Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells4613
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

Categorical1
Text3
DateTime3

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 (57.7%)Imbalance
소재지(도로명) has 4566 (45.7%) missing valuesMissing

Reproduction

Analysis started2024-01-28 15:24:47.805414
Analysis finished2024-01-28 15:24:49.369151
Duration1.56 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
7754 
휴게음식점
1472 
위탁급식영업
 
429
제과점영업
 
250
유흥주점영업
 
52

Length

Max length6
Median length5
Mean length5.0438
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 7754
77.5%
휴게음식점 1472
 
14.7%
위탁급식영업 429
 
4.3%
제과점영업 250
 
2.5%
유흥주점영업 52
 
0.5%
단란주점 43
 
0.4%

Length

2024-01-29T00:24:49.427533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:24:49.517619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 7754
77.5%
휴게음식점 1472
 
14.7%
위탁급식영업 429
 
4.3%
제과점영업 250
 
2.5%
유흥주점영업 52
 
0.5%
단란주점 43
 
0.4%

업소명
Text

Distinct8737
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-29T00:24:49.763669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length6.0535
Min length1

Characters and Unicode

Total characters60535
Distinct characters1086
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

Unique7957 ?
Unique (%)79.6%

Sample

1st row협회식당
2nd row영일만친구
3rd row디델리루원씨티점
4th row원조추어탕
5th row족꾼청라점
ValueCountFrequency (%)
청라점 70
 
0.6%
김밥천국 32
 
0.3%
카페 29
 
0.3%
검단점 26
 
0.2%
인천청라점 24
 
0.2%
cafe 20
 
0.2%
세븐일레븐 19
 
0.2%
gs25 16
 
0.1%
주)아워홈 15
 
0.1%
구내식당 14
 
0.1%
Other values (9295) 11234
97.7%
2024-01-29T00:24:50.157836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1499
 
2.5%
이 1300
 
2.1%
점 1250
 
2.1%
식 1128
 
1.9%
스 1075
 
1.8%
리 906
 
1.5%
당 866
 
1.4%
라 812
 
1.3%
가 682
 
1.1%
마 681
 
1.1%
Other values (1076) 50336
83.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54682
90.3%
Space Separator 1499
 
2.5%
Uppercase Letter 1148
 
1.9%
Lowercase Letter 933
 
1.5%
Decimal Number 684
 
1.1%
Close Punctuation 676
 
1.1%
Open Punctuation 675
 
1.1%
Other Punctuation 217
 
0.4%
Dash Punctuation 13
 
< 0.1%
Other Symbol 5
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1300
 
2.4%
점 1250
 
2.3%
식 1128
 
2.1%
스 1075
 
2.0%
리 906
 
1.7%
당 866
 
1.6%
라 812
 
1.5%
가 682
 
1.2%
마 681
 
1.2%
치 624
 
1.1%
Other values (994) 45358
82.9%
Uppercase Letter
ValueCountFrequency (%)
C 141
 
12.3%
S 107
 
9.3%
B 87
 
7.6%
G 79
 
6.9%
O 75
 
6.5%
E 70
 
6.1%
A 70
 
6.1%
P 53
 
4.6%
N 51
 
4.4%
F 48
 
4.2%
Other values (16) 367
32.0%
Lowercase Letter
ValueCountFrequency (%)
e 152
16.3%
a 116
12.4%
o 78
 
8.4%
r 61
 
6.5%
c 57
 
6.1%
f 56
 
6.0%
n 53
 
5.7%
s 49
 
5.3%
t 45
 
4.8%
i 43
 
4.6%
Other values (15) 223
23.9%
Other Punctuation
ValueCountFrequency (%)
& 86
39.6%
. 58
26.7%
, 29
 
13.4%
' 16
 
7.4%
! 8
 
3.7%
/ 6
 
2.8%
· 5
 
2.3%
? 4
 
1.8%
# 2
 
0.9%
% 1
 
0.5%
Other values (2) 2
 
0.9%
Decimal Number
ValueCountFrequency (%)
2 173
25.3%
5 101
14.8%
0 90
13.2%
1 78
11.4%
3 52
 
7.6%
9 47
 
6.9%
4 44
 
6.4%
8 35
 
5.1%
6 34
 
5.0%
7 30
 
4.4%
Other Symbol
ValueCountFrequency (%)
℃ 3
60.0%
㈜ 2
40.0%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
~ 1
50.0%
Space Separator
ValueCountFrequency (%)
1499
100.0%
Close Punctuation
ValueCountFrequency (%)
) 676
100.0%
Open Punctuation
ValueCountFrequency (%)
( 675
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54668
90.3%
Common 3770
 
6.2%
Latin 2081
 
3.4%
Han 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1300
 
2.4%
점 1250
 
2.3%
식 1128
 
2.1%
스 1075
 
2.0%
리 906
 
1.7%
당 866
 
1.6%
라 812
 
1.5%
가 682
 
1.2%
마 681
 
1.2%
치 624
 
1.1%
Other values (984) 45344
82.9%
Latin
ValueCountFrequency (%)
e 152
 
7.3%
C 141
 
6.8%
a 116
 
5.6%
S 107
 
5.1%
B 87
 
4.2%
G 79
 
3.8%
o 78
 
3.7%
O 75
 
3.6%
E 70
 
3.4%
A 70
 
3.4%
Other values (41) 1106
53.1%
Common
ValueCountFrequency (%)
1499
39.8%
) 676
17.9%
( 675
17.9%
2 173
 
4.6%
5 101
 
2.7%
0 90
 
2.4%
& 86
 
2.3%
1 78
 
2.1%
. 58
 
1.5%
3 52
 
1.4%
Other values (20) 282
 
7.5%
Han
ValueCountFrequency (%)
家 3
18.8%
辛 3
18.8%
大 2
12.5%
高 1
 
6.2%
張 1
 
6.2%
堂 1
 
6.2%
人 1
 
6.2%
情 1
 
6.2%
孝 1
 
6.2%
福 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54663
90.3%
ASCII 5842
 
9.7%
CJK 16
 
< 0.1%
None 8
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Letterlike Symbols 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1499
25.7%
) 676
 
11.6%
( 675
 
11.6%
2 173
 
3.0%
e 152
 
2.6%
C 141
 
2.4%
a 116
 
2.0%
S 107
 
1.8%
5 101
 
1.7%
0 90
 
1.5%
Other values (68) 2112
36.2%
Hangul
ValueCountFrequency (%)
이 1300
 
2.4%
점 1250
 
2.3%
식 1128
 
2.1%
스 1075
 
2.0%
리 906
 
1.7%
당 866
 
1.6%
라 812
 
1.5%
가 682
 
1.2%
마 681
 
1.2%
치 624
 
1.1%
Other values (982) 45339
82.9%
None
ValueCountFrequency (%)
· 5
62.5%
㈜ 2
 
25.0%
＆ 1
 
12.5%
CJK
ValueCountFrequency (%)
家 3
18.8%
辛 3
18.8%
大 2
12.5%
高 1
 
6.2%
張 1
 
6.2%
堂 1
 
6.2%
人 1
 
6.2%
情 1
 
6.2%
孝 1
 
6.2%
福 1
 
6.2%
Compat Jamo
ValueCountFrequency (%)
ㅊ 3
100.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 3
100.0%

소재지(도로명)
Text

MISSING 

Distinct5093
Distinct (%)93.7%
Missing4566
Missing (%)45.7%
Memory size156.2 KiB
2024-01-29T00:24:50.402398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length102
Median length74
Mean length35.182554
Min length20

Characters and Unicode

Total characters191182
Distinct characters470
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

Unique4816 ?
Unique (%)88.6%

Sample

1st row인천광역시 서구 봉오재1로 49, 상가동 101호 (신현동, 루원시티루에블리)
2nd row인천광역시 서구 청라에메랄드로149번길 4-11 (연희동, 1층전부)
3rd row인천광역시 서구 청라커낼로 280, 청라골든프라자 705호 (청라동)
4th row인천광역시 서구 승학로 321, 106호 (연희동)
5th row인천광역시 서구 서달로163번길 7 (석남동)
ValueCountFrequency (%)
인천광역시 5435
 
14.8%
서구 5434
 
14.8%
1층 1238
 
3.4%
가좌동 630
 
1.7%
연희동 564
 
1.5%
석남동 553
 
1.5%
청라동 536
 
1.5%
마전동 431
 
1.2%
경서동 419
 
1.1%
심곡동 353
 
1.0%
Other values (3984) 21035
57.4%
2024-01-29T00:24:50.748539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31215
 
16.3%
1 10240
 
5.4%
, 6376
 
3.3%
동 6250
 
3.3%
서 6176
 
3.2%
( 5806
 
3.0%
) 5804
 
3.0%
로 5587
 
2.9%
시 5583
 
2.9%
인 5546
 
2.9%
Other values (460) 102599
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104373
54.6%
Decimal Number 35213
 
18.4%
Space Separator 31215
 
16.3%
Other Punctuation 6394
 
3.3%
Open Punctuation 5807
 
3.0%
Close Punctuation 5805
 
3.0%
Dash Punctuation 1571
 
0.8%
Uppercase Letter 729
 
0.4%
Lowercase Letter 38
 
< 0.1%
Math Symbol 33
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6250
 
6.0%
서 6176
 
5.9%
로 5587
 
5.4%
시 5583
 
5.3%
인 5546
 
5.3%
천 5521
 
5.3%
구 5467
 
5.2%
광 5465
 
5.2%
역 5450
 
5.2%
호 3095
 
3.0%
Other values (398) 50233
48.1%
Uppercase Letter
ValueCountFrequency (%)
B 262
35.9%
A 157
21.5%
C 44
 
6.0%
K 34
 
4.7%
S 28
 
3.8%
E 24
 
3.3%
D 22
 
3.0%
I 18
 
2.5%
G 17
 
2.3%
F 17
 
2.3%
Other values (14) 106
14.5%
Lowercase Letter
ValueCountFrequency (%)
e 12
31.6%
s 5
13.2%
d 4
 
10.5%
a 4
 
10.5%
y 2
 
5.3%
c 2
 
5.3%
r 2
 
5.3%
k 2
 
5.3%
b 2
 
5.3%
w 1
 
2.6%
Other values (2) 2
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 10240
29.1%
2 4773
13.6%
0 4302
12.2%
3 2951
 
8.4%
4 2586
 
7.3%
5 2369
 
6.7%
6 2169
 
6.2%
8 2075
 
5.9%
7 1964
 
5.6%
9 1784
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 6376
99.7%
& 7
 
0.1%
. 4
 
0.1%
" 2
 
< 0.1%
' 2
 
< 0.1%
@ 2
 
< 0.1%
* 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5806
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 5804
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
31215
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1571
100.0%
Math Symbol
ValueCountFrequency (%)
~ 33
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 104373
54.6%
Common 86040
45.0%
Latin 769
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6250
 
6.0%
서 6176
 
5.9%
로 5587
 
5.4%
시 5583
 
5.3%
인 5546
 
5.3%
천 5521
 
5.3%
구 5467
 
5.2%
광 5465
 
5.2%
역 5450
 
5.2%
호 3095
 
3.0%
Other values (398) 50233
48.1%
Latin
ValueCountFrequency (%)
B 262
34.1%
A 157
20.4%
C 44
 
5.7%
K 34
 
4.4%
S 28
 
3.6%
E 24
 
3.1%
D 22
 
2.9%
I 18
 
2.3%
G 17
 
2.2%
F 17
 
2.2%
Other values (27) 146
19.0%
Common
ValueCountFrequency (%)
31215
36.3%
1 10240
 
11.9%
, 6376
 
7.4%
( 5806
 
6.7%
) 5804
 
6.7%
2 4773
 
5.5%
0 4302
 
5.0%
3 2951
 
3.4%
4 2586
 
3.0%
5 2369
 
2.8%
Other values (15) 9618
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 104344
54.6%
ASCII 86805
45.4%
Compat Jamo 29
 
< 0.1%
CJK Compat 2
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31215
36.0%
1 10240
 
11.8%
, 6376
 
7.3%
( 5806
 
6.7%
) 5804
 
6.7%
2 4773
 
5.5%
0 4302
 
5.0%
3 2951
 
3.4%
4 2586
 
3.0%
5 2369
 
2.7%
Other values (50) 10383
 
12.0%
Hangul
ValueCountFrequency (%)
동 6250
 
6.0%
서 6176
 
5.9%
로 5587
 
5.4%
시 5583
 
5.4%
인 5546
 
5.3%
천 5521
 
5.3%
구 5467
 
5.2%
광 5465
 
5.2%
역 5450
 
5.2%
호 3095
 
3.0%
Other values (397) 50204
48.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 29
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

소재지(지번)
Text

Distinct7668
Distinct (%)77.0%
Missing38
Missing (%)0.4%
Memory size156.2 KiB
2024-01-29T00:24:50.966584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length57
Mean length24.681189
Min length15

Characters and Unicode

Total characters245874
Distinct characters455
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

Unique6350 ?
Unique (%)63.7%

Sample

1st row인천광역시 서구 석남동 223-237
2nd row인천광역시 서구 마전동 0 당하지구5블럭4-1롯트흥겨운마당104호
3rd row인천광역시 서구 신현동 304-2 루원시티루에블리 상가동 101호
4th row인천광역시 서구 석남동 548-4
5th row인천광역시 서구 청라동 124-2
ValueCountFrequency (%)
인천광역시 9963
20.1%
서구 9962
20.1%
석남동 1482
 
3.0%
가좌동 1406
 
2.8%
청라동 1190
 
2.4%
1층 1086
 
2.2%
가정동 1041
 
2.1%
심곡동 859
 
1.7%
마전동 810
 
1.6%
신현동 465
 
0.9%
Other values (6459) 21323
43.0%
2024-01-29T00:24:51.292888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48451
19.7%
1 13967
 
5.7%
동 10748
 
4.4%
구 10448
 
4.2%
서 10267
 
4.2%
시 10119
 
4.1%
인 10100
 
4.1%
천 10060
 
4.1%
광 10004
 
4.1%
역 9980
 
4.1%
Other values (445) 101730
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 129957
52.9%
Decimal Number 55865
22.7%
Space Separator 48451
 
19.7%
Dash Punctuation 8610
 
3.5%
Uppercase Letter 791
 
0.3%
Other Punctuation 730
 
0.3%
Open Punctuation 682
 
0.3%
Close Punctuation 682
 
0.3%
Math Symbol 56
 
< 0.1%
Lowercase Letter 46
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10748
 
8.3%
구 10448
 
8.0%
서 10267
 
7.9%
시 10119
 
7.8%
인 10100
 
7.8%
천 10060
 
7.7%
광 10004
 
7.7%
역 9980
 
7.7%
호 3219
 
2.5%
가 3148
 
2.4%
Other values (387) 41864
32.2%
Uppercase Letter
ValueCountFrequency (%)
B 268
33.9%
A 207
26.2%
C 43
 
5.4%
K 31
 
3.9%
S 30
 
3.8%
M 28
 
3.5%
L 26
 
3.3%
E 25
 
3.2%
D 22
 
2.8%
T 14
 
1.8%
Other values (14) 97
 
12.3%
Lowercase Letter
ValueCountFrequency (%)
e 21
45.7%
s 6
 
13.0%
a 4
 
8.7%
d 4
 
8.7%
r 2
 
4.3%
k 2
 
4.3%
y 2
 
4.3%
c 2
 
4.3%
w 1
 
2.2%
v 1
 
2.2%
Decimal Number
ValueCountFrequency (%)
1 13967
25.0%
2 7071
12.7%
0 6304
11.3%
5 5133
 
9.2%
3 4922
 
8.8%
4 4870
 
8.7%
6 3932
 
7.0%
7 3423
 
6.1%
8 3200
 
5.7%
9 3043
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 690
94.5%
. 19
 
2.6%
& 7
 
1.0%
* 7
 
1.0%
@ 5
 
0.7%
' 2
 
0.3%
Space Separator
ValueCountFrequency (%)
48451
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8610
100.0%
Open Punctuation
ValueCountFrequency (%)
( 682
100.0%
Close Punctuation
ValueCountFrequency (%)
) 682
100.0%
Math Symbol
ValueCountFrequency (%)
~ 56
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 129957
52.9%
Common 115078
46.8%
Latin 839
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10748
 
8.3%
구 10448
 
8.0%
서 10267
 
7.9%
시 10119
 
7.8%
인 10100
 
7.8%
천 10060
 
7.7%
광 10004
 
7.7%
역 9980
 
7.7%
호 3219
 
2.5%
가 3148
 
2.4%
Other values (387) 41864
32.2%
Latin
ValueCountFrequency (%)
B 268
31.9%
A 207
24.7%
C 43
 
5.1%
K 31
 
3.7%
S 30
 
3.6%
M 28
 
3.3%
L 26
 
3.1%
E 25
 
3.0%
D 22
 
2.6%
e 21
 
2.5%
Other values (26) 138
16.4%
Common
ValueCountFrequency (%)
48451
42.1%
1 13967
 
12.1%
- 8610
 
7.5%
2 7071
 
6.1%
0 6304
 
5.5%
5 5133
 
4.5%
3 4922
 
4.3%
4 4870
 
4.2%
6 3932
 
3.4%
7 3423
 
3.0%
Other values (12) 8395
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 129929
52.8%
ASCII 115913
47.1%
Compat Jamo 28
 
< 0.1%
CJK Compat 2
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48451
41.8%
1 13967
 
12.0%
- 8610
 
7.4%
2 7071
 
6.1%
0 6304
 
5.4%
5 5133
 
4.4%
3 4922
 
4.2%
4 4870
 
4.2%
6 3932
 
3.4%
7 3423
 
3.0%
Other values (46) 9230
 
8.0%
Hangul
ValueCountFrequency (%)
동 10748
 
8.3%
구 10448
 
8.0%
서 10267
 
7.9%
시 10119
 
7.8%
인 10100
 
7.8%
천 10060
 
7.7%
광 10004
 
7.7%
역 9980
 
7.7%
호 3219
 
2.5%
가 3148
 
2.4%
Other values (386) 41836
32.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 28
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

인허가일자
Date

Distinct5249
Distinct (%)52.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1902-01-30 00:00:00
Maximum2023-06-07 00:00:00
2024-01-29T00:24:51.398408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:24:51.511823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

폐업일자
Date

Distinct4177
Distinct (%)41.8%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
Minimum2001-02-01 00:00:00
Maximum2023-07-31 00:00:00
2024-01-29T00:24:51.626437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:24:51.731308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-08-01 00:00:00
Maximum2023-08-01 00:00:00
2024-01-29T00:24:51.817562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:24:51.891692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-01-29T00:24:49.102315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:24:49.204082image/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.
2024-01-29T00:24:49.314681image/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
3262일반음식점협회식당<NA>인천광역시 서구 석남동 223-2371992-03-202011-02-012023-08-01
2576일반음식점영일만친구<NA>인천광역시 서구 마전동 0 당하지구5블럭4-1롯트흥겨운마당104호2007-03-022008-04-252023-08-01
6249일반음식점디델리루원씨티점인천광역시 서구 봉오재1로 49, 상가동 101호 (신현동, 루원시티루에블리)인천광역시 서구 신현동 304-2 루원시티루에블리 상가동 101호2018-11-132019-12-132023-08-01
3574일반음식점원조추어탕<NA>인천광역시 서구 석남동 548-41990-06-132012-05-042023-08-01
5818일반음식점족꾼청라점인천광역시 서구 청라에메랄드로149번길 4-11 (연희동, 1층전부)인천광역시 서구 청라동 124-22017-07-132018-09-102023-08-01
6106일반음식점다이닝몽드인천광역시 서구 청라커낼로 280, 청라골든프라자 705호 (청라동)인천광역시 서구 청라동 157-5 청라골든프라자2019-04-102019-05-222023-08-01
1735일반음식점진명동칼국수<NA>인천광역시 서구 석남동 584-162001-07-192007-02-062023-08-01
8170휴게음식점엄마김밥<NA>인천광역시 서구 가좌동 362 (1층)2007-05-312008-04-222023-08-01
8947휴게음식점지에스25연희중앙점인천광역시 서구 승학로 321, 106호 (연희동)인천광역시 서구 연희동 739-1 106호2013-11-082020-03-062023-08-01
1930일반음식점명동분식<NA>인천광역시 서구 가좌동 278-51998-09-012007-09-072023-08-01
업종명업소명소재지(도로명)소재지(지번)인허가일자폐업일자데이터기준일자
3303일반음식점디디푸드<NA>인천광역시 서구 공촌동 318-1 광명아파트상가 204호2011-04-072011-05-232023-08-01
7144일반음식점정든포장마차앤소곱창구이인천광역시 서구 새오개로 52, 203호 (신현동)인천광역시 서구 신현동 151-22 203호2007-08-282021-12-092023-08-01
8733휴게음식점멜리멜로우인천광역시 서구 청라커낼로288번길 8-10, 청라 봄 빌딩 B104,B105호 (경서동)인천광역시 서구 경서동 956-3 청라 봄 빌딩 B104,B105호2018-05-092018-06-222023-08-01
168일반음식점수아네김밥<NA>인천광역시 서구 가좌동 224-16 19통4반2002-05-102003-05-072023-08-01
10283제과점영업바림케이크인천광역시 서구 원당대로 683 (마전동, 나산프라자 107호)인천광역시 서구 마전동 1058-5 107호2016-01-192023-04-212023-08-01
3022일반음식점아미랑호프<NA>인천광역시 서구 가정동 504-162009-07-062010-04-192023-08-01
8650휴게음식점도그덤인천광역시 서구 완정로117번길 8 (왕길동, 2층)인천광역시 서구 왕길동 674-2 2층2014-05-262017-02-282023-08-01
10304유흥주점영업호박노래클럽<NA>인천광역시 서구 심곡동 242-32001-03-282006-04-202023-08-01
1405일반음식점어진네뼈다귀<NA>인천광역시 서구 심곡동 278-2 102호2005-03-032006-07-262023-08-01
7394일반음식점카페지니인천광역시 서구 여우재로 101, 1층 (가좌동)인천광역시 서구 가좌동 361-82019-12-132022-05-102023-08-01

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
5일반음식점김밥천국인천광역시 서구 가정로308번길 2 (석남동,외1필지)인천광역시 서구 석남동 457-12 외1필지2004-12-062013-01-012023-08-012
6일반음식점돈푸대 신현점<NA>인천광역시 서구 신현동 287-232004-08-202012-10-182023-08-012
7일반음식점떡볶이대통령인천광역시 서구 완정로202번안길 34 (마전동)인천광역시 서구 마전동 911-72014-02-102019-09-262023-08-012
8일반음식점명동분식<NA>인천광역시 서구 가좌동 278-51998-09-012007-09-072023-08-012
9일반음식점밥퍼주는 남자인천광역시 서구 심곡로 130 (심곡동, 영우빌딩,102호)인천광역시 서구 심곡동 2902010-04-012022-10-042023-08-012