Overview

Dataset statistics

Number of variables4
Number of observations57
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory35.3 B

Variable types

Numeric1
Text2
Categorical1

Dataset

Description인천광역시 부평구 자동차 공회전 제한지역 현황 데이터는 공회전 제한구역 명칭, 주소, 종류(차고지, 주차장, 다중이용시설)에 대한 데이터를 제공합니다.
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15102641&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 종류High correlation
종류 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
명칭 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2024-03-18 05:08:00.106860
Analysis finished2024-03-18 05:08:00.966230
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-03-18T14:08:01.027275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.8
Q115
median29
Q343
95-th percentile54.2
Maximum57
Range56
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.598193
Coefficient of variation (CV)0.57235147
Kurtosis-1.2
Mean29
Median Absolute Deviation (MAD)14
Skewness0
Sum1653
Variance275.5
MonotonicityStrictly increasing
2024-03-18T14:08:01.150594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
44 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
57 1
1.8%
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%

명칭
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-03-18T14:08:01.373859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length6.4210526
Min length3

Characters and Unicode

Total characters366
Distinct characters115
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

Unique57 ?
Unique (%)100.0%

Sample

1st row강인여객㈜
2nd row경인렌트카(자)
3rd row경진운수(자)
4th row동산운수㈜
5th row선경기업(자)
ValueCountFrequency (%)
강인여객㈜ 1
 
1.6%
삼산1차 1
 
1.6%
삼산4차 1
 
1.6%
평천로 1
 
1.6%
357번길 1
 
1.6%
시장로 1
 
1.6%
화랑남로5번길 1
 
1.6%
열우물길 1
 
1.6%
일신동 1
 
1.6%
청수3길 1
 
1.6%
Other values (51) 51
83.6%
2024-03-18T14:08:01.715400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 18
 
4.9%
차 15
 
4.1%
길 13
 
3.6%
로 11
 
3.0%
천 11
 
3.0%
장 10
 
2.7%
( 9
 
2.5%
) 9
 
2.5%
평 9
 
2.5%
3 8
 
2.2%
Other values (105) 253
69.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 306
83.6%
Decimal Number 35
 
9.6%
Open Punctuation 9
 
2.5%
Close Punctuation 9
 
2.5%
Space Separator 4
 
1.1%
Other Symbol 3
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 18
 
5.9%
차 15
 
4.9%
길 13
 
4.2%
로 11
 
3.6%
천 11
 
3.6%
장 10
 
3.3%
평 9
 
2.9%
개 8
 
2.6%
산 8
 
2.6%
주 8
 
2.6%
Other values (91) 195
63.7%
Decimal Number
ValueCountFrequency (%)
3 8
22.9%
1 7
20.0%
2 6
17.1%
4 3
 
8.6%
5 3
 
8.6%
6 2
 
5.7%
0 2
 
5.7%
9 2
 
5.7%
8 1
 
2.9%
7 1
 
2.9%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 309
84.4%
Common 57
 
15.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 18
 
5.8%
차 15
 
4.9%
길 13
 
4.2%
로 11
 
3.6%
천 11
 
3.6%
장 10
 
3.2%
평 9
 
2.9%
개 8
 
2.6%
산 8
 
2.6%
주 8
 
2.6%
Other values (92) 198
64.1%
Common
ValueCountFrequency (%)
( 9
15.8%
) 9
15.8%
3 8
14.0%
1 7
12.3%
2 6
10.5%
4
7.0%
4 3
 
5.3%
5 3
 
5.3%
6 2
 
3.5%
0 2
 
3.5%
Other values (3) 4
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 306
83.6%
ASCII 57
 
15.6%
None 3
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 18
 
5.9%
차 15
 
4.9%
길 13
 
4.2%
로 11
 
3.6%
천 11
 
3.6%
장 10
 
3.3%
평 9
 
2.9%
개 8
 
2.6%
산 8
 
2.6%
주 8
 
2.6%
Other values (91) 195
63.7%
ASCII
ValueCountFrequency (%)
( 9
15.8%
) 9
15.8%
3 8
14.0%
1 7
12.3%
2 6
10.5%
4
7.0%
4 3
 
5.3%
5 3
 
5.3%
6 2
 
3.5%
0 2
 
3.5%
Other values (3) 4
7.0%
None
ValueCountFrequency (%)
㈜ 3
100.0%

주소
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-03-18T14:08:01.962858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length20.649123
Min length16

Characters and Unicode

Total characters1177
Distinct characters56
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 백범로578번길 16 (십정동)
2nd row인천광역시 부평구 원적로416번길 50 (산곡동)
3rd row인천광역시 부평구 부평북로 367 (삼산동)
4th row인천광역시 부평구 백범로 569 (십정동)
5th row인천광역시 부평구 부평북로 46 (청천동)
ValueCountFrequency (%)
인천광역시 57
25.4%
부평구 31
 
13.8%
부평동 6
 
2.7%
외 6
 
2.7%
십정동 5
 
2.2%
삼산동 4
 
1.8%
부평구청천동 4
 
1.8%
부평구부평동 3
 
1.3%
부평북로 3
 
1.3%
부개2동 3
 
1.3%
Other values (93) 102
45.5%
2024-03-18T14:08:02.352185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
167
 
14.2%
부 83
 
7.1%
평 77
 
6.5%
천 65
 
5.5%
시 59
 
5.0%
인 57
 
4.8%
광 57
 
4.8%
역 57
 
4.8%
구 57
 
4.8%
동 57
 
4.8%
Other values (46) 441
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 701
59.6%
Decimal Number 246
 
20.9%
Space Separator 167
 
14.2%
Dash Punctuation 32
 
2.7%
Open Punctuation 15
 
1.3%
Close Punctuation 15
 
1.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 83
11.8%
평 77
11.0%
천 65
9.3%
시 59
8.4%
인 57
8.1%
광 57
8.1%
역 57
8.1%
구 57
8.1%
동 57
8.1%
산 21
 
3.0%
Other values (31) 111
15.8%
Decimal Number
ValueCountFrequency (%)
1 51
20.7%
2 35
14.2%
3 32
13.0%
6 25
10.2%
4 21
8.5%
5 21
8.5%
9 18
 
7.3%
7 17
 
6.9%
8 13
 
5.3%
0 13
 
5.3%
Space Separator
ValueCountFrequency (%)
167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 701
59.6%
Common 476
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 83
11.8%
평 77
11.0%
천 65
9.3%
시 59
8.4%
인 57
8.1%
광 57
8.1%
역 57
8.1%
구 57
8.1%
동 57
8.1%
산 21
 
3.0%
Other values (31) 111
15.8%
Common
ValueCountFrequency (%)
167
35.1%
1 51
 
10.7%
2 35
 
7.4%
- 32
 
6.7%
3 32
 
6.7%
6 25
 
5.3%
4 21
 
4.4%
5 21
 
4.4%
9 18
 
3.8%
7 17
 
3.6%
Other values (5) 57
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 701
59.6%
ASCII 476
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
167
35.1%
1 51
 
10.7%
2 35
 
7.4%
- 32
 
6.7%
3 32
 
6.7%
6 25
 
5.3%
4 21
 
4.4%
5 21
 
4.4%
9 18
 
3.8%
7 17
 
3.6%
Other values (5) 57
 
12.0%
Hangul
ValueCountFrequency (%)
부 83
11.8%
평 77
11.0%
천 65
9.3%
시 59
8.4%
인 57
8.1%
광 57
8.1%
역 57
8.1%
구 57
8.1%
동 57
8.1%
산 21
 
3.0%
Other values (31) 111
15.8%

종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
주차장
44 
차고지
7 
다중이용시설
5 
유치원
 
1

Length

Max length6
Median length3
Mean length3.2631579
Min length3

Unique

Unique1 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
주차장 44
77.2%
차고지 7
 
12.3%
다중이용시설 5
 
8.8%
유치원 1
 
1.8%

Length

2024-03-18T14:08:02.481728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:08:02.590155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주차장 44
77.2%
차고지 7
 
12.3%
다중이용시설 5
 
8.8%
유치원 1
 
1.8%

Interactions

2024-03-18T14:08:00.748541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:08:02.658156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번명칭주소종류
연번1.0001.0001.0000.877
명칭1.0001.0001.0001.000
주소1.0001.0001.0001.000
종류0.8771.0001.0001.000
2024-03-18T14:08:02.757769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종류
연번1.0000.697
종류0.6971.000

Missing values

2024-03-18T14:08:00.849015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:08:00.934579image/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

연번명칭주소종류
01강인여객㈜인천광역시 부평구 백범로578번길 16 (십정동)차고지
12경인렌트카(자)인천광역시 부평구 원적로416번길 50 (산곡동)차고지
23경진운수(자)인천광역시 부평구 부평북로 367 (삼산동)차고지
34동산운수㈜인천광역시 부평구 백범로 569 (십정동)차고지
45선경기업(자)인천광역시 부평구 부평북로 46 (청천동)차고지
56태양상운수인천광역시 부평구 부평북로 179 (청천동)차고지
67태양여객㈜인천광역시 부평구 송내대로373번길 54 (삼산동)차고지
78갈산역인천광역시 부평구 갈산1동 192주차장
89갈월산인천광역시 부평구 갈산1동 161-15주차장
910고니샘인천광역시 부평구 부평5동 10-766주차장
연번명칭주소종류
4748무지개아파트옆인천광역시 부평구산곡2동 254-3 외주차장
4849사랑샘공원인천광역시 부평구삼산1동 497주차장
4950길주로339번길인천광역시 부평구산곡1동 산132 외주차장
5051신트리로8번길인천광역시 부평구신트리로8번길 18 (부평동)주차장
5152더큰빛유치원인천광역시 부평구장제로195번길 42유치원
5253롯데마트부평역점(건축물주차장)인천광역시 부평구부평동 738-21다중이용시설
5354롯데마트삼산점인천광역시 부평구길주로 623 (삼산동)다중이용시설
5455롯데마트부평점인천광역시 부평구마장로 296 (산곡동)다중이용시설
5556인천성모병원(건축물주차장)인천광역시 부평구동수로52번길 2 (부평동)다중이용시설
5657세림병원(건축물주차장)인천광역시 부평구청천동 302-9다중이용시설