Filming 32
34.0%
Tennis court 14
14.9%
Basketball court 13
13.8%
Futsal field 12
 
12.8%
Foot Volleyball court 9
 
9.6%
Soccer field 4
 
4.3%
Multi-purpose Stadium 4
 
4.3%
Event 2
 
2.1%
Exhibition/Cruise 2
 
2.1%
Volleyball court 2
 
2.1%

Length

2024-05-11T04:01:11.345731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:01:11.730391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
court 38
23.6%
recording/filming 32
19.9%
field 16
9.9%
tennis 14
 
8.7%
basketball 13
 
8.1%
futsal 12
 
7.5%
volleyball 11
 
6.8%
foot 9
 
5.6%
soccer 4
 
2.5%
multi-purpose 4
 
2.5%
Other values (3) 8
 
5.0%

서비스상태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size884.0 B
Receipt of
73 
Reservation deadline
16 
Of information
 
3
Results received
 
2

Length

Max length20
Median length10
Mean length11.957447
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOf information
2nd rowOf information
3rd rowOf information
4th rowReservation deadline
5th rowReceipt of

Common Values

ValueCountFrequency (%)
Receipt of 73
77.7%
Reservation deadline 16
 
17.0%
Of information 3
 
3.2%
Results received 2
 
2.1%

Length

2024-05-11T04:01:12.289228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:01:12.636463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
of 76
40.4%
receipt 73
38.8%
reservation 16
 
8.5%
deadline 16
 
8.5%
information 3
 
1.6%
results 2
 
1.1%
received 2
 
1.1%

서비스명
Text

Distinct83
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-05-11T04:01:13.312705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length65
Mean length39.478723
Min length17

Characters and Unicode

Total characters3711
Distinct characters70
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)78.7%

Sample

1st rowWest Seoul Lake Park Futsal Stadium Rental (Weekday week ~08:00)
2nd rowWest Lake Park Futsal Stadium Rental (Weekday Night time, Weekend, Holiday)
3rd rowWest Seoul Lake Park Futsal Stadium Rental (Weekday week 08:00~)
4th row(sat) 2024 BomBom Seoul Forest - Seoul Forest Children&#39;s Expedition
5th row[weekdays night] 2024 Gocheok Sky Dome Futsal Stadium (2Q)
ValueCountFrequency (%)
2024 82
 
15.4%
court 28
 
5.3%
1 21
 
3.9%
tennis 14
 
2.6%
basketball 13
 
2.4%
futsal 12
 
2.3%
use 12
 
2.3%
1~12 12
 
2.3%
31 12
 
2.3%
period 12
 
2.3%
Other values (104) 314
59.0%
2024-05-11T04:01:14.356007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
442
 
11.9%
e 276
 
7.4%
i 194
 
5.2%
2 193
 
5.2%
a 186
 
5.0%
o 180
 
4.9%
t 156
 
4.2%
l 147
 
4.0%
n 137
 
3.7%
d 115
 
3.1%
Other values (60) 1685
45.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2239
60.3%
Decimal Number 464
 
12.5%
Space Separator 442
 
11.9%
Uppercase Letter 309
 
8.3%
Other Punctuation 70
 
1.9%
Open Punctuation 65
 
1.8%
Close Punctuation 65
 
1.8%
Dash Punctuation 40
 
1.1%
Math Symbol 17
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 276
12.3%
i 194
 
8.7%
a 186
 
8.3%
o 180
 
8.0%
t 156
 
7.0%
l 147
 
6.6%
n 137
 
6.1%
d 115
 
5.1%
u 114
 
5.1%
k 105
 
4.7%
Other values (13) 629
28.1%
Uppercase Letter
ValueCountFrequency (%)
F 39
12.6%
S 34
11.0%
W 25
 
8.1%
P 24
 
7.8%
B 19
 
6.1%
R 19
 
6.1%
D 19
 
6.1%
T 19
 
6.1%
N 19
 
6.1%
G 18
 
5.8%
Other values (13) 74
23.9%
Decimal Number
ValueCountFrequency (%)
2 193
41.6%
0 94
20.3%
4 85
18.3%
1 61
 
13.1%
3 16
 
3.4%
8 5
 
1.1%
5 4
 
0.9%
7 3
 
0.6%
6 2
 
0.4%
9 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 39
55.7%
, 17
24.3%
/ 7
 
10.0%
: 4
 
5.7%
# 1
 
1.4%
& 1
 
1.4%
; 1
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 60
92.3%
[ 5
 
7.7%
Close Punctuation
ValueCountFrequency (%)
) 60
92.3%
] 5
 
7.7%
Space Separator
ValueCountFrequency (%)
442
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2548
68.7%
Common 1163
31.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 276
 
10.8%
i 194
 
7.6%
a 186
 
7.3%
o 180
 
7.1%
t 156
 
6.1%
l 147
 
5.8%
n 137
 
5.4%
d 115
 
4.5%
u 114
 
4.5%
k 105
 
4.1%
Other values (36) 938
36.8%
Common
ValueCountFrequency (%)
442
38.0%
2 193
16.6%
0 94
 
8.1%
4 85
 
7.3%
1 61
 
5.2%
( 60
 
5.2%
) 60
 
5.2%
- 40
 
3.4%
. 39
 
3.4%
, 17
 
1.5%
Other values (14) 72
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3711
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
442
 
11.9%
e 276
 
7.4%
i 194
 
5.2%
2 193
 
5.2%
a 186
 
5.0%
o 180
 
4.9%
t 156
 
4.2%
l 147
 
4.0%
n 137
 
3.7%
d 115
 
3.1%
Other values (60) 1685
45.4%

결제방법
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
a charge
87 
a free
 
7

Length

Max length8
Median length8
Mean length7.8510638
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowa charge
2nd rowa charge
3rd rowa charge
4th rowa charge
5th rowa charge

Common Values

ValueCountFrequency (%)
a charge 87
92.6%
a free 7
 
7.4%

Length

2024-05-11T04:01:14.814356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:01:15.150705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a 94
50.0%
charge 87
46.3%
free 7
 
3.7%

장소명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size884.0 B
<NA>
35 
>
13 
Westlake Park
6 
Eungbong Park
5 
Ttukseom Hangang Park
 
3
Other values (14)
32 

Length

Max length46
Median length44
Mean length12.510638
Min length1

Unique

Unique3 ?
Unique (%)3.2%

Sample

1st rowWestlake Park
2nd rowWestlake Park
3rd rowWestlake Park
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 35
37.2%
> 13
 
13.8%
Westlake Park 6
 
6.4%
Eungbong Park 5
 
5.3%
Ttukseom Hangang Park 3
 
3.2%
Yeouido Hangang Park 3
 
3.2%
Banpo Hangang Park 3
 
3.2%
Jamwon Hangang Park >Jamwon Information Center 3
 
3.2%
Jamsil Hangang Park 3
 
3.2%
Gwangnaru Hangang Park 3
 
3.2%
Other values (9) 17
18.1%

Length

2024-05-11T04:01:15.527968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
park 43
22.6%
na 35
18.4%
hangang 32
16.8%
13
 
6.8%
center 7
 
3.7%
westlake 6
 
3.2%
jamwon 6
 
3.2%
eungbong 5
 
2.6%
nanji 5
 
2.6%
information 5
 
2.6%
Other values (15) 33
17.4%

서비스대상
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size884.0 B
All
91 
Children
 
1
All( foreign nationality)
 
1
Adults(foreigners only.), Youth((+13 years old))
 
1

Length

Max length49
Median length4
Mean length4.7659574
Min length4

Unique

Unique3 ?
Unique (%)3.2%

Sample

1st row All
2nd row All
3rd row All
4th row Children
5th row All

Common Values

ValueCountFrequency (%)
All 91
96.8%
Children 1
 
1.1%
All( foreign nationality) 1
 
1.1%
Adults(foreigners only.), Youth((+13 years old)) 1
 
1.1%

Length

2024-05-11T04:01:15.903209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:01:16.221327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
all 92
92.0%
children 1
 
1.0%
foreign 1
 
1.0%
nationality 1
 
1.0%
adults(foreigners 1
 
1.0%
only 1
 
1.0%
youth((+13 1
 
1.0%
years 1
 
1.0%
old 1
 
1.0%

바로가기URL
Text

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-05-11T04:01:16.999956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length92
Median length92
Mean length92
Min length92

Characters and Unicode

Total characters8648
Distinct characters39
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)100.0%

Sample

1st rowhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240430105734069402
2nd rowhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240508102718888983
3rd rowhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240508102250869149
4th rowhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240424162327007428
5th rowhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240325084139631405
ValueCountFrequency (%)
https://yeyak.seoul.go.kr/web/reservation/selectreservview.do?rsv_svc_id=s240430105734069402 1
 
1.1%
https://yeyak.seoul.go.kr/web/reservation/selectreservview.do?rsv_svc_id=s231108104359716676 1
 
1.1%
https://yeyak.seoul.go.kr/web/reservation/selectreservview.do?rsv_svc_id=s231102163210275611 1
 
1.1%
https://yeyak.seoul.go.kr/web/reservation/selectreservview.do?rsv_svc_id=s231030153120733548 1
 
1.1%
https://yeyak.seoul.go.kr/web/reservation/selectreservview.do?rsv_svc_id=s231030151708150434 1
 
1.1%
https://yeyak.seoul.go.kr/web/reservation/selectreservview.do?rsv_svc_id=s231127180612701976 1
 
1.1%
https://yeyak.seoul.go.kr/web/reservation/selectreservview.do?rsv_svc_id=s231127180318293666 1
 
1.1%
https://yeyak.seoul.go.kr/web/reservation/selectreservview.do?rsv_svc_id=s231127175843091098 1
 
1.1%
https://yeyak.seoul.go.kr/web/reservation/selectreservview.do?rsv_svc_id=s231127174944025714 1
 
1.1%
https://yeyak.seoul.go.kr/web/reservation/selectreservview.do?rsv_svc_id=s231127174523276322 1
 
1.1%
Other values (84) 84
89.4%
2024-05-11T04:01:18.246557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 940
 
10.9%
s 658
 
7.6%
/ 470
 
5.4%
r 470
 
5.4%
o 376
 
4.3%
. 376
 
4.3%
t 376
 
4.3%
v 376
 
4.3%
2 325
 
3.8%
1 301
 
3.5%
Other values (29) 3980
46.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5358
62.0%
Decimal Number 1692
 
19.6%
Other Punctuation 1034
 
12.0%
Uppercase Letter 282
 
3.3%
Connector Punctuation 188
 
2.2%
Math Symbol 94
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 940
17.5%
s 658
12.3%
r 470
 
8.8%
o 376
 
7.0%
t 376
 
7.0%
v 376
 
7.0%
i 282
 
5.3%
d 188
 
3.5%
l 188
 
3.5%
k 188
 
3.5%
Other values (10) 1316
24.6%
Decimal Number
ValueCountFrequency (%)
2 325
19.2%
1 301
17.8%
0 214
12.6%
3 195
11.5%
4 137
8.1%
8 136
8.0%
5 115
 
6.8%
7 95
 
5.6%
9 93
 
5.5%
6 81
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/ 470
45.5%
. 376
36.4%
? 94
 
9.1%
: 94
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
V 94
33.3%
R 94
33.3%
S 94
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 188
100.0%
Math Symbol
ValueCountFrequency (%)
= 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5640
65.2%
Common 3008
34.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 940
16.7%
s 658
11.7%
r 470
 
8.3%
o 376
 
6.7%
t 376
 
6.7%
v 376
 
6.7%
i 282
 
5.0%
d 188
 
3.3%
l 188
 
3.3%
k 188
 
3.3%
Other values (13) 1598
28.3%
Common
ValueCountFrequency (%)
/ 470
15.6%
. 376
12.5%
2 325
10.8%
1 301
10.0%
0 214
 
7.1%
3 195
 
6.5%
_ 188
 
6.2%
4 137
 
4.6%
8 136
 
4.5%
5 115
 
3.8%
Other values (6) 551
18.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 940
 
10.9%
s 658
 
7.6%
/ 470
 
5.4%
r 470
 
5.4%
o 376
 
4.3%
. 376
 
4.3%
t 376
 
4.3%
v 376
 
4.3%
2 325
 
3.8%
1 301
 
3.5%
Other values (29) 3980
46.0%

장소X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)40.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.97318
Minimum126.81601
Maximum127.12248
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-05-11T04:01:18.694244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.81601
5-th percentile126.83021
Q1126.89989
median126.98404
Q3127.04027
95-th percentile127.11567
Maximum127.12248
Range0.3064689
Interquartile range (IQR)0.14038092

Descriptive statistics

Standard deviation0.086728679
Coefficient of variation (CV)0.00068304725
Kurtosis-0.9823965
Mean126.97318
Median Absolute Deviation (MAD)0.056488733
Skewness-0.14847618
Sum11935.479
Variance0.0075218638
MonotonicityNot monotonic
2024-05-11T04:01:19.122429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
127.04026740730848 10
 
10.6%
126.8669 8
 
8.5%
126.83021 6
 
6.4%
126.96457353990522 5
 
5.3%
127.02182026085195 5
 
5.3%
127.12224993918046 3
 
3.2%
126.9927298532 3
 
3.2%
127.01227135864973 3
 
3.2%
127.07397601338305 3
 
3.2%
127.08673750627204 3
 
3.2%
Other values (28) 45
47.9%
ValueCountFrequency (%)
126.81601113365264 1
 
1.1%
126.81714 2
 
2.1%
126.83021 6
6.4%
126.8669 8
8.5%
126.88127742009968 2
 
2.1%
126.88147589231296 1
 
1.1%
126.8854210503 2
 
2.1%
126.88542105032526 1
 
1.1%
126.89988648400843 3
 
3.2%
126.90240365454292 3
 
3.2%
ValueCountFrequency (%)
127.12248003426048 2
 
2.1%
127.12224993918046 3
 
3.2%
127.11212908804232 2
 
2.1%
127.08673750627204 3
 
3.2%
127.07397601338305 3
 
3.2%
127.0736346290442 1
 
1.1%
127.0727311334152 1
 
1.1%
127.04079005774229 3
 
3.2%
127.04026740730848 10
10.6%
127.03798839692804 1
 
1.1%

장소Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)40.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.535566
Minimum37.49683
Maximum37.58798
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-05-11T04:01:19.554650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.49683
5-th percentile37.49683
Q137.520102
median37.529363
Q337.549966
95-th percentile37.576929
Maximum37.58798
Range0.09115
Interquartile range (IQR)0.029864384

Descriptive statistics

Standard deviation0.022327134
Coefficient of variation (CV)0.0005948261
Kurtosis-0.19562265
Mean37.535566
Median Absolute Deviation (MAD)0.016987898
Skewness0.30058507
Sum3528.3432
Variance0.00049850093
MonotonicityNot monotonic
2024-05-11T04:01:19.988117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
37.54640567522555 10
 
10.6%
37.49683 8
 
8.5%
37.52707 6
 
6.4%
37.51990244851704 5
 
5.3%
37.5569473910838 5
 
5.3%
37.54996645867258 3
 
3.2%
37.507693251 3
 
3.2%
37.520750186462806 3
 
3.2%
37.52936286135093 3
 
3.2%
37.51762673284826 3
 
3.2%
Other values (28) 45
47.9%
ValueCountFrequency (%)
37.49683 8
8.5%
37.507693251 3
 
3.2%
37.50812415357573 1
 
1.1%
37.516791253319454 1
 
1.1%
37.51762673284826 3
 
3.2%
37.51783 2
 
2.1%
37.51901249973488 1
 
1.1%
37.51990244851704 5
5.3%
37.520700954336434 2
 
2.1%
37.520750186462806 3
 
3.2%
ValueCountFrequency (%)
37.58798 1
 
1.1%
37.58790761786924 1
 
1.1%
37.58604 2
 
2.1%
37.57908 1
 
1.1%
37.57577125294095 2
 
2.1%
37.56464495168799 1
 
1.1%
37.56283678511617 1
 
1.1%
37.5628367851 2
 
2.1%
37.5569473910838 5
5.3%
37.55418 1
 
1.1%

서비스개시시작일시
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-01 00:00:00.0
35 
2023-12-28 00:00:00.0
32 
2024-04-23 00:00:00.0
8 
2024-04-15 00:00:00.0
5 
2023-12-02 00:00:00.0
5 
Other values (6)
9 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique4 ?
Unique (%)4.3%

Sample

1st row2024-05-13 00:00:00.0
2nd row2024-05-13 00:00:00.0
3rd row2024-05-13 00:00:00.0
4th row2024-04-25 00:00:00.0
5th row2024-04-23 00:00:00.0

Common Values

ValueCountFrequency (%)
2023-12-01 00:00:00.0 35
37.2%
2023-12-28 00:00:00.0 32
34.0%
2024-04-23 00:00:00.0 8
 
8.5%
2024-04-15 00:00:00.0 5
 
5.3%
2023-12-02 00:00:00.0 5
 
5.3%
2024-05-13 00:00:00.0 3
 
3.2%
2024-04-22 00:00:00.0 2
 
2.1%
2024-04-25 00:00:00.0 1
 
1.1%
2024-04-01 00:00:00.0 1
 
1.1%
2024-02-27 00:00:00.0 1
 
1.1%

Length

2024-05-11T04:01:20.416593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:00:00.0 94
50.0%
2023-12-01 35
 
18.6%
2023-12-28 32
 
17.0%
2024-04-23 8
 
4.3%
2024-04-15 5
 
2.7%
2023-12-02 5
 
2.7%
2024-05-13 3
 
1.6%
2024-04-22 2
 
1.1%
2024-04-25 1
 
0.5%
2024-04-01 1
 
0.5%
Other values (2) 2
 
1.1%

서비스개시종료일시
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-12-31 00:00:00.0
74 
2024-06-30 00:00:00.0
12 
2024-05-31 00:00:00.0
 
6
2024-05-18 00:00:00.0
 
1
2024-11-25 00:00:00.0
 
1

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique2 ?
Unique (%)2.1%

Sample

1st row2024-06-30 00:00:00.0
2nd row2024-06-30 00:00:00.0
3rd row2024-06-30 00:00:00.0
4th row2024-05-18 00:00:00.0
5th row2024-06-30 00:00:00.0

Common Values

ValueCountFrequency (%)
2024-12-31 00:00:00.0 74
78.7%
2024-06-30 00:00:00.0 12
 
12.8%
2024-05-31 00:00:00.0 6
 
6.4%
2024-05-18 00:00:00.0 1
 
1.1%
2024-11-25 00:00:00.0 1
 
1.1%

Length

2024-05-11T04:01:20.781504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:01:21.099941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00:00.0 94
50.0%
2024-12-31 74
39.4%
2024-06-30 12
 
6.4%
2024-05-31 6
 
3.2%
2024-05-18 1
 
0.5%
2024-11-25 1
 
0.5%

접수시작일시
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-28 00:00:00.0
32 
2023-12-01 14:00:00.0
24 
2024-02-13 09:00:00.0
10 
2024-04-23 10:00:00.0
8 
2024-04-15 14:00:00.0
5 
Other values (9)
15 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique7 ?
Unique (%)7.4%

Sample

1st row2024-05-13 14:00:00.0
2nd row2024-05-13 14:00:00.0
3rd row2024-05-13 14:00:00.0
4th row2024-04-25 09:00:00.0
5th row2024-04-23 10:00:00.0

Common Values

ValueCountFrequency (%)
2023-12-28 00:00:00.0 32
34.0%
2023-12-01 14:00:00.0 24
25.5%
2024-02-13 09:00:00.0 10
 
10.6%
2024-04-23 10:00:00.0 8
 
8.5%
2024-04-15 14:00:00.0 5
 
5.3%
2023-12-02 09:00:00.0 5
 
5.3%
2024-05-13 14:00:00.0 3
 
3.2%
2024-04-25 09:00:00.0 1
 
1.1%
2024-04-22 00:00:00.0 1
 
1.1%
2024-04-28 09:00:00.0 1
 
1.1%
Other values (4) 4
 
4.3%

Length

2024-05-11T04:01:21.613905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:00:00.0 33
17.6%
2023-12-28 32
17.0%
14:00:00.0 32
17.0%
2023-12-01 24
12.8%
09:00:00.0 17
9.0%
2024-02-13 10
 
5.3%
10:00:00.0 9
 
4.8%
2024-04-23 8
 
4.3%
2023-12-02 5
 
2.7%
2024-04-15 5
 
2.7%
Other values (9) 13
 
6.9%

접수종료일시
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-12-31 23:59:00.0
26 
2024-12-31 14:00:00.0
23 
2024-12-31 18:00:00.0
11 
2024-12-31 00:00:00.0
6 
2024-12-31 17:00:00.0
5 
Other values (13)
23 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique8 ?
Unique (%)8.5%

Sample

1st row2024-06-29 17:00:00.0
2nd row2024-06-29 17:00:00.0
3rd row2024-06-29 17:00:00.0
4th row2024-05-17 17:00:00.0
5th row2024-05-31 18:00:00.0

Common Values

ValueCountFrequency (%)
2024-12-31 23:59:00.0 26
27.7%
2024-12-31 14:00:00.0 23
24.5%
2024-12-31 18:00:00.0 11
11.7%
2024-12-31 00:00:00.0 6
 
6.4%
2024-12-31 17:00:00.0 5
 
5.3%
2024-05-29 18:00:00.0 4
 
4.3%
2024-06-29 17:00:00.0 3
 
3.2%
2024-05-28 18:00:00.0 3
 
3.2%
2024-05-30 17:00:00.0 3
 
3.2%
2024-05-31 15:00:00.0 2
 
2.1%
Other values (8) 8
 
8.5%

Length

2024-05-11T04:01:21.952018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-12-31 73
38.8%
23:59:00.0 26
 
13.8%
14:00:00.0 24
 
12.8%
18:00:00.0 20
 
10.6%
17:00:00.0 12
 
6.4%
00:00:00.0 7
 
3.7%
2024-05-29 4
 
2.1%
2024-05-30 3
 
1.6%
2024-05-31 3
 
1.6%
2024-05-28 3
 
1.6%
Other values (10) 13
 
6.9%

지역명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size884.0 B
Sungdong
20 
Yongsan
16 
Mapo
10 
Guro
8 
Seocho
7 
Other values (8)
33 

Length

Max length11
Median length9
Mean length6.9468085
Min length4

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st rowYangcheon
2nd rowYangcheon
3rd rowYangcheon
4th rowSungdong
5th rowGuro

Common Values

ValueCountFrequency (%)
Sungdong 20
21.3%
Yongsan 16
17.0%
Mapo 10
10.6%
Guro 8
 
8.5%
Seocho 7
 
7.4%
Yangcheon 6
 
6.4%
Yongdeungpo 6
 
6.4%
Songpa 6
 
6.4%
Gangdong 5
 
5.3%
Gwangjin 4
 
4.3%
Other values (3) 6
 
6.4%

Length

2024-05-11T04:01:22.431040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sungdong 20
21.3%
yongsan 16
17.0%
mapo 10
10.6%
guro 8
 
8.5%
seocho 7
 
7.4%
yangcheon 6
 
6.4%
yongdeungpo 6
 
6.4%
songpa 6
 
6.4%
gangdong 5
 
5.3%
gwangjin 4
 
4.3%
Other values (3) 6
 
6.4%

Interactions

2024-05-11T04:01:06.495221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:01:05.983152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:01:06.752902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:01:06.260464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T04:01:22.752064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
서비스ID대분류명소분류명서비스상태서비스명결제방법장소명서비스대상바로가기URL장소X좌표장소Y좌표서비스개시시작일시서비스개시종료일시접수시작일시접수종료일시지역명
서비스ID1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대분류명1.0001.0001.0000.0001.0000.5991.0000.9731.0000.1810.8281.0000.5581.0000.9640.836
소분류명1.0001.0001.0000.7491.0000.9980.9320.8301.0000.8820.8310.9150.9460.9480.9430.870
서비스상태1.0000.0000.7491.0000.0000.3080.6080.0001.0000.6850.5730.8190.3350.9440.9860.736
서비스명1.0001.0001.0000.0001.0001.0001.0001.0001.0000.9670.9580.9240.8060.9670.9030.988
결제방법1.0000.5990.9980.3081.0001.0000.2720.7001.0000.2580.4000.8350.2690.9930.9120.694
장소명1.0001.0000.9320.6081.0000.2721.0001.0001.0001.0001.0000.9290.8860.9160.9161.000
서비스대상1.0000.9730.8300.0001.0000.7001.0001.0001.0000.0000.3761.0000.8351.0000.9380.707
바로가기URL1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
장소X좌표1.0000.1810.8820.6850.9670.2581.0000.0001.0001.0000.9390.7820.7760.8400.8930.943
장소Y좌표1.0000.8280.8310.5730.9580.4001.0000.3761.0000.9391.0000.7810.8450.8290.8720.913
서비스개시시작일시1.0001.0000.9150.8190.9240.8350.9291.0001.0000.7820.7811.0000.9881.0000.9890.884
서비스개시종료일시1.0000.5580.9460.3350.8060.2690.8860.8351.0000.7760.8450.9881.0001.0001.0000.772
접수시작일시1.0001.0000.9480.9440.9670.9930.9161.0001.0000.8400.8291.0001.0001.0000.9860.887
접수종료일시1.0000.9640.9430.9860.9030.9120.9160.9381.0000.8930.8720.9891.0000.9861.0000.908
지역명1.0000.8360.8700.7360.9880.6941.0000.7071.0000.9430.9130.8840.7720.8870.9081.000
2024-05-11T04:01:23.145411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
서비스개시시작일시대분류명소분류명접수종료일시서비스개시종료일시장소명결제방법접수시작일시서비스상태지역명서비스대상
서비스개시시작일시1.0000.9310.7050.8990.9490.6740.7910.9820.6340.6140.960
대분류명0.9311.0000.9400.7410.6580.9380.4090.9040.0000.7690.836
소분류명0.7050.9401.0000.7160.6630.7010.9140.7700.5380.5960.644
접수종료일시0.8990.7410.7161.0000.9240.6090.7050.8800.8710.5950.752
서비스개시종료일시0.9490.6580.6630.9241.0000.6150.3220.9480.2760.5340.803
장소명0.6740.9380.7010.6090.6151.0000.1680.5190.3200.9240.848
결제방법0.7910.4090.9140.7050.3220.1681.0000.8630.2030.6170.491
접수시작일시0.9820.9040.7700.8800.9480.5190.8631.0000.8020.5810.943
서비스상태0.6340.0000.5380.8710.2760.3200.2030.8021.0000.5050.000
지역명0.6140.7690.5960.5950.5340.9240.6170.5810.5051.0000.474
서비스대상0.9600.8360.6440.7520.8030.8480.4910.9430.0000.4741.000
2024-05-11T04:01:23.521276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
장소X좌표장소Y좌표대분류명소분류명서비스상태결제방법장소명서비스대상서비스개시시작일시서비스개시종료일시접수시작일시접수종료일시지역명
장소X좌표1.0000.1300.1200.4660.4690.1860.8970.0000.4750.4190.5300.5890.770
장소Y좌표0.1301.0000.6140.3970.3670.2920.9060.2230.4750.4930.5120.5480.689
대분류명0.1200.6141.0000.9400.0000.4090.9380.8360.9310.6580.9040.7410.769
소분류명0.4660.3970.9401.0000.5380.9140.7010.6440.7050.6630.7700.7160.596
서비스상태0.4690.3670.0000.5381.0000.2030.3200.0000.6340.2760.8020.8710.505
결제방법0.1860.2920.4090.9140.2031.0000.1680.4910.7910.3220.8630.7050.617
장소명0.8970.9060.9380.7010.3200.1681.0000.8480.6740.6150.5190.6090.924
서비스대상0.0000.2230.8360.6440.0000.4910.8481.0000.9600.8030.9430.7520.474
서비스개시시작일시0.4750.4750.9310.7050.6340.7910.6740.9601.0000.9490.9820.8990.614
서비스개시종료일시0.4190.4930.6580.6630.2760.3220.6150.8030.9491.0000.9480.9240.534
접수시작일시0.5300.5120.9040.7700.8020.8630.5190.9430.9820.9481.0000.8800.581
접수종료일시0.5890.5480.7410.7160.8710.7050.6090.7520.8990.9240.8801.0000.595
지역명0.7700.6890.7690.5960.5050.6170.9240.4740.6140.5340.5810.5951.000

Missing values

2024-05-11T04:01:07.164819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T04:01:07.850634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

서비스구분서비스ID대분류명소분류명서비스상태서비스명결제방법장소명서비스대상바로가기URL장소X좌표장소Y좌표서비스개시시작일시서비스개시종료일시접수시작일시접수종료일시지역명
0Current SystemS240430105734069402GymsFutsal fieldOf informationWest Seoul Lake Park Futsal Stadium Rental (Weekday week ~08:00)a chargeWestlake ParkAllhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240430105734069402126.8302137.527072024-05-13 00:00:00.02024-06-30 00:00:00.02024-05-13 14:00:00.02024-06-29 17:00:00.0Yangcheon
1Current SystemS240508102718888983GymsFutsal fieldOf informationWest Lake Park Futsal Stadium Rental (Weekday Night time, Weekend, Holiday)a chargeWestlake ParkAllhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240508102718888983126.8302137.527072024-05-13 00:00:00.02024-06-30 00:00:00.02024-05-13 14:00:00.02024-06-29 17:00:00.0Yangcheon
2Current SystemS240508102250869149GymsFutsal fieldOf informationWest Seoul Lake Park Futsal Stadium Rental (Weekday week 08:00~)a chargeWestlake ParkAllhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240508102250869149126.8302137.527072024-05-13 00:00:00.02024-06-30 00:00:00.02024-05-13 14:00:00.02024-06-29 17:00:00.0Yangcheon
3Current SystemS240424162327007428Cultural EventsEventReservation deadline(sat) 2024 BomBom Seoul Forest - Seoul Forest Children&#39;s Expeditiona charge<NA>Childrenhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240424162327007428127.03798837.5446982024-04-25 00:00:00.02024-05-18 00:00:00.02024-04-25 09:00:00.02024-05-17 17:00:00.0Sungdong
4Current SystemS240325084139631405GymsFutsal fieldReceipt of[weekdays night] 2024 Gocheok Sky Dome Futsal Stadium (2Q)a charge<NA>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240325084139631405126.866937.496832024-04-23 00:00:00.02024-06-30 00:00:00.02024-04-23 10:00:00.02024-05-31 18:00:00.0Guro
5Current SystemS240322140815636101GymsSoccer fieldReceipt of(Weekdays daytime) 2024 Gocheok Sky Dome Outdoor Football Stadium(2Q)a charge<NA>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240322140815636101126.866937.496832024-04-23 00:00:00.02024-06-30 00:00:00.02024-04-23 10:00:00.02024-05-29 18:00:00.0Guro
6Current SystemS240322150355275172GymsSoccer fieldReceipt of(Weekdays night) 2024 Gocheok Sky Dome Outdoor Football Stadium (2Q)a charge<NA>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240322150355275172126.866937.496832024-04-23 00:00:00.02024-06-30 00:00:00.02024-04-23 10:00:00.02024-05-28 18:00:00.0Guro
7Current SystemS240322151804365520GymsSoccer fieldReceipt of[Weekend daytime] 2024 Gocheok Sky Dome Outdoor Football Stadium(2Q)a charge<NA>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240322151804365520126.866937.496832024-04-23 00:00:00.02024-06-30 00:00:00.02024-04-23 10:00:00.02024-05-28 18:00:00.0Guro
8Current SystemS240322153800827225GymsSoccer fieldReservation deadline(Weekend night) 2024 Gocheok Sky Dome Outdoor Football Stadium(2Q)a charge<NA>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240322153800827225126.866937.496832024-04-23 00:00:00.02024-06-30 00:00:00.02024-04-23 10:00:00.02024-05-28 18:00:00.0Guro
9Current SystemS240325074006620629GymsFutsal fieldReceipt of[weekdays daytime] 2024 Gocheok Sky Dome Futsal Stadium (2Q)a charge<NA>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S240325074006620629126.866937.496832024-04-23 00:00:00.02024-06-30 00:00:00.02024-04-23 10:00:00.02024-05-29 18:00:00.0Guro
서비스구분서비스ID대분류명소분류명서비스상태서비스명결제방법장소명서비스대상바로가기URL장소X좌표장소Y좌표서비스개시시작일시서비스개시종료일시접수시작일시접수종료일시지역명
84Current SystemS231101171949791044GymsBasketball courtReceipt of2024 Basketball courta charge<NA>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S231101171949791044126.97224537.5167912023-12-01 00:00:00.02024-12-31 00:00:00.02023-12-01 14:00:00.02024-12-31 14:00:00.0Yongsan
85Current SystemS231030163624980083GymsFoot Volleyball courtReceipt of2024 Kickball field 1a charge<NA>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S231030163624980083126.93807637.5411012023-12-01 00:00:00.02024-12-31 00:00:00.02023-12-01 14:00:00.02024-12-31 14:00:00.0Mapo
86Current SystemS231102155329986897GymsBasketball courtReceipt of2024 Basketball court 1a charge<NA>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S231102155329986897126.88147637.5646452023-12-01 00:00:00.02024-12-31 00:00:00.02023-12-01 14:00:00.02024-12-31 14:00:00.0Mapo
87Current SystemS231101170157304283GymsBasketball courtReceipt of2024 Basketball field 1 for the disableda charge<NA>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S231101170157304283127.07273137.5286182023-12-01 00:00:00.02024-12-31 00:00:00.02023-12-01 14:00:00.02024-12-31 14:00:00.0Gwangjin
88Current SystemS231101134143929987GymsBasketball courtReceipt of2024 Basketball courta charge<NA>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S231101134143929987127.07363537.5190122023-12-01 00:00:00.02024-12-31 00:00:00.02023-12-01 14:00:00.02024-12-31 14:00:00.0Songpa
89Current SystemS231121195228107266GymsMulti-purpose StadiumReceipt ofMultipurpose park-weekday(seoulforest, Period of use 2024. 1. 1~12. 31)a free>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S231121195228107266127.0407937.5462962023-12-01 00:00:00.02024-12-31 00:00:00.02024-02-01 10:00:00.02024-12-31 18:00:00.0Sungdong
90Current SystemS231114091643721746GymsTennis courtReservation deadlineTennis court 1 (weekend/holiday, Period of use 2024. 1. 1~12. 31)a charge>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S231114091643721746127.04026737.5464062023-12-01 00:00:00.02024-12-31 00:00:00.02024-02-13 09:00:00.02024-12-31 18:00:00.0Sungdong
91Current SystemS231124090620574246GymsTennis courtReservation deadlineTennis court 2 (weekend/holiday, Period of use 2024. 1. 1~12. 31)a charge>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S231124090620574246127.04026737.5464062023-12-01 00:00:00.02024-12-31 00:00:00.02024-02-13 09:00:00.02024-12-31 18:00:00.0Sungdong
92Current SystemS231124143254807780GymsTennis courtReservation deadlineTennis court 3 (weekend/holiday, Period of use 2024. 1. 1~12. 31)a charge>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S231124143254807780127.04026737.5464062023-12-01 00:00:00.02024-12-31 00:00:00.02024-02-13 09:00:00.02024-12-31 18:00:00.0Sungdong
93Current SystemS231124150238858287GymsTennis courtReservation deadlineTennis court 4 (weekend/holiday, Period of use 2024. 1. 1~12. 31)a charge>Allhttps://yeyak.seoul.go.kr/web/reservation/selectReservView.do?rsv_svc_id=S231124150238858287127.04026737.5464062023-12-01 00:00:00.02024-12-31 00:00:00.02024-02-13 09:00:00.02024-12-31 18:00:00.0Sungdong