Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells4580
Missing cells (%)6.5%
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 (57.9%)Imbalance
소재지(도로명) has 4530 (45.3%) missing valuesMissing

Reproduction

Analysis started2024-01-28 15:24:40.932304
Analysis finished2024-01-28 15:24:42.477985
Duration1.55 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
7758 
휴게음식점
1479 
위탁급식영업
 
425
제과점영업
 
248
유흥주점영업
 
47

Length

Max length6
Median length5
Mean length5.0429
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 7758
77.6%
휴게음식점 1479
 
14.8%
위탁급식영업 425
 
4.2%
제과점영업 248
 
2.5%
유흥주점영업 47
 
0.5%
단란주점 43
 
0.4%

Length

2024-01-29T00:24:42.533411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:24:42.625564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 7758
77.6%
휴게음식점 1479
 
14.8%
위탁급식영업 425
 
4.2%
제과점영업 248
 
2.5%
유흥주점영업 47
 
0.5%
단란주점 43
 
0.4%

업소명
Text

Distinct8753
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-29T00:24:42.855770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length6.0577
Min length1

Characters and Unicode

Total characters60577
Distinct characters1088
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

Unique7975 ?
Unique (%)79.8%

Sample

1st row번지없는주막
2nd row금자매포장마차
3rd row퀸
4th row다다식당
5th row피제이피자
ValueCountFrequency (%)
청라점 74
 
0.6%
김밥천국 31
 
0.3%
카페 27
 
0.2%
검단점 26
 
0.2%
인천청라점 25
 
0.2%
cafe 20
 
0.2%
세븐일레븐 19
 
0.2%
gs25 18
 
0.2%
주)아워홈 15
 
0.1%
정원식당 13
 
0.1%
Other values (9316) 11240
97.7%
2024-01-29T00:24:43.221390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1508
 
2.5%
이 1312
 
2.2%
점 1262
 
2.1%
식 1122
 
1.9%
스 1077
 
1.8%
리 900
 
1.5%
당 861
 
1.4%
라 836
 
1.4%
가 689
 
1.1%
마 675
 
1.1%
Other values (1078) 50335
83.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54677
90.3%
Space Separator 1508
 
2.5%
Uppercase Letter 1152
 
1.9%
Lowercase Letter 960
 
1.6%
Decimal Number 692
 
1.1%
Close Punctuation 673
 
1.1%
Open Punctuation 672
 
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 1312
 
2.4%
점 1262
 
2.3%
식 1122
 
2.1%
스 1077
 
2.0%
리 900
 
1.6%
당 861
 
1.6%
라 836
 
1.5%
가 689
 
1.3%
마 675
 
1.2%
치 626
 
1.1%
Other values (996) 45317
82.9%
Uppercase Letter
ValueCountFrequency (%)
C 136
 
11.8%
S 110
 
9.5%
B 89
 
7.7%
G 82
 
7.1%
O 75
 
6.5%
A 72
 
6.2%
E 70
 
6.1%
P 53
 
4.6%
N 51
 
4.4%
F 47
 
4.1%
Other values (16) 367
31.9%
Lowercase Letter
ValueCountFrequency (%)
e 151
15.7%
a 119
12.4%
o 82
 
8.5%
r 61
 
6.4%
c 60
 
6.2%
f 57
 
5.9%
n 55
 
5.7%
s 52
 
5.4%
i 46
 
4.8%
t 45
 
4.7%
Other values (15) 232
24.2%
Other Punctuation
ValueCountFrequency (%)
& 86
38.9%
. 60
27.1%
, 27
 
12.2%
' 18
 
8.1%
! 9
 
4.1%
· 6
 
2.7%
/ 6
 
2.7%
? 4
 
1.8%
# 2
 
0.9%
: 1
 
0.5%
Other values (2) 2
 
0.9%
Decimal Number
ValueCountFrequency (%)
2 176
25.4%
5 105
15.2%
0 87
12.6%
1 80
11.6%
3 55
 
7.9%
9 48
 
6.9%
4 45
 
6.5%
8 34
 
4.9%
6 33
 
4.8%
7 29
 
4.2%
Other Symbol
ValueCountFrequency (%)
℃ 3
60.0%
㈜ 2
40.0%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
~ 1
33.3%
Space Separator
ValueCountFrequency (%)
1508
100.0%
Close Punctuation
ValueCountFrequency (%)
) 673
100.0%
Open Punctuation
ValueCountFrequency (%)
( 672
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54663
90.2%
Common 3786
 
6.2%
Latin 2112
 
3.5%
Han 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1312
 
2.4%
점 1262
 
2.3%
식 1122
 
2.1%
스 1077
 
2.0%
리 900
 
1.6%
당 861
 
1.6%
라 836
 
1.5%
가 689
 
1.3%
마 675
 
1.2%
치 626
 
1.1%
Other values (986) 45303
82.9%
Latin
ValueCountFrequency (%)
e 151
 
7.1%
C 136
 
6.4%
a 119
 
5.6%
S 110
 
5.2%
B 89
 
4.2%
o 82
 
3.9%
G 82
 
3.9%
O 75
 
3.6%
A 72
 
3.4%
E 70
 
3.3%
Other values (41) 1126
53.3%
Common
ValueCountFrequency (%)
1508
39.8%
) 673
17.8%
( 672
17.7%
2 176
 
4.6%
5 105
 
2.8%
0 87
 
2.3%
& 86
 
2.3%
1 80
 
2.1%
. 60
 
1.6%
3 55
 
1.5%
Other values (20) 284
 
7.5%
Han
ValueCountFrequency (%)
家 3
18.8%
辛 3
18.8%
大 2
12.5%
高 1
 
6.2%
福 1
 
6.2%
孝 1
 
6.2%
情 1
 
6.2%
堂 1
 
6.2%
人 1
 
6.2%
元 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54658
90.2%
ASCII 5888
 
9.7%
CJK 16
 
< 0.1%
None 9
 
< 0.1%
Letterlike Symbols 3
 
< 0.1%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1508
25.6%
) 673
 
11.4%
( 672
 
11.4%
2 176
 
3.0%
e 151
 
2.6%
C 136
 
2.3%
a 119
 
2.0%
S 110
 
1.9%
5 105
 
1.8%
B 89
 
1.5%
Other values (68) 2149
36.5%
Hangul
ValueCountFrequency (%)
이 1312
 
2.4%
점 1262
 
2.3%
식 1122
 
2.1%
스 1077
 
2.0%
리 900
 
1.6%
당 861
 
1.6%
라 836
 
1.5%
가 689
 
1.3%
마 675
 
1.2%
치 626
 
1.1%
Other values (984) 45298
82.9%
None
ValueCountFrequency (%)
· 6
66.7%
㈜ 2
 
22.2%
＆ 1
 
11.1%
CJK
ValueCountFrequency (%)
家 3
18.8%
辛 3
18.8%
大 2
12.5%
高 1
 
6.2%
福 1
 
6.2%
孝 1
 
6.2%
情 1
 
6.2%
堂 1
 
6.2%
人 1
 
6.2%
元 1
 
6.2%
Letterlike Symbols
ValueCountFrequency (%)
℃ 3
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅊ 3
100.0%

소재지(도로명)
Text

MISSING 

Distinct5137
Distinct (%)93.9%
Missing4530
Missing (%)45.3%
Memory size156.2 KiB
2024-01-29T00:24:43.464863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length102
Median length74
Mean length35.214442
Min length20

Characters and Unicode

Total characters192623
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

Unique4864 ?
Unique (%)88.9%

Sample

1st row인천광역시 서구 연희로 38, 1층 (연희동)
2nd row인천광역시 서구 원적로96번길 26 (가좌동,가좌프라자쇼핑(1층 112-3호))
3rd row인천광역시 서구 청라라임로 85, A동 108호 (연희동, 린스트라우스상가)
4th row인천광역시 서구 완정로 35 (마전동, 대운프라자 105호)
5th row인천광역시 서구 가정로 374, 3층 (가정동)
ValueCountFrequency (%)
인천광역시 5471
 
14.8%
서구 5470
 
14.8%
1층 1235
 
3.3%
가좌동 623
 
1.7%
연희동 580
 
1.6%
석남동 554
 
1.5%
청라동 547
 
1.5%
마전동 437
 
1.2%
경서동 429
 
1.2%
심곡동 346
 
0.9%
Other values (4007) 21198
57.5%
2024-01-29T00:24:43.837901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31443
 
16.3%
1 10353
 
5.4%
, 6427
 
3.3%
동 6303
 
3.3%
서 6226
 
3.2%
( 5841
 
3.0%
) 5839
 
3.0%
로 5627
 
2.9%
시 5618
 
2.9%
인 5589
 
2.9%
Other values (463) 103357
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105141
54.6%
Decimal Number 35513
 
18.4%
Space Separator 31443
 
16.3%
Other Punctuation 6445
 
3.3%
Open Punctuation 5842
 
3.0%
Close Punctuation 5840
 
3.0%
Dash Punctuation 1578
 
0.8%
Uppercase Letter 739
 
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 6303
 
6.0%
서 6226
 
5.9%
로 5627
 
5.4%
시 5618
 
5.3%
인 5589
 
5.3%
천 5563
 
5.3%
광 5504
 
5.2%
구 5500
 
5.2%
역 5485
 
5.2%
호 3131
 
3.0%
Other values (401) 50595
48.1%
Uppercase Letter
ValueCountFrequency (%)
B 265
35.9%
A 162
21.9%
C 44
 
6.0%
K 34
 
4.6%
S 29
 
3.9%
D 23
 
3.1%
E 23
 
3.1%
F 19
 
2.6%
I 18
 
2.4%
G 17
 
2.3%
Other values (14) 105
 
14.2%
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%
y 2
 
4.5%
k 2
 
4.5%
i 2
 
4.5%
Other values (2) 2
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 10353
29.2%
2 4810
13.5%
0 4337
12.2%
3 2977
 
8.4%
4 2620
 
7.4%
5 2387
 
6.7%
6 2191
 
6.2%
8 2097
 
5.9%
7 1981
 
5.6%
9 1760
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 6427
99.7%
& 7
 
0.1%
. 4
 
0.1%
" 2
 
< 0.1%
' 2
 
< 0.1%
@ 2
 
< 0.1%
* 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5841
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 5839
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
31443
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 105141
54.6%
Common 86696
45.0%
Latin 786
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6303
 
6.0%
서 6226
 
5.9%
로 5627
 
5.4%
시 5618
 
5.3%
인 5589
 
5.3%
천 5563
 
5.3%
광 5504
 
5.2%
구 5500
 
5.2%
역 5485
 
5.2%
호 3131
 
3.0%
Other values (401) 50595
48.1%
Latin
ValueCountFrequency (%)
B 265
33.7%
A 162
20.6%
C 44
 
5.6%
K 34
 
4.3%
S 29
 
3.7%
D 23
 
2.9%
E 23
 
2.9%
F 19
 
2.4%
I 18
 
2.3%
G 17
 
2.2%
Other values (27) 152
19.3%
Common
ValueCountFrequency (%)
31443
36.3%
1 10353
 
11.9%
, 6427
 
7.4%
( 5841
 
6.7%
) 5839
 
6.7%
2 4810
 
5.5%
0 4337
 
5.0%
3 2977
 
3.4%
4 2620
 
3.0%
5 2387
 
2.8%
Other values (15) 9662
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105111
54.6%
ASCII 87477
45.4%
Compat Jamo 30
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK Compat 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31443
35.9%
1 10353
 
11.8%
, 6427
 
7.3%
( 5841
 
6.7%
) 5839
 
6.7%
2 4810
 
5.5%
0 4337
 
5.0%
3 2977
 
3.4%
4 2620
 
3.0%
5 2387
 
2.7%
Other values (50) 10443
 
11.9%
Hangul
ValueCountFrequency (%)
동 6303
 
6.0%
서 6226
 
5.9%
로 5627
 
5.4%
시 5618
 
5.3%
인 5589
 
5.3%
천 5563
 
5.3%
광 5504
 
5.2%
구 5500
 
5.2%
역 5485
 
5.2%
호 3131
 
3.0%
Other values (400) 50565
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

Distinct7675
Distinct (%)77.1%
Missing41
Missing (%)0.4%
Memory size156.2 KiB
2024-01-29T00:24:44.059877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length57
Mean length24.688322
Min length15

Characters and Unicode

Total characters245871
Distinct characters456
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

Unique6360 ?
Unique (%)63.9%

Sample

1st row인천광역시 서구 연희동 738-1 1층
2nd row인천광역시 서구 신현동 185-19
3rd row인천광역시 서구 석남동 518-2
4th row인천광역시 서구 가좌동 143-93
5th row인천광역시 서구 가좌동 30-48 가좌프라자쇼핑(1층 112-3호)
ValueCountFrequency (%)
인천광역시 9960
20.1%
서구 9959
20.1%
석남동 1470
 
3.0%
가좌동 1390
 
2.8%
청라동 1217
 
2.5%
1층 1074
 
2.2%
가정동 1036
 
2.1%
심곡동 855
 
1.7%
마전동 817
 
1.6%
신현동 459
 
0.9%
Other values (6471) 21359
43.1%
2024-01-29T00:24:44.398152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48454
19.7%
1 14033
 
5.7%
동 10755
 
4.4%
구 10439
 
4.2%
서 10261
 
4.2%
시 10113
 
4.1%
인 10100
 
4.1%
천 10060
 
4.1%
광 10002
 
4.1%
역 9975
 
4.1%
Other values (446) 101679
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 129916
52.8%
Decimal Number 55891
22.7%
Space Separator 48454
 
19.7%
Dash Punctuation 8606
 
3.5%
Uppercase Letter 796
 
0.3%
Other Punctuation 743
 
0.3%
Open Punctuation 676
 
0.3%
Close Punctuation 676
 
0.3%
Math Symbol 55
 
< 0.1%
Lowercase Letter 53
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10755
 
8.3%
구 10439
 
8.0%
서 10261
 
7.9%
시 10113
 
7.8%
인 10100
 
7.8%
천 10060
 
7.7%
광 10002
 
7.7%
역 9975
 
7.7%
호 3236
 
2.5%
가 3126
 
2.4%
Other values (388) 41849
32.2%
Uppercase Letter
ValueCountFrequency (%)
B 274
34.4%
A 207
26.0%
C 40
 
5.0%
S 32
 
4.0%
K 30
 
3.8%
M 29
 
3.6%
L 26
 
3.3%
E 24
 
3.0%
D 23
 
2.9%
T 14
 
1.8%
Other values (14) 97
 
12.2%
Lowercase Letter
ValueCountFrequency (%)
e 22
41.5%
s 9
17.0%
a 5
 
9.4%
d 4
 
7.5%
c 3
 
5.7%
y 2
 
3.8%
r 2
 
3.8%
i 2
 
3.8%
k 2
 
3.8%
v 1
 
1.9%
Decimal Number
ValueCountFrequency (%)
1 14033
25.1%
2 7083
12.7%
0 6291
11.3%
5 5132
 
9.2%
3 4909
 
8.8%
4 4844
 
8.7%
6 3964
 
7.1%
7 3416
 
6.1%
8 3189
 
5.7%
9 3030
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 702
94.5%
. 20
 
2.7%
& 7
 
0.9%
* 7
 
0.9%
@ 5
 
0.7%
' 2
 
0.3%
Space Separator
ValueCountFrequency (%)
48454
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8606
100.0%
Open Punctuation
ValueCountFrequency (%)
( 676
100.0%
Close Punctuation
ValueCountFrequency (%)
) 676
100.0%
Math Symbol
ValueCountFrequency (%)
~ 55
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 129916
52.8%
Common 115103
46.8%
Latin 852
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10755
 
8.3%
구 10439
 
8.0%
서 10261
 
7.9%
시 10113
 
7.8%
인 10100
 
7.8%
천 10060
 
7.7%
광 10002
 
7.7%
역 9975
 
7.7%
호 3236
 
2.5%
가 3126
 
2.4%
Other values (388) 41849
32.2%
Latin
ValueCountFrequency (%)
B 274
32.2%
A 207
24.3%
C 40
 
4.7%
S 32
 
3.8%
K 30
 
3.5%
M 29
 
3.4%
L 26
 
3.1%
E 24
 
2.8%
D 23
 
2.7%
e 22
 
2.6%
Other values (26) 145
17.0%
Common
ValueCountFrequency (%)
48454
42.1%
1 14033
 
12.2%
- 8606
 
7.5%
2 7083
 
6.2%
0 6291
 
5.5%
5 5132
 
4.5%
3 4909
 
4.3%
4 4844
 
4.2%
6 3964
 
3.4%
7 3416
 
3.0%
Other values (12) 8371
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 129887
52.8%
ASCII 115950
47.2%
Compat Jamo 29
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK Compat 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48454
41.8%
1 14033
 
12.1%
- 8606
 
7.4%
2 7083
 
6.1%
0 6291
 
5.4%
5 5132
 
4.4%
3 4909
 
4.2%
4 4844
 
4.2%
6 3964
 
3.4%
7 3416
 
2.9%
Other values (46) 9218
 
7.9%
Hangul
ValueCountFrequency (%)
동 10755
 
8.3%
구 10439
 
8.0%
서 10261
 
7.9%
시 10113
 
7.8%
인 10100
 
7.8%
천 10060
 
7.7%
광 10002
 
7.7%
역 9975
 
7.7%
호 3236
 
2.5%
가 3126
 
2.4%
Other values (387) 41820
32.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 29
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%

인허가일자
Date

Distinct5237
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1902-01-30 00:00:00
Maximum2023-06-07 00:00:00
2024-01-29T00:24:44.509704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:24:44.616091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

폐업일자
Date

Distinct4164
Distinct (%)41.7%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
Minimum2001-02-01 00:00:00
Maximum2023-07-31 00:00:00
2024-01-29T00:24:44.722117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:24:44.831340image/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

2024-01-29T00:24:44.959040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:24:45.039568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-01 10000
100.0%

Missing values

2024-01-29T00:24:42.243093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:24:42.336659image/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.
2024-01-29T00:24:42.421808image/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
6092일반음식점번지없는주막인천광역시 서구 연희로 38, 1층 (연희동)인천광역시 서구 연희동 738-1 1층2011-08-252019-04-302023-08-01
1001일반음식점금자매포장마차<NA>인천광역시 서구 신현동 185-192004-01-022005-06-032023-08-01
1296일반음식점퀸<NA>인천광역시 서구 석남동 518-22002-08-162006-03-132023-08-01
1488일반음식점다다식당<NA>인천광역시 서구 가좌동 143-932004-07-012006-11-102023-08-01
6882일반음식점피제이피자인천광역시 서구 원적로96번길 26 (가좌동,가좌프라자쇼핑(1층 112-3호))인천광역시 서구 가좌동 30-48 가좌프라자쇼핑(1층 112-3호)2011-09-202021-04-202023-08-01
4907일반음식점압구정봉구비어청라점인천광역시 서구 청라라임로 85, A동 108호 (연희동, 린스트라우스상가)인천광역시 서구 청라동 160-1 린스트라우스 상가 A동 108호2013-12-032016-04-082023-08-01
747일반음식점호남식당<NA>인천광역시 서구 심곡동 254-71996-05-102004-11-182023-08-01
6000일반음식점보스떡볶이 검단점인천광역시 서구 완정로 35 (마전동, 대운프라자 105호)인천광역시 서구 마전동 1021-5 대운프라자 105호2008-04-242018-11-122023-08-01
1347일반음식점미리내<NA>인천광역시 서구 가좌동 30-832004-08-032006-05-152023-08-01
833일반음식점백두분식<NA>인천광역시 서구 불로동 324-91996-01-272004-09-212023-08-01
업종명업소명소재지(도로명)소재지(지번)인허가일자폐업일자데이터기준일자
5561일반음식점킹콩와플 검단점인천광역시 서구 검단로487번길 6, 103호 (마전동)인천광역시 서구 마전동 933-3 103호2014-11-262017-04-182023-08-01
4535일반음식점돼지네식당<NA>인천광역시 서구 가정동 533-11994-06-202015-04-092023-08-01
7088일반음식점한끼한죽인천광역시 서구 담지로86번길 5-21, 1층일부 (청라동)인천광역시 서구 청라동 133-72019-11-182021-10-222023-08-01
6548일반음식점이가네황소곱창인천광역시 서구 율도로 45 (신현동)인천광역시 서구 신현동 140-922010-01-142020-08-192023-08-01
6859일반음식점쏘생크인천광역시 서구 율도로 31 (신현동)인천광역시 서구 신현동 151-262002-08-122021-04-022023-08-01
545일반음식점뚝심이네<NA>인천광역시 서구 신현동 80-22000-01-192004-03-292023-08-01
3453일반음식점대관령<NA>인천광역시 서구 마전동 0 검단1지구38블럭1롯트 경일빌딩1층2007-09-042011-05-062023-08-01
8411휴게음식점토마토 아저씨인천광역시 서구 완정로 61 (마전동, 2층)인천광역시 서구 마전동 1028-7 2층2013-09-232014-09-242023-08-01
2985일반음식점전주한식분식<NA>인천광역시 서구 연희동 712-172005-07-262010-02-232023-08-01
9148휴게음식점씨유청라중흥점인천광역시 서구 청라라임로122번길 2, 1층 편의점 내 일부호 (청라동)인천광역시 서구 청라동 117-23 1층 편의점 내 일부2019-11-212021-07-272023-08-01

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
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