Overview

Dataset statistics

Number of variables51
Number of observations10000
Missing cells153334
Missing cells (%)30.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 MiB
Average record size in memory439.0 B

Variable types

Text8
Categorical26
Numeric12
Unsupported5

Dataset

Description대전광역시 유성구의 주차장(공영+민영) 정보를 조회하는 서비스대전광역시 유성구의 주차장(노상+노외+부설) 정보를 조회하는 서비스사용좌표계: EPSG 4326
Author대전광역시 유성구
URLhttps://www.data.go.kr/data/15109854/fileData.do

Alerts

데이터 관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
주차장구분 is highly imbalanced (93.3%)Imbalance
주차장유형 is highly imbalanced (93.4%)Imbalance
주차시설형태 is highly imbalanced (54.7%)Imbalance
계획주차구획(면) 수 is highly imbalanced (99.9%)Imbalance
전용주차구획(기타) 수 is highly imbalanced (80.0%)Imbalance
전기차충전기 수 is highly imbalanced (99.3%)Imbalance
부제시행구분 is highly imbalanced (96.8%)Imbalance
일반인 개방 여부 is highly imbalanced (95.3%)Imbalance
운영방식 is highly imbalanced (93.7%)Imbalance
운영요일 is highly imbalanced (95.2%)Imbalance
평일운영시작시각 is highly imbalanced (94.2%)Imbalance
평일운영종료시각 is highly imbalanced (95.3%)Imbalance
토요일운영시작시각 is highly imbalanced (94.1%)Imbalance
토요일운영종료시각 is highly imbalanced (95.2%)Imbalance
공휴일운영시작시각 is highly imbalanced (94.1%)Imbalance
공휴일운영종료시각 is highly imbalanced (95.2%)Imbalance
요금정보 is highly imbalanced (93.3%)Imbalance
주차기본시간 is highly imbalanced (98.4%)Imbalance
추가단위시간 is highly imbalanced (99.6%)Imbalance
1일주차권요금적용시간 is highly imbalanced (99.7%)Imbalance
월정기권요금 is highly imbalanced (99.5%)Imbalance
결제방법 is highly imbalanced (97.6%)Imbalance
소유주체 is highly imbalanced (94.8%)Imbalance
운영주체 is highly imbalanced (95.4%)Imbalance
건물명 has 8405 (84.0%) missing valuesMissing
허가일자 has 5036 (50.4%) missing valuesMissing
사용검사일자 has 5097 (51.0%) missing valuesMissing
소재지도로명주소 has 366 (3.7%) missing valuesMissing
법정주차구획(면) 수 has 4892 (48.9%) missing valuesMissing
전용주차구획(장애인) 수 has 9694 (96.9%) missing valuesMissing
전용주차구획(경차) 수 has 9935 (99.4%) missing valuesMissing
전용주차구획(여성) 수 has 9994 (99.9%) missing valuesMissing
전용주차구획(전기차) 수 has 9986 (99.9%) missing valuesMissing
전용주차구획(나눔카) 수 has 10000 (100.0%) missing valuesMissing
방범설비유형 has 9995 (> 99.9%) missing valuesMissing
급지구분 has 10000 (100.0%) missing valuesMissing
주차기본요금 has 9972 (99.7%) missing valuesMissing
추가단위요금 has 9973 (99.7%) missing valuesMissing
1일주차권요금 has 9989 (99.9%) missing valuesMissing
특기사항 has 10000 (100.0%) missing valuesMissing
전화번호 has 10000 (100.0%) missing valuesMissing
현장 이미지 has 10000 (100.0%) missing valuesMissing
위도 is highly skewed (γ1 = 49.94228548)Skewed
경도 is highly skewed (γ1 = 90.29057325)Skewed
고유번호(관리번호) has unique valuesUnique
전용주차구획(나눔카) 수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
급지구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
특기사항 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전화번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
현장 이미지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총 주차구획(면) 수 has 3643 (36.4%) zerosZeros
일반주차구획 수 has 3644 (36.4%) zerosZeros

Reproduction

Analysis started2023-12-12 21:50:51.017856
Analysis finished2023-12-12 21:50:53.283657
Duration2.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고유번호(관리번호)
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:50:53.505650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters120000
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st row367-3-016217
2nd row367-3-005325
3rd row367-3-014741
4th row367-3-000012
5th row367-3-003686
ValueCountFrequency (%)
367-3-016217 1
 
< 0.1%
367-3-015338 1
 
< 0.1%
367-3-000414 1
 
< 0.1%
367-3-014898 1
 
< 0.1%
367-3-003570 1
 
< 0.1%
367-3-015221 1
 
< 0.1%
367-3-013557 1
 
< 0.1%
367-3-000698 1
 
< 0.1%
367-3-016020 1
 
< 0.1%
367-3-010938 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-13T06:50:54.210469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 24105
20.1%
0 20523
17.1%
- 20000
16.7%
6 13935
11.6%
7 13509
11.3%
1 8262
 
6.9%
2 4319
 
3.6%
4 4197
 
3.5%
5 4091
 
3.4%
9 3565
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100000
83.3%
Dash Punctuation 20000
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 24105
24.1%
0 20523
20.5%
6 13935
13.9%
7 13509
13.5%
1 8262
 
8.3%
2 4319
 
4.3%
4 4197
 
4.2%
5 4091
 
4.1%
9 3565
 
3.6%
8 3494
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 24105
20.1%
0 20523
17.1%
- 20000
16.7%
6 13935
11.6%
7 13509
11.3%
1 8262
 
6.9%
2 4319
 
3.6%
4 4197
 
3.5%
5 4091
 
3.4%
9 3565
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 24105
20.1%
0 20523
17.1%
- 20000
16.7%
6 13935
11.6%
7 13509
11.3%
1 8262
 
6.9%
2 4319
 
3.6%
4 4197
 
3.5%
5 4091
 
3.4%
9 3565
 
3.0%

건물명
Text

MISSING 

Distinct1511
Distinct (%)94.7%
Missing8405
Missing (%)84.0%
Memory size156.2 KiB
2023-12-13T06:50:54.486868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length5.615674
Min length1

Characters and Unicode

Total characters8957
Distinct characters571
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1449 ?
Unique (%)90.8%

Sample

1st row(주)메디진
2nd row넥스투빌
3rd row제이아그로연구소
4th row덕명지구 공영(6)
5th row노은근린생활시설
ValueCountFrequency (%)
민영주차장 21
 
1.2%
전용주차장 17
 
0.9%
학하지구 12
 
0.7%
죽동 9
 
0.5%
주차장 7
 
0.4%
아파트 6
 
0.3%
제로에너지주택 5
 
0.3%
1동 5
 
0.3%
주택 5
 
0.3%
도룡동 5
 
0.3%
Other values (1577) 1713
94.9%
2023-12-13T06:50:54.881254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
빌 569
 
6.4%
315
 
3.5%
스 262
 
2.9%
라 260
 
2.9%
주 196
 
2.2%
하 170
 
1.9%
아 153
 
1.7%
우 152
 
1.7%
리 149
 
1.7%
지 148
 
1.7%
Other values (561) 6583
73.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8078
90.2%
Space Separator 315
 
3.5%
Uppercase Letter 178
 
2.0%
Decimal Number 163
 
1.8%
Open Punctuation 63
 
0.7%
Close Punctuation 63
 
0.7%
Lowercase Letter 63
 
0.7%
Other Punctuation 21
 
0.2%
Dash Punctuation 10
 
0.1%
Other Symbol 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빌 569
 
7.0%
스 262
 
3.2%
라 260
 
3.2%
주 196
 
2.4%
하 170
 
2.1%
아 153
 
1.9%
우 152
 
1.9%
리 149
 
1.8%
지 148
 
1.8%
대 144
 
1.8%
Other values (499) 5875
72.7%
Uppercase Letter
ValueCountFrequency (%)
A 15
 
8.4%
I 14
 
7.9%
J 13
 
7.3%
B 13
 
7.3%
L 13
 
7.3%
C 11
 
6.2%
H 10
 
5.6%
K 10
 
5.6%
O 9
 
5.1%
S 9
 
5.1%
Other values (14) 61
34.3%
Lowercase Letter
ValueCountFrequency (%)
e 11
17.5%
s 7
11.1%
l 6
9.5%
a 6
9.5%
c 5
 
7.9%
v 3
 
4.8%
o 3
 
4.8%
r 3
 
4.8%
k 3
 
4.8%
i 3
 
4.8%
Other values (8) 13
20.6%
Decimal Number
ValueCountFrequency (%)
1 52
31.9%
2 38
23.3%
4 18
 
11.0%
3 18
 
11.0%
5 10
 
6.1%
9 8
 
4.9%
6 8
 
4.9%
0 5
 
3.1%
8 4
 
2.5%
7 2
 
1.2%
Other Punctuation
ValueCountFrequency (%)
/ 14
66.7%
& 4
 
19.0%
. 3
 
14.3%
Space Separator
ValueCountFrequency (%)
315
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8078
90.2%
Common 636
 
7.1%
Latin 242
 
2.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빌 569
 
7.0%
스 262
 
3.2%
라 260
 
3.2%
주 196
 
2.4%
하 170
 
2.1%
아 153
 
1.9%
우 152
 
1.9%
리 149
 
1.8%
지 148
 
1.8%
대 144
 
1.8%
Other values (499) 5875
72.7%
Latin
ValueCountFrequency (%)
A 15
 
6.2%
I 14
 
5.8%
J 13
 
5.4%
B 13
 
5.4%
L 13
 
5.4%
e 11
 
4.5%
C 11
 
4.5%
H 10
 
4.1%
K 10
 
4.1%
O 9
 
3.7%
Other values (33) 123
50.8%
Common
ValueCountFrequency (%)
315
49.5%
( 63
 
9.9%
) 63
 
9.9%
1 52
 
8.2%
2 38
 
6.0%
4 18
 
2.8%
3 18
 
2.8%
/ 14
 
2.2%
5 10
 
1.6%
- 10
 
1.6%
Other values (8) 35
 
5.5%
Han
ValueCountFrequency (%)
下 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8076
90.2%
ASCII 877
 
9.8%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%
CJK 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
빌 569
 
7.0%
스 262
 
3.2%
라 260
 
3.2%
주 196
 
2.4%
하 170
 
2.1%
아 153
 
1.9%
우 152
 
1.9%
리 149
 
1.8%
지 148
 
1.8%
대 144
 
1.8%
Other values (497) 5873
72.7%
ASCII
ValueCountFrequency (%)
315
35.9%
( 63
 
7.2%
) 63
 
7.2%
1 52
 
5.9%
2 38
 
4.3%
4 18
 
2.1%
3 18
 
2.1%
A 15
 
1.7%
/ 14
 
1.6%
I 14
 
1.6%
Other values (50) 267
30.4%
None
ValueCountFrequency (%)
㈜ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%
CJK
ValueCountFrequency (%)
下 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅍ 1
100.0%

허가일자
Text

MISSING 

Distinct3108
Distinct (%)62.6%
Missing5036
Missing (%)50.4%
Memory size156.2 KiB
2023-12-13T06:50:55.236128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9995971
Min length8

Characters and Unicode

Total characters49638
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1971 ?
Unique (%)39.7%

Sample

1st row2016-06-20
2nd row2014-03-05
3rd row2007-07-09
4th row2002-05-20
5th row2000-06-26
ValueCountFrequency (%)
2002-07-04 13
 
0.3%
2001-06-29 12
 
0.2%
2001-07-03 12
 
0.2%
2001-06-28 11
 
0.2%
2001-07-04 11
 
0.2%
2001-07-02 10
 
0.2%
2003-12-13 10
 
0.2%
1996-06-28 9
 
0.2%
2016-07-08 9
 
0.2%
1995-03-09 9
 
0.2%
Other values (3097) 4857
97.9%
2023-12-13T06:50:55.704766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12900
26.0%
- 9926
20.0%
2 7633
15.4%
1 7467
15.0%
9 2627
 
5.3%
3 1886
 
3.8%
6 1609
 
3.2%
4 1550
 
3.1%
5 1454
 
2.9%
7 1446
 
2.9%
Other values (2) 1140
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39704
80.0%
Dash Punctuation 9926
 
20.0%
Space Separator 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12900
32.5%
2 7633
19.2%
1 7467
18.8%
9 2627
 
6.6%
3 1886
 
4.8%
6 1609
 
4.1%
4 1550
 
3.9%
5 1454
 
3.7%
7 1446
 
3.6%
8 1132
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 9926
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49638
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12900
26.0%
- 9926
20.0%
2 7633
15.4%
1 7467
15.0%
9 2627
 
5.3%
3 1886
 
3.8%
6 1609
 
3.2%
4 1550
 
3.1%
5 1454
 
2.9%
7 1446
 
2.9%
Other values (2) 1140
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49638
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12900
26.0%
- 9926
20.0%
2 7633
15.4%
1 7467
15.0%
9 2627
 
5.3%
3 1886
 
3.8%
6 1609
 
3.2%
4 1550
 
3.1%
5 1454
 
2.9%
7 1446
 
2.9%
Other values (2) 1140
 
2.3%

사용검사일자
Text

MISSING 

Distinct2713
Distinct (%)55.3%
Missing5097
Missing (%)51.0%
Memory size156.2 KiB
2023-12-13T06:50:55.977741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9991842
Min length8

Characters and Unicode

Total characters49026
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1577 ?
Unique (%)32.2%

Sample

1st row2016-08-22
2nd row2014-12-30
3rd row2009-08-11
4th row2002-12-16
5th row2003-12-10
ValueCountFrequency (%)
2011-10-04 225
 
4.6%
2005-05-12 192
 
3.9%
2015-01-19 14
 
0.3%
2002-07-31 10
 
0.2%
2004-04-26 10
 
0.2%
2005-01-14 9
 
0.2%
2004-04-20 9
 
0.2%
2011-11-15 8
 
0.2%
2018-03-08 7
 
0.1%
2012-04-12 7
 
0.1%
Other values (2702) 4410
90.0%
2023-12-13T06:50:56.423641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12825
26.2%
- 9802
20.0%
2 8201
16.7%
1 8073
16.5%
5 1664
 
3.4%
3 1546
 
3.2%
4 1504
 
3.1%
9 1424
 
2.9%
7 1384
 
2.8%
6 1359
 
2.8%
Other values (2) 1244
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39208
80.0%
Dash Punctuation 9802
 
20.0%
Space Separator 16
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12825
32.7%
2 8201
20.9%
1 8073
20.6%
5 1664
 
4.2%
3 1546
 
3.9%
4 1504
 
3.8%
9 1424
 
3.6%
7 1384
 
3.5%
6 1359
 
3.5%
8 1228
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 9802
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49026
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12825
26.2%
- 9802
20.0%
2 8201
16.7%
1 8073
16.5%
5 1664
 
3.4%
3 1546
 
3.2%
4 1504
 
3.1%
9 1424
 
2.9%
7 1384
 
2.8%
6 1359
 
2.8%
Other values (2) 1244
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49026
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12825
26.2%
- 9802
20.0%
2 8201
16.7%
1 8073
16.5%
5 1664
 
3.4%
3 1546
 
3.2%
4 1504
 
3.1%
9 1424
 
2.9%
7 1384
 
2.8%
6 1359
 
2.8%
Other values (2) 1244
 
2.5%

주차장명
Text

Distinct9914
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:50:56.689280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length13.9746
Min length4

Characters and Unicode

Total characters139746
Distinct characters583
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9846 ?
Unique (%)98.5%

Sample

1st row학하동 756-13번지 주차장
2nd row덕명동 608-3번지 주차장
3rd row지족동 431-6번지 주차장
4th row(주)메디진 주차장
5th row넥스투빌 주차장
ValueCountFrequency (%)
주차장 9911
34.7%
구암동 661
 
2.3%
봉명동 575
 
2.0%
장대동 472
 
1.7%
궁동 439
 
1.5%
지족동 343
 
1.2%
원내동 332
 
1.2%
관평동 331
 
1.2%
신성동 293
 
1.0%
용계동 272
 
1.0%
Other values (8273) 14906
52.2%
2023-12-13T06:50:57.060449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18535
 
13.3%
장 10490
 
7.5%
주 10111
 
7.2%
차 9971
 
7.1%
지 8972
 
6.4%
동 8529
 
6.1%
번 8389
 
6.0%
- 7187
 
5.1%
1 6187
 
4.4%
2 4285
 
3.1%
Other values (573) 47090
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79111
56.6%
Decimal Number 34511
24.7%
Space Separator 18535
 
13.3%
Dash Punctuation 7187
 
5.1%
Uppercase Letter 177
 
0.1%
Close Punctuation 65
 
< 0.1%
Open Punctuation 65
 
< 0.1%
Lowercase Letter 63
 
< 0.1%
Other Punctuation 23
 
< 0.1%
Math Symbol 7
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 10490
13.3%
주 10111
12.8%
차 9971
12.6%
지 8972
11.3%
동 8529
10.8%
번 8389
10.6%
대 1044
 
1.3%
봉 870
 
1.1%
명 833
 
1.1%
구 786
 
1.0%
Other values (509) 19116
24.2%
Uppercase Letter
ValueCountFrequency (%)
A 15
 
8.5%
I 14
 
7.9%
B 13
 
7.3%
L 13
 
7.3%
J 12
 
6.8%
C 11
 
6.2%
H 10
 
5.6%
K 10
 
5.6%
O 9
 
5.1%
M 9
 
5.1%
Other values (14) 61
34.5%
Lowercase Letter
ValueCountFrequency (%)
e 11
17.5%
s 7
11.1%
a 6
9.5%
l 6
9.5%
c 5
 
7.9%
v 3
 
4.8%
o 3
 
4.8%
k 3
 
4.8%
r 3
 
4.8%
i 3
 
4.8%
Other values (8) 13
20.6%
Decimal Number
ValueCountFrequency (%)
1 6187
17.9%
2 4285
12.4%
5 3670
10.6%
3 3661
10.6%
4 3659
10.6%
6 3456
10.0%
7 2599
7.5%
0 2508
7.3%
8 2271
 
6.6%
9 2215
 
6.4%
Other Punctuation
ValueCountFrequency (%)
/ 13
56.5%
& 4
 
17.4%
. 3
 
13.0%
@ 2
 
8.7%
, 1
 
4.3%
Space Separator
ValueCountFrequency (%)
18535
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7187
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79111
56.6%
Common 60393
43.2%
Latin 241
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 10490
13.3%
주 10111
12.8%
차 9971
12.6%
지 8972
11.3%
동 8529
10.8%
번 8389
10.6%
대 1044
 
1.3%
봉 870
 
1.1%
명 833
 
1.1%
구 786
 
1.0%
Other values (509) 19116
24.2%
Latin
ValueCountFrequency (%)
A 15
 
6.2%
I 14
 
5.8%
B 13
 
5.4%
L 13
 
5.4%
J 12
 
5.0%
C 11
 
4.6%
e 11
 
4.6%
H 10
 
4.1%
K 10
 
4.1%
O 9
 
3.7%
Other values (33) 123
51.0%
Common
ValueCountFrequency (%)
18535
30.7%
- 7187
 
11.9%
1 6187
 
10.2%
2 4285
 
7.1%
5 3670
 
6.1%
3 3661
 
6.1%
4 3659
 
6.1%
6 3456
 
5.7%
7 2599
 
4.3%
0 2508
 
4.2%
Other values (10) 4646
 
7.7%
Han
ValueCountFrequency (%)
下 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79110
56.6%
ASCII 60633
43.4%
None 1
 
< 0.1%
CJK 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18535
30.6%
- 7187
 
11.9%
1 6187
 
10.2%
2 4285
 
7.1%
5 3670
 
6.1%
3 3661
 
6.0%
4 3659
 
6.0%
6 3456
 
5.7%
7 2599
 
4.3%
0 2508
 
4.1%
Other values (52) 4886
 
8.1%
Hangul
ValueCountFrequency (%)
장 10490
13.3%
주 10111
12.8%
차 9971
12.6%
지 8972
11.3%
동 8529
10.8%
번 8389
10.6%
대 1044
 
1.3%
봉 870
 
1.1%
명 833
 
1.1%
구 786
 
1.0%
Other values (508) 19115
24.2%
None
ValueCountFrequency (%)
㈜ 1
100.0%
CJK
ValueCountFrequency (%)
下 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%

주차장구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
민영
9921 
공영
 
79

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row민영
2nd row민영
3rd row민영
4th row민영
5th row민영

Common Values

ValueCountFrequency (%)
민영 9921
99.2%
공영 79
 
0.8%

Length

2023-12-13T06:50:57.182917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:50:57.272952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민영 9921
99.2%
공영 79
 
0.8%

주차장유형
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부설
9878 
노외
 
90
노상
 
32

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부설
2nd row부설
3rd row부설
4th row부설
5th row부설

Common Values

ValueCountFrequency (%)
부설 9878
98.8%
노외 90
 
0.9%
노상 32
 
0.3%

Length

2023-12-13T06:50:57.387959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:50:57.479173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부설 9878
98.8%
노외 90
 
0.9%
노상 32
 
0.3%

주차시설형태
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
자주식
5278 
<NA>
4651 
기계식
 
69
ㅈ자
 
1
 
1

Length

Max length4
Median length3
Mean length3.4648
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row자주식
2nd row자주식
3rd row자주식
4th row자주식
5th row기계식

Common Values

ValueCountFrequency (%)
자주식 5278
52.8%
<NA> 4651
46.5%
기계식 69
 
0.7%
ㅈ자 1
 
< 0.1%
1
 
< 0.1%

Length

2023-12-13T06:50:57.602282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:50:57.733138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자주식 5278
52.8%
na 4651
46.5%
기계식 69
 
0.7%
ㅈ자 1
 
< 0.1%

소재지도로명주소
Text

MISSING 

Distinct9590
Distinct (%)99.5%
Missing366
Missing (%)3.7%
Memory size156.2 KiB
2023-12-13T06:50:58.082423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length40
Mean length23.636288
Min length2

Characters and Unicode

Total characters227712
Distinct characters356
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9573 ?
Unique (%)99.4%

Sample

1st row대전광역시 유성구 학하남로90번길 25
2nd row대전광역시 유성구 학하서로 162
3rd row대전광역시 유성구 노은서로 137
4th row대전광역시 유성구 유성대로1628번길 37-7
5th row대전광역시 유성구 유성대로736번길 19
ValueCountFrequency (%)
대전광역시 9631
22.9%
유성구 9618
22.9%
용계동 261
 
0.6%
장대동 238
 
0.6%
봉명동 223
 
0.5%
대정동 221
 
0.5%
덕명동 177
 
0.4%
원신흥동 155
 
0.4%
원내동 135
 
0.3%
복용동 128
 
0.3%
Other values (4521) 21203
50.5%
2023-12-13T06:50:58.735004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32726
 
14.4%
대 12814
 
5.6%
성 11375
 
5.0%
구 10683
 
4.7%
유 10610
 
4.7%
전 9999
 
4.4%
시 9643
 
4.2%
광 9638
 
4.2%
역 9633
 
4.2%
로 9348
 
4.1%
Other values (346) 101243
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139937
61.5%
Decimal Number 41773
 
18.3%
Space Separator 32726
 
14.4%
Open Punctuation 4832
 
2.1%
Close Punctuation 4831
 
2.1%
Dash Punctuation 3280
 
1.4%
Other Punctuation 272
 
0.1%
Uppercase Letter 43
 
< 0.1%
Lowercase Letter 17
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 12814
 
9.2%
성 11375
 
8.1%
구 10683
 
7.6%
유 10610
 
7.6%
전 9999
 
7.1%
시 9643
 
6.9%
광 9638
 
6.9%
역 9633
 
6.9%
로 9348
 
6.7%
길 6760
 
4.8%
Other values (300) 39434
28.2%
Uppercase Letter
ValueCountFrequency (%)
E 5
11.6%
A 5
11.6%
T 4
 
9.3%
S 3
 
7.0%
H 3
 
7.0%
B 3
 
7.0%
F 2
 
4.7%
C 2
 
4.7%
I 2
 
4.7%
N 2
 
4.7%
Other values (8) 12
27.9%
Lowercase Letter
ValueCountFrequency (%)
u 3
17.6%
s 3
17.6%
o 3
17.6%
l 1
 
5.9%
e 1
 
5.9%
r 1
 
5.9%
h 1
 
5.9%
t 1
 
5.9%
n 1
 
5.9%
i 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
1 8469
20.3%
2 5626
13.5%
5 4289
10.3%
3 4232
10.1%
6 3927
9.4%
4 3776
9.0%
7 3329
 
8.0%
8 2782
 
6.7%
0 2733
 
6.5%
9 2610
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 267
98.2%
/ 5
 
1.8%
Space Separator
ValueCountFrequency (%)
32726
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4832
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4831
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3280
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 139937
61.5%
Common 87714
38.5%
Latin 61
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 12814
 
9.2%
성 11375
 
8.1%
구 10683
 
7.6%
유 10610
 
7.6%
전 9999
 
7.1%
시 9643
 
6.9%
광 9638
 
6.9%
역 9633
 
6.9%
로 9348
 
6.7%
길 6760
 
4.8%
Other values (300) 39434
28.2%
Latin
ValueCountFrequency (%)
E 5
 
8.2%
A 5
 
8.2%
T 4
 
6.6%
S 3
 
4.9%
H 3
 
4.9%
B 3
 
4.9%
u 3
 
4.9%
s 3
 
4.9%
o 3
 
4.9%
F 2
 
3.3%
Other values (20) 27
44.3%
Common
ValueCountFrequency (%)
32726
37.3%
1 8469
 
9.7%
2 5626
 
6.4%
( 4832
 
5.5%
) 4831
 
5.5%
5 4289
 
4.9%
3 4232
 
4.8%
6 3927
 
4.5%
4 3776
 
4.3%
7 3329
 
3.8%
Other values (6) 11677
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139937
61.5%
ASCII 87774
38.5%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32726
37.3%
1 8469
 
9.6%
2 5626
 
6.4%
( 4832
 
5.5%
) 4831
 
5.5%
5 4289
 
4.9%
3 4232
 
4.8%
6 3927
 
4.5%
4 3776
 
4.3%
7 3329
 
3.8%
Other values (35) 11737
 
13.4%
Hangul
ValueCountFrequency (%)
대 12814
 
9.2%
성 11375
 
8.1%
구 10683
 
7.6%
유 10610
 
7.6%
전 9999
 
7.1%
시 9643
 
6.9%
광 9638
 
6.9%
역 9633
 
6.9%
로 9348
 
6.7%
길 6760
 
4.8%
Other values (300) 39434
28.2%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%

소재지지번주소
Text

Distinct9990
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:50:59.301751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length18.9194
Min length14

Characters and Unicode

Total characters189194
Distinct characters226
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9980 ?
Unique (%)99.8%

Sample

1st row대전광역시 유성구 학하동 756-13
2nd row대전광역시 유성구 덕명동 608-3
3rd row대전광역시 유성구 지족동 431-6
4th row대전광역시 유성구 전민동 461-57
5th row대전광역시 유성구 장대동 278-2
ValueCountFrequency (%)
유성구 9997
25.0%
대전광역시 9996
25.0%
구암동 763
 
1.9%
봉명동 669
 
1.7%
장대동 646
 
1.6%
궁동 489
 
1.2%
지족동 466
 
1.2%
원내동 432
 
1.1%
신성동 392
 
1.0%
전민동 380
 
0.9%
Other values (7741) 15778
39.4%
2023-12-13T06:51:00.173881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30010
15.9%
대 11138
 
5.9%
구 10815
 
5.7%
성 10552
 
5.6%
전 10387
 
5.5%
유 10006
 
5.3%
동 10004
 
5.3%
광 10002
 
5.3%
시 10001
 
5.3%
역 10000
 
5.3%
Other values (216) 66279
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 109651
58.0%
Decimal Number 40955
 
21.6%
Space Separator 30010
 
15.9%
Dash Punctuation 8571
 
4.5%
Control 2
 
< 0.1%
Math Symbol 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 11138
10.2%
구 10815
9.9%
성 10552
9.6%
전 10387
9.5%
유 10006
9.1%
동 10004
9.1%
광 10002
9.1%
시 10001
9.1%
역 10000
9.1%
봉 954
 
0.9%
Other values (198) 15792
14.4%
Decimal Number
ValueCountFrequency (%)
1 7243
17.7%
2 4931
12.0%
5 4441
10.8%
3 4438
10.8%
4 4307
10.5%
6 4200
10.3%
7 3069
7.5%
0 2959
7.2%
8 2698
 
6.6%
9 2669
 
6.5%
Space Separator
ValueCountFrequency (%)
30010
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8571
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 109651
58.0%
Common 79541
42.0%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 11138
10.2%
구 10815
9.9%
성 10552
9.6%
전 10387
9.5%
유 10006
9.1%
동 10004
9.1%
광 10002
9.1%
시 10001
9.1%
역 10000
9.1%
봉 954
 
0.9%
Other values (198) 15792
14.4%
Common
ValueCountFrequency (%)
30010
37.7%
- 8571
 
10.8%
1 7243
 
9.1%
2 4931
 
6.2%
5 4441
 
5.6%
3 4438
 
5.6%
4 4307
 
5.4%
6 4200
 
5.3%
7 3069
 
3.9%
0 2959
 
3.7%
Other values (6) 5372
 
6.8%
Latin
ValueCountFrequency (%)
B 1
50.0%
e 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 109651
58.0%
ASCII 79543
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30010
37.7%
- 8571
 
10.8%
1 7243
 
9.1%
2 4931
 
6.2%
5 4441
 
5.6%
3 4438
 
5.6%
4 4307
 
5.4%
6 4200
 
5.3%
7 3069
 
3.9%
0 2959
 
3.7%
Other values (8) 5374
 
6.8%
Hangul
ValueCountFrequency (%)
대 11138
10.2%
구 10815
9.9%
성 10552
9.6%
전 10387
9.5%
유 10006
9.1%
동 10004
9.1%
광 10002
9.1%
시 10001
9.1%
역 10000
9.1%
봉 954
 
0.9%
Other values (198) 15792
14.4%

총 주차구획(면) 수
Real number (ℝ)

ZEROS 

Distinct234
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5543
Minimum0
Maximum2975
Zeros3643
Zeros (%)36.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:51:00.379622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q35
95-th percentile25
Maximum2975
Range2975
Interquartile range (IQR)5

Descriptive statistics

Standard deviation85.894742
Coefficient of variation (CV)6.8418583
Kurtosis297.53761
Mean12.5543
Median Absolute Deviation (MAD)2
Skewness15.027577
Sum125543
Variance7377.9066
MonotonicityNot monotonic
2023-12-13T06:51:00.535197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3643
36.4%
2 1030
 
10.3%
1 932
 
9.3%
4 774
 
7.7%
3 672
 
6.7%
5 628
 
6.3%
6 484
 
4.8%
8 354
 
3.5%
7 272
 
2.7%
10 124
 
1.2%
Other values (224) 1087
 
10.9%
ValueCountFrequency (%)
0 3643
36.4%
1 932
 
9.3%
2 1030
 
10.3%
3 672
 
6.7%
4 774
 
7.7%
5 628
 
6.3%
6 484
 
4.8%
7 272
 
2.7%
8 354
 
3.5%
9 89
 
0.9%
ValueCountFrequency (%)
2975 1
< 0.1%
1838 1
< 0.1%
1734 1
< 0.1%
1677 1
< 0.1%
1587 1
< 0.1%
1573 1
< 0.1%
1350 1
< 0.1%
1324 1
< 0.1%
1321 1
< 0.1%
1271 1
< 0.1%

법정주차구획(면) 수
Real number (ℝ)

MISSING 

Distinct204
Distinct (%)4.0%
Missing4892
Missing (%)48.9%
Infinite0
Infinite (%)0.0%
Mean20.164252
Minimum0
Maximum2939
Zeros9
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:51:00.668875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q36
95-th percentile34.65
Maximum2939
Range2939
Interquartile range (IQR)4

Descriptive statistics

Standard deviation113.55371
Coefficient of variation (CV)5.6314366
Kurtosis159.38763
Mean20.164252
Median Absolute Deviation (MAD)2
Skewness10.95987
Sum102999
Variance12894.444
MonotonicityNot monotonic
2023-12-13T06:51:00.841759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 913
 
9.1%
1 909
 
9.1%
3 606
 
6.1%
4 588
 
5.9%
5 476
 
4.8%
6 400
 
4.0%
8 246
 
2.5%
7 205
 
2.1%
10 76
 
0.8%
9 63
 
0.6%
Other values (194) 626
 
6.3%
(Missing) 4892
48.9%
ValueCountFrequency (%)
0 9
 
0.1%
1 909
9.1%
2 913
9.1%
3 606
6.1%
4 588
5.9%
5 476
4.8%
6 400
4.0%
7 205
 
2.1%
8 246
 
2.5%
9 63
 
0.6%
ValueCountFrequency (%)
2939 1
< 0.1%
1624 1
< 0.1%
1539 1
< 0.1%
1532 1
< 0.1%
1472 1
< 0.1%
1342 1
< 0.1%
1321 1
< 0.1%
1285 1
< 0.1%
1278 1
< 0.1%
1243 1
< 0.1%

계획주차구획(면) 수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
0
 
1

Length

Max length4
Median length4
Mean length3.9997
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9999
> 99.9%
0 1
 
< 0.1%

Length

2023-12-13T06:51:00.975387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:01.059024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
0 1
 
< 0.1%

일반주차구획 수
Real number (ℝ)

ZEROS 

Distinct223
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.2118
Minimum0
Maximum2939
Zeros3644
Zeros (%)36.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:51:01.152925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q35
95-th percentile24
Maximum2939
Range2939
Interquartile range (IQR)5

Descriptive statistics

Standard deviation82.423552
Coefficient of variation (CV)6.7495006
Kurtosis302.0005
Mean12.2118
Median Absolute Deviation (MAD)2
Skewness14.99329
Sum122118
Variance6793.6419
MonotonicityNot monotonic
2023-12-13T06:51:01.274345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3644
36.4%
2 1033
 
10.3%
1 932
 
9.3%
4 775
 
7.8%
3 669
 
6.7%
5 628
 
6.3%
6 482
 
4.8%
8 354
 
3.5%
7 275
 
2.8%
10 127
 
1.3%
Other values (213) 1081
 
10.8%
ValueCountFrequency (%)
0 3644
36.4%
1 932
 
9.3%
2 1033
 
10.3%
3 669
 
6.7%
4 775
 
7.8%
5 628
 
6.3%
6 482
 
4.8%
7 275
 
2.8%
8 354
 
3.5%
9 90
 
0.9%
ValueCountFrequency (%)
2939 1
< 0.1%
1624 1
< 0.1%
1539 1
< 0.1%
1532 1
< 0.1%
1472 1
< 0.1%
1342 1
< 0.1%
1321 1
< 0.1%
1285 1
< 0.1%
1278 1
< 0.1%
1243 1
< 0.1%

전용주차구획(장애인) 수
Real number (ℝ)

MISSING 

Distinct38
Distinct (%)12.4%
Missing9694
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean6.372549
Minimum0
Maximum49
Zeros10
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:51:01.396163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q36
95-th percentile26.5
Maximum49
Range49
Interquartile range (IQR)5

Descriptive statistics

Standard deviation9.4142427
Coefficient of variation (CV)1.4773119
Kurtosis6.3038011
Mean6.372549
Median Absolute Deviation (MAD)1
Skewness2.4778149
Sum1950
Variance88.627965
MonotonicityNot monotonic
2023-12-13T06:51:01.535482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
1 99
 
1.0%
2 57
 
0.6%
3 28
 
0.3%
5 14
 
0.1%
4 11
 
0.1%
6 11
 
0.1%
0 10
 
0.1%
7 7
 
0.1%
14 6
 
0.1%
8 5
 
0.1%
Other values (28) 58
 
0.6%
(Missing) 9694
96.9%
ValueCountFrequency (%)
0 10
 
0.1%
1 99
1.0%
2 57
0.6%
3 28
 
0.3%
4 11
 
0.1%
5 14
 
0.1%
6 11
 
0.1%
7 7
 
0.1%
8 5
 
0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
49 1
< 0.1%
48 2
< 0.1%
46 1
< 0.1%
44 1
< 0.1%
41 1
< 0.1%
39 2
< 0.1%
36 1
< 0.1%
35 1
< 0.1%
34 1
< 0.1%
29 1
< 0.1%

전용주차구획(경차) 수
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)33.8%
Missing9935
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean8.2769231
Minimum1
Maximum61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:51:01.641100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q310
95-th percentile26.4
Maximum61
Range60
Interquartile range (IQR)8

Descriptive statistics

Standard deviation12.231501
Coefficient of variation (CV)1.4777836
Kurtosis8.1390133
Mean8.2769231
Median Absolute Deviation (MAD)2
Skewness2.7314
Sum538
Variance149.60962
MonotonicityNot monotonic
2023-12-13T06:51:01.735261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 16
 
0.2%
2 13
 
0.1%
3 7
 
0.1%
4 4
 
< 0.1%
5 3
 
< 0.1%
10 2
 
< 0.1%
19 2
 
< 0.1%
20 2
 
< 0.1%
6 2
 
< 0.1%
9 2
 
< 0.1%
Other values (12) 12
 
0.1%
(Missing) 9935
99.4%
ValueCountFrequency (%)
1 16
0.2%
2 13
0.1%
3 7
0.1%
4 4
 
< 0.1%
5 3
 
< 0.1%
6 2
 
< 0.1%
8 1
 
< 0.1%
9 2
 
< 0.1%
10 2
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
61 1
< 0.1%
54 1
< 0.1%
47 1
< 0.1%
27 1
< 0.1%
24 1
< 0.1%
22 1
< 0.1%
20 2
< 0.1%
19 2
< 0.1%
18 1
< 0.1%
17 1
< 0.1%

전용주차구획(여성) 수
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)100.0%
Missing9994
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean149.16667
Minimum1
Maximum360
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:51:01.826711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.25
Q12.5
median116
Q3282
95-th percentile345
Maximum360
Range359
Interquartile range (IQR)279.5

Descriptive statistics

Standard deviation166.19316
Coefficient of variation (CV)1.1141441
Kurtosis-2.6464787
Mean149.16667
Median Absolute Deviation (MAD)114.5
Skewness0.24795404
Sum895
Variance27620.167
MonotonicityNot monotonic
2023-12-13T06:51:01.920385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 1
 
< 0.1%
2 1
 
< 0.1%
4 1
 
< 0.1%
228 1
 
< 0.1%
360 1
 
< 0.1%
300 1
 
< 0.1%
(Missing) 9994
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
4 1
< 0.1%
228 1
< 0.1%
300 1
< 0.1%
360 1
< 0.1%
ValueCountFrequency (%)
360 1
< 0.1%
300 1
< 0.1%
228 1
< 0.1%
4 1
< 0.1%
2 1
< 0.1%
1 1
< 0.1%

전용주차구획(전기차) 수
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)42.9%
Missing9986
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean3.5
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:51:02.020547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1.5
Q33.75
95-th percentile11.55
Maximum20
Range19
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation5.0649626
Coefficient of variation (CV)1.4471322
Kurtosis10.022411
Mean3.5
Median Absolute Deviation (MAD)0.5
Skewness3.0520997
Sum49
Variance25.653846
MonotonicityNot monotonic
2023-12-13T06:51:02.113158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 7
 
0.1%
4 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%
3 1
 
< 0.1%
20 1
 
< 0.1%
(Missing) 9986
99.9%
ValueCountFrequency (%)
1 7
0.1%
2 2
 
< 0.1%
3 1
 
< 0.1%
4 2
 
< 0.1%
7 1
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
7 1
 
< 0.1%
4 2
 
< 0.1%
3 1
 
< 0.1%
2 2
 
< 0.1%
1 7
0.1%

전용주차구획(나눔카) 수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전용주차구획(기타) 수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9688 
0
 
312

Length

Max length4
Median length4
Mean length3.9064
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9688
96.9%
0 312
 
3.1%

Length

2023-12-13T06:51:02.224882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:02.315145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9688
96.9%
0 312
 
3.1%

전기차충전기 수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9994 
1
 
6

Length

Max length4
Median length4
Mean length3.9982
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9994
99.9%
1 6
 
0.1%

Length

2023-12-13T06:51:02.468940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:02.562279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9994
99.9%
1 6
 
0.1%

방범설비유형
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing9995
Missing (%)> 99.9%
Memory size156.2 KiB
2023-12-13T06:51:02.683195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length10.2
Min length10

Characters and Unicode

Total characters51
Distinct characters12
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)40.0%

Sample

1st rowCCTV(수량:2)
2nd rowCCTV(수량:15)
3rd rowCCTV(수량:2)
4th rowCCTV(수량:4)
5th rowCCTV(수량:2)
ValueCountFrequency (%)
cctv(수량:2 3
60.0%
cctv(수량:15 1
 
20.0%
cctv(수량:4 1
 
20.0%
2023-12-13T06:51:02.971173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 10
19.6%
T 5
9.8%
V 5
9.8%
( 5
9.8%
수 5
9.8%
량 5
9.8%
: 5
9.8%
) 5
9.8%
2 3
 
5.9%
1 1
 
2.0%
Other values (2) 2
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 20
39.2%
Other Letter 10
19.6%
Decimal Number 6
 
11.8%
Open Punctuation 5
 
9.8%
Other Punctuation 5
 
9.8%
Close Punctuation 5
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 1
 
16.7%
5 1
 
16.7%
4 1
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
C 10
50.0%
T 5
25.0%
V 5
25.0%
Other Letter
ValueCountFrequency (%)
수 5
50.0%
량 5
50.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
: 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21
41.2%
Latin 20
39.2%
Hangul 10
19.6%

Most frequent character per script

Common
ValueCountFrequency (%)
( 5
23.8%
: 5
23.8%
) 5
23.8%
2 3
14.3%
1 1
 
4.8%
5 1
 
4.8%
4 1
 
4.8%
Latin
ValueCountFrequency (%)
C 10
50.0%
T 5
25.0%
V 5
25.0%
Hangul
ValueCountFrequency (%)
수 5
50.0%
량 5
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41
80.4%
Hangul 10
 
19.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 10
24.4%
T 5
12.2%
V 5
12.2%
( 5
12.2%
: 5
12.2%
) 5
12.2%
2 3
 
7.3%
1 1
 
2.4%
5 1
 
2.4%
4 1
 
2.4%
Hangul
ValueCountFrequency (%)
수 5
50.0%
량 5
50.0%

급지구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

부제시행구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9967 
미시행
 
33

Length

Max length4
Median length4
Mean length3.9967
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9967
99.7%
미시행 33
 
0.3%

Length

2023-12-13T06:51:03.141301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:03.584241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9967
99.7%
미시행 33
 
0.3%

일반인 개방 여부
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9918 
개방
 
65
미개방
 
17

Length

Max length4
Median length4
Mean length3.9853
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9918
99.2%
개방 65
 
0.7%
미개방 17
 
0.2%

Length

2023-12-13T06:51:03.705641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:03.842696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9918
99.2%
개방 65
 
0.7%
미개방 17
 
0.2%

운영방식
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9886 
일반(시간제)주차장
 
82
일반노상주차장
 
32

Length

Max length10
Median length4
Mean length4.0588
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9886
98.9%
일반(시간제)주차장 82
 
0.8%
일반노상주차장 32
 
0.3%

Length

2023-12-13T06:51:03.988114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:04.114704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9886
98.9%
일반(시간제)주차장 82
 
0.8%
일반노상주차장 32
 
0.3%

운영요일
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9881 
평일+토요일+공휴일
 
115
평일
 
3
평일+토요일
 
1

Length

Max length10
Median length4
Mean length4.0686
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9881
98.8%
평일+토요일+공휴일 115
 
1.1%
평일 3
 
< 0.1%
평일+토요일 1
 
< 0.1%

Length

2023-12-13T06:51:04.250623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:04.390563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9881
98.8%
평일+토요일+공휴일 115
 
1.1%
평일 3
 
< 0.1%
평일+토요일 1
 
< 0.1%

평일운영시작시각
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9885 
00:00
 
114
10:30
 
1

Length

Max length6
Median length4
Mean length4.023
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9885
98.9%
00:00 114
 
1.1%
10:30 1
 
< 0.1%

Length

2023-12-13T06:51:04.526165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:04.633430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9885
98.9%
00:00 114
 
1.1%
10:30 1
 
< 0.1%

평일운영종료시각
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9885 
23:59
 
110
00:00
 
4
23:00
 
1

Length

Max length6
Median length4
Mean length4.023
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9885
98.9%
23:59 110
 
1.1%
00:00 4
 
< 0.1%
23:00 1
 
< 0.1%

Length

2023-12-13T06:51:04.800431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:04.922249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9885
98.9%
23:59 110
 
1.1%
00:00 4
 
< 0.1%
23:00 1
 
< 0.1%

토요일운영시작시각
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9882 
00:00
 
117
10:30
 
1

Length

Max length6
Median length4
Mean length4.0236
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9882
98.8%
00:00 117
 
1.2%
10:30 1
 
< 0.1%

Length

2023-12-13T06:51:05.032938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:05.133959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9882
98.8%
00:00 117
 
1.2%
10:30 1
 
< 0.1%

토요일운영종료시각
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9882 
23:59
 
113
00:00
 
4
23:00
 
1

Length

Max length6
Median length4
Mean length4.0236
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9882
98.8%
23:59 113
 
1.1%
00:00 4
 
< 0.1%
23:00 1
 
< 0.1%

Length

2023-12-13T06:51:05.255504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:05.357923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9882
98.8%
23:59 113
 
1.1%
00:00 4
 
< 0.1%
23:00 1
 
< 0.1%

공휴일운영시작시각
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9882 
00:00
 
117
10:30
 
1

Length

Max length6
Median length4
Mean length4.0236
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9882
98.8%
00:00 117
 
1.2%
10:30 1
 
< 0.1%

Length

2023-12-13T06:51:05.514437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:05.636077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9882
98.8%
00:00 117
 
1.2%
10:30 1
 
< 0.1%

공휴일운영종료시각
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9882 
23:59
 
113
00:00
 
4
23:00
 
1

Length

Max length6
Median length4
Mean length4.0236
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9882
98.8%
23:59 113
 
1.1%
00:00 4
 
< 0.1%
23:00 1
 
< 0.1%

Length

2023-12-13T06:51:05.763740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:05.889994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9882
98.8%
23:59 113
 
1.1%
00:00 4
 
< 0.1%
23:00 1
 
< 0.1%

요금정보
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부분적 유료
9878 
무료
 
88
유료
 
34

Length

Max length6
Median length6
Mean length5.9512
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부분적 유료
2nd row부분적 유료
3rd row부분적 유료
4th row부분적 유료
5th row부분적 유료

Common Values

ValueCountFrequency (%)
부분적 유료 9878
98.8%
무료 88
 
0.9%
유료 34
 
0.3%

Length

2023-12-13T06:51:06.004955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:06.118164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 9912
49.9%
부분적 9878
49.7%
무료 88
 
0.4%

주차기본시간
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9972 
30
 
14
15
 
7
10
 
7

Length

Max length4
Median length4
Mean length3.9944
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9972
99.7%
30 14
 
0.1%
15 7
 
0.1%
10 7
 
0.1%

Length

2023-12-13T06:51:06.219409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:06.346301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9972
99.7%
30 14
 
0.1%
15 7
 
0.1%
10 7
 
0.1%

주차기본요금
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)25.0%
Missing9972
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean837.5
Minimum100
Maximum2000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:51:06.445396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile100
Q1400
median1000
Q31000
95-th percentile2000
Maximum2000
Range1900
Interquartile range (IQR)600

Descriptive statistics

Standard deviation612.61809
Coefficient of variation (CV)0.73148429
Kurtosis-0.35654662
Mean837.5
Median Absolute Deviation (MAD)600
Skewness0.71281913
Sum23450
Variance375300.93
MonotonicityNot monotonic
2023-12-13T06:51:06.555280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1000 10
 
0.1%
400 6
 
0.1%
2000 4
 
< 0.1%
100 4
 
< 0.1%
500 2
 
< 0.1%
1500 1
 
< 0.1%
150 1
 
< 0.1%
(Missing) 9972
99.7%
ValueCountFrequency (%)
100 4
 
< 0.1%
150 1
 
< 0.1%
400 6
0.1%
500 2
 
< 0.1%
1000 10
0.1%
1500 1
 
< 0.1%
2000 4
 
< 0.1%
ValueCountFrequency (%)
2000 4
 
< 0.1%
1500 1
 
< 0.1%
1000 10
0.1%
500 2
 
< 0.1%
400 6
0.1%
150 1
 
< 0.1%
100 4
 
< 0.1%

추가단위시간
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9997 
15
 
3

Length

Max length4
Median length4
Mean length3.9994
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9997
> 99.9%
15 3
 
< 0.1%

Length

2023-12-13T06:51:06.686638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:06.768187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9997
> 99.9%
15 3
 
< 0.1%

추가단위요금
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)33.3%
Missing9973
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean701.85185
Minimum100
Maximum2000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:51:06.843453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile165
Q1300
median500
Q31000
95-th percentile1850
Maximum2000
Range1900
Interquartile range (IQR)700

Descriptive statistics

Standard deviation522.65621
Coefficient of variation (CV)0.74468167
Kurtosis0.95458564
Mean701.85185
Median Absolute Deviation (MAD)300
Skewness1.1672962
Sum18950
Variance273169.52
MonotonicityNot monotonic
2023-12-13T06:51:06.937686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1000 8
 
0.1%
500 5
 
0.1%
400 3
 
< 0.1%
200 3
 
< 0.1%
300 3
 
< 0.1%
2000 2
 
< 0.1%
100 1
 
< 0.1%
1500 1
 
< 0.1%
150 1
 
< 0.1%
(Missing) 9973
99.7%
ValueCountFrequency (%)
100 1
 
< 0.1%
150 1
 
< 0.1%
200 3
 
< 0.1%
300 3
 
< 0.1%
400 3
 
< 0.1%
500 5
0.1%
1000 8
0.1%
1500 1
 
< 0.1%
2000 2
 
< 0.1%
ValueCountFrequency (%)
2000 2
 
< 0.1%
1500 1
 
< 0.1%
1000 8
0.1%
500 5
0.1%
400 3
 
< 0.1%
300 3
 
< 0.1%
200 3
 
< 0.1%
150 1
 
< 0.1%
100 1
 
< 0.1%

1일주차권요금적용시간
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9996 
12000
 
3
10
 
1

Length

Max length5
Median length4
Mean length4.0001
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9996
> 99.9%
12000 3
 
< 0.1%
10 1
 
< 0.1%

Length

2023-12-13T06:51:07.148984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:07.240560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9996
> 99.9%
12000 3
 
< 0.1%
10 1
 
< 0.1%

1일주차권요금
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)63.6%
Missing9989
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean20900
Minimum2400
Maximum97000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:51:07.311452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2400
5-th percentile4450
Q19000
median10000
Q312000
95-th percentile73500
Maximum97000
Range94600
Interquartile range (IQR)3000

Descriptive statistics

Standard deviation28192.375
Coefficient of variation (CV)1.3489175
Kurtosis5.8468518
Mean20900
Median Absolute Deviation (MAD)2000
Skewness2.4430117
Sum229900
Variance7.9481 × 108
MonotonicityNot monotonic
2023-12-13T06:51:07.396168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
10000 3
 
< 0.1%
12000 3
 
< 0.1%
2400 1
 
< 0.1%
97000 1
 
< 0.1%
6500 1
 
< 0.1%
50000 1
 
< 0.1%
8000 1
 
< 0.1%
(Missing) 9989
99.9%
ValueCountFrequency (%)
2400 1
 
< 0.1%
6500 1
 
< 0.1%
8000 1
 
< 0.1%
10000 3
< 0.1%
12000 3
< 0.1%
50000 1
 
< 0.1%
97000 1
 
< 0.1%
ValueCountFrequency (%)
97000 1
 
< 0.1%
50000 1
 
< 0.1%
12000 3
< 0.1%
10000 3
< 0.1%
8000 1
 
< 0.1%
6500 1
 
< 0.1%
2400 1
 
< 0.1%

월정기권요금
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9991 
43000
 
4
140000
 
3
72000
 
1
100000
 
1

Length

Max length6
Median length4
Mean length4.0013
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9991
99.9%
43000 4
 
< 0.1%
140000 3
 
< 0.1%
72000 1
 
< 0.1%
100000 1
 
< 0.1%

Length

2023-12-13T06:51:07.500701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:07.602158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9991
99.9%
43000 4
 
< 0.1%
140000 3
 
< 0.1%
72000 1
 
< 0.1%
100000 1
 
< 0.1%

결제방법
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9955 
현금+카드
 
25
카드
 
11
현금
 
9

Length

Max length5
Median length4
Mean length3.9985
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9955
99.6%
현금+카드 25
 
0.2%
카드 11
 
0.1%
현금 9
 
0.1%

Length

2023-12-13T06:51:07.697932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:07.781592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9955
99.6%
현금+카드 25
 
0.2%
카드 11
 
0.1%
현금 9
 
0.1%

특기사항
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

소유주체
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9888 
구
 
54
민간
 
44
시
 
14

Length

Max length4
Median length4
Mean length3.9708
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9888
98.9%
구 54
 
0.5%
민간 44
 
0.4%
시 14
 
0.1%

Length

2023-12-13T06:51:07.872403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:07.973131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9888
98.9%
구 54
 
0.5%
민간 44
 
0.4%
시 14
 
0.1%

운영주체
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9890 
구직영
 
48
민간직영
 
42
시직영
 
12
민간위탁
 
8

Length

Max length4
Median length4
Mean length3.994
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9890
98.9%
구직영 48
 
0.5%
민간직영 42
 
0.4%
시직영 12
 
0.1%
민간위탁 8
 
0.1%

Length

2023-12-13T06:51:08.065175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:08.163934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9890
98.9%
구직영 48
 
0.5%
민간직영 42
 
0.4%
시직영 12
 
0.1%
민간위탁 8
 
0.1%

데이터 관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대전광역시 유성구청
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대전광역시 유성구청
2nd row대전광역시 유성구청
3rd row대전광역시 유성구청
4th row대전광역시 유성구청
5th row대전광역시 유성구청

Common Values

ValueCountFrequency (%)
대전광역시 유성구청 10000
100.0%

Length

2023-12-13T06:51:08.247866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:08.326688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 10000
50.0%
유성구청 10000
50.0%

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

위도
Real number (ℝ)

SKEWED 

Distinct9925
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.402303
Minimum36.26589
Maximum127.34547
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:51:08.426076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.26589
5-th percentile36.300282
Q136.34372
median36.361415
Q336.389795
95-th percentile36.435258
Maximum127.34547
Range91.079577
Interquartile range (IQR)0.046074325

Descriptive statistics

Standard deviation1.8195499
Coefficient of variation (CV)0.049984473
Kurtosis2493.9035
Mean36.402303
Median Absolute Deviation (MAD)0.02459455
Skewness49.942285
Sum364023.03
Variance3.310762
MonotonicityNot monotonic
2023-12-13T06:51:08.562218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.3889 4
 
< 0.1%
36.3891 4
 
< 0.1%
36.3887 3
 
< 0.1%
36.3883 3
 
< 0.1%
36.389 3
 
< 0.1%
36.3209698 2
 
< 0.1%
36.3888 2
 
< 0.1%
36.3618328 2
 
< 0.1%
36.3862 2
 
< 0.1%
36.388226 2
 
< 0.1%
Other values (9915) 9973
99.7%
ValueCountFrequency (%)
36.2658898 1
< 0.1%
36.2663176 1
< 0.1%
36.2672404 1
< 0.1%
36.2672535 1
< 0.1%
36.2680303 1
< 0.1%
36.268065 1
< 0.1%
36.2686214 1
< 0.1%
36.2687518 1
< 0.1%
36.2690552 1
< 0.1%
36.2691861 1
< 0.1%
ValueCountFrequency (%)
127.345467 1
< 0.1%
127.334027 1
< 0.1%
127.333185 1
< 0.1%
127.330146 1
< 0.1%
36.4956204 1
< 0.1%
36.4943072 1
< 0.1%
36.4942631 1
< 0.1%
36.4941359 1
< 0.1%
36.4941279 1
< 0.1%
36.4940715 1
< 0.1%

경도
Real number (ℝ)

SKEWED 

Distinct9394
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.36589
Minimum36.297475
Maximum1127.388
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:51:08.691871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.297475
5-th percentile127.29421
Q1127.31653
median127.33423
Q3127.35144
95-th percentile127.40151
Maximum1127.388
Range1091.0905
Interquartile range (IQR)0.03491325

Descriptive statistics

Standard deviation10.326748
Coefficient of variation (CV)0.081079386
Kurtosis8801.937
Mean127.36589
Median Absolute Deviation (MAD)0.017526
Skewness90.290573
Sum1273658.9
Variance106.64172
MonotonicityNot monotonic
2023-12-13T06:51:08.829682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.3522 4
 
< 0.1%
127.3489 4
 
< 0.1%
127.315558 3
 
< 0.1%
127.320114 3
 
< 0.1%
127.3528 3
 
< 0.1%
127.392777 3
 
< 0.1%
127.336839 3
 
< 0.1%
127.3487 3
 
< 0.1%
127.315828 3
 
< 0.1%
127.35097 3
 
< 0.1%
Other values (9384) 9968
99.7%
ValueCountFrequency (%)
36.2974753 1
< 0.1%
36.3023273 1
< 0.1%
36.326678 1
< 0.1%
36.3555291 1
< 0.1%
36.3734713 1
< 0.1%
36.3855961 1
< 0.1%
36.437937 1
< 0.1%
36.4452806 1
< 0.1%
127.2493 1
< 0.1%
127.249844 1
< 0.1%
ValueCountFrequency (%)
1127.388 1
< 0.1%
127.4162614 1
< 0.1%
127.4161255 1
< 0.1%
127.4159714 1
< 0.1%
127.415945 1
< 0.1%
127.4158998 1
< 0.1%
127.4157748 1
< 0.1%
127.4157696 1
< 0.1%
127.4148884 1
< 0.1%
127.413699 1
< 0.1%

현장 이미지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022-10-31
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-10-31
2nd row2022-10-31
3rd row2022-10-31
4th row2022-10-31
5th row2022-10-31

Common Values

ValueCountFrequency (%)
2022-10-31 10000
100.0%

Length

2023-12-13T06:51:08.957851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:51:09.044304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-10-31 10000
100.0%

Sample

고유번호(관리번호)건물명허가일자사용검사일자주차장명주차장구분주차장유형주차시설형태소재지도로명주소소재지지번주소총 주차구획(면) 수법정주차구획(면) 수계획주차구획(면) 수일반주차구획 수전용주차구획(장애인) 수전용주차구획(경차) 수전용주차구획(여성) 수전용주차구획(전기차) 수전용주차구획(나눔카) 수전용주차구획(기타) 수전기차충전기 수방범설비유형급지구분부제시행구분일반인 개방 여부운영방식운영요일평일운영시작시각평일운영종료시각토요일운영시작시각토요일운영종료시각공휴일운영시작시각공휴일운영종료시각요금정보주차기본시간주차기본요금추가단위시간추가단위요금1일주차권요금적용시간1일주차권요금월정기권요금결제방법특기사항소유주체운영주체데이터 관리기관명전화번호위도경도현장 이미지데이터기준일자
16418367-3-016217<NA>2016-06-202016-08-22학하동 756-13번지 주차장민영부설자주식대전광역시 유성구 학하남로90번길 25대전광역시 유성구 학하동 756-1322<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>부분적 유료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 유성구청<NA>36.336196127.307174<NA>2022-10-31
5526367-3-005325<NA>2014-03-052014-12-30덕명동 608-3번지 주차장민영부설자주식대전광역시 유성구 학하서로 162대전광역시 유성구 덕명동 608-31010<NA>10<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>부분적 유료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 유성구청<NA>36.34554127.303969<NA>2022-10-31
14942367-3-014741<NA>2007-07-092009-08-11지족동 431-6번지 주차장민영부설자주식대전광역시 유성구 노은서로 137대전광역시 유성구 지족동 431-622<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>부분적 유료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 유성구청<NA>36.37242127.315228<NA>2022-10-31
213367-3-000012(주)메디진2002-05-202002-12-16(주)메디진 주차장민영부설자주식대전광역시 유성구 유성대로1628번길 37-7대전광역시 유성구 전민동 461-571717<NA>17<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>부분적 유료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 유성구청<NA>36.399904127.389379<NA>2022-10-31
3887367-3-003686넥스투빌2000-06-262003-12-10넥스투빌 주차장민영부설기계식대전광역시 유성구 유성대로736번길 19대전광역시 유성구 장대동 278-29292<NA>92<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>부분적 유료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 유성구청<NA>36.358759127.334726<NA>2022-10-31
9210367-3-009009<NA><NA><NA>세동 266번지 주차장민영부설<NA>대전광역시 유성구 세동로 357-48(세동)대전광역시 유성구 세동 2660<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>부분적 유료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 유성구청<NA>36.299318127.270358<NA>2022-10-31
7602367-3-007401<NA><NA><NA>봉명동 535-8번지 주차장민영부설<NA>대전광역시 유성구 계룡로87번길 50대전광역시 유성구 봉명동 535-80<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>부분적 유료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 유성구청<NA>36.355937127.341544<NA>2022-10-31
14305367-3-014104제이아그로연구소2010-03-082011-10-31제이아그로연구소 주차장민영부설자주식대전광역시 유성구 테크노2로 291대전광역시 유성구 탑립동 8462213<NA>193<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>부분적 유료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 유성구청<NA>36.416264127.41225<NA>2022-10-31
6359367-3-006158<NA>2005-12-092007-08-06반석동 628-1번지 주차장민영부설자주식대전광역시 유성구 반석로12번길 26대전광역시 유성구 반석동 628-133<NA>3<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>부분적 유료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 유성구청<NA>36.392882127.313025<NA>2022-10-31
1695367-3-001494<NA><NA><NA>구룡동 610-3번지 주차장민영부설<NA><NA>대전광역시 유성구 구룡동 610-30<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>부분적 유료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 유성구청<NA>36.440647127.347769<NA>2022-10-31
고유번호(관리번호)건물명허가일자사용검사일자주차장명주차장구분주차장유형주차시설형태소재지도로명주소소재지지번주소총 주차구획(면) 수법정주차구획(면) 수계획주차구획(면) 수일반주차구획 수전용주차구획(장애인) 수전용주차구획(경차) 수전용주차구획(여성) 수전용주차구획(전기차) 수전용주차구획(나눔카) 수전용주차구획(기타) 수전기차충전기 수방범설비유형급지구분부제시행구분일반인 개방 여부운영방식운영요일평일운영시작시각평일운영종료시각토요일운영시작시각토요일운영종료시각공휴일운영시작시각공휴일운영종료시각요금정보주차기본시간주차기본요금추가단위시간추가단위요금1일주차권요금적용시간1일주차권요금월정기권요금결제방법특기사항소유주체운영주체데이터 관리기관명전화번호위도경도현장 이미지데이터기준일자
1612367-3-001411<NA>2009-06-052010-11-10교촌동 640-5번지 주차장민영부설자주식대전광역시 유성구 교촌로6번길 37-11 (교촌동)대전광역시 유성구 교촌동 640-511<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>부분적 유료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 유성구청<NA>36.301168127.313829<NA>2022-10-31
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