Overview

Dataset statistics

Number of variables8
Number of observations167
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.7 KiB
Average record size in memory65.8 B

Variable types

Numeric1
Categorical4
Text3

Dataset

Description인천광역시 남동구 공중위생관리법위반업소 지도점검결과에 대한 데이터로 연번, 지도점검 일, 점검결과, 업종명, 업소명, 소재지(도로명), 소재지(지번), 데이터기준일 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15087669&srcSe=7661IVAWM27C61E190

Alerts

점검결과 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 지도점검일High correlation
지도점검일 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-18 05:57:11.911140
Analysis finished2024-03-18 05:57:14.489293
Duration2.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct167
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84
Minimum1
Maximum167
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-03-18T14:57:14.570302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.3
Q142.5
median84
Q3125.5
95-th percentile158.7
Maximum167
Range166
Interquartile range (IQR)83

Descriptive statistics

Standard deviation48.35287
Coefficient of variation (CV)0.5756294
Kurtosis-1.2
Mean84
Median Absolute Deviation (MAD)42
Skewness0
Sum14028
Variance2338
MonotonicityStrictly increasing
2024-03-18T14:57:14.709373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
116 1
 
0.6%
108 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
111 1
 
0.6%
112 1
 
0.6%
113 1
 
0.6%
114 1
 
0.6%
115 1
 
0.6%
Other values (157) 157
94.0%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
167 1
0.6%
166 1
0.6%
165 1
0.6%
164 1
0.6%
163 1
0.6%
162 1
0.6%
161 1
0.6%
160 1
0.6%
159 1
0.6%
158 1
0.6%

지도점검일
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-04-14
20 
2023-04-13
15 
2023-03-09
 
7
2023-03-24
 
6
2023-04-27
 
6
Other values (40)
113 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique12 ?
Unique (%)7.2%

Sample

1st row2023-01-05
2nd row2023-01-10
3rd row2023-01-10
4th row2023-01-10
5th row2023-01-10

Common Values

ValueCountFrequency (%)
2023-04-14 20
 
12.0%
2023-04-13 15
 
9.0%
2023-03-09 7
 
4.2%
2023-03-24 6
 
3.6%
2023-04-27 6
 
3.6%
2023-01-18 6
 
3.6%
2023-04-19 6
 
3.6%
2023-01-27 6
 
3.6%
2023-01-10 6
 
3.6%
2023-03-15 6
 
3.6%
Other values (35) 83
49.7%

Length

2024-03-18T14:57:14.861077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-04-14 20
 
12.0%
2023-04-13 15
 
9.0%
2023-03-09 7
 
4.2%
2023-03-24 6
 
3.6%
2023-04-27 6
 
3.6%
2023-01-18 6
 
3.6%
2023-04-19 6
 
3.6%
2023-01-27 6
 
3.6%
2023-01-10 6
 
3.6%
2023-03-15 6
 
3.6%
Other values (35) 83
49.7%

점검결과
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
미처분대상
167 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미처분대상 167
100.0%

Length

2024-03-18T14:57:14.987062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:57:15.116222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미처분대상 167
100.0%

업종명
Categorical

Distinct19
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
숙박업(일반)
46 
일반미용업
25 
목욕장업
17 
피부미용업
16 
네일미용업
13 
Other values (14)
50 

Length

Max length23
Median length16
Mean length6.5688623
Min length3

Unique

Unique6 ?
Unique (%)3.6%

Sample

1st row피부미용업, 네일미용업
2nd row피부미용업
3rd row건물위생관리업
4th row미용업
5th row네일미용업

Common Values

ValueCountFrequency (%)
숙박업(일반) 46
27.5%
일반미용업 25
15.0%
목욕장업 17
 
10.2%
피부미용업 16
 
9.6%
네일미용업 13
 
7.8%
건물위생관리업 12
 
7.2%
종합미용업 8
 
4.8%
화장,분장 미용업 6
 
3.6%
숙박업(생활) 5
 
3.0%
네일미용업, 화장,분장 미용업 4
 
2.4%
Other values (9) 15
 
9.0%

Length

2024-03-18T14:57:15.258156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
숙박업(일반 46
23.4%
일반미용업 28
14.2%
피부미용업 23
11.7%
네일미용업 22
11.2%
목욕장업 17
 
8.6%
미용업 16
 
8.1%
화장,분장 15
 
7.6%
건물위생관리업 12
 
6.1%
종합미용업 8
 
4.1%
숙박업(생활 5
 
2.5%
Other values (2) 5
 
2.5%

업소명
Text

Distinct148
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-18T14:57:15.548101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length13
Mean length5.8383234
Min length2

Characters and Unicode

Total characters975
Distinct characters275
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)80.8%

Sample

1st row탑뷰티클래스&레푸스
2nd row예서뷰티
3rd row주식회사 가주
4th row예뻐지는 날
5th row비손네일
ValueCountFrequency (%)
카카오모텔 5
 
2.7%
v3(브이쓰리)호텔 4
 
2.2%
아페리온24스파랜드 3
 
1.6%
주식회사 3
 
1.6%
로얄모텔 2
 
1.1%
코끼리 2
 
1.1%
백악관여관 2
 
1.1%
리치아노호텔 2
 
1.1%
패밀리타운 2
 
1.1%
인천 2
 
1.1%
Other values (152) 157
85.3%
2024-03-18T14:57:15.968364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 32
 
3.3%
리 26
 
2.7%
스 24
 
2.5%
일 19
 
1.9%
모 19
 
1.9%
네 18
 
1.8%
17
 
1.7%
( 16
 
1.6%
이 16
 
1.6%
어 16
 
1.6%
Other values (265) 772
79.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 861
88.3%
Decimal Number 27
 
2.8%
Space Separator 17
 
1.7%
Lowercase Letter 17
 
1.7%
Open Punctuation 16
 
1.6%
Close Punctuation 16
 
1.6%
Other Punctuation 11
 
1.1%
Uppercase Letter 10
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 32
 
3.7%
리 26
 
3.0%
스 24
 
2.8%
일 19
 
2.2%
모 19
 
2.2%
네 18
 
2.1%
이 16
 
1.9%
어 16
 
1.9%
헤 15
 
1.7%
아 14
 
1.6%
Other values (233) 662
76.9%
Lowercase Letter
ValueCountFrequency (%)
o 3
17.6%
a 2
11.8%
r 2
11.8%
n 2
11.8%
e 2
11.8%
l 2
11.8%
d 1
 
5.9%
s 1
 
5.9%
i 1
 
5.9%
u 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
4 8
29.6%
2 6
22.2%
3 5
18.5%
5 2
 
7.4%
8 2
 
7.4%
0 1
 
3.7%
6 1
 
3.7%
1 1
 
3.7%
7 1
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
V 4
40.0%
M 1
 
10.0%
F 1
 
10.0%
O 1
 
10.0%
S 1
 
10.0%
W 1
 
10.0%
B 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
& 4
36.4%
, 4
36.4%
. 3
27.3%
Space Separator
ValueCountFrequency (%)
17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 861
88.3%
Common 87
 
8.9%
Latin 27
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 32
 
3.7%
리 26
 
3.0%
스 24
 
2.8%
일 19
 
2.2%
모 19
 
2.2%
네 18
 
2.1%
이 16
 
1.9%
어 16
 
1.9%
헤 15
 
1.7%
아 14
 
1.6%
Other values (233) 662
76.9%
Latin
ValueCountFrequency (%)
V 4
14.8%
o 3
11.1%
a 2
 
7.4%
r 2
 
7.4%
n 2
 
7.4%
e 2
 
7.4%
l 2
 
7.4%
M 1
 
3.7%
F 1
 
3.7%
O 1
 
3.7%
Other values (7) 7
25.9%
Common
ValueCountFrequency (%)
17
19.5%
( 16
18.4%
) 16
18.4%
4 8
9.2%
2 6
 
6.9%
3 5
 
5.7%
& 4
 
4.6%
, 4
 
4.6%
. 3
 
3.4%
5 2
 
2.3%
Other values (5) 6
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 861
88.3%
ASCII 114
 
11.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 32
 
3.7%
리 26
 
3.0%
스 24
 
2.8%
일 19
 
2.2%
모 19
 
2.2%
네 18
 
2.1%
이 16
 
1.9%
어 16
 
1.9%
헤 15
 
1.7%
아 14
 
1.6%
Other values (233) 662
76.9%
ASCII
ValueCountFrequency (%)
17
14.9%
( 16
14.0%
) 16
14.0%
4 8
 
7.0%
2 6
 
5.3%
3 5
 
4.4%
& 4
 
3.5%
, 4
 
3.5%
V 4
 
3.5%
. 3
 
2.6%
Other values (22) 31
27.2%

소재지(도로명)
Text

Distinct148
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-18T14:57:16.307291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length48
Mean length37.383234
Min length22

Characters and Unicode

Total characters6243
Distinct characters213
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)80.8%

Sample

1st row인천광역시 남동구 인하로489번길 22, 동남빌딩 7층 701호 (구월동)
2nd row인천광역시 남동구 문화서로 44, 1층 일부호 (구월동)
3rd row인천광역시 남동구 남촌로93번길 39, 204호 (남촌동)
4th row인천광역시 남동구 당좌로5번길 46, 1층 104호 (구월동)
5th row인천광역시 남동구 장승로 5, 1층 103호 (만수동)
ValueCountFrequency (%)
인천광역시 167
 
14.4%
남동구 167
 
14.4%
구월동 50
 
4.3%
1층 46
 
4.0%
간석동 42
 
3.6%
논현동 34
 
2.9%
2층 22
 
1.9%
만수동 20
 
1.7%
일부호 19
 
1.6%
전부호 8
 
0.7%
Other values (370) 587
50.5%
2024-03-18T14:57:16.878592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
995
 
15.9%
동 386
 
6.2%
구 242
 
3.9%
1 236
 
3.8%
남 212
 
3.4%
) 190
 
3.0%
( 190
 
3.0%
인 183
 
2.9%
역 179
 
2.9%
시 177
 
2.8%
Other values (203) 3253
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3573
57.2%
Decimal Number 1062
 
17.0%
Space Separator 995
 
15.9%
Close Punctuation 190
 
3.0%
Open Punctuation 190
 
3.0%
Other Punctuation 166
 
2.7%
Dash Punctuation 26
 
0.4%
Uppercase Letter 18
 
0.3%
Math Symbol 16
 
0.3%
Lowercase Letter 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 386
 
10.8%
구 242
 
6.8%
남 212
 
5.9%
인 183
 
5.1%
역 179
 
5.0%
시 177
 
5.0%
천 172
 
4.8%
로 171
 
4.8%
광 168
 
4.7%
호 153
 
4.3%
Other values (173) 1530
42.8%
Decimal Number
ValueCountFrequency (%)
1 236
22.2%
2 175
16.5%
3 108
10.2%
0 102
9.6%
6 87
 
8.2%
5 82
 
7.7%
4 81
 
7.6%
9 66
 
6.2%
8 64
 
6.0%
7 61
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
n 1
14.3%
a 1
14.3%
i 1
14.3%
s 1
14.3%
e 1
14.3%
r 1
14.3%
o 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
B 7
38.9%
A 4
22.2%
V 2
 
11.1%
G 2
 
11.1%
C 2
 
11.1%
F 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 165
99.4%
/ 1
 
0.6%
Space Separator
ValueCountFrequency (%)
995
100.0%
Close Punctuation
ValueCountFrequency (%)
) 190
100.0%
Open Punctuation
ValueCountFrequency (%)
( 190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3573
57.2%
Common 2645
42.4%
Latin 25
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 386
 
10.8%
구 242
 
6.8%
남 212
 
5.9%
인 183
 
5.1%
역 179
 
5.0%
시 177
 
5.0%
천 172
 
4.8%
로 171
 
4.8%
광 168
 
4.7%
호 153
 
4.3%
Other values (173) 1530
42.8%
Common
ValueCountFrequency (%)
995
37.6%
1 236
 
8.9%
) 190
 
7.2%
( 190
 
7.2%
2 175
 
6.6%
, 165
 
6.2%
3 108
 
4.1%
0 102
 
3.9%
6 87
 
3.3%
5 82
 
3.1%
Other values (7) 315
 
11.9%
Latin
ValueCountFrequency (%)
B 7
28.0%
A 4
16.0%
V 2
 
8.0%
G 2
 
8.0%
C 2
 
8.0%
n 1
 
4.0%
a 1
 
4.0%
i 1
 
4.0%
s 1
 
4.0%
e 1
 
4.0%
Other values (3) 3
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3573
57.2%
ASCII 2670
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
995
37.3%
1 236
 
8.8%
) 190
 
7.1%
( 190
 
7.1%
2 175
 
6.6%
, 165
 
6.2%
3 108
 
4.0%
0 102
 
3.8%
6 87
 
3.3%
5 82
 
3.1%
Other values (20) 340
 
12.7%
Hangul
ValueCountFrequency (%)
동 386
 
10.8%
구 242
 
6.8%
남 212
 
5.9%
인 183
 
5.1%
역 179
 
5.0%
시 177
 
5.0%
천 172
 
4.8%
로 171
 
4.8%
광 168
 
4.7%
호 153
 
4.3%
Other values (173) 1530
42.8%

소재지(지번)
Text

Distinct140
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-18T14:57:17.216733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length25.706587
Min length19

Characters and Unicode

Total characters4293
Distinct characters174
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)71.9%

Sample

1st row인천광역시 남동구 구월동 1466 동남빌딩
2nd row인천광역시 남동구 구월동 1353-3
3rd row인천광역시 남동구 남촌동 563-1
4th row인천광역시 남동구 구월동 1242-11
5th row인천광역시 남동구 만수동 1076-5
ValueCountFrequency (%)
인천광역시 167
21.4%
남동구 167
21.4%
구월동 53
 
6.8%
간석동 44
 
5.6%
논현동 36
 
4.6%
만수동 22
 
2.8%
서창동 6
 
0.8%
678-3 5
 
0.6%
174-3 4
 
0.5%
687-3 4
 
0.5%
Other values (224) 272
34.9%
2024-03-18T14:57:17.712883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1000
23.3%
동 340
 
7.9%
구 225
 
5.2%
1 215
 
5.0%
시 175
 
4.1%
남 172
 
4.0%
인 169
 
3.9%
광 168
 
3.9%
천 167
 
3.9%
역 167
 
3.9%
Other values (164) 1495
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2330
54.3%
Space Separator 1000
23.3%
Decimal Number 782
 
18.2%
Dash Punctuation 136
 
3.2%
Other Punctuation 10
 
0.2%
Math Symbol 9
 
0.2%
Uppercase Letter 9
 
0.2%
Lowercase Letter 7
 
0.2%
Close Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 340
14.6%
구 225
 
9.7%
시 175
 
7.5%
남 172
 
7.4%
인 169
 
7.3%
광 168
 
7.2%
천 167
 
7.2%
역 167
 
7.2%
월 58
 
2.5%
석 45
 
1.9%
Other values (135) 644
27.6%
Decimal Number
ValueCountFrequency (%)
1 215
27.5%
6 92
11.8%
3 86
 
11.0%
7 78
 
10.0%
2 70
 
9.0%
4 70
 
9.0%
5 57
 
7.3%
0 41
 
5.2%
8 40
 
5.1%
9 33
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
e 1
14.3%
o 1
14.3%
n 1
14.3%
a 1
14.3%
i 1
14.3%
s 1
14.3%
r 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
B 2
22.2%
V 2
22.2%
C 2
22.2%
G 2
22.2%
F 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 9
90.0%
/ 1
 
10.0%
Space Separator
ValueCountFrequency (%)
1000
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 136
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2330
54.3%
Common 1947
45.4%
Latin 16
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 340
14.6%
구 225
 
9.7%
시 175
 
7.5%
남 172
 
7.4%
인 169
 
7.3%
광 168
 
7.2%
천 167
 
7.2%
역 167
 
7.2%
월 58
 
2.5%
석 45
 
1.9%
Other values (135) 644
27.6%
Common
ValueCountFrequency (%)
1000
51.4%
1 215
 
11.0%
- 136
 
7.0%
6 92
 
4.7%
3 86
 
4.4%
7 78
 
4.0%
2 70
 
3.6%
4 70
 
3.6%
5 57
 
2.9%
0 41
 
2.1%
Other values (7) 102
 
5.2%
Latin
ValueCountFrequency (%)
B 2
12.5%
V 2
12.5%
C 2
12.5%
G 2
12.5%
e 1
6.2%
F 1
6.2%
o 1
6.2%
n 1
6.2%
a 1
6.2%
i 1
6.2%
Other values (2) 2
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2330
54.3%
ASCII 1963
45.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1000
50.9%
1 215
 
11.0%
- 136
 
6.9%
6 92
 
4.7%
3 86
 
4.4%
7 78
 
4.0%
2 70
 
3.6%
4 70
 
3.6%
5 57
 
2.9%
0 41
 
2.1%
Other values (19) 118
 
6.0%
Hangul
ValueCountFrequency (%)
동 340
14.6%
구 225
 
9.7%
시 175
 
7.5%
남 172
 
7.4%
인 169
 
7.3%
광 168
 
7.2%
천 167
 
7.2%
역 167
 
7.2%
월 58
 
2.5%
석 45
 
1.9%
Other values (135) 644
27.6%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-05-12
167 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-12
2nd row2023-05-12
3rd row2023-05-12
4th row2023-05-12
5th row2023-05-12

Common Values

ValueCountFrequency (%)
2023-05-12 167
100.0%

Length

2024-03-18T14:57:17.880869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:57:18.002160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-12 167
100.0%

Interactions

2024-03-18T14:57:14.008988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:57:18.092423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지도점검일업종명
연번1.0000.9930.671
지도점검일0.9931.0000.810
업종명0.6710.8101.000
2024-03-18T14:57:18.212544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지도점검일업종명
지도점검일1.0000.306
업종명0.3061.000
2024-03-18T14:57:18.341234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지도점검일업종명
연번1.0000.8050.313
지도점검일0.8051.0000.306
업종명0.3130.3061.000

Missing values

2024-03-18T14:57:14.247155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:57:14.412217image/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

연번지도점검일점검결과업종명업소명소재지(도로명)소재지(지번)데이터기준일자
012023-01-05미처분대상피부미용업, 네일미용업탑뷰티클래스&레푸스인천광역시 남동구 인하로489번길 22, 동남빌딩 7층 701호 (구월동)인천광역시 남동구 구월동 1466 동남빌딩2023-05-12
122023-01-10미처분대상피부미용업예서뷰티인천광역시 남동구 문화서로 44, 1층 일부호 (구월동)인천광역시 남동구 구월동 1353-32023-05-12
232023-01-10미처분대상건물위생관리업주식회사 가주인천광역시 남동구 남촌로93번길 39, 204호 (남촌동)인천광역시 남동구 남촌동 563-12023-05-12
342023-01-10미처분대상미용업예뻐지는 날인천광역시 남동구 당좌로5번길 46, 1층 104호 (구월동)인천광역시 남동구 구월동 1242-112023-05-12
452023-01-10미처분대상네일미용업비손네일인천광역시 남동구 장승로 5, 1층 103호 (만수동)인천광역시 남동구 만수동 1076-52023-05-12
562023-01-10미처분대상종합미용업써니헤어인천광역시 남동구 용천로 144, 1층 제3호 (간석동)인천광역시 남동구 간석동 34-32023-05-12
672023-01-10미처분대상종합미용업최은혜뷰티인천광역시 남동구 남촌동로35번길 9-13, 삼성빌딩 3층 (남촌동)인천광역시 남동구 남촌동 356-7 삼성빌딩2023-05-12
782023-01-12미처분대상숙박업(일반)골드코스트호텔인천인천광역시 남동구 논현로26번길 46, 1층 일부,6~15층 일부호 (논현동)인천광역시 남동구 논현동 645-82023-05-12
892023-01-18미처분대상종합미용업바이엘헤어인천광역시 남동구 장아산로 159, 서창자이아파트상가 상가동 107호 (서창동)인천광역시 남동구 서창동 561-1 서창자이아파트상가2023-05-12
9102023-01-18미처분대상피부미용업애린에스테틱인천광역시 남동구 논고개로 61, 라피에스타 4층 409호일부호 (논현동)인천광역시 남동구 논현동 747-1 라피에스타2023-05-12
연번지도점검일점검결과업종명업소명소재지(도로명)소재지(지번)데이터기준일자
1571582023-05-10미처분대상목욕장업24시선수촌 숯가마사우나인천광역시 남동구 남동대로 684 (구월동, 지하1,2/2,3,4층)인천광역시 남동구 구월동 1178-2 지하1,2 / 2,3,4층2023-05-12
1581592023-05-10미처분대상목욕장업아페리온24스파랜드인천광역시 남동구 서창남순환로 223, 아페리온 A동 8층 801호 (서창동)인천광역시 남동구 서창동 687-3 아페리온2023-05-12
1591602023-05-11미처분대상목욕장업소래해수사우나인천광역시 남동구 장도로 64 (논현동,동아씨랜드 4~5층 전부)인천광역시 남동구 논현동 678-4 동아씨랜드 4~5층 전부2023-05-12
1601612023-05-11미처분대상목욕장업성강해수사우나인천광역시 남동구 논현고잔로109번길 106 (고잔동,1층 136호)인천광역시 남동구 고잔동 256-5 1층 136호2023-05-12
1611622023-05-11미처분대상네일미용업네일 채우다인천광역시 남동구 선수촌공원로 36, 더블루시티 1층 122호일부호 (구월동)인천광역시 남동구 구월동 1527 더블루시티2023-05-12
1621632023-05-12미처분대상일반미용업에이원헤어인천광역시 남동구 인주대로604번길 51, 1층 전부호 (구월동)인천광역시 남동구 구월동 11622023-05-12
1631642023-05-12미처분대상일반미용업유나헤어인천광역시 남동구 용천로17번길 34, 금호타운 1층 전부호 (구월동)인천광역시 남동구 구월동 1211-22 금호타운2023-05-12
1641652023-05-12미처분대상네일미용업, 화장,분장 미용업오늘도 네일해인천광역시 남동구 구월남로85번길 12-13, 1층 일부(101호)호 (구월동)인천광역시 남동구 구월동 1090-92023-05-12
1651662023-05-12미처분대상네일미용업, 화장,분장 미용업네일,그리밍인천광역시 남동구 인주대로604번길 51, 2층 전부호 (구월동)인천광역시 남동구 구월동 11622023-05-12
1661672023-05-12미처분대상일반미용업엘리헤어샾인천광역시 남동구 복개동로66번길 5, 1층 일부호 (만수동)인천광역시 남동구 만수동 920-52023-05-12