Overview

Dataset statistics

Number of variables23
Number of observations40
Missing cells108
Missing cells (%)11.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.8 KiB
Average record size in memory199.3 B

Variable types

Categorical8
Unsupported1
Text7
Numeric6
DateTime1

Dataset

Description전라남도 순천시 도시재생 활성화 구역 포함 장소값 기준 주차 전용구역 데이터를 개방합니다 ( 주차장명, 주소정보, 주차면수 정보)
Author전라남도 순천시
URLhttps://www.data.go.kr/data/15111520/fileData.do

Alerts

시도 명칭 has constant value ""Constant
시군구 명칭 has constant value ""Constant
수소차 주차면수 has constant value ""Constant
전용주차구획-기타 has constant value ""Constant
최종작성일 has constant value ""Constant
전기차 주차면수 is highly imbalanced (74.8%)Imbalance
경차 전용 주차면수 is highly imbalanced (61.3%)Imbalance
여성우선 주차면수 is highly imbalanced (52.8%)Imbalance
리 명칭 has 40 (100.0%) missing valuesMissing
도로명 이름 has 17 (42.5%) missing valuesMissing
건물 번호 has 17 (42.5%) missing valuesMissing
도로명주소 has 17 (42.5%) missing valuesMissing
주차장연락처 has 17 (42.5%) missing valuesMissing
주차장이름 has unique valuesUnique
리 명칭 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주차면수 has 9 (22.5%) zerosZeros
장애인 전용 주차면수 has 25 (62.5%) zerosZeros
개방주차장 개방면수 has 6 (15.0%) zerosZeros

Reproduction

Analysis started2023-12-12 12:14:51.970677
Analysis finished2023-12-12 12:14:52.435770
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도 명칭
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
전라남도
40 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 40
100.0%

Length

2023-12-12T21:14:52.510170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:14:52.649656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 40
100.0%

시군구 명칭
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
순천시
40 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
순천시 40
100.0%

Length

2023-12-12T21:14:52.783242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:14:52.949433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
순천시 40
100.0%

법정읍면동명칭
Categorical

Distinct9
Distinct (%)22.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
장천동
20 
동외동
6 
덕암동
5 
영동
3 
남정동
 
2
Other values (4)
4 

Length

Max length3
Median length3
Mean length2.925
Min length2

Unique

Unique4 ?
Unique (%)10.0%

Sample

1st row남내동
2nd row남정동
3rd row남정동
4th row덕암동
5th row덕암동

Common Values

ValueCountFrequency (%)
장천동 20
50.0%
동외동 6
 
15.0%
덕암동 5
 
12.5%
영동 3
 
7.5%
남정동 2
 
5.0%
남내동 1
 
2.5%
옥천동 1
 
2.5%
저전동 1
 
2.5%
조곡동 1
 
2.5%

Length

2023-12-12T21:14:53.094026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:14:53.241235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장천동 20
50.0%
동외동 6
 
15.0%
덕암동 5
 
12.5%
영동 3
 
7.5%
남정동 2
 
5.0%
남내동 1
 
2.5%
옥천동 1
 
2.5%
저전동 1
 
2.5%
조곡동 1
 
2.5%

리 명칭
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing40
Missing (%)100.0%
Memory size492.0 B

번지
Text

Distinct37
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T21:14:53.475614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.325
Min length4

Characters and Unicode

Total characters293
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)85.0%

Sample

1st row35-1 번지
2nd row544-11 번지
3rd row538-10 번지
4th row188-100 번지
5th row226-23 번지
ValueCountFrequency (%)
번지 40
50.0%
18-35 2
 
2.5%
198-5 2
 
2.5%
54-4 2
 
2.5%
28-7 1
 
1.2%
55-3 1
 
1.2%
47-5 1
 
1.2%
217 1
 
1.2%
225-2 1
 
1.2%
133-3 1
 
1.2%
Other values (28) 28
35.0%
2023-12-12T21:14:53.903736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40
13.7%
번 40
13.7%
지 40
13.7%
- 32
10.9%
1 31
10.6%
8 20
6.8%
5 17
5.8%
2 17
5.8%
3 14
 
4.8%
4 12
 
4.1%
Other values (6) 30
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 138
47.1%
Other Letter 83
28.3%
Space Separator 40
 
13.7%
Dash Punctuation 32
 
10.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 31
22.5%
8 20
14.5%
5 17
12.3%
2 17
12.3%
3 14
10.1%
4 12
 
8.7%
0 9
 
6.5%
6 7
 
5.1%
7 6
 
4.3%
9 5
 
3.6%
Other Letter
ValueCountFrequency (%)
번 40
48.2%
지 40
48.2%
동 2
 
2.4%
외 1
 
1.2%
Space Separator
ValueCountFrequency (%)
40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 210
71.7%
Hangul 83
 
28.3%

Most frequent character per script

Common
ValueCountFrequency (%)
40
19.0%
- 32
15.2%
1 31
14.8%
8 20
9.5%
5 17
8.1%
2 17
8.1%
3 14
 
6.7%
4 12
 
5.7%
0 9
 
4.3%
6 7
 
3.3%
Other values (2) 11
 
5.2%
Hangul
ValueCountFrequency (%)
번 40
48.2%
지 40
48.2%
동 2
 
2.4%
외 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 210
71.7%
Hangul 83
 
28.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40
19.0%
- 32
15.2%
1 31
14.8%
8 20
9.5%
5 17
8.1%
2 17
8.1%
3 14
 
6.7%
4 12
 
5.7%
0 9
 
4.3%
6 7
 
3.3%
Other values (2) 11
 
5.2%
Hangul
ValueCountFrequency (%)
번 40
48.2%
지 40
48.2%
동 2
 
2.4%
외 1
 
1.2%

도로명 이름
Text

MISSING 

Distinct13
Distinct (%)56.5%
Missing17
Missing (%)42.5%
Memory size452.0 B
2023-12-12T21:14:54.128808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.3478261
Min length3

Characters and Unicode

Total characters77
Distinct characters25
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)39.1%

Sample

1st row황금2길
2nd row팔마로
3rd row역전장길
4th row팔마로
5th row강남로
ValueCountFrequency (%)
중앙로 5
21.7%
장명로 5
21.7%
팔마로 2
 
8.7%
강남로 2
 
8.7%
황금2길 1
 
4.3%
역전장길 1
 
4.3%
도서관길 1
 
4.3%
영동길 1
 
4.3%
남문변천길 1
 
4.3%
중앙2길 1
 
4.3%
Other values (3) 3
13.0%
2023-12-12T21:14:54.546958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 14
18.2%
길 9
11.7%
앙 7
 
9.1%
중 7
 
9.1%
장 7
 
9.1%
명 6
 
7.8%
남 3
 
3.9%
2 2
 
2.6%
팔 2
 
2.6%
역 2
 
2.6%
Other values (15) 18
23.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73
94.8%
Decimal Number 4
 
5.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 14
19.2%
길 9
12.3%
앙 7
9.6%
중 7
9.6%
장 7
9.6%
명 6
8.2%
남 3
 
4.1%
팔 2
 
2.7%
역 2
 
2.7%
전 2
 
2.7%
Other values (12) 14
19.2%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
3 1
25.0%
4 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73
94.8%
Common 4
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 14
19.2%
길 9
12.3%
앙 7
9.6%
중 7
9.6%
장 7
9.6%
명 6
8.2%
남 3
 
4.1%
팔 2
 
2.7%
역 2
 
2.7%
전 2
 
2.7%
Other values (12) 14
19.2%
Common
ValueCountFrequency (%)
2 2
50.0%
3 1
25.0%
4 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73
94.8%
ASCII 4
 
5.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 14
19.2%
길 9
12.3%
앙 7
9.6%
중 7
9.6%
장 7
9.6%
명 6
8.2%
남 3
 
4.1%
팔 2
 
2.7%
역 2
 
2.7%
전 2
 
2.7%
Other values (12) 14
19.2%
ASCII
ValueCountFrequency (%)
2 2
50.0%
3 1
25.0%
4 1
25.0%

건물 번호
Text

MISSING 

Distinct18
Distinct (%)78.3%
Missing17
Missing (%)42.5%
Memory size452.0 B
2023-12-12T21:14:54.698340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.1304348
Min length3

Characters and Unicode

Total characters95
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)60.9%

Sample

1st row11-1 번
2nd row135 번
3rd row30 번
4th row159 번
5th row115 번
ValueCountFrequency (%)
번 23
50.0%
30 3
 
6.5%
16 2
 
4.3%
4 2
 
4.3%
26 2
 
4.3%
95 1
 
2.2%
11-1 1
 
2.2%
17 1
 
2.2%
8 1
 
2.2%
18 1
 
2.2%
Other values (9) 9
 
19.6%
2023-12-12T21:14:55.046877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23
24.2%
번 23
24.2%
1 13
13.7%
3 7
 
7.4%
2 5
 
5.3%
6 4
 
4.2%
9 4
 
4.2%
5 4
 
4.2%
8 4
 
4.2%
0 3
 
3.2%
Other values (3) 5
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
50.5%
Space Separator 23
24.2%
Other Letter 23
24.2%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
27.1%
3 7
14.6%
2 5
 
10.4%
6 4
 
8.3%
9 4
 
8.3%
5 4
 
8.3%
8 4
 
8.3%
0 3
 
6.2%
4 2
 
4.2%
7 2
 
4.2%
Space Separator
ValueCountFrequency (%)
23
100.0%
Other Letter
ValueCountFrequency (%)
번 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 72
75.8%
Hangul 23
 
24.2%

Most frequent character per script

Common
ValueCountFrequency (%)
23
31.9%
1 13
18.1%
3 7
 
9.7%
2 5
 
6.9%
6 4
 
5.6%
9 4
 
5.6%
5 4
 
5.6%
8 4
 
5.6%
0 3
 
4.2%
4 2
 
2.8%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
번 23
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
75.8%
Hangul 23
 
24.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23
31.9%
1 13
18.1%
3 7
 
9.7%
2 5
 
6.9%
6 4
 
5.6%
9 4
 
5.6%
5 4
 
5.6%
8 4
 
5.6%
0 3
 
4.2%
4 2
 
2.8%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
번 23
100.0%

위도
Real number (ℝ)

Distinct38
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.950394
Minimum34.938832
Maximum34.958586
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T21:14:55.245989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.938832
5-th percentile34.942928
Q134.947706
median34.95086
Q334.953041
95-th percentile34.957943
Maximum34.958586
Range0.0197532
Interquartile range (IQR)0.005334775

Descriptive statistics

Standard deviation0.0047705583
Coefficient of variation (CV)0.00013649512
Kurtosis0.20995041
Mean34.950394
Median Absolute Deviation (MAD)0.0030907
Skewness-0.48584422
Sum1398.0158
Variance2.2758226 × 10-5
MonotonicityNot monotonic
2023-12-12T21:14:55.467753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
34.9508233 2
 
5.0%
34.9585857 2
 
5.0%
34.9547821 1
 
2.5%
34.9490587 1
 
2.5%
34.9494149 1
 
2.5%
34.9499925 1
 
2.5%
34.951217 1
 
2.5%
34.9512807 1
 
2.5%
34.950357 1
 
2.5%
34.9499901 1
 
2.5%
Other values (28) 28
70.0%
ValueCountFrequency (%)
34.9388325 1
2.5%
34.939106 1
2.5%
34.9431294 1
2.5%
34.9432103 1
2.5%
34.9443299 1
2.5%
34.9446583 1
2.5%
34.9459141 1
2.5%
34.9464167 1
2.5%
34.9472271 1
2.5%
34.9473944 1
2.5%
ValueCountFrequency (%)
34.9585857 2
5.0%
34.9579091 1
2.5%
34.9568792 1
2.5%
34.9559998 1
2.5%
34.9556718 1
2.5%
34.9548641 1
2.5%
34.9547821 1
2.5%
34.9541713 1
2.5%
34.9539909 1
2.5%
34.9527237 1
2.5%

경도
Real number (ℝ)

Distinct38
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.48897
Minimum127.47773
Maximum127.50657
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T21:14:55.663532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.47773
5-th percentile127.48267
Q1127.48578
median127.48687
Q3127.48876
95-th percentile127.50548
Maximum127.50657
Range0.0288351
Interquartile range (IQR)0.00297515

Descriptive statistics

Standard deviation0.0068956063
Coefficient of variation (CV)5.4087864 × 10-5
Kurtosis1.6247755
Mean127.48897
Median Absolute Deviation (MAD)0.0016144
Skewness1.5341198
Sum5099.559
Variance4.7549386 × 10-5
MonotonicityNot monotonic
2023-12-12T21:14:55.842441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
127.4868131 2
 
5.0%
127.4859435 2
 
5.0%
127.4852347 1
 
2.5%
127.4914301 1
 
2.5%
127.4873781 1
 
2.5%
127.4858395 1
 
2.5%
127.4880369 1
 
2.5%
127.485619 1
 
2.5%
127.4871893 1
 
2.5%
127.4869803 1
 
2.5%
Other values (28) 28
70.0%
ValueCountFrequency (%)
127.47773 1
2.5%
127.4812689 1
2.5%
127.4827433 1
2.5%
127.483135 1
2.5%
127.4836236 1
2.5%
127.4841657 1
2.5%
127.4847232 1
2.5%
127.4852229 1
2.5%
127.4852347 1
2.5%
127.485619 1
2.5%
ValueCountFrequency (%)
127.5065651 1
2.5%
127.5057543 1
2.5%
127.5054625 1
2.5%
127.5031036 1
2.5%
127.5028834 1
2.5%
127.5003718 1
2.5%
127.4914301 1
2.5%
127.4910513 1
2.5%
127.4892556 1
2.5%
127.4888889 1
2.5%

우편번호
Real number (ℝ)

Distinct15
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean238897.3
Minimum54096
Maximum540960
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T21:14:55.986295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54096
5-th percentile57940.9
Q157956
median57958
Q3540941
95-th percentile540959
Maximum540960
Range486864
Interquartile range (IQR)482985

Descriptive statistics

Standard deviation236776.47
Coefficient of variation (CV)0.99112243
Kurtosis-1.8048201
Mean238897.3
Median Absolute Deviation (MAD)16.5
Skewness0.53672082
Sum9555892
Variance5.6063098 × 1010
MonotonicityNot monotonic
2023-12-12T21:14:56.136343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
57956 12
30.0%
540959 5
12.5%
57942 3
 
7.5%
57964 3
 
7.5%
540945 3
 
7.5%
57941 3
 
7.5%
540941 2
 
5.0%
540120 2
 
5.0%
57962 1
 
2.5%
57939 1
 
2.5%
Other values (5) 5
12.5%
ValueCountFrequency (%)
54096 1
 
2.5%
57939 1
 
2.5%
57941 3
 
7.5%
57942 3
 
7.5%
57956 12
30.0%
57960 1
 
2.5%
57962 1
 
2.5%
57964 3
 
7.5%
540030 1
 
2.5%
540120 2
 
5.0%
ValueCountFrequency (%)
540960 1
 
2.5%
540959 5
12.5%
540945 3
7.5%
540941 2
 
5.0%
540180 1
 
2.5%
540120 2
 
5.0%
540030 1
 
2.5%
57964 3
7.5%
57962 1
 
2.5%
57960 1
 
2.5%

도로명주소
Text

MISSING 

Distinct22
Distinct (%)95.7%
Missing17
Missing (%)42.5%
Memory size452.0 B
2023-12-12T21:14:56.389652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length16.130435
Min length13

Characters and Unicode

Total characters371
Distinct characters74
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)91.3%

Sample

1st row전남 순천시 황금2길 11-1
2nd row전남 순천시 팔마로 135
3rd row전남 순천시 역전장길 30 제일떡집
4th row전남 순천시 팔마로 159 궁전스파랜드
5th row전남 순천시 강남로 115
ValueCountFrequency (%)
전남 23
22.8%
순천시 23
22.8%
장명로 5
 
5.0%
중앙로 5
 
5.0%
30 3
 
3.0%
26 2
 
2.0%
16 2
 
2.0%
팔마로 2
 
2.0%
4 2
 
2.0%
강남로 2
 
2.0%
Other values (32) 32
31.7%
2023-12-12T21:14:56.859244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
78
21.0%
남 27
 
7.3%
전 26
 
7.0%
천 25
 
6.7%
순 24
 
6.5%
시 24
 
6.5%
로 14
 
3.8%
1 13
 
3.5%
길 9
 
2.4%
3 8
 
2.2%
Other values (64) 123
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 239
64.4%
Space Separator 78
 
21.0%
Decimal Number 52
 
14.0%
Other Punctuation 1
 
0.3%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 27
11.3%
전 26
 
10.9%
천 25
 
10.5%
순 24
 
10.0%
시 24
 
10.0%
로 14
 
5.9%
길 9
 
3.8%
앙 8
 
3.3%
중 8
 
3.3%
장 7
 
2.9%
Other values (51) 67
28.0%
Decimal Number
ValueCountFrequency (%)
1 13
25.0%
3 8
15.4%
2 7
13.5%
5 4
 
7.7%
6 4
 
7.7%
8 4
 
7.7%
9 4
 
7.7%
4 3
 
5.8%
0 3
 
5.8%
7 2
 
3.8%
Space Separator
ValueCountFrequency (%)
78
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 239
64.4%
Common 132
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 27
11.3%
전 26
 
10.9%
천 25
 
10.5%
순 24
 
10.0%
시 24
 
10.0%
로 14
 
5.9%
길 9
 
3.8%
앙 8
 
3.3%
중 8
 
3.3%
장 7
 
2.9%
Other values (51) 67
28.0%
Common
ValueCountFrequency (%)
78
59.1%
1 13
 
9.8%
3 8
 
6.1%
2 7
 
5.3%
5 4
 
3.0%
6 4
 
3.0%
8 4
 
3.0%
9 4
 
3.0%
4 3
 
2.3%
0 3
 
2.3%
Other values (3) 4
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 239
64.4%
ASCII 132
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
78
59.1%
1 13
 
9.8%
3 8
 
6.1%
2 7
 
5.3%
5 4
 
3.0%
6 4
 
3.0%
8 4
 
3.0%
9 4
 
3.0%
4 3
 
2.3%
0 3
 
2.3%
Other values (3) 4
 
3.0%
Hangul
ValueCountFrequency (%)
남 27
11.3%
전 26
 
10.9%
천 25
 
10.5%
순 24
 
10.0%
시 24
 
10.0%
로 14
 
5.9%
길 9
 
3.8%
앙 8
 
3.3%
중 8
 
3.3%
장 7
 
2.9%
Other values (51) 67
28.0%

지번주소
Text

Distinct38
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T21:14:57.119143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length15.275
Min length11

Characters and Unicode

Total characters611
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)90.0%

Sample

1st row전남 순천시 남내동 35-1
2nd row전남 순천시 남정동 544-11
3rd row전남 순천시 남정동 538-10
4th row전남 순천시 덕암동 188-100
5th row전남 순천시 덕암동 226-23
ValueCountFrequency (%)
전남 40
25.2%
순천시 39
24.5%
장천동 20
12.6%
동외동 5
 
3.1%
덕암동 5
 
3.1%
영동 2
 
1.3%
남정동 2
 
1.3%
54-4 2
 
1.3%
198-5 2
 
1.3%
15-14 1
 
0.6%
Other values (41) 41
25.8%
2023-12-12T21:14:57.606956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
19.6%
천 61
10.0%
동 46
 
7.5%
남 43
 
7.0%
전 41
 
6.7%
순 40
 
6.5%
시 40
 
6.5%
1 32
 
5.2%
- 32
 
5.2%
장 20
 
3.3%
Other values (20) 136
22.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 318
52.0%
Decimal Number 141
23.1%
Space Separator 120
 
19.6%
Dash Punctuation 32
 
5.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 61
19.2%
동 46
14.5%
남 43
13.5%
전 41
12.9%
순 40
12.6%
시 40
12.6%
장 20
 
6.3%
외 6
 
1.9%
덕 5
 
1.6%
암 5
 
1.6%
Other values (8) 11
 
3.5%
Decimal Number
ValueCountFrequency (%)
1 32
22.7%
2 19
13.5%
8 19
13.5%
5 17
12.1%
3 13
9.2%
4 12
 
8.5%
0 9
 
6.4%
6 8
 
5.7%
7 7
 
5.0%
9 5
 
3.5%
Space Separator
ValueCountFrequency (%)
120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 318
52.0%
Common 293
48.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 61
19.2%
동 46
14.5%
남 43
13.5%
전 41
12.9%
순 40
12.6%
시 40
12.6%
장 20
 
6.3%
외 6
 
1.9%
덕 5
 
1.6%
암 5
 
1.6%
Other values (8) 11
 
3.5%
Common
ValueCountFrequency (%)
120
41.0%
1 32
 
10.9%
- 32
 
10.9%
2 19
 
6.5%
8 19
 
6.5%
5 17
 
5.8%
3 13
 
4.4%
4 12
 
4.1%
0 9
 
3.1%
6 8
 
2.7%
Other values (2) 12
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 318
52.0%
ASCII 293
48.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
41.0%
1 32
 
10.9%
- 32
 
10.9%
2 19
 
6.5%
8 19
 
6.5%
5 17
 
5.8%
3 13
 
4.4%
4 12
 
4.1%
0 9
 
3.1%
6 8
 
2.7%
Other values (2) 12
 
4.1%
Hangul
ValueCountFrequency (%)
천 61
19.2%
동 46
14.5%
남 43
13.5%
전 41
12.9%
순 40
12.6%
시 40
12.6%
장 20
 
6.3%
외 6
 
1.9%
덕 5
 
1.6%
암 5
 
1.6%
Other values (8) 11
 
3.5%

주차장이름
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T21:14:57.870805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14.5
Mean length10.275
Min length5

Characters and Unicode

Total characters411
Distinct characters118
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row에프아이알 주차장
2nd row보금헬스온천2번주차장
3rd row보금헬스온천1번주차장
4th row코레일네트웍스 순천역주차장
5th row여수수협 순천지점전용주차장
ValueCountFrequency (%)
주차장 17
22.7%
민영 6
 
8.0%
공영 5
 
6.7%
웃장 2
 
2.7%
노상 2
 
2.7%
에프아이알 1
 
1.3%
순천시청민원인주차장 1
 
1.3%
프리머스 1
 
1.3%
경도주차장 1
 
1.3%
금화 1
 
1.3%
Other values (38) 38
50.7%
2023-12-12T21:14:58.301406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 44
 
10.7%
주 42
 
10.2%
차 40
 
9.7%
36
 
8.8%
천 16
 
3.9%
영 15
 
3.6%
순 14
 
3.4%
공 10
 
2.4%
민 8
 
1.9%
시 7
 
1.7%
Other values (108) 179
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 358
87.1%
Space Separator 36
 
8.8%
Decimal Number 9
 
2.2%
Uppercase Letter 6
 
1.5%
Other Punctuation 1
 
0.2%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 44
 
12.3%
주 42
 
11.7%
차 40
 
11.2%
천 16
 
4.5%
영 15
 
4.2%
순 14
 
3.9%
공 10
 
2.8%
민 8
 
2.2%
시 7
 
2.0%
전 7
 
2.0%
Other values (96) 155
43.3%
Uppercase Letter
ValueCountFrequency (%)
V 1
16.7%
G 1
16.7%
C 1
16.7%
B 1
16.7%
J 1
16.7%
K 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 4
44.4%
1 3
33.3%
3 2
22.2%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 359
87.3%
Common 46
 
11.2%
Latin 6
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 44
 
12.3%
주 42
 
11.7%
차 40
 
11.1%
천 16
 
4.5%
영 15
 
4.2%
순 14
 
3.9%
공 10
 
2.8%
민 8
 
2.2%
시 7
 
1.9%
전 7
 
1.9%
Other values (97) 156
43.5%
Latin
ValueCountFrequency (%)
V 1
16.7%
G 1
16.7%
C 1
16.7%
B 1
16.7%
J 1
16.7%
K 1
16.7%
Common
ValueCountFrequency (%)
36
78.3%
2 4
 
8.7%
1 3
 
6.5%
3 2
 
4.3%
, 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 358
87.1%
ASCII 52
 
12.7%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 44
 
12.3%
주 42
 
11.7%
차 40
 
11.2%
천 16
 
4.5%
영 15
 
4.2%
순 14
 
3.9%
공 10
 
2.8%
민 8
 
2.2%
시 7
 
2.0%
전 7
 
2.0%
Other values (96) 155
43.3%
ASCII
ValueCountFrequency (%)
36
69.2%
2 4
 
7.7%
1 3
 
5.8%
3 2
 
3.8%
V 1
 
1.9%
G 1
 
1.9%
C 1
 
1.9%
, 1
 
1.9%
B 1
 
1.9%
J 1
 
1.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

주차장연락처
Text

MISSING 

Distinct21
Distinct (%)91.3%
Missing17
Missing (%)42.5%
Memory size452.0 B
2023-12-12T21:14:58.513240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.695652
Min length7

Characters and Unicode

Total characters269
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

Unique19 ?
Unique (%)82.6%

Sample

1st row061-741-1260
2nd row7411260
3rd row02-3271-0720
4th row061-743-8880
5th row617440272
ValueCountFrequency (%)
1661-9408 2
 
8.7%
0503-7745-7258 2
 
8.7%
061-744-6428 1
 
4.3%
061-752-0010 1
 
4.3%
061-742-8803 1
 
4.3%
0507-1345-9736 1
 
4.3%
061-745-6331 1
 
4.3%
061-744-2171 1
 
4.3%
061-811-2222 1
 
4.3%
061-749-3114 1
 
4.3%
Other values (11) 11
47.8%
2023-12-12T21:14:58.895430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40
14.9%
- 39
14.5%
1 36
13.4%
7 30
11.2%
4 25
9.3%
6 23
8.6%
2 22
8.2%
5 18
6.7%
3 15
 
5.6%
8 13
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230
85.5%
Dash Punctuation 39
 
14.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40
17.4%
1 36
15.7%
7 30
13.0%
4 25
10.9%
6 23
10.0%
2 22
9.6%
5 18
7.8%
3 15
 
6.5%
8 13
 
5.7%
9 8
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40
14.9%
- 39
14.5%
1 36
13.4%
7 30
11.2%
4 25
9.3%
6 23
8.6%
2 22
8.2%
5 18
6.7%
3 15
 
5.6%
8 13
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40
14.9%
- 39
14.5%
1 36
13.4%
7 30
11.2%
4 25
9.3%
6 23
8.6%
2 22
8.2%
5 18
6.7%
3 15
 
5.6%
8 13
 
4.8%

주차면수
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.175
Minimum0
Maximum185
Zeros9
Zeros (%)22.5%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T21:14:59.071969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.25
median15
Q350.5
95-th percentile152.75
Maximum185
Range185
Interquartile range (IQR)43.25

Descriptive statistics

Standard deviation46.728835
Coefficient of variation (CV)1.2917439
Kurtosis3.1446332
Mean36.175
Median Absolute Deviation (MAD)15
Skewness1.8749083
Sum1447
Variance2183.584
MonotonicityNot monotonic
2023-12-12T21:14:59.243065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 9
22.5%
12 4
 
10.0%
11 2
 
5.0%
15 2
 
5.0%
37 2
 
5.0%
64 1
 
2.5%
18 1
 
2.5%
5 1
 
2.5%
10 1
 
2.5%
50 1
 
2.5%
Other values (16) 16
40.0%
ValueCountFrequency (%)
0 9
22.5%
5 1
 
2.5%
8 1
 
2.5%
10 1
 
2.5%
11 2
 
5.0%
12 4
10.0%
13 1
 
2.5%
15 2
 
5.0%
18 1
 
2.5%
19 1
 
2.5%
ValueCountFrequency (%)
185 1
2.5%
167 1
2.5%
152 1
2.5%
101 1
2.5%
93 1
2.5%
82 1
2.5%
70 1
2.5%
64 1
2.5%
57 1
2.5%
52 1
2.5%

전기차 주차면수
Categorical

IMBALANCE 

Distinct4
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
37 
2
 
1
3
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)7.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 37
92.5%
2 1
 
2.5%
3 1
 
2.5%
4 1
 
2.5%

Length

2023-12-12T21:14:59.416764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:14:59.598122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 37
92.5%
2 1
 
2.5%
3 1
 
2.5%
4 1
 
2.5%

수소차 주차면수
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
40 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 40
100.0%

Length

2023-12-12T21:14:59.739619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:14:59.865891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 40
100.0%

장애인 전용 주차면수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.175
Minimum0
Maximum6
Zeros25
Zeros (%)62.5%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T21:14:59.969014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile5.05
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8795458
Coefficient of variation (CV)1.5996134
Kurtosis0.87983346
Mean1.175
Median Absolute Deviation (MAD)0
Skewness1.4652193
Sum47
Variance3.5326923
MonotonicityNot monotonic
2023-12-12T21:15:00.082883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 25
62.5%
1 4
 
10.0%
3 3
 
7.5%
6 2
 
5.0%
5 2
 
5.0%
2 2
 
5.0%
4 2
 
5.0%
ValueCountFrequency (%)
0 25
62.5%
1 4
 
10.0%
2 2
 
5.0%
3 3
 
7.5%
4 2
 
5.0%
5 2
 
5.0%
6 2
 
5.0%
ValueCountFrequency (%)
6 2
 
5.0%
5 2
 
5.0%
4 2
 
5.0%
3 3
 
7.5%
2 2
 
5.0%
1 4
 
10.0%
0 25
62.5%

경차 전용 주차면수
Categorical

IMBALANCE 

Distinct5
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
34 
2
 
2
1
 
2
17
 
1
6
 
1

Length

Max length2
Median length1
Mean length1.025
Min length1

Unique

Unique2 ?
Unique (%)5.0%

Sample

1st row0
2nd row0
3rd row0
4th row2
5th row0

Common Values

ValueCountFrequency (%)
0 34
85.0%
2 2
 
5.0%
1 2
 
5.0%
17 1
 
2.5%
6 1
 
2.5%

Length

2023-12-12T21:15:00.231319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:15:00.355799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 34
85.0%
2 2
 
5.0%
1 2
 
5.0%
17 1
 
2.5%
6 1
 
2.5%

전용주차구획-기타
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
40 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 40
100.0%

Length

2023-12-12T21:15:00.507230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:15:00.636946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 40
100.0%

개방주차장 개방면수
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.225
Minimum0
Maximum152
Zeros6
Zeros (%)15.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T21:15:00.738897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110.25
median17.5
Q343.75
95-th percentile148.2
Maximum152
Range152
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation42.001519
Coefficient of variation (CV)1.1923781
Kurtosis2.3776532
Mean35.225
Median Absolute Deviation (MAD)14
Skewness1.7452967
Sum1409
Variance1764.1276
MonotonicityNot monotonic
2023-12-12T21:15:00.865492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 6
 
15.0%
12 4
 
10.0%
15 3
 
7.5%
152 2
 
5.0%
5 2
 
5.0%
8 2
 
5.0%
37 2
 
5.0%
101 1
 
2.5%
50 1
 
2.5%
46 1
 
2.5%
Other values (16) 16
40.0%
ValueCountFrequency (%)
0 6
15.0%
5 2
 
5.0%
8 2
 
5.0%
11 1
 
2.5%
12 4
10.0%
13 1
 
2.5%
15 3
7.5%
17 1
 
2.5%
18 1
 
2.5%
19 1
 
2.5%
ValueCountFrequency (%)
152 2
5.0%
148 1
2.5%
101 1
2.5%
93 1
2.5%
82 1
2.5%
70 1
2.5%
64 1
2.5%
50 1
2.5%
46 1
2.5%
43 1
2.5%

여성우선 주차면수
Categorical

IMBALANCE 

Distinct3
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
34 
2
4 
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 34
85.0%
2 4
 
10.0%
3 2
 
5.0%

Length

2023-12-12T21:15:01.029408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:15:01.141788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 34
85.0%
2 4
 
10.0%
3 2
 
5.0%

최종작성일
Date

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
Minimum2022-11-23 00:00:00
Maximum2022-11-23 00:00:00
2023-12-12T21:15:01.264417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:01.364612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

시도 명칭시군구 명칭법정읍면동명칭리 명칭번지도로명 이름건물 번호위도경도우편번호도로명주소지번주소주차장이름주차장연락처주차면수전기차 주차면수수소차 주차면수장애인 전용 주차면수경차 전용 주차면수전용주차구획-기타개방주차장 개방면수여성우선 주차면수최종작성일
0전라남도순천시남내동<NA>35-1 번지황금2길11-1 번34.954782127.48523557942전남 순천시 황금2길 11-1전남 순천시 남내동 35-1에프아이알 주차장<NA>11000001102022-11-23
1전라남도순천시남정동<NA>544-11 번지<NA><NA>34.938832127.489256540941<NA>전남 순천시 남정동 544-11보금헬스온천2번주차장061-741-126015000001502022-11-23
2전라남도순천시남정동<NA>538-10 번지<NA><NA>34.939106127.488716540941<NA>전남 순천시 남정동 538-10보금헬스온천1번주차장74112600000002002022-11-23
3전라남도순천시덕암동<NA>188-100 번지팔마로135 번34.945914127.50310457964전남 순천시 팔마로 135전남 순천시 덕암동 188-100코레일네트웍스 순천역주차장02-3271-072018500620002022-11-23
4전라남도순천시덕암동<NA>226-23 번지역전장길30 번34.944658127.50288357962전남 순천시 역전장길 30 제일떡집전남 순천시 덕암동 226-23여수수협 순천지점전용주차장061-743-8880000000502022-11-23
5전라남도순천시덕암동<NA>188-89 번지팔마로159 번34.94433127.50546257964전남 순천시 팔마로 159 궁전스파랜드전남 순천시 덕암동 188-89역전제3 노상 공영 주차장<NA>00060014802022-11-23
6전라남도순천시덕암동<NA>220 번지<NA><NA>34.94321127.506565540120<NA>전남 순천시 덕암동 220역전3공영유료주차장6174402720001101702022-11-23
7전라남도순천시덕암동<NA>223-8 번지<NA><NA>34.943129127.505754540120<NA>전남 순천시 덕암동 223-8역전시장제2주차장<NA>0001003302022-11-23
8전라남도순천시동외동<NA>83 번지강남로115 번34.954864127.48691957942전남 순천시 강남로 115전남 순천시 동외동 83성동 공영 주차장<NA>82005008232022-11-23
9전라남도순천시동외동<NA>198-5 번지<NA><NA>34.958586127.485944540945<NA>전남 순천시 동외동 198-5웃장 공영 주차장0503-7745-512364003006402022-11-23
시도 명칭시군구 명칭법정읍면동명칭리 명칭번지도로명 이름건물 번호위도경도우편번호도로명주소지번주소주차장이름주차장연락처주차면수전기차 주차면수수소차 주차면수장애인 전용 주차면수경차 전용 주차면수전용주차구획-기타개방주차장 개방면수여성우선 주차면수최종작성일
30전라남도순천시장천동<NA>62-1 번지<NA><NA>34.94999127.48698540959<NA>전남 순천시 장천동 62-1순천시청민원인주차장1661-94081674056015202022-11-23
31전라남도순천시장천동<NA>15-14 번지<NA><NA>34.949059127.49143540959<NA>전남 순천시 장천동 15-14로얄호텔웨딩홀제2주차장<NA>37000003702022-11-23
32전라남도순천시장천동<NA>28-7 번지중앙로4 번34.947394127.48815357956전남 순천시 중앙로 4 순천희망병원전남 순천시 장천동 28-7순천희망병원주차장061-811-222250002005022022-11-23
33전라남도순천시장천동<NA>88-9 번지중앙로30 번34.94914127.48617257956전남 순천시 중앙로 30 티월드. 레코드쏠파전남 순천시 장천동 88-9순천시노인회관부설주차장<NA>1000000002022-11-23
34전라남도순천시장천동<NA>133-3 번지중앙로72 번34.952058127.48416657956전남 순천시 중앙로 72 광주은행전남 순천시 장천동 133-3KJB광주은행 순천지점고객전용주차장061-744-217115000001502022-11-23
35전라남도순천시장천동<NA>225-2 번지<NA><NA>34.951722127.487441540959<NA>전남 순천시 장천동 225-2순광식당전용주차장061-745-633112000001202022-11-23
36전라남도순천시장천동<NA>217 번지<NA><NA>34.95171127.48647540959<NA>전남 순천시 장천동 217남흥회관주차장0507-1345-973612000001202022-11-23
37전라남도순천시장천동<NA>47-5 번지<NA><NA>34.951774127.48825540959<NA>전남 순천시 장천동 47-5해강주차장061-742-8803500000502022-11-23
38전라남도순천시저전동<NA>27-1 번지<NA><NA>34.95246127.483135540180<NA>전남 순천시 저전동 27-1태정전용주차장061-743-7001000020802022-11-23
39전라남도순천시조곡동<NA>139-16 번지역전길16 번34.947227127.50037257964전남 순천시 역전길 16 한국철도시설공단호남지역본부전남 순천시 조곡동 139-16한국철도시설공단 순천사무소주차장<NA>000000002022-11-23