Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells4585
Missing cells (%)6.6%
Duplicate rows18
Duplicate rows (%)0.2%
Total size in memory625.0 KiB
Average record size in memory64.0 B

Variable types

Categorical2
Text3
DateTime2

Dataset

Description인천광역시 서구관내에 위치한 식품접객업소 폐업현황(업종명, 업소명, 소재지, 인허가일자, 폐업일자)입니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15047499&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 18 (0.2%) duplicate rowsDuplicates
업종명 is highly imbalanced (58.0%)Imbalance
소재지(도로명) has 4539 (45.4%) missing valuesMissing

Reproduction

Analysis started2024-01-28 15:24:34.254759
Analysis finished2024-01-28 15:24:35.922685
Duration1.67 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반음식점
7772 
휴게음식점
1460 
위탁급식영업
 
426
제과점영업
 
250
유흥주점영업
 
51

Length

Max length6
Median length5
Mean length5.0436
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row휴게음식점
2nd row일반음식점
3rd row위탁급식영업
4th row일반음식점
5th row일반음식점

Common Values

ValueCountFrequency (%)
일반음식점 7772
77.7%
휴게음식점 1460
 
14.6%
위탁급식영업 426
 
4.3%
제과점영업 250
 
2.5%
유흥주점영업 51
 
0.5%
단란주점 41
 
0.4%

Length

2024-01-29T00:24:35.981784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:24:36.064440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 7772
77.7%
휴게음식점 1460
 
14.6%
위탁급식영업 426
 
4.3%
제과점영업 250
 
2.5%
유흥주점영업 51
 
0.5%
단란주점 41
 
0.4%

업소명
Text

Distinct8755
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-29T00:24:36.287854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length6.0483
Min length1

Characters and Unicode

Total characters60483
Distinct characters1085
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7979 ?
Unique (%)79.8%

Sample

1st row에멘탈커피
2nd row투다리
3rd row조은식당
4th row소주방
5th row장터빈대떡
ValueCountFrequency (%)
청라점 70
 
0.6%
김밥천국 29
 
0.3%
카페 29
 
0.3%
인천청라점 25
 
0.2%
검단점 24
 
0.2%
cafe 20
 
0.2%
세븐일레븐 18
 
0.2%
gs25 17
 
0.1%
떡볶이 15
 
0.1%
주)아워홈 15
 
0.1%
Other values (9312) 11241
97.7%
2024-01-29T00:24:36.655636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1503
 
2.5%
이 1306
 
2.2%
점 1248
 
2.1%
식 1125
 
1.9%
스 1077
 
1.8%
리 908
 
1.5%
당 862
 
1.4%
라 813
 
1.3%
가 688
 
1.1%
) 681
 
1.1%
Other values (1075) 50272
83.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54657
90.4%
Space Separator 1503
 
2.5%
Uppercase Letter 1104
 
1.8%
Lowercase Letter 945
 
1.6%
Close Punctuation 681
 
1.1%
Open Punctuation 680
 
1.1%
Decimal Number 676
 
1.1%
Other Punctuation 215
 
0.4%
Dash Punctuation 13
 
< 0.1%
Other Symbol 5
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1306
 
2.4%
점 1248
 
2.3%
식 1125
 
2.1%
스 1077
 
2.0%
리 908
 
1.7%
당 862
 
1.6%
라 813
 
1.5%
가 688
 
1.3%
마 673
 
1.2%
치 627
 
1.1%
Other values (993) 45330
82.9%
Uppercase Letter
ValueCountFrequency (%)
C 140
 
12.7%
S 103
 
9.3%
B 85
 
7.7%
G 77
 
7.0%
O 70
 
6.3%
A 68
 
6.2%
E 62
 
5.6%
P 54
 
4.9%
F 48
 
4.3%
N 46
 
4.2%
Other values (16) 351
31.8%
Lowercase Letter
ValueCountFrequency (%)
e 152
16.1%
a 118
12.5%
o 78
 
8.3%
r 61
 
6.5%
c 60
 
6.3%
f 57
 
6.0%
s 52
 
5.5%
n 50
 
5.3%
i 45
 
4.8%
t 45
 
4.8%
Other values (15) 227
24.0%
Other Punctuation
ValueCountFrequency (%)
& 85
39.5%
. 54
25.1%
, 29
 
13.5%
' 17
 
7.9%
! 9
 
4.2%
/ 6
 
2.8%
· 6
 
2.8%
? 4
 
1.9%
# 2
 
0.9%
% 1
 
0.5%
Other values (2) 2
 
0.9%
Decimal Number
ValueCountFrequency (%)
2 170
25.1%
5 104
15.4%
0 86
12.7%
1 79
11.7%
3 55
 
8.1%
9 47
 
7.0%
4 41
 
6.1%
8 34
 
5.0%
6 31
 
4.6%
7 29
 
4.3%
Other Symbol
ValueCountFrequency (%)
℃ 3
60.0%
㈜ 2
40.0%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
~ 1
33.3%
Space Separator
ValueCountFrequency (%)
1503
100.0%
Close Punctuation
ValueCountFrequency (%)
) 681
100.0%
Open Punctuation
ValueCountFrequency (%)
( 680
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54646
90.3%
Common 3775
 
6.2%
Latin 2049
 
3.4%
Han 13
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1306
 
2.4%
점 1248
 
2.3%
식 1125
 
2.1%
스 1077
 
2.0%
리 908
 
1.7%
당 862
 
1.6%
라 813
 
1.5%
가 688
 
1.3%
마 673
 
1.2%
치 627
 
1.1%
Other values (985) 45319
82.9%
Latin
ValueCountFrequency (%)
e 152
 
7.4%
C 140
 
6.8%
a 118
 
5.8%
S 103
 
5.0%
B 85
 
4.1%
o 78
 
3.8%
G 77
 
3.8%
O 70
 
3.4%
A 68
 
3.3%
E 62
 
3.0%
Other values (41) 1096
53.5%
Common
ValueCountFrequency (%)
1503
39.8%
) 681
18.0%
( 680
18.0%
2 170
 
4.5%
5 104
 
2.8%
0 86
 
2.3%
& 85
 
2.3%
1 79
 
2.1%
3 55
 
1.5%
. 54
 
1.4%
Other values (20) 278
 
7.4%
Han
ValueCountFrequency (%)
家 3
23.1%
辛 3
23.1%
張 1
 
7.7%
人 1
 
7.7%
高 1
 
7.7%
元 1
 
7.7%
福 1
 
7.7%
大 1
 
7.7%
堂 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54641
90.3%
ASCII 5814
 
9.6%
CJK 13
 
< 0.1%
None 9
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Letterlike Symbols 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1503
25.9%
) 681
 
11.7%
( 680
 
11.7%
2 170
 
2.9%
e 152
 
2.6%
C 140
 
2.4%
a 118
 
2.0%
5 104
 
1.8%
S 103
 
1.8%
0 86
 
1.5%
Other values (68) 2077
35.7%
Hangul
ValueCountFrequency (%)
이 1306
 
2.4%
점 1248
 
2.3%
식 1125
 
2.1%
스 1077
 
2.0%
리 908
 
1.7%
당 862
 
1.6%
라 813
 
1.5%
가 688
 
1.3%
마 673
 
1.2%
치 627
 
1.1%
Other values (983) 45314
82.9%
None
ValueCountFrequency (%)
· 6
66.7%
㈜ 2
 
22.2%
＆ 1
 
11.1%
CJK
ValueCountFrequency (%)
家 3
23.1%
辛 3
23.1%
張 1
 
7.7%
人 1
 
7.7%
高 1
 
7.7%
元 1
 
7.7%
福 1
 
7.7%
大 1
 
7.7%
堂 1
 
7.7%
Compat Jamo
ValueCountFrequency (%)
ㅊ 3
100.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 3
100.0%

소재지(도로명)
Text

MISSING 

Distinct5124
Distinct (%)93.8%
Missing4539
Missing (%)45.4%
Memory size156.2 KiB
2024-01-29T00:24:36.898603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length102
Median length74
Mean length35.202527
Min length20

Characters and Unicode

Total characters192241
Distinct characters473
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4848 ?
Unique (%)88.8%

Sample

1st row인천광역시 서구 푸른로16번길 9, 1층 (청라동)
2nd row인천광역시 서구 중봉대로198번길 2 (가좌동, 아주산업구내식당 지하1층)
3rd row인천광역시 서구 대평로8번길 14 (연희동)
4th row인천광역시 서구 신석로77번길 34-1, 1층 (석남동)
5th row인천광역시 서구 청라루비로144번길 6-8, 102호 (경서동)
ValueCountFrequency (%)
인천광역시 5462
 
14.8%
서구 5461
 
14.8%
1층 1244
 
3.4%
가좌동 634
 
1.7%
연희동 577
 
1.6%
석남동 560
 
1.5%
청라동 535
 
1.5%
마전동 432
 
1.2%
경서동 425
 
1.2%
심곡동 356
 
1.0%
Other values (4000) 21142
57.4%
2024-01-29T00:24:37.257100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31390
 
16.3%
1 10306
 
5.4%
, 6436
 
3.3%
동 6287
 
3.3%
서 6213
 
3.2%
( 5832
 
3.0%
) 5830
 
3.0%
로 5616
 
2.9%
시 5608
 
2.9%
인 5577
 
2.9%
Other values (463) 103146
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104893
54.6%
Decimal Number 35459
 
18.4%
Space Separator 31390
 
16.3%
Other Punctuation 6453
 
3.4%
Open Punctuation 5833
 
3.0%
Close Punctuation 5831
 
3.0%
Dash Punctuation 1578
 
0.8%
Uppercase Letter 722
 
0.4%
Lowercase Letter 44
 
< 0.1%
Math Symbol 33
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6287
 
6.0%
서 6213
 
5.9%
로 5616
 
5.4%
시 5608
 
5.3%
인 5577
 
5.3%
천 5552
 
5.3%
구 5493
 
5.2%
광 5493
 
5.2%
역 5477
 
5.2%
호 3115
 
3.0%
Other values (401) 50462
48.1%
Uppercase Letter
ValueCountFrequency (%)
B 261
36.1%
A 158
21.9%
C 45
 
6.2%
K 33
 
4.6%
S 27
 
3.7%
D 22
 
3.0%
E 22
 
3.0%
F 18
 
2.5%
G 17
 
2.4%
I 17
 
2.4%
Other values (14) 102
 
14.1%
Lowercase Letter
ValueCountFrequency (%)
e 12
27.3%
s 8
18.2%
a 5
11.4%
d 4
 
9.1%
c 3
 
6.8%
y 2
 
4.5%
i 2
 
4.5%
b 2
 
4.5%
k 2
 
4.5%
r 2
 
4.5%
Other values (2) 2
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 10306
29.1%
2 4814
13.6%
0 4335
12.2%
3 2976
 
8.4%
4 2621
 
7.4%
5 2378
 
6.7%
6 2165
 
6.1%
8 2085
 
5.9%
7 1987
 
5.6%
9 1792
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 6436
99.7%
& 6
 
0.1%
. 4
 
0.1%
@ 2
 
< 0.1%
' 2
 
< 0.1%
" 2
 
< 0.1%
* 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5832
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 5830
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
31390
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1578
100.0%
Math Symbol
ValueCountFrequency (%)
~ 33
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 104893
54.6%
Common 86579
45.0%
Latin 769
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6287
 
6.0%
서 6213
 
5.9%
로 5616
 
5.4%
시 5608
 
5.3%
인 5577
 
5.3%
천 5552
 
5.3%
구 5493
 
5.2%
광 5493
 
5.2%
역 5477
 
5.2%
호 3115
 
3.0%
Other values (401) 50462
48.1%
Latin
ValueCountFrequency (%)
B 261
33.9%
A 158
20.5%
C 45
 
5.9%
K 33
 
4.3%
S 27
 
3.5%
D 22
 
2.9%
E 22
 
2.9%
F 18
 
2.3%
G 17
 
2.2%
I 17
 
2.2%
Other values (27) 149
19.4%
Common
ValueCountFrequency (%)
31390
36.3%
1 10306
 
11.9%
, 6436
 
7.4%
( 5832
 
6.7%
) 5830
 
6.7%
2 4814
 
5.6%
0 4335
 
5.0%
3 2976
 
3.4%
4 2621
 
3.0%
5 2378
 
2.7%
Other values (15) 9661
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 104863
54.5%
ASCII 87343
45.4%
Compat Jamo 30
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK Compat 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31390
35.9%
1 10306
 
11.8%
, 6436
 
7.4%
( 5832
 
6.7%
) 5830
 
6.7%
2 4814
 
5.5%
0 4335
 
5.0%
3 2976
 
3.4%
4 2621
 
3.0%
5 2378
 
2.7%
Other values (50) 10425
 
11.9%
Hangul
ValueCountFrequency (%)
동 6287
 
6.0%
서 6213
 
5.9%
로 5616
 
5.4%
시 5608
 
5.3%
인 5577
 
5.3%
천 5552
 
5.3%
구 5493
 
5.2%
광 5493
 
5.2%
역 5477
 
5.2%
호 3115
 
3.0%
Other values (400) 50432
48.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 30
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%

소재지(지번)
Text

Distinct7678
Distinct (%)77.1%
Missing37
Missing (%)0.4%
Memory size156.2 KiB
2024-01-29T00:24:37.489035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length57
Mean length24.688447
Min length15

Characters and Unicode

Total characters245971
Distinct characters458
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6357 ?
Unique (%)63.8%

Sample

1st row인천광역시 서구 청라동 105-112
2nd row인천광역시 서구 가정동 515-26
3rd row인천광역시 서구 가좌동 602-6 아주산업구내식당 지하1층
4th row인천광역시 서구 가좌동 45-2
5th row인천광역시 서구 연희동 687-17
ValueCountFrequency (%)
인천광역시 9964
20.1%
서구 9963
20.1%
석남동 1481
 
3.0%
가좌동 1403
 
2.8%
청라동 1203
 
2.4%
1층 1083
 
2.2%
가정동 1028
 
2.1%
심곡동 856
 
1.7%
마전동 814
 
1.6%
신현동 461
 
0.9%
Other values (6456) 21358
43.0%
2024-01-29T00:24:37.849678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48480
19.7%
1 13982
 
5.7%
동 10752
 
4.4%
구 10444
 
4.2%
서 10264
 
4.2%
시 10116
 
4.1%
인 10104
 
4.1%
천 10064
 
4.1%
광 10004
 
4.1%
역 9980
 
4.1%
Other values (448) 101781
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 129982
52.8%
Decimal Number 55907
22.7%
Space Separator 48480
 
19.7%
Dash Punctuation 8609
 
3.5%
Uppercase Letter 782
 
0.3%
Other Punctuation 741
 
0.3%
Open Punctuation 680
 
0.3%
Close Punctuation 680
 
0.3%
Lowercase Letter 53
 
< 0.1%
Math Symbol 52
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10752
 
8.3%
구 10444
 
8.0%
서 10264
 
7.9%
시 10116
 
7.8%
인 10104
 
7.8%
천 10064
 
7.7%
광 10004
 
7.7%
역 9980
 
7.7%
호 3226
 
2.5%
가 3138
 
2.4%
Other values (390) 41890
32.2%
Uppercase Letter
ValueCountFrequency (%)
B 270
34.5%
A 200
25.6%
C 42
 
5.4%
S 31
 
4.0%
K 30
 
3.8%
L 28
 
3.6%
M 28
 
3.6%
E 23
 
2.9%
D 22
 
2.8%
T 15
 
1.9%
Other values (14) 93
 
11.9%
Lowercase Letter
ValueCountFrequency (%)
e 22
41.5%
s 9
17.0%
a 5
 
9.4%
d 4
 
7.5%
c 3
 
5.7%
k 2
 
3.8%
y 2
 
3.8%
r 2
 
3.8%
i 2
 
3.8%
v 1
 
1.9%
Decimal Number
ValueCountFrequency (%)
1 13982
25.0%
2 7078
12.7%
0 6310
11.3%
5 5173
 
9.3%
3 4908
 
8.8%
4 4867
 
8.7%
6 3944
 
7.1%
7 3418
 
6.1%
8 3178
 
5.7%
9 3049
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 702
94.7%
. 19
 
2.6%
* 7
 
0.9%
& 6
 
0.8%
@ 5
 
0.7%
' 2
 
0.3%
Space Separator
ValueCountFrequency (%)
48480
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8609
100.0%
Open Punctuation
ValueCountFrequency (%)
( 680
100.0%
Close Punctuation
ValueCountFrequency (%)
) 680
100.0%
Math Symbol
ValueCountFrequency (%)
~ 52
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 129982
52.8%
Common 115151
46.8%
Latin 838
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10752
 
8.3%
구 10444
 
8.0%
서 10264
 
7.9%
시 10116
 
7.8%
인 10104
 
7.8%
천 10064
 
7.7%
광 10004
 
7.7%
역 9980
 
7.7%
호 3226
 
2.5%
가 3138
 
2.4%
Other values (390) 41890
32.2%
Latin
ValueCountFrequency (%)
B 270
32.2%
A 200
23.9%
C 42
 
5.0%
S 31
 
3.7%
K 30
 
3.6%
L 28
 
3.3%
M 28
 
3.3%
E 23
 
2.7%
D 22
 
2.6%
e 22
 
2.6%
Other values (26) 142
16.9%
Common
ValueCountFrequency (%)
48480
42.1%
1 13982
 
12.1%
- 8609
 
7.5%
2 7078
 
6.1%
0 6310
 
5.5%
5 5173
 
4.5%
3 4908
 
4.3%
4 4867
 
4.2%
6 3944
 
3.4%
7 3418
 
3.0%
Other values (12) 8382
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 129953
52.8%
ASCII 115984
47.2%
Compat Jamo 29
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK Compat 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48480
41.8%
1 13982
 
12.1%
- 8609
 
7.4%
2 7078
 
6.1%
0 6310
 
5.4%
5 5173
 
4.5%
3 4908
 
4.2%
4 4867
 
4.2%
6 3944
 
3.4%
7 3418
 
2.9%
Other values (46) 9215
 
7.9%
Hangul
ValueCountFrequency (%)
동 10752
 
8.3%
구 10444
 
8.0%
서 10264
 
7.9%
시 10116
 
7.8%
인 10104
 
7.8%
천 10064
 
7.7%
광 10004
 
7.7%
역 9980
 
7.7%
호 3226
 
2.5%
가 3138
 
2.4%
Other values (389) 41861
32.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 29
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%

인허가일자
Date

Distinct5245
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1902-01-30 00:00:00
Maximum2023-06-07 00:00:00
2024-01-29T00:24:37.959581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:24:38.077987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

폐업일자
Date

Distinct4159
Distinct (%)41.6%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
Minimum2001-02-01 00:00:00
Maximum2023-07-31 00:00:00
2024-01-29T00:24:38.189580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:24:38.293055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-08-01
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-01
2nd row2023-08-01
3rd row2023-08-01
4th row2023-08-01
5th row2023-08-01

Common Values

ValueCountFrequency (%)
2023-08-01 10000
100.0%

Length

2024-01-29T00:24:38.400033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:24:38.470252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-01 10000
100.0%

Missing values

2024-01-29T00:24:35.672693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:24:35.774610image/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.
2024-01-29T00:24:35.864584image/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

업종명업소명소재지(도로명)소재지(지번)인허가일자폐업일자데이터기준일자
9328휴게음식점에멘탈커피인천광역시 서구 푸른로16번길 9, 1층 (청라동)인천광역시 서구 청라동 105-1122021-01-202022-09-022023-08-01
2335일반음식점투다리<NA>인천광역시 서구 가정동 515-261990-06-232008-07-222023-08-01
10196위탁급식영업조은식당인천광역시 서구 중봉대로198번길 2 (가좌동, 아주산업구내식당 지하1층)인천광역시 서구 가좌동 602-6 아주산업구내식당 지하1층2017-06-212021-07-192023-08-01
1552일반음식점소주방<NA>인천광역시 서구 가좌동 45-21996-09-062006-12-142023-08-01
4989일반음식점장터빈대떡인천광역시 서구 대평로8번길 14 (연희동)인천광역시 서구 연희동 687-172002-12-232016-07-122023-08-01
85일반음식점알엠2<NA>인천광역시 서구 가정동 540-131999-04-282003-02-142023-08-01
6108일반음식점신명태조림인천광역시 서구 신석로77번길 34-1, 1층 (석남동)인천광역시 서구 석남동 450-302016-01-182019-05-242023-08-01
9826위탁급식영업디씨에프푸드서비스(주)<NA>인천광역시 서구 당하동 0 당하지구 30블럭 1~5롯트 현대건설현장2010-05-072011-09-092023-08-01
8724휴게음식점피크닉바스켓 인천서구점인천광역시 서구 청라루비로144번길 6-8, 102호 (경서동)인천광역시 서구 청라동 142-5 102호2018-02-092018-05-172023-08-01
4934일반음식점계동치킨청라점인천광역시 서구 청라에메랄드로149번길 4-13, 1층 (연희동)인천광역시 서구 청라동 124-1 1층2013-11-112016-05-252023-08-01
업종명업소명소재지(도로명)소재지(지번)인허가일자폐업일자데이터기준일자
9557휴게음식점토즈멤버십라운지 원당당하센터인천광역시 서구 고산후로95번길 38, 웰빙메디칼프라자 301호 (당하동)인천광역시 서구 당하동 1028-1 웰빙메디칼프라자2022-01-142023-01-202023-08-01
7512일반음식점장모족발인천광역시 서구 청라라임로 85, 판매시설B동 125호 (청라동, 청라린스트라우스)인천광역시 서구 청라동 160-1 청라린스트라우스2021-03-292022-09-272023-08-01
3769일반음식점뜨더뜨더 검단점인천광역시 서구 봉수대로1440번안길 28-11 (왕길동)인천광역시 서구 왕길동 643-62009-06-252012-12-212023-08-01
4352일반음식점보리수닭갈비인천광역시 서구 승학로 446 (검암동,삼보프라자 111호)인천광역시 서구 검암동 630-1 삼보프라자 111호2005-01-272014-12-292023-08-01
4865일반음식점박가네빈대떡인천광역시 서구 신석로 79, 1층 (석남동)인천광역시 서구 석남동 4772015-01-142016-02-112023-08-01
842일반음식점누렁이네보신탕<NA>인천광역시 서구 왕길동 648-12002-10-092004-11-162023-08-01
6219일반음식점야미야미 김밥인천광역시 서구 원당대로117번길 10, 110호 (오류동, 더경프라자)인천광역시 서구 오류동 1663-1 110호2015-05-072019-11-062023-08-01
10313단란주점한우리노래하는단란주점<NA>인천광역시 서구 석남동 577-831995-12-012007-04-102023-08-01
5431일반음식점강촌인천광역시 서구 서곶로314번길 9 (심곡동)인천광역시 서구 심곡동 279-122015-05-042017-09-152023-08-01
369일반음식점인삼식당<NA>인천광역시 서구 가정동 512-71994-10-062003-12-112023-08-01

Duplicate rows

Most frequently occurring

업종명업소명소재지(도로명)소재지(지번)인허가일자폐업일자데이터기준일자# duplicates
0단란주점아리랑단란주점<NA>인천광역시 서구 가정동 485-151994-03-292008-10-202023-08-012
1위탁급식영업만미식품<NA>인천광역시 서구 신현동 2782009-08-132009-09-092023-08-012
2일반음식점BBQ<NA>인천광역시 서구 심곡동 298-21997-11-182012-08-202023-08-012
3일반음식점고향영양탕<NA>인천광역시 서구 가정동 279-42003-07-232008-09-302023-08-012
4일반음식점구들짱삽겹살<NA>인천광역시 서구 가정동 510-92003-10-232010-01-082023-08-012
5일반음식점돈푸대 신현점<NA>인천광역시 서구 신현동 287-232004-08-202012-10-182023-08-012
6일반음식점떡볶이대통령인천광역시 서구 완정로202번안길 34 (마전동)인천광역시 서구 마전동 911-72014-02-102019-09-262023-08-012
7일반음식점명동분식<NA>인천광역시 서구 가좌동 278-51998-09-012007-09-072023-08-012
8일반음식점밥퍼주는 남자인천광역시 서구 심곡로 130 (심곡동, 영우빌딩,102호)인천광역시 서구 심곡동 2902010-04-012022-10-042023-08-012
9일반음식점비어라인천광역시 서구 승학로 515, 대림프라자1동 1층 101호 (검암동, 596-3외1필지 대림프라자1 101호)인천광역시 서구 검암동 596-3 외1필지 대림프라자1 101호2012-12-042014-10-222023-08-012