Overview

Dataset statistics

Number of variables12
Number of observations320
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.1 KiB
Average record size in memory99.4 B

Variable types

Numeric3
Categorical3
Text6

Dataset

Description인천광역시경찰청에서 생활경제 활성화를 위한 주정차 허용 현황<br/>※ 주‧정차 허용 효력은 현장에 교통안전시설물(안전표지 등)이 설치된 때로부터 발생함(현장 확인 요망).<br/> - 각 지자체 별 예산 등 사정에 따라 시설물 설치 일정이 달라 질 수 있음에 유의<br/> - 위의 규제 내용과 설치된 교통안전시설물(보조표지 기재내용)이 상이한 경우 현장의 교통안전시설물이 우선됨.<br/> - 구간에 따라 주정차허용이 안되는 차종도 있음(구분에 표시). 금지차종은 교통안전시설물(안전표지) 참고
Author경찰청 인천광역시경찰청
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15006919&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 관할High correlation
연장(km) is highly overall correlated with 주차수(승용차)High correlation
주차수(승용차) is highly overall correlated with 연장(km)High correlation
관할 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
허용면 is highly overall correlated with 허용시간High correlation
허용시간 is highly overall correlated with 관할 and 1 other fieldsHigh correlation
허용면 is highly imbalanced (60.9%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2024-05-10 21:59:45.825724
Analysis finished2024-05-10 21:59:56.331299
Duration10.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct320
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean160.5
Minimum1
Maximum320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-10T21:59:56.556586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16.95
Q180.75
median160.5
Q3240.25
95-th percentile304.05
Maximum320
Range319
Interquartile range (IQR)159.5

Descriptive statistics

Standard deviation92.520268
Coefficient of variation (CV)0.57645027
Kurtosis-1.2
Mean160.5
Median Absolute Deviation (MAD)80
Skewness0
Sum51360
Variance8560
MonotonicityStrictly increasing
2024-05-10T21:59:57.116747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
162 1
 
0.3%
220 1
 
0.3%
219 1
 
0.3%
218 1
 
0.3%
217 1
 
0.3%
216 1
 
0.3%
215 1
 
0.3%
214 1
 
0.3%
213 1
 
0.3%
Other values (310) 310
96.9%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
320 1
0.3%
319 1
0.3%
318 1
0.3%
317 1
0.3%
316 1
0.3%
315 1
0.3%
314 1
0.3%
313 1
0.3%
312 1
0.3%
311 1
0.3%

관할
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
부평
32 
서구(서부)
31 
연수구
25 
미추홀구
22 
서구
20 
Other values (30)
190 

Length

Max length10
Median length8
Mean length5.021875
Min length2

Unique

Unique8 ?
Unique (%)2.5%

Sample

1st row중부서(중구)
2nd row중부서(중구)
3rd row중부서(중구)
4th row중부서(중구)
5th row중부서(동구)

Common Values

ValueCountFrequency (%)
부평 32
 
10.0%
서구(서부) 31
 
9.7%
연수구 25
 
7.8%
미추홀구 22
 
6.9%
서구 20
 
6.2%
남동서(남동) 19
 
5.9%
중구 18
 
5.6%
미추홀구(미추홀서) 16
 
5.0%
부평서(부평) 16
 
5.0%
서구(서구청) 13
 
4.1%
Other values (25) 108
33.8%

Length

2024-05-10T21:59:57.604507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부평 35
 
10.7%
서구(서부 31
 
9.5%
연수구 25
 
7.7%
미추홀구 22
 
6.7%
서구 21
 
6.4%
남동서(남동 19
 
5.8%
중구 18
 
5.5%
미추홀구(미추홀서 16
 
4.9%
부평서(부평 16
 
4.9%
서구(서구청 13
 
4.0%
Other values (25) 110
33.7%
Distinct214
Distinct (%)66.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-10T21:59:58.239198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length4.775
Min length2

Characters and Unicode

Total characters1528
Distinct characters214
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique160 ?
Unique (%)50.0%

Sample

1st row연안부두로 33번길
2nd row연안부도로
3rd row월미로 260번길
4th row샛골로
5th row동산로
ValueCountFrequency (%)
매소홀로 10
 
2.7%
미정 10
 
2.7%
평천로 9
 
2.4%
마장로 9
 
2.4%
안남로 6
 
1.6%
주부토로 5
 
1.4%
검단로 5
 
1.4%
남동대로 5
 
1.4%
경원대로 4
 
1.1%
방축로 4
 
1.1%
Other values (222) 303
81.9%
2024-05-10T21:59:59.385663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
306
 
20.0%
60
 
3.9%
55
 
3.6%
50
 
3.3%
2 40
 
2.6%
1 37
 
2.4%
36
 
2.4%
24
 
1.6%
3 22
 
1.4%
20
 
1.3%
Other values (204) 878
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1258
82.3%
Decimal Number 189
 
12.4%
Space Separator 50
 
3.3%
Open Punctuation 8
 
0.5%
Close Punctuation 8
 
0.5%
Dash Punctuation 7
 
0.5%
Uppercase Letter 7
 
0.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
306
24.3%
60
 
4.8%
55
 
4.4%
36
 
2.9%
24
 
1.9%
20
 
1.6%
19
 
1.5%
19
 
1.5%
19
 
1.5%
17
 
1.4%
Other values (182) 683
54.3%
Decimal Number
ValueCountFrequency (%)
2 40
21.2%
1 37
19.6%
3 22
11.6%
0 16
 
8.5%
6 16
 
8.5%
4 15
 
7.9%
9 13
 
6.9%
5 13
 
6.9%
7 10
 
5.3%
8 7
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
E 1
14.3%
A 1
14.3%
C 1
14.3%
D 1
14.3%
B 1
14.3%
G 1
14.3%
F 1
14.3%
Space Separator
ValueCountFrequency (%)
50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1258
82.3%
Common 263
 
17.2%
Latin 7
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
306
24.3%
60
 
4.8%
55
 
4.4%
36
 
2.9%
24
 
1.9%
20
 
1.6%
19
 
1.5%
19
 
1.5%
19
 
1.5%
17
 
1.4%
Other values (182) 683
54.3%
Common
ValueCountFrequency (%)
50
19.0%
2 40
15.2%
1 37
14.1%
3 22
8.4%
0 16
 
6.1%
6 16
 
6.1%
4 15
 
5.7%
9 13
 
4.9%
5 13
 
4.9%
7 10
 
3.8%
Other values (5) 31
11.8%
Latin
ValueCountFrequency (%)
E 1
14.3%
A 1
14.3%
C 1
14.3%
D 1
14.3%
B 1
14.3%
G 1
14.3%
F 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1258
82.3%
ASCII 269
 
17.6%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
306
24.3%
60
 
4.8%
55
 
4.4%
36
 
2.9%
24
 
1.9%
20
 
1.6%
19
 
1.5%
19
 
1.5%
19
 
1.5%
17
 
1.4%
Other values (182) 683
54.3%
ASCII
ValueCountFrequency (%)
50
18.6%
2 40
14.9%
1 37
13.8%
3 22
8.2%
0 16
 
5.9%
6 16
 
5.9%
4 15
 
5.6%
9 13
 
4.8%
5 13
 
4.8%
7 10
 
3.7%
Other values (11) 37
13.8%
None
ValueCountFrequency (%)
· 1
100.0%
Distinct69
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-10T21:59:59.888892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length4
Mean length5.5125
Min length2

Characters and Unicode

Total characters1764
Distinct characters90
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)11.6%

Sample

1st row음식점밀집
2nd row상가밀집
3rd row상가밀집
4th row주택가밀집
5th row주택가밀집
ValueCountFrequency (%)
상가밀집 78
17.1%
산업단지 55
12.1%
밀집 35
 
7.7%
주택가 26
 
5.7%
식당밀집 25
 
5.5%
아파트 23
 
5.0%
주거밀집 22
 
4.8%
공원· 21
 
4.6%
단지· 20
 
4.4%
공원 16
 
3.5%
Other values (63) 135
29.6%
2024-05-10T22:00:00.853409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
178
 
10.1%
178
 
10.1%
153
 
8.7%
136
 
7.7%
110
 
6.2%
109
 
6.2%
98
 
5.6%
84
 
4.8%
· 72
 
4.1%
57
 
3.2%
Other values (80) 589
33.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1536
87.1%
Space Separator 136
 
7.7%
Other Punctuation 77
 
4.4%
Decimal Number 7
 
0.4%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
178
 
11.6%
178
 
11.6%
153
 
10.0%
110
 
7.2%
109
 
7.1%
98
 
6.4%
84
 
5.5%
57
 
3.7%
56
 
3.6%
54
 
3.5%
Other values (70) 459
29.9%
Decimal Number
ValueCountFrequency (%)
7 4
57.1%
1 1
 
14.3%
5 1
 
14.3%
3 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
· 72
93.5%
. 3
 
3.9%
/ 2
 
2.6%
Space Separator
ValueCountFrequency (%)
136
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1536
87.1%
Common 228
 
12.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
178
 
11.6%
178
 
11.6%
153
 
10.0%
110
 
7.2%
109
 
7.1%
98
 
6.4%
84
 
5.5%
57
 
3.7%
56
 
3.6%
54
 
3.5%
Other values (70) 459
29.9%
Common
ValueCountFrequency (%)
136
59.6%
· 72
31.6%
) 4
 
1.8%
7 4
 
1.8%
( 4
 
1.8%
. 3
 
1.3%
/ 2
 
0.9%
1 1
 
0.4%
5 1
 
0.4%
3 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1536
87.1%
ASCII 156
 
8.8%
None 72
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
178
 
11.6%
178
 
11.6%
153
 
10.0%
110
 
7.2%
109
 
7.1%
98
 
6.4%
84
 
5.5%
57
 
3.7%
56
 
3.6%
54
 
3.5%
Other values (70) 459
29.9%
ASCII
ValueCountFrequency (%)
136
87.2%
) 4
 
2.6%
7 4
 
2.6%
( 4
 
2.6%
. 3
 
1.9%
/ 2
 
1.3%
1 1
 
0.6%
5 1
 
0.6%
3 1
 
0.6%
None
ValueCountFrequency (%)
· 72
100.0%

장소
Text

Distinct186
Distinct (%)58.3%
Missing1
Missing (%)0.3%
Memory size2.6 KiB
2024-05-10T22:00:01.443190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.8181818
Min length3

Characters and Unicode

Total characters2494
Distinct characters259
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136 ?
Unique (%)42.6%

Sample

1st row종합어시장 일원
2nd row여객터미널
3rd row월미도문화거리 일원
4th row인천축구 경기장
5th row동산고교
ValueCountFrequency (%)
일원 44
 
7.7%
국제도시 42
 
7.4%
검단산업 27
 
4.7%
단지일원 27
 
4.7%
송도 25
 
4.4%
청라 17
 
3.0%
주변 13
 
2.3%
일대 12
 
2.1%
식당가 10
 
1.8%
상가 8
 
1.4%
Other values (225) 346
60.6%
2024-05-10T22:00:02.489745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
255
 
10.2%
95
 
3.8%
93
 
3.7%
90
 
3.6%
88
 
3.5%
77
 
3.1%
72
 
2.9%
62
 
2.5%
46
 
1.8%
46
 
1.8%
Other values (249) 1570
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2089
83.8%
Space Separator 255
 
10.2%
Decimal Number 99
 
4.0%
Other Punctuation 18
 
0.7%
Uppercase Letter 13
 
0.5%
Close Punctuation 9
 
0.4%
Open Punctuation 9
 
0.4%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
95
 
4.5%
93
 
4.5%
90
 
4.3%
88
 
4.2%
77
 
3.7%
72
 
3.4%
62
 
3.0%
46
 
2.2%
46
 
2.2%
41
 
2.0%
Other values (221) 1379
66.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
15.4%
P 2
15.4%
M 1
7.7%
G 1
7.7%
V 1
7.7%
Q 1
7.7%
L 1
7.7%
U 1
7.7%
S 1
7.7%
T 1
7.7%
Decimal Number
ValueCountFrequency (%)
2 24
24.2%
1 16
16.2%
3 15
15.2%
4 10
10.1%
7 8
 
8.1%
0 6
 
6.1%
5 6
 
6.1%
9 5
 
5.1%
6 5
 
5.1%
8 4
 
4.0%
Other Punctuation
ValueCountFrequency (%)
· 14
77.8%
@ 3
 
16.7%
. 1
 
5.6%
Space Separator
ValueCountFrequency (%)
255
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2089
83.8%
Common 392
 
15.7%
Latin 13
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
95
 
4.5%
93
 
4.5%
90
 
4.3%
88
 
4.2%
77
 
3.7%
72
 
3.4%
62
 
3.0%
46
 
2.2%
46
 
2.2%
41
 
2.0%
Other values (221) 1379
66.0%
Common
ValueCountFrequency (%)
255
65.1%
2 24
 
6.1%
1 16
 
4.1%
3 15
 
3.8%
· 14
 
3.6%
4 10
 
2.6%
) 9
 
2.3%
( 9
 
2.3%
7 8
 
2.0%
0 6
 
1.5%
Other values (7) 26
 
6.6%
Latin
ValueCountFrequency (%)
B 2
15.4%
P 2
15.4%
M 1
7.7%
G 1
7.7%
V 1
7.7%
Q 1
7.7%
L 1
7.7%
U 1
7.7%
S 1
7.7%
T 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2089
83.8%
ASCII 391
 
15.7%
None 14
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
255
65.2%
2 24
 
6.1%
1 16
 
4.1%
3 15
 
3.8%
4 10
 
2.6%
) 9
 
2.3%
( 9
 
2.3%
7 8
 
2.0%
0 6
 
1.5%
5 6
 
1.5%
Other values (17) 33
 
8.4%
Hangul
ValueCountFrequency (%)
95
 
4.5%
93
 
4.5%
90
 
4.3%
88
 
4.2%
77
 
3.7%
72
 
3.4%
62
 
3.0%
46
 
2.2%
46
 
2.2%
41
 
2.0%
Other values (221) 1379
66.0%
None
ValueCountFrequency (%)
· 14
100.0%
Distinct291
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-10T22:00:03.021834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/