Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells4597
Missing cells (%)6.6%
Duplicate rows17
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 17 (0.2%) duplicate rowsDuplicates
업종명 is highly imbalanced (57.6%)Imbalance
소재지(도로명) has 4547 (45.5%) missing valuesMissing

Reproduction

Analysis started2024-01-28 15:24:54.545916
Analysis finished2024-01-28 15:24:56.189884
Duration1.64 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
7745 
휴게음식점
1476 
위탁급식영업
 
436
제과점영업
 
247
유흥주점영업
 
53

Length

Max length6
Median length5
Mean length5.0446
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 7745
77.5%
휴게음식점 1476
 
14.8%
위탁급식영업 436
 
4.4%
제과점영업 247
 
2.5%
유흥주점영업 53
 
0.5%
단란주점 43
 
0.4%

Length

2024-01-29T00:24:56.246863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:24:56.341334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 7745
77.5%
휴게음식점 1476
 
14.8%
위탁급식영업 436
 
4.4%
제과점영업 247
 
2.5%
유흥주점영업 53
 
0.5%
단란주점 43
 
0.4%

업소명
Text

Distinct8768
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-29T00:24:56.572247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length6.0674
Min length1

Characters and Unicode

Total characters60674
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

Unique8008 ?
Unique (%)80.1%

Sample

1st row죽여주는열꼬치
2nd row가좌써키트 구내식당
3rd row삼성푸드시스템 새한미디어
4th row만리장성
5th row돌투반한치회무침
ValueCountFrequency (%)
청라점 75
 
0.7%
김밥천국 29
 
0.3%
카페 28
 
0.2%
검단점 27
 
0.2%
인천청라점 25
 
0.2%
세븐일레븐 19
 
0.2%
cafe 19
 
0.2%
gs25 17
 
0.1%
주)아워홈 14
 
0.1%
떡볶이 14
 
0.1%
Other values (9333) 11243
97.7%
2024-01-29T00:24:56.930291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1510
 
2.5%
이 1309
 
2.2%
점 1269
 
2.1%
식 1123
 
1.9%
스 1073
 
1.8%
리 908
 
1.5%
당 865
 
1.4%
라 829
 
1.4%
가 689
 
1.1%
마 680
 
1.1%
Other values (1076) 50419
83.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54852
90.4%
Space Separator 1510
 
2.5%
Uppercase Letter 1110
 
1.8%
Lowercase Letter 927
 
1.5%
Close Punctuation 678
 
1.1%
Open Punctuation 677
 
1.1%
Decimal Number 677
 
1.1%
Other Punctuation 221
 
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 1309
 
2.4%
점 1269
 
2.3%
식 1123
 
2.0%
스 1073
 
2.0%
리 908
 
1.7%
당 865
 
1.6%
라 829
 
1.5%
가 689
 
1.3%
마 680
 
1.2%
치 630
 
1.1%
Other values (994) 45477
82.9%
Uppercase Letter
ValueCountFrequency (%)
C 134
 
12.1%
S 104
 
9.4%
B 85
 
7.7%
G 79
 
7.1%
O 71
 
6.4%
A 69
 
6.2%
E 67
 
6.0%
P 51
 
4.6%
N 47
 
4.2%
F 44
 
4.0%
Other values (16) 359
32.3%
Lowercase Letter
ValueCountFrequency (%)
e 150
16.2%
a 115
12.4%
o 78
 
8.4%
c 59
 
6.4%
r 58
 
6.3%
f 56
 
6.0%
s 51
 
5.5%
n 50
 
5.4%
t 45
 
4.9%
i 42
 
4.5%
Other values (15) 223
24.1%
Other Punctuation
ValueCountFrequency (%)
& 86
38.9%
. 61
27.6%
, 28
 
12.7%
' 17
 
7.7%
! 9
 
4.1%
· 6
 
2.7%
/ 5
 
2.3%
? 4
 
1.8%
# 2
 
0.9%
＆ 1
 
0.5%
Other values (2) 2
 
0.9%
Decimal Number
ValueCountFrequency (%)
2 174
25.7%
5 101
14.9%
0 88
13.0%
1 77
11.4%
3 54
 
8.0%
9 45
 
6.6%
4 45
 
6.6%
6 34
 
5.0%
8 31
 
4.6%
7 28
 
4.1%
Other Symbol
ValueCountFrequency (%)
℃ 3
60.0%
㈜ 2
40.0%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
~ 1
33.3%
Space Separator
ValueCountFrequency (%)
1510
100.0%
Close Punctuation
ValueCountFrequency (%)
) 678
100.0%
Open Punctuation
ValueCountFrequency (%)
( 677
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54839
90.4%
Common 3783
 
6.2%
Latin 2037
 
3.4%
Han 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1309
 
2.4%
점 1269
 
2.3%
식 1123
 
2.0%
스 1073
 
2.0%
리 908
 
1.7%
당 865
 
1.6%
라 829
 
1.5%
가 689
 
1.3%
마 680
 
1.2%
치 630
 
1.1%
Other values (985) 45464
82.9%
Latin
ValueCountFrequency (%)
e 150
 
7.4%
C 134
 
6.6%
a 115
 
5.6%
S 104
 
5.1%
B 85
 
4.2%
G 79
 
3.9%
o 78
 
3.8%
O 71
 
3.5%
A 69
 
3.4%
E 67
 
3.3%
Other values (41) 1085
53.3%
Common
ValueCountFrequency (%)
1510
39.9%
) 678
17.9%
( 677
17.9%
2 174
 
4.6%
5 101
 
2.7%
0 88
 
2.3%
& 86
 
2.3%
1 77
 
2.0%
. 61
 
1.6%
3 54
 
1.4%
Other values (20) 277
 
7.3%
Han
ValueCountFrequency (%)
辛 3
20.0%
家 3
20.0%
大 2
13.3%
元 1
 
6.7%
孝 1
 
6.7%
人 1
 
6.7%
張 1
 
6.7%
高 1
 
6.7%
福 1
 
6.7%
堂 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54834
90.4%
ASCII 5810
 
9.6%
CJK 15
 
< 0.1%
None 9
 
< 0.1%
Letterlike Symbols 3
 
< 0.1%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1510
26.0%
) 678
 
11.7%
( 677
 
11.7%
2 174
 
3.0%
e 150
 
2.6%
C 134
 
2.3%
a 115
 
2.0%
S 104
 
1.8%
5 101
 
1.7%
0 88
 
1.5%
Other values (68) 2079
35.8%
Hangul
ValueCountFrequency (%)
이 1309
 
2.4%
점 1269
 
2.3%
식 1123
 
2.0%
스 1073
 
2.0%
리 908
 
1.7%
당 865
 
1.6%
라 829
 
1.5%
가 689
 
1.3%
마 680
 
1.2%
치 630
 
1.1%
Other values (983) 45459
82.9%
None
ValueCountFrequency (%)
· 6
66.7%
㈜ 2
 
22.2%
＆ 1
 
11.1%
Letterlike Symbols
ValueCountFrequency (%)
℃ 3
100.0%
CJK
ValueCountFrequency (%)
辛 3
20.0%
家 3
20.0%
大 2
13.3%
元 1
 
6.7%
孝 1
 
6.7%
人 1
 
6.7%
張 1
 
6.7%
高 1
 
6.7%
福 1
 
6.7%
堂 1
 
6.7%
Compat Jamo
ValueCountFrequency (%)
ㅊ 3
100.0%

소재지(도로명)
Text

MISSING 

Distinct5120
Distinct (%)93.9%
Missing4547
Missing (%)45.5%
Memory size156.2 KiB
2024-01-29T00:24:57.181310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length102
Median length74
Mean length35.226481
Min length20

Characters and Unicode

Total characters192090
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

Unique4849 ?
Unique (%)88.9%

Sample

1st row인천광역시 서구 새오개로111번안길 29, 엠디프라자 103호 (신현동)
2nd row인천광역시 서구 명가골로 6 (석남동, 1층일부)
3rd row인천광역시 서구 푸른로14번길 8 (경서동, 청경채 102호)
4th row인천광역시 서구 열우물로282번길 20-5 (가좌동, 1층)
5th row인천광역시 서구 심곡로56번길 2 (심곡동, 256 삼원빌딩(지하1층))
ValueCountFrequency (%)
인천광역시 5454
 
14.8%
서구 5453
 
14.8%
1층 1241
 
3.4%
가좌동 632
 
1.7%
연희동 580
 
1.6%
석남동 547
 
1.5%
청라동 537
 
1.5%
마전동 432
 
1.2%
경서동 419
 
1.1%
심곡동 356
 
1.0%
Other values (4002) 21135
57.5%
2024-01-29T00:24:57.540093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31355
 
16.3%
1 10327
 
5.4%
, 6412
 
3.3%
동 6287
 
3.3%
서 6194
 
3.2%
( 5829
 
3.0%
) 5827
 
3.0%
로 5611
 
2.9%
시 5605
 
2.9%
인 5565
 
2.9%
Other values (463) 103078
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104781
54.5%
Decimal Number 35467
 
18.5%
Space Separator 31355
 
16.3%
Other Punctuation 6428
 
3.3%
Open Punctuation 5830
 
3.0%
Close Punctuation 5828
 
3.0%
Dash Punctuation 1594
 
0.8%
Uppercase Letter 727
 
0.4%
Lowercase Letter 44
 
< 0.1%
Math Symbol 31
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6287
 
6.0%
서 6194
 
5.9%
로 5611
 
5.4%
시 5605
 
5.3%
인 5565
 
5.3%
천 5540
 
5.3%
광 5485
 
5.2%
구 5484
 
5.2%
역 5468
 
5.2%
호 3102
 
3.0%
Other values (401) 50440
48.1%
Uppercase Letter
ValueCountFrequency (%)
B 267
36.7%
A 161
22.1%
C 44
 
6.1%
K 32
 
4.4%
S 27
 
3.7%
D 22
 
3.0%
E 22
 
3.0%
G 18
 
2.5%
F 18
 
2.5%
I 17
 
2.3%
Other values (14) 99
 
13.6%
Lowercase Letter
ValueCountFrequency (%)
e 12
27.3%
s 8
18.2%
a 5
11.4%
d 4
 
9.1%
c 3
 
6.8%
r 2
 
4.5%
b 2
 
4.5%
k 2
 
4.5%
i 2
 
4.5%
y 2
 
4.5%
Other values (2) 2
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 10327
29.1%
2 4827
13.6%
0 4324
12.2%
3 2969
 
8.4%
4 2605
 
7.3%
5 2371
 
6.7%
6 2188
 
6.2%
8 2092
 
5.9%
7 1986
 
5.6%
9 1778
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 6412
99.8%
& 6
 
0.1%
. 4
 
0.1%
' 2
 
< 0.1%
" 2
 
< 0.1%
@ 1
 
< 0.1%
* 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5829
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 5827
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
31355
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1594
100.0%
Math Symbol
ValueCountFrequency (%)
~ 31
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 104781
54.5%
Common 86535
45.0%
Latin 774
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6287
 
6.0%
서 6194
 
5.9%
로 5611
 
5.4%
시 5605
 
5.3%
인 5565
 
5.3%
천 5540
 
5.3%
광 5485
 
5.2%
구 5484
 
5.2%
역 5468
 
5.2%
호 3102
 
3.0%
Other values (401) 50440
48.1%
Latin
ValueCountFrequency (%)
B 267
34.5%
A 161
20.8%
C 44
 
5.7%
K 32
 
4.1%
S 27
 
3.5%
D 22
 
2.8%
E 22
 
2.8%
G 18
 
2.3%
F 18
 
2.3%
I 17
 
2.2%
Other values (27) 146
18.9%
Common
ValueCountFrequency (%)
31355
36.2%
1 10327
 
11.9%
, 6412
 
7.4%
( 5829
 
6.7%
) 5827
 
6.7%
2 4827
 
5.6%
0 4324
 
5.0%
3 2969
 
3.4%
4 2605
 
3.0%
5 2371
 
2.7%
Other values (15) 9689
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 104753
54.5%
ASCII 87304
45.4%
Compat Jamo 28
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK Compat 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31355
35.9%
1 10327
 
11.8%
, 6412
 
7.3%
( 5829
 
6.7%
) 5827
 
6.7%
2 4827
 
5.5%
0 4324
 
5.0%
3 2969
 
3.4%
4 2605
 
3.0%
5 2371
 
2.7%
Other values (50) 10458
 
12.0%
Hangul
ValueCountFrequency (%)
동 6287
 
6.0%
서 6194
 
5.9%
로 5611
 
5.4%
시 5605
 
5.4%
인 5565
 
5.3%
천 5540
 
5.3%
광 5485
 
5.2%
구 5484
 
5.2%
역 5468
 
5.2%
호 3102
 
3.0%
Other values (400) 50412
48.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 28
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%

소재지(지번)
Text

Distinct7703
Distinct (%)77.3%
Missing41
Missing (%)0.4%
Memory size156.2 KiB
2024-01-29T00:24:57.755797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length57
Mean length24.702982
Min length15

Characters and Unicode

Total characters246017
Distinct characters457
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

Unique6398 ?
Unique (%)64.2%

Sample

1st row인천광역시 서구 심곡동 255 1층가호
2nd row인천광역시 서구 가좌동 576
3rd row인천광역시 서구 가좌동 552-27
4th row인천광역시 서구 가정동 294-17
5th row인천광역시 서구 석남동 469 명성빌딩 101호
ValueCountFrequency (%)
인천광역시 9960
20.1%
서구 9959
20.1%
석남동 1468
 
3.0%
가좌동 1403
 
2.8%
청라동 1200
 
2.4%
1층 1076
 
2.2%
가정동 1034
 
2.1%
심곡동 856
 
1.7%
마전동 811
 
1.6%
신현동 456
 
0.9%
Other values (6466) 21387
43.1%
2024-01-29T00:24:58.078899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48485
19.7%
1 13989
 
5.7%
동 10753
 
4.4%
구 10453
 
4.2%
서 10267
 
4.2%
시 10118
 
4.1%
인 10095
 
4.1%
천 10055
 
4.1%
광 9999
 
4.1%
역 9977
 
4.1%
Other values (447) 101826
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130037
52.9%
Decimal Number 55895
22.7%
Space Separator 48485
 
19.7%
Dash Punctuation 8604
 
3.5%
Uppercase Letter 794
 
0.3%
Other Punctuation 743
 
0.3%
Close Punctuation 674
 
0.3%
Open Punctuation 674
 
0.3%
Math Symbol 54
 
< 0.1%
Lowercase Letter 52
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10753
 
8.3%
구 10453
 
8.0%
서 10267
 
7.9%
시 10118
 
7.8%
인 10095
 
7.8%
천 10055
 
7.7%
광 9999
 
7.7%
역 9977
 
7.7%
호 3226
 
2.5%
가 3137
 
2.4%
Other values (389) 41957
32.3%
Uppercase Letter
ValueCountFrequency (%)
B 276
34.8%
A 209
26.3%
C 41
 
5.2%
S 30
 
3.8%
M 29
 
3.7%
K 29
 
3.7%
L 29
 
3.7%
E 23
 
2.9%
D 22
 
2.8%
T 15
 
1.9%
Other values (14) 91
 
11.5%
Lowercase Letter
ValueCountFrequency (%)
e 21
40.4%
s 9
17.3%
a 5
 
9.6%
d 4
 
7.7%
c 3
 
5.8%
r 2
 
3.8%
y 2
 
3.8%
i 2
 
3.8%
k 2
 
3.8%
w 1
 
1.9%
Decimal Number
ValueCountFrequency (%)
1 13989
25.0%
2 7102
12.7%
0 6305
11.3%
5 5134
 
9.2%
3 4910
 
8.8%
4 4855
 
8.7%
6 3963
 
7.1%
7 3401
 
6.1%
8 3190
 
5.7%
9 3046
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 706
95.0%
. 19
 
2.6%
* 6
 
0.8%
& 6
 
0.8%
@ 4
 
0.5%
' 2
 
0.3%
Space Separator
ValueCountFrequency (%)
48485
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8604
100.0%
Close Punctuation
ValueCountFrequency (%)
) 674
100.0%
Open Punctuation
ValueCountFrequency (%)
( 674
100.0%
Math Symbol
ValueCountFrequency (%)
~ 54
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130037
52.9%
Common 115131
46.8%
Latin 849
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10753
 
8.3%
구 10453
 
8.0%
서 10267
 
7.9%
시 10118
 
7.8%
인 10095
 
7.8%
천 10055
 
7.7%
광 9999
 
7.7%
역 9977
 
7.7%
호 3226
 
2.5%
가 3137
 
2.4%
Other values (389) 41957
32.3%
Latin
ValueCountFrequency (%)
B 276
32.5%
A 209
24.6%
C 41
 
4.8%
S 30
 
3.5%
M 29
 
3.4%
K 29
 
3.4%
L 29
 
3.4%
E 23
 
2.7%
D 22
 
2.6%
e 21
 
2.5%
Other values (26) 140
16.5%
Common
ValueCountFrequency (%)
48485
42.1%
1 13989
 
12.2%
- 8604
 
7.5%
2 7102
 
6.2%
0 6305
 
5.5%
5 5134
 
4.5%
3 4910
 
4.3%
4 4855
 
4.2%
6 3963
 
3.4%
7 3401
 
3.0%
Other values (12) 8383
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130010
52.8%
ASCII 115975
47.1%
Compat Jamo 27
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK Compat 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48485
41.8%
1 13989
 
12.1%
- 8604
 
7.4%
2 7102
 
6.1%
0 6305
 
5.4%
5 5134
 
4.4%
3 4910
 
4.2%
4 4855
 
4.2%
6 3963
 
3.4%
7 3401
 
2.9%
Other values (46) 9227
 
8.0%
Hangul
ValueCountFrequency (%)
동 10753
 
8.3%
구 10453
 
8.0%
서 10267
 
7.9%
시 10118
 
7.8%
인 10095
 
7.8%
천 10055
 
7.7%
광 9999
 
7.7%
역 9977
 
7.7%
호 3226
 
2.5%
가 3137
 
2.4%
Other values (388) 41930
32.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 27
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%

인허가일자
Date

Distinct5235
Distinct (%)52.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1902-01-30 00:00:00
Maximum2023-06-07 00:00:00
2024-01-29T00:24:58.188418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:24:58.301467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

폐업일자
Date

Distinct4175
Distinct (%)41.8%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
Minimum2001-02-01 00:00:00
Maximum2023-07-31 00:00:00
2024-01-29T00:24:58.412764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:24:58.522556image/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
2024-01-29T00:24:58.617961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:24:58.692580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-01-29T00:24:55.938651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:24:56.055246image/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.
2024-01-29T00:24:56.140320image/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
8241휴게음식점죽여주는열꼬치<NA>인천광역시 서구 심곡동 255 1층가호2008-12-102011-03-072023-08-01
9599위탁급식영업가좌써키트 구내식당<NA>인천광역시 서구 가좌동 5762003-08-232004-05-192023-08-01
9702위탁급식영업삼성푸드시스템 새한미디어<NA>인천광역시 서구 가좌동 552-272003-08-232008-03-202023-08-01
2445일반음식점만리장성<NA>인천광역시 서구 가정동 294-171989-04-012008-10-062023-08-01
3650일반음식점돌투반한치회무침<NA>인천광역시 서구 석남동 469 명성빌딩 101호2010-10-142012-08-272023-08-01
7488일반음식점명가통닭(신현점)인천광역시 서구 새오개로111번안길 29, 엠디프라자 103호 (신현동)인천광역시 서구 신현동 307-22020-05-252022-08-182023-08-01
5882일반음식점돼지금고인천광역시 서구 명가골로 6 (석남동, 1층일부)인천광역시 서구 석남동 482-39 1층일부2016-03-252018-12-052023-08-01
5791일반음식점스타야시장인천광역시 서구 푸른로14번길 8 (경서동, 청경채 102호)인천광역시 서구 경서동 976-32 청경채 102호2016-12-272018-07-262023-08-01
2617일반음식점항아리해물칼국수<NA>인천광역시 서구 원당동 0 원당지구24블럭3-2롯트 B동 101,102,103호2007-10-082008-11-132023-08-01
8842휴게음식점아바노스인천광역시 서구 열우물로282번길 20-5 (가좌동, 1층)인천광역시 서구 가좌동 331-24 1층2017-03-062019-05-072023-08-01
업종명업소명소재지(도로명)소재지(지번)인허가일자폐업일자데이터기준일자
313일반음식점여인천하<NA>인천광역시 서구 가정동 482-31992-10-262003-10-132023-08-01
6678일반음식점죽이야기 완정점인천광역시 서구 청마로19번길 20 (당하동, 102호)인천광역시 서구 당하동 1082-2 102호2014-09-262020-01-082023-08-01
7838일반음식점청라밥집인천광역시 서구 청라에메랄드로 99, 지젤엠청라 1층 47호 (청라동)인천광역시 서구 청라동 165-12 지젤엠청라 47호2023-02-012023-03-082023-08-01
1184일반음식점예진식당<NA>인천광역시 서구 금곡동 1822000-06-072005-01-242023-08-01
5763일반음식점날라리 즉석떡볶이인천광역시 서구 검암로20번길 35 (검암동, 해동프라자 202호)인천광역시 서구 검암동 513-82016-08-012018-06-122023-08-01
4147일반음식점청기와뼈다귀해장국인천광역시 서구 길주로63번길 25 (석남동, 524-13외 1필지(1,2층))인천광역시 서구 석남동 524-13 외1필지(1,2층)2012-02-032014-03-312023-08-01
8007일반음식점독도해물알찜&차돌쭈꾸미찜인천광역시 서구 완정로178번길 37, 102호 (마전동)인천광역시 서구 마전동 917-4 102호2021-12-202023-01-192023-08-01
2869일반음식점촌돼지막창<NA>인천광역시 서구 마전동 - 검단2지구25블럭2,12롯트A동2층일부2007-04-132009-02-052023-08-01
8255휴게음식점고구려<NA>인천광역시 서구 검암동 604-12006-01-062011-09-262023-08-01
5991일반음식점신동마을인천광역시 서구 신동길 6 (금곡동)인천광역시 서구 금곡동 522-51995-09-202018-10-022023-08-01

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
4일반음식점돈푸대 신현점<NA>인천광역시 서구 신현동 287-232004-08-202012-10-182023-08-012
5일반음식점떡볶이대통령인천광역시 서구 완정로202번안길 34 (마전동)인천광역시 서구 마전동 911-72014-02-102019-09-262023-08-012
6일반음식점명동분식<NA>인천광역시 서구 가좌동 278-51998-09-012007-09-072023-08-012
7일반음식점밥퍼주는 남자인천광역시 서구 심곡로 130 (심곡동, 영우빌딩,102호)인천광역시 서구 심곡동 2902010-04-012022-10-042023-08-012
8일반음식점비어라인천광역시 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
9일반음식점소낙비<NA>인천광역시 서구 가좌동 186-12005-08-112009-07-292023-08-012