Overview

Dataset statistics

Number of variables7
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory62.3 B

Variable types

Numeric2
Text3
DateTime1
Categorical1

Dataset

Description인천광역시 남동구 금연아파트 현황에 대한 데이터로 연번, 지정번호, 명칭, 소재지, 지정일자, 계도기한, 거주세대, 금연구역지정 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3077612&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 금연구역지정High correlation
금연구역지정 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
지정번호 has unique valuesUnique
명칭 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2024-03-13 06:28:30.077622
Analysis finished2024-03-13 06:28:31.154495
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-03-13T15:28:31.234685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q18.5
median16
Q323.5
95-th percentile29.5
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.0921211
Coefficient of variation (CV)0.56825757
Kurtosis-1.2
Mean16
Median Absolute Deviation (MAD)8
Skewness0
Sum496
Variance82.666667
MonotonicityStrictly increasing
2024-03-13T15:28:31.374209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 1
 
3.2%
2 1
 
3.2%
31 1
 
3.2%
30 1
 
3.2%
29 1
 
3.2%
28 1
 
3.2%
27 1
 
3.2%
26 1
 
3.2%
25 1
 
3.2%
24 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
1 1
3.2%
2 1
3.2%
3 1
3.2%
4 1
3.2%
5 1
3.2%
6 1
3.2%
7 1
3.2%
8 1
3.2%
9 1
3.2%
10 1
3.2%
ValueCountFrequency (%)
31 1
3.2%
30 1
3.2%
29 1
3.2%
28 1
3.2%
27 1
3.2%
26 1
3.2%
25 1
3.2%
24 1
3.2%
23 1
3.2%
22 1
3.2%

지정번호
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-03-13T15:28:31.554330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.7096774
Min length8

Characters and Unicode

Total characters270
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row남동구 제 1호
2nd row남동구 제 2호
3rd row남동구 제 3호
4th row남동구 제 4호
5th row남동구 제 5호
ValueCountFrequency (%)
남동구 31
33.3%
제 31
33.3%
30호 1
 
1.1%
29호 1
 
1.1%
28호 1
 
1.1%
27호 1
 
1.1%
26호 1
 
1.1%
25호 1
 
1.1%
16호 1
 
1.1%
23호 1
 
1.1%
Other values (23) 23
24.7%
2024-03-13T15:28:31.844544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
62
23.0%
남 31
11.5%
동 31
11.5%
구 31
11.5%
제 31
11.5%
호 31
11.5%
1 14
 
5.2%
2 13
 
4.8%
3 5
 
1.9%
4 3
 
1.1%
Other values (6) 18
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 155
57.4%
Space Separator 62
 
23.0%
Decimal Number 53
 
19.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
26.4%
2 13
24.5%
3 5
 
9.4%
4 3
 
5.7%
5 3
 
5.7%
6 3
 
5.7%
7 3
 
5.7%
8 3
 
5.7%
9 3
 
5.7%
0 3
 
5.7%
Other Letter
ValueCountFrequency (%)
남 31
20.0%
동 31
20.0%
구 31
20.0%
제 31
20.0%
호 31
20.0%
Space Separator
ValueCountFrequency (%)
62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 155
57.4%
Common 115
42.6%

Most frequent character per script

Common
ValueCountFrequency (%)
62
53.9%
1 14
 
12.2%
2 13
 
11.3%
3 5
 
4.3%
4 3
 
2.6%
5 3
 
2.6%
6 3
 
2.6%
7 3
 
2.6%
8 3
 
2.6%
9 3
 
2.6%
Hangul
ValueCountFrequency (%)
남 31
20.0%
동 31
20.0%
구 31
20.0%
제 31
20.0%
호 31
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 155
57.4%
ASCII 115
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
62
53.9%
1 14
 
12.2%
2 13
 
11.3%
3 5
 
4.3%
4 3
 
2.6%
5 3
 
2.6%
6 3
 
2.6%
7 3
 
2.6%
8 3
 
2.6%
9 3
 
2.6%
Hangul
ValueCountFrequency (%)
남 31
20.0%
동 31
20.0%
구 31
20.0%
제 31
20.0%
호 31
20.0%

명칭
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-03-13T15:28:32.057023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length8.9677419
Min length4

Characters and Unicode

Total characters278
Distinct characters98
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row구월아시아드선수촌센트럴자이
2nd row소래LH4단지
3rd row뉴삼환빌라
4th row서창LH6단지
5th row송림아트빌라
ValueCountFrequency (%)
논현 2
 
5.1%
구월아시아드선수촌센트럴자이 1
 
2.6%
7단지 1
 
2.6%
인천서창꿈에그린 1
 
2.6%
한양수자인아르디에 1
 
2.6%
에코메트로 1
 
2.6%
3차 1
 
2.6%
더타워 1
 
2.6%
한화에코메트로 1
 
2.6%
서창센트라스아파트 1
 
2.6%
Other values (28) 28
71.8%
2024-03-13T15:28:32.430634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 16
 
5.8%
트 15
 
5.4%
지 14
 
5.0%
단 11
 
4.0%
에 8
 
2.9%
한 8
 
2.9%
8
 
2.9%
파 8
 
2.9%
창 7
 
2.5%
서 7
 
2.5%
Other values (88) 176
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 248
89.2%
Decimal Number 13
 
4.7%
Space Separator 8
 
2.9%
Uppercase Letter 6
 
2.2%
Lowercase Letter 1
 
0.4%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 16
 
6.5%
트 15
 
6.0%
지 14
 
5.6%
단 11
 
4.4%
에 8
 
3.2%
한 8
 
3.2%
파 8
 
3.2%
창 7
 
2.8%
서 7
 
2.8%
스 6
 
2.4%
Other values (74) 148
59.7%
Decimal Number
ValueCountFrequency (%)
1 5
38.5%
7 2
 
15.4%
4 1
 
7.7%
3 1
 
7.7%
9 1
 
7.7%
6 1
 
7.7%
2 1
 
7.7%
8 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
H 3
50.0%
L 3
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 248
89.2%
Common 23
 
8.3%
Latin 7
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 16
 
6.5%
트 15
 
6.0%
지 14
 
5.6%
단 11
 
4.4%
에 8
 
3.2%
한 8
 
3.2%
파 8
 
3.2%
창 7
 
2.8%
서 7
 
2.8%
스 6
 
2.4%
Other values (74) 148
59.7%
Common
ValueCountFrequency (%)
8
34.8%
1 5
21.7%
7 2
 
8.7%
4 1
 
4.3%
3 1
 
4.3%
9 1
 
4.3%
6 1
 
4.3%
2 1
 
4.3%
) 1
 
4.3%
( 1
 
4.3%
Latin
ValueCountFrequency (%)
H 3
42.9%
L 3
42.9%
e 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 248
89.2%
ASCII 30
 
10.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 16
 
6.5%
트 15
 
6.0%
지 14
 
5.6%
단 11
 
4.4%
에 8
 
3.2%
한 8
 
3.2%
파 8
 
3.2%
창 7
 
2.8%
서 7
 
2.8%
스 6
 
2.4%
Other values (74) 148
59.7%
ASCII
ValueCountFrequency (%)
8
26.7%
1 5
16.7%
H 3
 
10.0%
L 3
 
10.0%
7 2
 
6.7%
4 1
 
3.3%
3 1
 
3.3%
9 1
 
3.3%
6 1
 
3.3%
2 1
 
3.3%
Other values (4) 4
13.3%

소재지
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-03-13T15:28:32.646448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length23
Mean length19.516129
Min length14

Characters and Unicode

Total characters605
Distinct characters58
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

Unique31 ?
Unique (%)100.0%

Sample

1st row인천광역시 남동구 선수촌로 55
2nd row인천광역시 남동구 논고개로68번길 34
3rd row인천광역시 남동구 용천로17번길 9, 용천로17번길 11
4th row인천광역시 남동구 서창남순환로 190-100
5th row인천광역시 남동구 구월로64번길 6
ValueCountFrequency (%)
인천광역시 31
25.6%
남동구 27
22.3%
서창남순환로 3
 
2.5%
에코중앙로 3
 
2.5%
선수촌로 2
 
1.7%
만수서로 2
 
1.7%
34 2
 
1.7%
용천로17번길 2
 
1.7%
9 2
 
1.7%
11 2
 
1.7%
Other values (44) 45
37.2%
2024-03-13T15:28:33.027283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90
14.9%
남 35
 
5.8%
천 34
 
5.6%
구 34
 
5.6%
역 33
 
5.5%
로 32
 
5.3%
동 31
 
5.1%
인 31
 
5.1%
시 31
 
5.1%
광 31
 
5.1%
Other values (48) 223
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 404
66.8%
Decimal Number 100
 
16.5%
Space Separator 90
 
14.9%
Dash Punctuation 4
 
0.7%
Open Punctuation 3
 
0.5%
Close Punctuation 3
 
0.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 35
 
8.7%
천 34
 
8.4%
구 34
 
8.4%
역 33
 
8.2%
로 32
 
7.9%
동 31
 
7.7%
인 31
 
7.7%
시 31
 
7.7%
광 31
 
7.7%
번 12
 
3.0%
Other values (33) 100
24.8%
Decimal Number
ValueCountFrequency (%)
1 19
19.0%
6 13
13.0%
4 13
13.0%
0 12
12.0%
9 11
11.0%
5 10
10.0%
3 7
 
7.0%
7 6
 
6.0%
8 5
 
5.0%
2 4
 
4.0%
Space Separator
ValueCountFrequency (%)
90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 404
66.8%
Common 201
33.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 35
 
8.7%
천 34
 
8.4%
구 34
 
8.4%
역 33
 
8.2%
로 32
 
7.9%
동 31
 
7.7%
인 31
 
7.7%
시 31
 
7.7%
광 31
 
7.7%
번 12
 
3.0%
Other values (33) 100
24.8%
Common
ValueCountFrequency (%)
90
44.8%
1 19
 
9.5%
6 13
 
6.5%
4 13
 
6.5%
0 12
 
6.0%
9 11
 
5.5%
5 10
 
5.0%
3 7
 
3.5%
7 6
 
3.0%
8 5
 
2.5%
Other values (5) 15
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 404
66.8%
ASCII 201
33.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
90
44.8%
1 19
 
9.5%
6 13
 
6.5%
4 13
 
6.5%
0 12
 
6.0%
9 11
 
5.5%
5 10
 
5.0%
3 7
 
3.5%
7 6
 
3.0%
8 5
 
2.5%
Other values (5) 15
 
7.5%
Hangul
ValueCountFrequency (%)
남 35
 
8.7%
천 34
 
8.4%
구 34
 
8.4%
역 33
 
8.2%
로 32
 
7.9%
동 31
 
7.7%
인 31
 
7.7%
시 31
 
7.7%
광 31
 
7.7%
번 12
 
3.0%
Other values (33) 100
24.8%

지정일자
Date

Distinct27
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2017-01-06 00:00:00
Maximum2023-05-10 00:00:00
2024-03-13T15:28:33.150896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T15:28:33.268710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

거주세대
Real number (ℝ)

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean711.93548
Minimum5
Maximum3208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-03-13T15:28:33.435155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile14
Q1337
median754
Q3852.5
95-th percentile1409
Maximum3208
Range3203
Interquartile range (IQR)515.5

Descriptive statistics

Standard deviation614.26221
Coefficient of variation (CV)0.862806
Kurtosis8.3973476
Mean711.93548
Median Absolute Deviation (MAD)316
Skewness2.2436681
Sum22070
Variance377318.06
MonotonicityNot monotonic
2024-03-13T15:28:33.564127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
376 2
 
6.5%
298 1
 
3.2%
228 1
 
3.2%
643 1
 
3.2%
810 1
 
3.2%
795 1
 
3.2%
1622 1
 
3.2%
898 1
 
3.2%
566 1
 
3.2%
848 1
 
3.2%
Other values (20) 20
64.5%
ValueCountFrequency (%)
5 1
3.2%
10 1
3.2%
18 1
3.2%
26 1
3.2%
34 1
3.2%
228 1
3.2%
236 1
3.2%
298 1
3.2%
376 2
6.5%
438 1
3.2%
ValueCountFrequency (%)
3208 1
3.2%
1622 1
3.2%
1196 1
3.2%
1189 1
3.2%
1160 1
3.2%
982 1
3.2%
898 1
3.2%
855 1
3.2%
850 1
3.2%
848 1
3.2%

금연구역지정
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
복도+계단+엘리베이터+지하주차장
16 
복도+엘리베이터+계단+지하주차장
11 
계단
3 
복도+계단+엘리베이터
 
1

Length

Max length17
Median length17
Mean length15.354839
Min length2

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row복도+계단+엘리베이터+지하주차장
2nd row복도+계단+엘리베이터+지하주차장
3rd row계단
4th row복도+계단+엘리베이터+지하주차장
5th row계단

Common Values

ValueCountFrequency (%)
복도+계단+엘리베이터+지하주차장 16
51.6%
복도+엘리베이터+계단+지하주차장 11
35.5%
계단 3
 
9.7%
복도+계단+엘리베이터 1
 
3.2%

Length

2024-03-13T15:28:33.694461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T15:28:33.811611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
복도+계단+엘리베이터+지하주차장 16
51.6%
복도+엘리베이터+계단+지하주차장 11
35.5%
계단 3
 
9.7%
복도+계단+엘리베이터 1
 
3.2%

Interactions

2024-03-13T15:28:30.769842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T15:28:30.357028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T15:28:30.857346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T15:28:30.437815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T15:28:33.891551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지정번호명칭소재지지정일자거주세대금연구역지정
연번1.0001.0001.0001.0001.0000.0000.696
지정번호1.0001.0001.0001.0001.0001.0001.000
명칭1.0001.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.0001.000
지정일자1.0001.0001.0001.0001.0000.0000.875
거주세대0.0001.0001.0001.0000.0001.0000.372
금연구역지정0.6961.0001.0001.0000.8750.3721.000
2024-03-13T15:28:33.988299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번거주세대금연구역지정
연번1.0000.0460.519
거주세대0.0461.0000.227
금연구역지정0.5190.2271.000

Missing values

2024-03-13T15:28:30.980965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T15:28:31.095659image/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

연번지정번호명칭소재지지정일자거주세대금연구역지정
01남동구 제 1호구월아시아드선수촌센트럴자이인천광역시 남동구 선수촌로 552017-01-06850복도+계단+엘리베이터+지하주차장
12남동구 제 2호소래LH4단지인천광역시 남동구 논고개로68번길 342017-01-06820복도+계단+엘리베이터+지하주차장
23남동구 제 3호뉴삼환빌라인천광역시 남동구 용천로17번길 9, 용천로17번길 112017-01-0634계단
34남동구 제 4호서창LH6단지인천광역시 남동구 서창남순환로 190-1002017-06-09855복도+계단+엘리베이터+지하주차장
45남동구 제 5호송림아트빌라인천광역시 남동구 구월로64번길 62017-08-0210계단
56남동구 제 6호서창LH7단지인천광역시 남동구 서창남순환로 190-152017-11-221196복도+계단+엘리베이터+지하주차장
67남동구 제 7호미광빌라인천광역시 남동구 구월말로39번길 50-32017-11-295계단
78남동구 제 8호구월아시아드선수촌 8단지(자이아파트)인천광역시 남동구 선수촌로 82018-03-19768복도+계단+엘리베이터+지하주차장
89남동구 제 9호e편한세상서창인천광역시 남동구 서창남순환로 92018-05-08835복도+계단+엘리베이터+지하주차장
910남동구 제 10호향촌휴먼시아2단지인천광역시 남동구 만수서로 362018-06-14438복도+계단+엘리베이터+지하주차장
연번지정번호명칭소재지지정일자거주세대금연구역지정
2122남동구 제 22호에코메트로 3차 더타워인천광역시 남동구 소래역남로 402021-02-18644복도+엘리베이터+계단+지하주차장
2223남동구 제 23호한화에코메트로 7단지인천광역시 남동구 에코중앙로 1632021-08-11848복도+엘리베이터+계단+지하주차장
2324남동구 제 24호서창센트라스아파트인천광역시 남동구 서청남순환로 2012021-08-11566복도+엘리베이터+계단+지하주차장
2425남동구 제 25호구월지웰시티푸르지오아파트인천광역시 남동구 남동대로799번길 342021-08-23376복도+엘리베이터+계단+지하주차장
2526남동구 제 26호단풍마을휴먼시아11단지인천광역시 남동구 소래역로 942021-11-17898복도+엘리베이터+계단+지하주차장
2627남동구 제 27호한화에코메트로11단지인천광역시 남동구 논고개로 172021-12-071622복도+엘리베이터+계단+지하주차장
2728남동구 제 28호하우스스토리 만수아파트인천광역시 남동구 구월로372번길 902022-01-03795복도+엘리베이터+계단+지하주차장
2829남동구 제 29호한화에코메트로9단지아파트인천광역시 남동구 에코중앙로962022-10-05810복도+엘리베이터+계단+지하주차장
2930남동구 제 30호간석한신더휴아파트인천광역시 남동구 석정로461번길 502022-10-26643복도+엘리베이터+계단+지하주차장
3031남동구 제 31호한라아파트인천광역시 남동구 포구로 64-62023-05-10228복도+엘리베이터+계단+지하주차장