Overview

Dataset statistics

Number of variables7
Number of observations648
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.6 KiB
Average record size in memory56.2 B

Variable types

Text3
Categorical4

Dataset

Description광주광역시 공영 및 민영주차장 현황입니다- 원 자료는 각 구청 교통과 또는 교통지도과에 있으며- 민영주차장의 경우 교통부서에 자율적으로 신고한 자료로 작성 되어 있음
Author광주광역시
URLhttps://www.data.go.kr/data/15107987/fileData.do

Alerts

주차장구분 is highly overall correlated with 주차장유형 and 2 other fieldsHigh correlation
관리기관 전화번호 is highly overall correlated with 주차장구분 and 1 other fieldsHigh correlation
관리기관명 is highly overall correlated with 주차장구분 and 1 other fieldsHigh correlation
주차장유형 is highly overall correlated with 주차장구분High correlation
주차장유형 is highly imbalanced (59.5%)Imbalance

Reproduction

Analysis started2024-03-14 19:14:45.591887
Analysis finished2024-03-14 19:14:47.012058
Duration1.42 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주차장명
Text

Distinct606
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-03-15T04:14:48.073557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length8.2669753
Min length1

Characters and Unicode

Total characters5357
Distinct characters365
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique572 ?
Unique (%)88.3%

Sample

1st row대인동 광주우체국 옆
2nd row광산교회 앞
3rd row웨딩의 거리 단기주차장
4th row전남여고 후문 앞 공영주차장
5th row동명동(푸른길)
ValueCountFrequency (%)
주차장 220
 
19.0%
공영주차장 67
 
5.8%
앞 23
 
2.0%
옆 15
 
1.3%
하남3지구 14
 
1.2%
진곡일반산업단지 13
 
1.1%
우산동 9
 
0.8%
주거환경개선지구 8
 
0.7%
주변 8
 
0.7%
계림동 7
 
0.6%
Other values (648) 774
66.8%
2024-03-15T04:14:49.735199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 566
 
10.6%
장 516
 
9.6%
515
 
9.6%
차 506
 
9.4%
동 203
 
3.8%
공 136
 
2.5%
영 128
 
2.4%
지 88
 
1.6%
산 83
 
1.5%
1 67
 
1.3%
Other values (355) 2549
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4419
82.5%
Space Separator 515
 
9.6%
Decimal Number 252
 
4.7%
Close Punctuation 43
 
0.8%
Open Punctuation 42
 
0.8%
Uppercase Letter 30
 
0.6%
Dash Punctuation 24
 
0.4%
Math Symbol 16
 
0.3%
Other Punctuation 10
 
0.2%
Other Symbol 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 566
 
12.8%
장 516
 
11.7%
차 506
 
11.5%
동 203
 
4.6%
공 136
 
3.1%
영 128
 
2.9%
지 88
 
2.0%
산 83
 
1.9%
남 49
 
1.1%
구 47
 
1.1%
Other values (323) 2097
47.5%
Uppercase Letter
ValueCountFrequency (%)
K 7
23.3%
T 6
20.0%
C 3
10.0%
I 3
10.0%
M 2
 
6.7%
A 2
 
6.7%
B 2
 
6.7%
G 1
 
3.3%
F 1
 
3.3%
P 1
 
3.3%
Other values (2) 2
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 67
26.6%
2 47
18.7%
3 41
16.3%
5 22
 
8.7%
9 19
 
7.5%
4 15
 
6.0%
0 12
 
4.8%
8 11
 
4.4%
6 9
 
3.6%
7 9
 
3.6%
Other Punctuation
ValueCountFrequency (%)
@ 6
60.0%
, 3
30.0%
: 1
 
10.0%
Space Separator
ValueCountFrequency (%)
515
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4424
82.6%
Common 902
 
16.8%
Latin 31
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 566
 
12.8%
장 516
 
11.7%
차 506
 
11.4%
동 203
 
4.6%
공 136
 
3.1%
영 128
 
2.9%
지 88
 
2.0%
산 83
 
1.9%
남 49
 
1.1%
구 47
 
1.1%
Other values (324) 2102
47.5%
Common
ValueCountFrequency (%)
515
57.1%
1 67
 
7.4%
2 47
 
5.2%
) 43
 
4.8%
( 42
 
4.7%
3 41
 
4.5%
- 24
 
2.7%
5 22
 
2.4%
9 19
 
2.1%
~ 16
 
1.8%
Other values (8) 66
 
7.3%
Latin
ValueCountFrequency (%)
K 7
22.6%
T 6
19.4%
C 3
9.7%
I 3
9.7%
M 2
 
6.5%
A 2
 
6.5%
B 2
 
6.5%
G 1
 
3.2%
F 1
 
3.2%
P 1
 
3.2%
Other values (3) 3
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4419
82.5%
ASCII 933
 
17.4%
None 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 566
 
12.8%
장 516
 
11.7%
차 506
 
11.5%
동 203
 
4.6%
공 136
 
3.1%
영 128
 
2.9%
지 88
 
2.0%
산 83
 
1.9%
남 49
 
1.1%
구 47
 
1.1%
Other values (323) 2097
47.5%
ASCII
ValueCountFrequency (%)
515
55.2%
1 67
 
7.2%
2 47
 
5.0%
) 43
 
4.6%
( 42
 
4.5%
3 41
 
4.4%
- 24
 
2.6%
5 22
 
2.4%
9 19
 
2.0%
~ 16
 
1.7%
Other values (21) 97
 
10.4%
None
ValueCountFrequency (%)
㈜ 5
100.0%

주차장구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
민영
284 
공영
216 
민영주차장
91 
공영주차장
55 
공공기관
 
2

Length

Max length5
Median length2
Mean length2.6820988
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
민영 284
43.8%
공영 216
33.3%
민영주차장 91
 
14.0%
공영주차장 55
 
8.5%
공공기관 2
 
0.3%

Length

2024-03-15T04:14:50.122107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:14:50.332743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민영 284
43.8%
공영 216
33.3%
민영주차장 91
 
14.0%
공영주차장 55
 
8.5%
공공기관 2
 
0.3%

주차장유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
노외
568 
노상
59 
부설
 
21

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노외 568
87.7%
노상 59
 
9.1%
부설 21
 
3.2%

Length

2024-03-15T04:14:50.541674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:14:50.726179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노외 568
87.7%
노상 59
 
9.1%
부설 21
 
3.2%

소재지도로명주소
Text

Distinct636
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-03-15T04:14:51.628582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length28
Mean length13.949074
Min length3

Characters and Unicode

Total characters9039
Distinct characters168
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique625 ?
Unique (%)96.5%

Sample

1st row대인동 16-13
2nd row제봉로98번길 11-3 주변
3rd row웨딩의 거리 구간
4th row장동 139
5th row동명동 25번지 주변
ValueCountFrequency (%)
광주광역시 226
 
11.5%
서구 93
 
4.7%
외 71
 
3.6%
광산구 50
 
2.5%
북구 47
 
2.4%
남구 36
 
1.8%
1필지 35
 
1.8%
계림동 33
 
1.7%
지산동 32
 
1.6%
송정동 22
 
1.1%
Other values (843) 1319
67.2%
2024-03-15T04:14:52.850677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1320
 
14.6%
1 617
 
6.8%
동 599
 
6.6%
광 518
 
5.7%
- 438
 
4.8%
2 330
 
3.7%
3 280
 
3.1%
5 265
 
2.9%
7 244
 
2.7%
주 242
 
2.7%
Other values (158) 4186
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4320
47.8%
Decimal Number 2730
30.2%
Space Separator 1320
 
14.6%
Dash Punctuation 438
 
4.8%
Open Punctuation 88
 
1.0%
Close Punctuation 88
 
1.0%
Other Punctuation 41
 
0.5%
Math Symbol 14
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 599
 
13.9%
광 518
 
12.0%
주 242
 
5.6%
시 234
 
5.4%
구 230
 
5.3%
역 226
 
5.2%
로 163
 
3.8%
산 144
 
3.3%
서 119
 
2.8%
지 116
 
2.7%
Other values (140) 1729
40.0%
Decimal Number
ValueCountFrequency (%)
1 617
22.6%
2 330
12.1%
3 280
10.3%
5 265
9.7%
7 244
 
8.9%
4 216
 
7.9%
9 206
 
7.5%
8 202
 
7.4%
0 189
 
6.9%
6 181
 
6.6%
Other Punctuation
ValueCountFrequency (%)
, 33
80.5%
@ 6
 
14.6%
/ 2
 
4.9%
Space Separator
ValueCountFrequency (%)
1320
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 438
100.0%
Open Punctuation
ValueCountFrequency (%)
( 88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 88
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4719
52.2%
Hangul 4320
47.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 599
 
13.9%
광 518
 
12.0%
주 242
 
5.6%
시 234
 
5.4%
구 230
 
5.3%
역 226
 
5.2%
로 163
 
3.8%
산 144
 
3.3%
서 119
 
2.8%
지 116
 
2.7%
Other values (140) 1729
40.0%
Common
ValueCountFrequency (%)
1320
28.0%
1 617
13.1%
- 438
 
9.3%
2 330
 
7.0%
3 280
 
5.9%
5 265
 
5.6%
7 244
 
5.2%
4 216
 
4.6%
9 206
 
4.4%
8 202
 
4.3%
Other values (8) 601
12.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4719
52.2%
Hangul 4320
47.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1320
28.0%
1 617
13.1%
- 438
 
9.3%
2 330
 
7.0%
3 280
 
5.9%
5 265
 
5.6%
7 244
 
5.2%
4 216
 
4.6%
9 206
 
4.4%
8 202
 
4.3%
Other values (8) 601
12.7%
Hangul
ValueCountFrequency (%)
동 599
 
13.9%
광 518
 
12.0%
주 242
 
5.6%
시 234
 
5.4%
구 230
 
5.3%
역 226
 
5.2%
로 163
 
3.8%
산 144
 
3.3%
서 119
 
2.8%
지 116
 
2.7%
Other values (140) 1729
40.0%

주차구획수(대)
Text

Distinct125
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-03-15T04:14:54.049091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length1.9367284
Min length1

Characters and Unicode

Total characters1255
Distinct characters14
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

Unique63 ?
Unique (%)9.7%

Sample

1st row8
2nd row14
3rd row26
4th row44
5th row32
ValueCountFrequency (%)
20 41
 
6.3%
10 28
 
4.3%
17 24
 
3.7%
14 24
 
3.7%
16 24
 
3.7%
9 23
 
3.5%
15 23
 
3.5%
18 23
 
3.5%
12 20
 
3.1%
13 18
 
2.8%
Other values (116) 401
61.8%
2024-03-15T04:14:55.652670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 302
24.1%
2 210
16.7%
0 127
10.1%
3 115
 
9.2%
4 106
 
8.4%
6 91
 
7.3%
5 80
 
6.4%
8 80
 
6.4%
7 73
 
5.8%
9 67
 
5.3%
Other values (4) 4
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1251
99.7%
Other Letter 2
 
0.2%
Space Separator 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 302
24.1%
2 210
16.8%
0 127
10.2%
3 115
 
9.2%
4 106
 
8.5%
6 91
 
7.3%
5 80
 
6.4%
8 80
 
6.4%
7 73
 
5.8%
9 67
 
5.4%
Other Letter
ValueCountFrequency (%)
월 1
50.0%
일 1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1253
99.8%
Hangul 2
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 302
24.1%
2 210
16.8%
0 127
10.1%
3 115
 
9.2%
4 106
 
8.5%
6 91
 
7.3%
5 80
 
6.4%
8 80
 
6.4%
7 73
 
5.8%
9 67
 
5.3%
Other values (2) 2
 
0.2%
Hangul
ValueCountFrequency (%)
월 1
50.0%
일 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1253
99.8%
Hangul 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 302
24.1%
2 210
16.8%
0 127
10.1%
3 115
 
9.2%
4 106
 
8.5%
6 91
 
7.3%
5 80
 
6.4%
8 80
 
6.4%
7 73
 
5.8%
9 67
 
5.3%
Other values (2) 2
 
0.2%
Hangul
ValueCountFrequency (%)
월 1
50.0%
일 1
50.0%

관리기관명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
<NA>
365 
동구청 교통과
88 
광산구청
65 
서구청
55 
남구청
 
26
Other values (10)
49 

Length

Max length10
Median length4
Mean length4.5216049
Min length2

Unique

Unique5 ?
Unique (%)0.8%

Sample

1st row동구청 교통과
2nd row동구청 교통과
3rd row동구청 교통과
4th row동구청 교통과
5th row동구청 교통과

Common Values

ValueCountFrequency (%)
<NA> 365
56.3%
동구청 교통과 88
 
13.6%
광산구청 65
 
10.0%
서구청 55
 
8.5%
남구청 26
 
4.0%
북구시설관리공단 26
 
4.0%
민영 9
 
1.4%
동구청 일자리경제과 5
 
0.8%
광주도시공사 2
 
0.3%
코레일 2
 
0.3%
Other values (5) 5
 
0.8%

Length

2024-03-15T04:14:55.962107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 365
49.2%
동구청 94
 
12.7%
교통과 88
 
11.9%
광산구청 65
 
8.8%
서구청 55
 
7.4%
남구청 26
 
3.5%
북구시설관리공단 26
 
3.5%
민영 9
 
1.2%
일자리경제과 5
 
0.7%
광주도시공사 2
 
0.3%
Other values (6) 7
 
0.9%

관리기관 전화번호
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
<NA>
376 
062-608-2914
99 
062-960-8632
65 
062-360-7810
55 
062-607-4231
 
26
Other values (2)
 
27

Length

Max length12
Median length4
Mean length7.3580247
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row062-608-2914
2nd row062-608-2914
3rd row062-608-2914
4th row062-608-2914
5th row062-608-2914

Common Values

ValueCountFrequency (%)
<NA> 376
58.0%
062-608-2914 99
 
15.3%
062-960-8632 65
 
10.0%
062-360-7810 55
 
8.5%
062-607-4231 26
 
4.0%
062-524-0825 26
 
4.0%
062-674-1457 1
 
0.2%

Length

2024-03-15T04:14:56.206581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:14:56.440914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
58.0%
062-608-2914 99
 
15.3%
062-960-8632 65
 
10.0%
062-360-7810 55
 
8.5%
062-607-4231 26
 
4.0%
062-524-0825 26
 
4.0%
062-674-1457 1
 
0.2%

Correlations

2024-03-15T04:14:56.595724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차장구분주차장유형관리기관명관리기관 전화번호
주차장구분1.0000.5760.9851.000
주차장유형0.5761.0000.6490.777
관리기관명0.9850.6491.0001.000
관리기관 전화번호1.0000.7771.0001.000
2024-03-15T04:14:56.835524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차장구분관리기관 전화번호주차장유형관리기관명
주차장구분1.0000.9940.5220.929
관리기관 전화번호0.9941.0000.4540.989
주차장유형0.5220.4541.0000.454
관리기관명0.9290.9890.4541.000
2024-03-15T04:14:57.096389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차장구분주차장유형관리기관명관리기관 전화번호
주차장구분1.0000.5220.9290.994
주차장유형0.5221.0000.4540.454
관리기관명0.9290.4541.0000.989
관리기관 전화번호0.9940.4540.9891.000

Missing values

2024-03-15T04:14:46.355351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:14:46.841754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

주차장명주차장구분주차장유형소재지도로명주소주차구획수(대)관리기관명관리기관 전화번호
0대인동 광주우체국 옆공영노상대인동 16-138동구청 교통과062-608-2914
1광산교회 앞공영노상제봉로98번길 11-3 주변14동구청 교통과062-608-2914
2웨딩의 거리 단기주차장공영노상웨딩의 거리 구간26동구청 교통과062-608-2914
3전남여고 후문 앞 공영주차장공영노상장동 13944동구청 교통과062-608-2914
4동명동(푸른길)공영노상동명동 25번지 주변32동구청 교통과062-608-2914
5동명동 가족회관 앞공영노상동명로(동명동159-7)5동구청 교통과062-608-2914
6서석교회 옆공영노상동명동 142-347동구청 교통과062-608-2914
7계림구시청 뒷길공영노상계림동 533-112동구청 교통과062-608-2914
8계림동 푸른길 옆공영노상계림동 73223동구청 교통과062-608-2914
9광고앞 공영주차장공영노상계림동 505-329,289-238동구청 교통과062-608-2914
주차장명주차장구분주차장유형소재지도로명주소주차구획수(대)관리기관명관리기관 전화번호
638(유)대통민영노외월전동 59-3 외 2필지100<NA><NA>
639서석물류민영노외월전동 39-49외 2필지25<NA><NA>
640뉴세림테크㈜민영노외연산동 1122-119<NA><NA>
641진곡화물공영차고지민영노외하남동 837430<NA><NA>
642남호주차장민영노외수완동 110920<NA><NA>
643파킹24민영노외장덕동 166827<NA><NA>
644공원주차장민영노외소촌동 521-17,19,23,2542<NA><NA>
645황룡주차장민영노외소촌동 522-3, 522-8940<NA><NA>
646호텔자라민영노외쌍암동 667-5, 667-423<NA><NA>
647희망주차장민영노외도산동 839 외 1필지10<NA><NA>