Overview

Dataset statistics

Number of variables6
Number of observations1752
Missing cells409
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory84.0 KiB
Average record size in memory49.1 B

Variable types

Numeric1
Categorical1
Text3
DateTime1

Dataset

Description인천광역시 남동구 소재 소독의무시설에 대한 데이터로 연번, 업종명, 업소명, 영업소 주소(도로명), 소재지전화, 데이터기준일을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15038940&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 연번High correlation
소재지전화 has 393 (22.4%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 05:22:14.034466
Analysis finished2024-01-28 05:22:14.991248
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1752
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean876.5
Minimum1
Maximum1752
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.5 KiB
2024-01-28T14:22:15.052847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile88.55
Q1438.75
median876.5
Q31314.25
95-th percentile1664.45
Maximum1752
Range1751
Interquartile range (IQR)875.5

Descriptive statistics

Standard deviation505.90315
Coefficient of variation (CV)0.57718557
Kurtosis-1.2
Mean876.5
Median Absolute Deviation (MAD)438
Skewness0
Sum1535628
Variance255938
MonotonicityStrictly increasing
2024-01-28T14:22:15.177262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1166 1
 
0.1%
1177 1
 
0.1%
1176 1
 
0.1%
1175 1
 
0.1%
1174 1
 
0.1%
1173 1
 
0.1%
1172 1
 
0.1%
1171 1
 
0.1%
1170 1
 
0.1%
Other values (1742) 1742
99.4%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1752 1
0.1%
1751 1
0.1%
1750 1
0.1%
1749 1
0.1%
1748 1
0.1%
1747 1
0.1%
1746 1
0.1%
1745 1
0.1%
1744 1
0.1%
1743 1
0.1%

업종명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size13.8 KiB
집단급식소
758 
식품접객업소
216 
기타건축물
211 
어린이집,유치원
176 
공동주택
135 
Other values (7)
256 

Length

Max length8
Median length5
Mean length5.0724886
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
집단급식소 758
43.3%
식품접객업소 216
 
12.3%
기타건축물 211
 
12.0%
어린이집,유치원 176
 
10.0%
공동주택 135
 
7.7%
숙박업소 93
 
5.3%
학교 76
 
4.3%
병원 44
 
2.5%
백화점시장 20
 
1.1%
버스철도 17
 
1.0%
Other values (2) 6
 
0.3%

Length

2024-01-28T14:22:15.338546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
집단급식소 758
43.3%
식품접객업소 216
 
12.3%
기타건축물 211
 
12.0%
어린이집,유치원 176
 
10.0%
공동주택 135
 
7.7%
숙박업소 93
 
5.3%
학교 76
 
4.3%
병원 44
 
2.5%
백화점시장 20
 
1.1%
버스철도 17
 
1.0%
Other values (2) 6
 
0.3%

업소명
Text

Distinct1490
Distinct (%)85.8%
Missing15
Missing (%)0.9%
Memory size13.8 KiB
2024-01-28T14:22:15.550263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length22
Mean length7.5187104
Min length2

Characters and Unicode

Total characters13060
Distinct characters599
Distinct categories10 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1245 ?
Unique (%)71.7%

Sample

1st row주얼리모텔
2nd row화승여관
3rd row산장여인숙
4th row옥수장여관
5th row광명장여관
ValueCountFrequency (%)
고려요양병원 3
 
0.2%
해마루플러스 3
 
0.2%
숲속의유치원 2
 
0.1%
인천고잔유치원 2
 
0.1%
인천송천고등학교 2
 
0.1%
논현어린이집 2
 
0.1%
움트리어린이집 2
 
0.1%
남동구청어린이집 2
 
0.1%
웰메이드 2
 
0.1%
파이디온어린이집 2
 
0.1%
Other values (1480) 1715
98.7%
2024-01-28T14:22:15.913626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 436
 
3.3%
주 370
 
2.8%
) 349
 
2.7%
( 349
 
2.7%
인 348
 
2.7%
원 296
 
2.3%
천 286
 
2.2%
어 265
 
2.0%
집 265
 
2.0%
린 264
 
2.0%
Other values (589) 9832
75.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11935
91.4%
Close Punctuation 349
 
2.7%
Open Punctuation 349
 
2.7%
Decimal Number 195
 
1.5%
Uppercase Letter 146
 
1.1%
Lowercase Letter 48
 
0.4%
Dash Punctuation 17
 
0.1%
Other Punctuation 17
 
0.1%
Other Symbol 2
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 436
 
3.7%
주 370
 
3.1%
인 348
 
2.9%
원 296
 
2.5%
천 286
 
2.4%
어 265
 
2.2%
집 265
 
2.2%
린 264
 
2.2%
스 219
 
1.8%
교 198
 
1.7%
Other values (529) 8988
75.3%
Uppercase Letter
ValueCountFrequency (%)
L 21
14.4%
H 20
13.7%
S 13
 
8.9%
T 11
 
7.5%
B 8
 
5.5%
E 8
 
5.5%
D 7
 
4.8%
M 7
 
4.8%
O 7
 
4.8%
A 7
 
4.8%
Other values (12) 37
25.3%
Lowercase Letter
ValueCountFrequency (%)
e 8
16.7%
a 5
10.4%
o 5
10.4%
s 5
10.4%
r 4
8.3%
c 4
8.3%
m 3
 
6.2%
t 2
 
4.2%
d 2
 
4.2%
l 2
 
4.2%
Other values (7) 8
16.7%
Decimal Number
ValueCountFrequency (%)
1 63
32.3%
2 55
28.2%
3 14
 
7.2%
5 13
 
6.7%
6 11
 
5.6%
4 10
 
5.1%
0 10
 
5.1%
7 8
 
4.1%
8 6
 
3.1%
9 5
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 6
35.3%
& 4
23.5%
/ 3
17.6%
· 2
 
11.8%
, 2
 
11.8%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
50.0%
Ⅱ 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 349
100.0%
Open Punctuation
ValueCountFrequency (%)
( 349
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11932
91.4%
Common 927
 
7.1%
Latin 195
 
1.5%
Han 5
 
< 0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 436
 
3.7%
주 370
 
3.1%
인 348
 
2.9%
원 296
 
2.5%
천 286
 
2.4%
어 265
 
2.2%
집 265
 
2.2%
린 264
 
2.2%
스 219
 
1.8%
교 198
 
1.7%
Other values (525) 8985
75.3%
Latin
ValueCountFrequency (%)
L 21
 
10.8%
H 20
 
10.3%
S 13
 
6.7%
T 11
 
5.6%
e 8
 
4.1%
B 8
 
4.1%
E 8
 
4.1%
D 7
 
3.6%
M 7
 
3.6%
O 7
 
3.6%
Other values (30) 85
43.6%
Common
ValueCountFrequency (%)
) 349
37.6%
( 349
37.6%
1 63
 
6.8%
2 55
 
5.9%
- 17
 
1.8%
3 14
 
1.5%
5 13
 
1.4%
6 11
 
1.2%
4 10
 
1.1%
0 10
 
1.1%
Other values (8) 36
 
3.9%
Han
ValueCountFrequency (%)
名 1
20.0%
品 1
20.0%
月 1
20.0%
禧 1
20.0%
宴 1
20.0%
Greek
ValueCountFrequency (%)
π 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11930
91.3%
ASCII 1118
 
8.6%
None 5
 
< 0.1%
CJK 5
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 436
 
3.7%
주 370
 
3.1%
인 348
 
2.9%
원 296
 
2.5%
천 286
 
2.4%
어 265
 
2.2%
집 265
 
2.2%
린 264
 
2.2%
스 219
 
1.8%
교 198
 
1.7%
Other values (524) 8983
75.3%
ASCII
ValueCountFrequency (%)
) 349
31.2%
( 349
31.2%
1 63
 
5.6%
2 55
 
4.9%
L 21
 
1.9%
H 20
 
1.8%
- 17
 
1.5%
3 14
 
1.3%
5 13
 
1.2%
S 13
 
1.2%
Other values (45) 204
18.2%
None
ValueCountFrequency (%)
㈜ 2
40.0%
· 2
40.0%
π 1
20.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
50.0%
Ⅱ 1
50.0%
CJK
ValueCountFrequency (%)
名 1
20.0%
品 1
20.0%
月 1
20.0%
禧 1
20.0%
宴 1
20.0%

영업소주소(도로명)
Text

Distinct1665
Distinct (%)95.1%
Missing1
Missing (%)0.1%
Memory size13.8 KiB
2024-01-28T14:22:16.147166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length38
Mean length19.254712
Min length4

Characters and Unicode

Total characters33715
Distinct characters352
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1580 ?
Unique (%)90.2%

Sample

1st row남동대로921번길21(간석동,(남동대로921번길21))
2nd row경인로644번길12-1(간석동)
3rd row남동대로916번길83(간석동)
4th row만수로71번길6(만수동,89,90번지)
5th row호구포로889번길16,3층(간석동)
ValueCountFrequency (%)
석산로208번길37(구월동 3
 
0.2%
남동서로237,5층(논현동 2
 
0.1%
수현로9(장수동 2
 
0.1%
능허대로563,a동지하1층(고잔동,133블록6로트 2
 
0.1%
아암대로1503번길48(논현동 2
 
0.1%
논곡로13,가동지1층(남촌동 2
 
0.1%
백범로248번길38(만수동 2
 
0.1%
인주대로899(만수동 2
 
0.1%
남동동로192,지하1층(고잔동,76블록15로트 2
 
0.1%
당좌로15-1(구월동 2
 
0.1%
Other values (1655) 1730
98.8%
2024-01-28T14:22:16.514022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2528
 
7.5%
동 2166
 
6.4%
로 1821
 
5.4%
( 1508
 
4.5%
) 1508
 
4.5%
2 1444
 
4.3%
, 1396
 
4.1%
3 1065
 
3.2%
4 933
 
2.8%
층 852
 
2.5%
Other values (342) 18494
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18262
54.2%
Decimal Number 10221
30.3%
Open Punctuation 1508
 
4.5%
Close Punctuation 1508
 
4.5%
Other Punctuation 1408
 
4.2%
Dash Punctuation 511
 
1.5%
Uppercase Letter 238
 
0.7%
Math Symbol 58
 
0.2%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2166
 
11.9%
로 1821
 
10.0%
층 852
 
4.7%
길 819
 
4.5%
번 815
 
4.5%
남 530
 
2.9%
구 503
 
2.8%
고 457
 
2.5%
월 417
 
2.3%
논 396
 
2.2%
Other values (308) 9486
51.9%
Uppercase Letter
ValueCountFrequency (%)
L 78
32.8%
B 73
30.7%
A 28
 
11.8%
H 18
 
7.6%
T 15
 
6.3%
C 9
 
3.8%
D 4
 
1.7%
S 3
 
1.3%
M 2
 
0.8%
G 2
 
0.8%
Other values (5) 6
 
2.5%
Decimal Number
ValueCountFrequency (%)
1 2528
24.7%
2 1444
14.1%
3 1065
10.4%
4 933
 
9.1%
5 842
 
8.2%
6 741
 
7.2%
0 718
 
7.0%
7 700
 
6.8%
9 644
 
6.3%
8 606
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 1396
99.1%
/ 7
 
0.5%
. 4
 
0.3%
& 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1508
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1508
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 511
100.0%
Math Symbol
ValueCountFrequency (%)
~ 58
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18262
54.2%
Common 15214
45.1%
Latin 239
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2166
 
11.9%
로 1821
 
10.0%
층 852
 
4.7%
길 819
 
4.5%
번 815
 
4.5%
남 530
 
2.9%
구 503
 
2.8%
고 457
 
2.5%
월 417
 
2.3%
논 396
 
2.2%
Other values (308) 9486
51.9%
Common
ValueCountFrequency (%)
1 2528
16.6%
( 1508
9.9%
) 1508
9.9%
2 1444
9.5%
, 1396
9.2%
3 1065
7.0%
4 933
 
6.1%
5 842
 
5.5%
6 741
 
4.9%
0 718
 
4.7%
Other values (8) 2531
16.6%
Latin
ValueCountFrequency (%)
L 78
32.6%
B 73
30.5%
A 28
 
11.7%
H 18
 
7.5%
T 15
 
6.3%
C 9
 
3.8%
D 4
 
1.7%
S 3
 
1.3%
M 2
 
0.8%
G 2
 
0.8%
Other values (6) 7
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18262
54.2%
ASCII 15453
45.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2528
16.4%
( 1508
9.8%
) 1508
9.8%
2 1444
9.3%
, 1396
9.0%
3 1065
 
6.9%
4 933
 
6.0%
5 842
 
5.4%
6 741
 
4.8%
0 718
 
4.6%
Other values (24) 2770
17.9%
Hangul
ValueCountFrequency (%)
동 2166
 
11.9%
로 1821
 
10.0%
층 852
 
4.7%
길 819
 
4.5%
번 815
 
4.5%
남 530
 
2.9%
구 503
 
2.8%
고 457
 
2.5%
월 417
 
2.3%
논 396
 
2.2%
Other values (308) 9486
51.9%

소재지전화
Text

MISSING 

Distinct1185
Distinct (%)87.2%
Missing393
Missing (%)22.4%
Memory size13.8 KiB
2024-01-28T14:22:16.772385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.980868
Min length9

Characters and Unicode

Total characters16282
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

Unique1043 ?
Unique (%)76.7%

Sample

1st row032-428-7779
2nd row032-434-5330
3rd row032-434-5437
4th row032-467-9962
5th row032-435-0113
ValueCountFrequency (%)
032-465-2533 13
 
1.0%
032-421-3300 7
 
0.5%
032-466-1190 7
 
0.5%
032-346-1000 7
 
0.5%
032-465-7154 6
 
0.4%
032-462-3065 3
 
0.2%
032-442-0343 3
 
0.2%
032-469-1210 2
 
0.1%
032-464-3419 2
 
0.1%
032-814-1760 2
 
0.1%
Other values (1175) 1307
96.2%
2024-01-28T14:22:17.117614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2709
16.6%
2 2414
14.8%
0 2333
14.3%
3 2244
13.8%
4 1550
9.5%
1 1145
7.0%
6 946
 
5.8%
8 881
 
5.4%
7 772
 
4.7%
5 737
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13573
83.4%
Dash Punctuation 2709
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2414
17.8%
0 2333
17.2%
3 2244
16.5%
4 1550
11.4%
1 1145
8.4%
6 946
 
7.0%
8 881
 
6.5%
7 772
 
5.7%
5 737
 
5.4%
9 551
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 2709
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16282
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2709
16.6%
2 2414
14.8%
0 2333
14.3%
3 2244
13.8%
4 1550
9.5%
1 1145
7.0%
6 946
 
5.8%
8 881
 
5.4%
7 772
 
4.7%
5 737
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16282
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2709
16.6%
2 2414
14.8%
0 2333
14.3%
3 2244
13.8%
4 1550
9.5%
1 1145
7.0%
6 946
 
5.8%
8 881
 
5.4%
7 772
 
4.7%
5 737
 
4.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.8 KiB
Minimum2023-08-03 00:00:00
Maximum2023-08-03 00:00:00
2024-01-28T14:22:17.231823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:22:17.326522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-28T14:22:14.653615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T14:22:17.401580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.910
업종명0.9101.000
2024-01-28T14:22:17.490010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.698
업종명0.6981.000

Missing values

2024-01-28T14:22:14.771266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T14:22:14.863805image/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.
2024-01-28T14:22:14.945483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번업종명업소명영업소주소(도로명)소재지전화데이터기준일자
01숙박업소주얼리모텔남동대로921번길21(간석동,(남동대로921번길21))032-428-77792023-08-03
12숙박업소화승여관경인로644번길12-1(간석동)032-434-53302023-08-03
23숙박업소산장여인숙남동대로916번길83(간석동)032-434-54372023-08-03
34숙박업소옥수장여관만수로71번길6(만수동,89,90번지)032-467-99622023-08-03
45숙박업소광명장여관호구포로889번길16,3층(간석동)032-435-01132023-08-03
56숙박업소명성여관하촌로70번길73(만수동)032-461-22372023-08-03
67숙박업소청운모텔구월말로118(만수동)032-462-02852023-08-03
78숙박업소렉스리빙텔남동대로916번길89(간석동)032-438-97002023-08-03
89숙박업소도원장남동대로921번길23(간석동)032-424-52972023-08-03
910숙박업소새여인숙백범로214번길6-6(만수동,(백범로214번길6-6))032-463-54412023-08-03
연번업종명업소명영업소주소(도로명)소재지전화데이터기준일자
17421743공동주택에코메트로10단지아암대로1503번길21032-438-83992023-08-03
17431744공동주택에코메트로9단지에코중앙로96032-433-67942023-08-03
17441745공동주택소래휴먼시아3단지앵고개로815번길22032-439-74842023-08-03
17451746공동주택소래휴먼시아1단지앵고개로815번길70032-429-88172023-08-03
17461747공동주택논현유호N-CITY1단지포구로35032-423-42292023-08-03
17471748공동주택에코메트로3차더타워소래역남로40032-423-56912023-08-03
17481749공동주택소래휴먼시아4단지논고개로68번길34032-429-68332023-08-03
17491750공동주택유승한내들와이드오션에코중앙로66번길6032-421-76412023-08-03
17501751공동주택논현푸르지오포구로40032-429-70662023-08-03
17511752공동주택논현LH15단지함박뫼로456032-429-73542023-08-03