Overview

Dataset statistics

Number of variables16
Number of observations457
Missing cells428
Missing cells (%)5.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory60.8 KiB
Average record size in memory136.3 B

Variable types

Categorical5
Numeric6
Text5

Dataset

Description시군구코드,지정년도,지정번호,신청일자,지정일자,취소일자,불가일자,업소명,소재지도로명,소재지지번,허가(신고)번호,업태명,주된음식,영업장면적(㎡),행정동명,급수시설구분
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-11468/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정동명 is highly overall correlated with 불가일자 and 1 other fieldsHigh correlation
불가일자 is highly overall correlated with 신청일자 and 3 other fieldsHigh correlation
업태명 is highly overall correlated with 불가일자 and 1 other fieldsHigh correlation
급수시설구분 is highly overall correlated with 지정년도 and 7 other fieldsHigh correlation
지정년도 is highly overall correlated with 신청일자 and 2 other fieldsHigh correlation
지정번호 is highly overall correlated with 급수시설구분High correlation
신청일자 is highly overall correlated with 지정년도 and 3 other fieldsHigh correlation
지정일자 is highly overall correlated with 지정년도 and 2 other fieldsHigh correlation
취소일자 is highly overall correlated with 급수시설구분High correlation
영업장면적(㎡) is highly overall correlated with 불가일자 and 1 other fieldsHigh correlation
불가일자 is highly imbalanced (94.3%)Imbalance
업태명 is highly imbalanced (54.6%)Imbalance
지정년도 has 9 (2.0%) missing valuesMissing
지정번호 has 9 (2.0%) missing valuesMissing
지정일자 has 9 (2.0%) missing valuesMissing
취소일자 has 333 (72.9%) missing valuesMissing
주된음식 has 68 (14.9%) missing valuesMissing

Reproduction

Analysis started2024-05-11 06:41:36.713628
Analysis finished2024-05-11 06:41:50.636335
Duration13.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
3230000
457 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 457
100.0%

Length

2024-05-11T15:41:50.833768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:41:51.005179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 457
100.0%

지정년도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct17
Distinct (%)3.8%
Missing9
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean2013.0357
Minimum2007
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-05-11T15:41:51.185097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2007
Q12007
median2012
Q32018
95-th percentile2022
Maximum2023
Range16
Interquartile range (IQR)11

Descriptive statistics

Standard deviation5.6831767
Coefficient of variation (CV)0.0028231872
Kurtosis-1.4984982
Mean2013.0357
Median Absolute Deviation (MAD)5
Skewness0.28190425
Sum901840
Variance32.298498
MonotonicityNot monotonic
2024-05-11T15:41:51.436175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2007 126
27.6%
2008 62
13.6%
2018 47
 
10.3%
2016 31
 
6.8%
2017 27
 
5.9%
2022 22
 
4.8%
2023 20
 
4.4%
2019 20
 
4.4%
2020 18
 
3.9%
2010 13
 
2.8%
Other values (7) 62
13.6%
ValueCountFrequency (%)
2007 126
27.6%
2008 62
13.6%
2009 11
 
2.4%
2010 13
 
2.8%
2011 9
 
2.0%
2012 9
 
2.0%
2013 6
 
1.3%
2014 8
 
1.8%
2015 8
 
1.8%
2016 31
 
6.8%
ValueCountFrequency (%)
2023 20
4.4%
2022 22
4.8%
2021 11
 
2.4%
2020 18
 
3.9%
2019 20
4.4%
2018 47
10.3%
2017 27
5.9%
2016 31
6.8%
2015 8
 
1.8%
2014 8
 
1.8%

지정번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct240
Distinct (%)53.6%
Missing9
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean149.62723
Minimum1
Maximum355
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-05-11T15:41:51.757515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q134.75
median141.5
Q3268
95-th percentile317.65
Maximum355
Range354
Interquartile range (IQR)233.25

Descriptive statistics

Standard deviation117.49348
Coefficient of variation (CV)0.78524128
Kurtosis-1.6279333
Mean149.62723
Median Absolute Deviation (MAD)116.5
Skewness0.13312971
Sum67033
Variance13804.718
MonotonicityNot monotonic
2024-05-11T15:41:52.009339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 6
 
1.3%
64 6
 
1.3%
5 6
 
1.3%
1 6
 
1.3%
20 5
 
1.1%
15 5
 
1.1%
52 5
 
1.1%
8 5
 
1.1%
3 5
 
1.1%
2 5
 
1.1%
Other values (230) 394
86.2%
(Missing) 9
 
2.0%
ValueCountFrequency (%)
1 6
1.3%
2 5
1.1%
3 5
1.1%
4 3
0.7%
5 6
1.3%
6 6
1.3%
7 4
0.9%
8 5
1.1%
9 3
0.7%
10 2
 
0.4%
ValueCountFrequency (%)
355 1
0.2%
354 1
0.2%
352 1
0.2%
348 1
0.2%
346 1
0.2%
345 1
0.2%
344 1
0.2%
342 1
0.2%
341 1
0.2%
340 1
0.2%

신청일자
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20131499
Minimum20070928
Maximum20230915
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-05-11T15:41:52.260769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070928
5-th percentile20071016
Q120071019
median20121114
Q320181015
95-th percentile20221207
Maximum20230915
Range159987
Interquartile range (IQR)109996

Descriptive statistics

Standard deviation57129.025
Coefficient of variation (CV)0.0028377929
Kurtosis-1.5214732
Mean20131499
Median Absolute Deviation (MAD)50098
Skewness0.26829886
Sum9.2000952 × 109
Variance3.2637255 × 109
MonotonicityDecreasing
2024-05-11T15:41:52.545671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
20071016 101
22.1%
20081103 62
13.6%
20181015 51
11.2%
20161031 31
 
6.8%
20171010 27
 
5.9%
20230915 20
 
4.4%
20191018 20
 
4.4%
20201109 18
 
3.9%
20071019 14
 
3.1%
20100728 10
 
2.2%
Other values (24) 103
22.5%
ValueCountFrequency (%)
20070928 9
 
2.0%
20071016 101
22.1%
20071018 1
 
0.2%
20071019 14
 
3.1%
20071022 7
 
1.5%
20081103 62
13.6%
20081110 1
 
0.2%
20091013 7
 
1.5%
20091102 1
 
0.2%
20091109 1
 
0.2%
ValueCountFrequency (%)
20230915 20
4.4%
20221207 9
2.0%
20221202 2
 
0.4%
20221130 3
 
0.7%
20221129 8
 
1.8%
20211201 3
 
0.7%
20211130 1
 
0.2%
20211129 1
 
0.2%
20211126 2
 
0.4%
20211118 6
 
1.3%

지정일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20
Distinct (%)4.5%
Missing9
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean20131469
Minimum20071016
Maximum20231107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-05-11T15:41:52.787736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20071016
5-th percentile20071019
Q120071019
median20121217
Q320181112
95-th percentile20221226
Maximum20231107
Range160091
Interquartile range (IQR)110093

Descriptive statistics

Standard deviation56891.076
Coefficient of variation (CV)0.0028259775
Kurtosis-1.4993854
Mean20131469
Median Absolute Deviation (MAD)50198
Skewness0.28117168
Sum9.0188979 × 109
Variance3.2365946 × 109
MonotonicityNot monotonic
2024-05-11T15:41:53.039680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20071019 124
27.1%
20081103 62
13.6%
20181112 47
 
10.3%
20161130 31
 
6.8%
20171214 27
 
5.9%
20221226 22
 
4.8%
20231107 20
 
4.4%
20191211 20
 
4.4%
20201222 18
 
3.9%
20100910 13
 
2.8%
Other values (10) 64
14.0%
ValueCountFrequency (%)
20071016 1
 
0.2%
20071019 124
27.1%
20071219 1
 
0.2%
20081103 62
13.6%
20091113 10
 
2.2%
20091228 1
 
0.2%
20100910 13
 
2.8%
20111116 9
 
2.0%
20121217 9
 
2.0%
20131223 6
 
1.3%
ValueCountFrequency (%)
20231107 20
4.4%
20221226 22
4.8%
20211221 11
 
2.4%
20201222 18
 
3.9%
20191211 20
4.4%
20181112 47
10.3%
20171214 27
5.9%
20161130 31
6.8%
20151228 8
 
1.8%
20141219 8
 
1.8%

취소일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct31
Distinct (%)25.0%
Missing333
Missing (%)72.9%
Infinite0
Infinite (%)0.0%
Mean20152024
Minimum20071019
Maximum20240510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-05-11T15:41:53.296375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20071019
5-th percentile20090570
Q120111116
median20121217
Q320211221
95-th percentile20231107
Maximum20240510
Range169491
Interquartile range (IQR)100105

Descriptive statistics

Standard deviation52687.265
Coefficient of variation (CV)0.00261449
Kurtosis-1.4574708
Mean20152024
Median Absolute Deviation (MAD)30542.5
Skewness0.33612014
Sum2.4988509 × 109
Variance2.7759479 × 109
MonotonicityNot monotonic
2024-05-11T15:41:53.535471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20111116 25
 
5.5%
20121217 18
 
3.9%
20211221 14
 
3.1%
20231107 12
 
2.6%
20181112 11
 
2.4%
20091113 10
 
2.2%
20171214 6
 
1.3%
20100120 2
 
0.4%
20240510 2
 
0.4%
20090824 2
 
0.4%
Other values (21) 22
 
4.8%
(Missing) 333
72.9%
ValueCountFrequency (%)
20071019 1
 
0.2%
20080704 1
 
0.2%
20081102 1
 
0.2%
20090428 1
 
0.2%
20090506 1
 
0.2%
20090521 1
 
0.2%
20090525 1
 
0.2%
20090824 2
 
0.4%
20091113 10
2.2%
20091231 1
 
0.2%
ValueCountFrequency (%)
20240510 2
 
0.4%
20240424 1
 
0.2%
20240409 1
 
0.2%
20231107 12
2.6%
20230927 2
 
0.4%
20221226 1
 
0.2%
20211221 14
3.1%
20211028 1
 
0.2%
20201222 1
 
0.2%
20200130 1
 
0.2%

불가일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
454 
20181101
 
3

Length

Max length8
Median length4
Mean length4.0262582
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 454
99.3%
20181101 3
 
0.7%

Length

2024-05-11T15:41:53.841181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:41:54.056148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 454
99.3%
20181101 3
 
0.7%

업소명
Text

Distinct379
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T15:41:54.363773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length7.0678337
Min length2

Characters and Unicode

Total characters3230
Distinct characters449
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

Unique317 ?
Unique (%)69.4%

Sample

1st row크래버대게나라 잠실점
2nd row풍납주먹고기
3rd row청진동해장국
4th row나고야
5th row진진 가마솥 설렁탕
ValueCountFrequency (%)
방이점 16
 
2.3%
잠실점 10
 
1.5%
주식회사 7
 
1.0%
가든파이브점 6
 
0.9%
롯데월드몰 5
 
0.7%
명륜진사갈비 5
 
0.7%
발아메밀막국수 4
 
0.6%
문정점 4
 
0.6%
현대시티몰 4
 
0.6%
마포식당 4
 
0.6%
Other values (503) 623
90.6%
2024-05-11T15:41:54.947335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
231
 
7.2%
점 101
 
3.1%
이 71
 
2.2%
주 50
 
1.5%
가 49
 
1.5%
( 41
 
1.3%
) 41
 
1.3%
한 41
 
1.3%
식 39
 
1.2%
방 34
 
1.1%
Other values (439) 2532
78.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2825
87.5%
Space Separator 231
 
7.2%
Open Punctuation 41
 
1.3%
Close Punctuation 41
 
1.3%
Uppercase Letter 32
 
1.0%
Lowercase Letter 28
 
0.9%
Decimal Number 19
 
0.6%
Other Punctuation 13
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 101
 
3.6%
이 71
 
2.5%
주 50
 
1.8%
가 49
 
1.7%
한 41
 
1.5%
식 39
 
1.4%
방 34
 
1.2%
리 34
 
1.2%
사 31
 
1.1%
정 30
 
1.1%
Other values (391) 2345
83.0%
Uppercase Letter
ValueCountFrequency (%)
L 5
15.6%
I 4
12.5%
U 2
 
6.2%
M 2
 
6.2%
H 2
 
6.2%
T 2
 
6.2%
G 2
 
6.2%
F 2
 
6.2%
C 2
 
6.2%
B 2
 
6.2%
Other values (7) 7
21.9%
Lowercase Letter
ValueCountFrequency (%)
e 6
21.4%
u 3
10.7%
i 3
10.7%
f 2
 
7.1%
o 2
 
7.1%
r 2
 
7.1%
m 1
 
3.6%
t 1
 
3.6%
l 1
 
3.6%
y 1
 
3.6%
Other values (6) 6
21.4%
Decimal Number
ValueCountFrequency (%)
2 4
21.1%
1 4
21.1%
4 3
15.8%
9 2
10.5%
0 2
10.5%
6 1
 
5.3%
7 1
 
5.3%
3 1
 
5.3%
5 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 8
61.5%
& 3
 
23.1%
, 2
 
15.4%
Space Separator
ValueCountFrequency (%)
231
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2825
87.5%
Common 345
 
10.7%
Latin 60
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 101
 
3.6%
이 71
 
2.5%
주 50
 
1.8%
가 49
 
1.7%
한 41
 
1.5%
식 39
 
1.4%
방 34
 
1.2%
리 34
 
1.2%
사 31
 
1.1%
정 30
 
1.1%
Other values (391) 2345
83.0%
Latin
ValueCountFrequency (%)
e 6
 
10.0%
L 5
 
8.3%
I 4
 
6.7%
u 3
 
5.0%
i 3
 
5.0%
U 2
 
3.3%
M 2
 
3.3%
H 2
 
3.3%
T 2
 
3.3%
G 2
 
3.3%
Other values (23) 29
48.3%
Common
ValueCountFrequency (%)
231
67.0%
( 41
 
11.9%
) 41
 
11.9%
. 8
 
2.3%
2 4
 
1.2%
1 4
 
1.2%
4 3
 
0.9%
& 3
 
0.9%
, 2
 
0.6%
9 2
 
0.6%
Other values (5) 6
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2825
87.5%
ASCII 405
 
12.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
231
57.0%
( 41
 
10.1%
) 41
 
10.1%
. 8
 
2.0%
e 6
 
1.5%
L 5
 
1.2%
2 4
 
1.0%
I 4
 
1.0%
1 4
 
1.0%
4 3
 
0.7%
Other values (38) 58
 
14.3%
Hangul
ValueCountFrequency (%)
점 101
 
3.6%
이 71
 
2.5%
주 50
 
1.8%
가 49
 
1.7%
한 41
 
1.5%
식 39
 
1.4%
방 34
 
1.2%
리 34
 
1.2%
사 31
 
1.1%
정 30
 
1.1%
Other values (391) 2345
83.0%

소재지도로명
Text

Distinct369
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T15:41:55.406311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length51
Mean length33.36105
Min length23

Characters and Unicode

Total characters15246
Distinct characters222
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

Unique300 ?
Unique (%)65.6%

Sample

1st row서울특별시 송파구 위례성대로 92, (방이동,1층)
2nd row서울특별시 송파구 토성로15길 3-3, 경원빌딩 1층 101호, 102호 (풍납동)
3rd row서울특별시 송파구 풍성로 77, C동 지상1층 (풍납동)
4th row서울특별시 송파구 중대로25길 10, (오금동)
5th row서울특별시 송파구 거마로 12, (거여동)
ValueCountFrequency (%)
서울특별시 457
 
15.8%
송파구 457
 
15.8%
지상1층 106
 
3.7%
1층 92
 
3.2%
방이동 89
 
3.1%
잠실동 62
 
2.1%
문정동 52
 
1.8%
가락동 46
 
1.6%
올림픽로 45
 
1.6%
석촌동 36
 
1.2%
Other values (529) 1457
50.3%
2024-05-11T15:41:56.133889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2445
 
16.0%
1 745
 
4.9%
, 651
 
4.3%
파 562
 
3.7%
송 549
 
3.6%
동 515
 
3.4%
시 475
 
3.1%
( 462
 
3.0%
) 462
 
3.0%
로 461
 
3.0%
Other values (212) 7919
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8837
58.0%
Space Separator 2445
 
16.0%
Decimal Number 2257
 
14.8%
Other Punctuation 654
 
4.3%
Open Punctuation 462
 
3.0%
Close Punctuation 462
 
3.0%
Dash Punctuation 68
 
0.4%
Uppercase Letter 51
 
0.3%
Math Symbol 6
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 562
 
6.4%
송 549
 
6.2%
동 515
 
5.8%
시 475
 
5.4%
로 461
 
5.2%
서 460
 
5.2%
울 460
 
5.2%
구 459
 
5.2%
별 457
 
5.2%
특 457
 
5.2%
Other values (177) 3982
45.1%
Uppercase Letter
ValueCountFrequency (%)
A 18
35.3%
B 13
25.5%
G 5
 
9.8%
T 2
 
3.9%
E 2
 
3.9%
D 2
 
3.9%
C 2
 
3.9%
F 2
 
3.9%
N 1
 
2.0%
S 1
 
2.0%
Other values (3) 3
 
5.9%
Decimal Number
ValueCountFrequency (%)
1 745
33.0%
2 366
16.2%
3 221
 
9.8%
0 214
 
9.5%
4 144
 
6.4%
5 139
 
6.2%
6 129
 
5.7%
9 102
 
4.5%
8 101
 
4.5%
7 96
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
u 1
25.0%
i 1
25.0%
t 1
25.0%
e 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 651
99.5%
& 2
 
0.3%
. 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2445
100.0%
Open Punctuation
ValueCountFrequency (%)
( 462
100.0%
Close Punctuation
ValueCountFrequency (%)
) 462
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8837
58.0%
Common 6354
41.7%
Latin 55
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 562
 
6.4%
송 549
 
6.2%
동 515
 
5.8%
시 475
 
5.4%
로 461
 
5.2%
서 460
 
5.2%
울 460
 
5.2%
구 459
 
5.2%
별 457
 
5.2%
특 457
 
5.2%
Other values (177) 3982
45.1%
Common
ValueCountFrequency (%)
2445
38.5%
1 745
 
11.7%
, 651
 
10.2%
( 462
 
7.3%
) 462
 
7.3%
2 366
 
5.8%
3 221
 
3.5%
0 214
 
3.4%
4 144
 
2.3%
5 139
 
2.2%
Other values (8) 505
 
7.9%
Latin
ValueCountFrequency (%)
A 18
32.7%
B 13
23.6%
G 5
 
9.1%
T 2
 
3.6%
E 2
 
3.6%
D 2
 
3.6%
C 2
 
3.6%
F 2
 
3.6%
N 1
 
1.8%
S 1
 
1.8%
Other values (7) 7
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8837
58.0%
ASCII 6409
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2445
38.1%
1 745
 
11.6%
, 651
 
10.2%
( 462
 
7.2%
) 462
 
7.2%
2 366
 
5.7%
3 221
 
3.4%
0 214
 
3.3%
4 144
 
2.2%
5 139
 
2.2%
Other values (25) 560
 
8.7%
Hangul
ValueCountFrequency (%)
파 562
 
6.4%
송 549
 
6.2%
동 515
 
5.8%
시 475
 
5.4%
로 461
 
5.2%
서 460
 
5.2%
울 460
 
5.2%
구 459
 
5.2%
별 457
 
5.2%
특 457
 
5.2%
Other values (177) 3982
45.1%

소재지지번
Text

Distinct341
Distinct (%)74.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T15:41:56.622085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length45
Mean length28.076586
Min length20

Characters and Unicode

Total characters12831
Distinct characters202
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

Unique263 ?
Unique (%)57.5%

Sample

1st row서울특별시 송파구 방이동 165번지 4호 1층
2nd row서울특별시 송파구 풍납동 405번지 2호 경원빌딩
3rd row서울특별시 송파구 풍납동 497번지 C 지상1층
4th row서울특별시 송파구 오금동 48번지 11호
5th row서울특별시 송파구 거여동 42번지 13호
ValueCountFrequency (%)
서울특별시 457
17.8%
송파구 457
17.8%
지상1층 106
 
4.1%
방이동 101
 
3.9%
잠실동 64
 
2.5%
문정동 56
 
2.2%
1호 53
 
2.1%
가락동 53
 
2.1%
3호 38
 
1.5%
석촌동 37
 
1.4%
Other values (340) 1141
44.5%
2024-05-11T15:41:57.423916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3183
24.8%
지 617
 
4.8%
1 557
 
4.3%
파 512
 
4.0%
송 503
 
3.9%
동 473
 
3.7%
시 468
 
3.6%
서 460
 
3.6%
울 458
 
3.6%
별 457
 
3.6%
Other values (192) 5143
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7601
59.2%
Space Separator 3183
24.8%
Decimal Number 1946
 
15.2%
Other Punctuation 47
 
0.4%
Uppercase Letter 17
 
0.1%
Dash Punctuation 13
 
0.1%
Open Punctuation 8
 
0.1%
Close Punctuation 8
 
0.1%
Math Symbol 4
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 617
 
8.1%
파 512
 
6.7%
송 503
 
6.6%
동 473
 
6.2%
시 468
 
6.2%
서 460
 
6.1%
울 458
 
6.0%
별 457
 
6.0%
번 457
 
6.0%
구 457
 
6.0%
Other values (160) 2739
36.0%
Decimal Number
ValueCountFrequency (%)
1 557
28.6%
2 264
13.6%
4 164
 
8.4%
3 162
 
8.3%
0 146
 
7.5%
5 145
 
7.5%
6 143
 
7.3%
7 133
 
6.8%
8 122
 
6.3%
9 110
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
B 4
23.5%
A 3
17.6%
F 2
11.8%
C 2
11.8%
N 1
 
5.9%
O 1
 
5.9%
P 1
 
5.9%
S 1
 
5.9%
T 1
 
5.9%
K 1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
u 1
25.0%
i 1
25.0%
t 1
25.0%
e 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 44
93.6%
& 2
 
4.3%
. 1
 
2.1%
Space Separator
ValueCountFrequency (%)
3183
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7601
59.2%
Common 5209
40.6%
Latin 21
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 617
 
8.1%
파 512
 
6.7%
송 503
 
6.6%
동 473
 
6.2%
시 468
 
6.2%
서 460
 
6.1%
울 458
 
6.0%
별 457
 
6.0%
번 457
 
6.0%
구 457
 
6.0%
Other values (160) 2739
36.0%
Common
ValueCountFrequency (%)
3183
61.1%
1 557
 
10.7%
2 264
 
5.1%
4 164
 
3.1%
3 162
 
3.1%
0 146
 
2.8%
5 145
 
2.8%
6 143
 
2.7%
7 133
 
2.6%
8 122
 
2.3%
Other values (8) 190
 
3.6%
Latin
ValueCountFrequency (%)
B 4
19.0%
A 3
14.3%
F 2
9.5%
C 2
9.5%
N 1
 
4.8%
u 1
 
4.8%
i 1
 
4.8%
t 1
 
4.8%
e 1
 
4.8%
O 1
 
4.8%
Other values (4) 4
19.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7601
59.2%
ASCII 5230
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3183
60.9%
1 557
 
10.7%
2 264
 
5.0%
4 164
 
3.1%
3 162
 
3.1%
0 146
 
2.8%
5 145
 
2.8%
6 143
 
2.7%
7 133
 
2.5%
8 122
 
2.3%
Other values (22) 211
 
4.0%
Hangul
ValueCountFrequency (%)
지 617
 
8.1%
파 512
 
6.7%
송 503
 
6.6%
동 473
 
6.2%
시 468
 
6.2%
서 460
 
6.1%
울 458
 
6.0%
별 457
 
6.0%
번 457
 
6.0%
구 457
 
6.0%
Other values (160) 2739
36.0%

허가(신고)번호
Text

Distinct379
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T15:41:57.785661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10054
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique317 ?
Unique (%)69.4%

Sample

1st row3230000-101-2005-00531
2nd row3230000-101-2004-00621
3rd row3230000-101-2010-00283
4th row3230000-101-2001-16908
5th row3230000-101-1993-11843
ValueCountFrequency (%)
3230000-101-1997-07823 4
 
0.9%
3230000-101-1995-08618 4
 
0.9%
3230000-101-2004-00659 3
 
0.7%
3230000-101-1987-14236 3
 
0.7%
3230000-101-2005-00274 3
 
0.7%
3230000-101-2003-00599 3
 
0.7%
3230000-101-2007-00042 3
 
0.7%
3230000-101-1996-11065 3
 
0.7%
3230000-101-2005-00197 3
 
0.7%
3230000-101-1999-00773 3
 
0.7%
Other values (369) 425
93.0%
2024-05-11T15:41:58.221874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3614
35.9%
1 1483
14.8%
- 1371
 
13.6%
3 1136
 
11.3%
2 986
 
9.8%
9 387
 
3.8%
7 255
 
2.5%
8 224
 
2.2%
5 205
 
2.0%
4 199
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8683
86.4%
Dash Punctuation 1371
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3614
41.6%
1 1483
17.1%
3 1136
 
13.1%
2 986
 
11.4%
9 387
 
4.5%
7 255
 
2.9%
8 224
 
2.6%
5 205
 
2.4%
4 199
 
2.3%
6 194
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 1371
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10054
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3614
35.9%
1 1483
14.8%
- 1371
 
13.6%
3 1136
 
11.3%
2 986
 
9.8%
9 387
 
3.8%
7 255
 
2.5%
8 224
 
2.2%
5 205
 
2.0%
4 199
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10054
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3614
35.9%
1 1483
14.8%
- 1371
 
13.6%
3 1136
 
11.3%
2 986
 
9.8%
9 387
 
3.8%
7 255
 
2.5%
8 224
 
2.2%
5 205
 
2.0%
4 199
 
2.0%

업태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct15
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
한식
316 
일식
36 
기타
36 
중국식
 
21
경양식
 
20
Other values (10)
 
28

Length

Max length15
Median length2
Mean length2.2275711
Min length2

Unique

Unique4 ?
Unique (%)0.9%

Sample

1st row한식
2nd row한식
3rd row한식
4th row일식
5th row분식

Common Values

ValueCountFrequency (%)
한식 316
69.1%
일식 36
 
7.9%
기타 36
 
7.9%
중국식 21
 
4.6%
경양식 20
 
4.4%
분식 8
 
1.8%
호프/통닭 5
 
1.1%
뷔페식 4
 
0.9%
회집 3
 
0.7%
외국음식전문점(인도,태국등) 2
 
0.4%
Other values (5) 6
 
1.3%

Length

2024-05-11T15:41:58.399469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 316
69.1%
일식 36
 
7.9%
기타 36
 
7.9%
중국식 21
 
4.6%
경양식 20
 
4.4%
분식 8
 
1.8%
호프/통닭 5
 
1.1%
뷔페식 4
 
0.9%
회집 3
 
0.7%
외국음식전문점(인도,태국등 2
 
0.4%
Other values (5) 6
 
1.3%

주된음식
Text

MISSING 

Distinct242
Distinct (%)62.2%
Missing68
Missing (%)14.9%
Memory size3.7 KiB
2024-05-11T15:41:58.736888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length4.3496144
Min length1

Characters and Unicode

Total characters1692
Distinct characters194
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique188 ?
Unique (%)48.3%

Sample

1st row대게, 킹크랩
2nd row구이
3rd row해장국
4th row회
5th row설렁탕
ValueCountFrequency (%)
삼겹살 19
 
4.3%
돼지갈비 14
 
3.1%
스테이크 9
 
2.0%
설렁탕 9
 
2.0%
회 9
 
2.0%
추어탕 8
 
1.8%
냉면 8
 
1.8%
고기구이 8
 
1.8%
쌀국수 7
 
1.6%
갈비 6
 
1.3%
Other values (224) 348
78.2%
2024-05-11T15:41:59.272672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 96
 
5.7%
탕 62
 
3.7%
56
 
3.3%
비 48
 
2.8%
이 47
 
2.8%
국 45
 
2.7%
갈 44
 
2.6%
구 43
 
2.5%
수 35
 
2.1%
스 35
 
2.1%
Other values (184) 1181
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1534
90.7%
Other Punctuation 98
 
5.8%
Space Separator 56
 
3.3%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 62
 
4.0%
비 48
 
3.1%
이 47
 
3.1%
국 45
 
2.9%
갈 44
 
2.9%
구 43
 
2.8%
수 35
 
2.3%
스 35
 
2.3%
지 34
 
2.2%
삼 33
 
2.2%
Other values (179) 1108
72.2%
Other Punctuation
ValueCountFrequency (%)
, 96
98.0%
. 2
 
2.0%
Space Separator
ValueCountFrequency (%)
56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1534
90.7%
Common 158
 
9.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 62
 
4.0%
비 48
 
3.1%
이 47
 
3.1%
국 45
 
2.9%
갈 44
 
2.9%
구 43
 
2.8%
수 35
 
2.3%
스 35
 
2.3%
지 34
 
2.2%
삼 33
 
2.2%
Other values (179) 1108
72.2%
Common
ValueCountFrequency (%)
, 96
60.8%
56
35.4%
. 2
 
1.3%
( 2
 
1.3%
) 2
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1534
90.7%
ASCII 158
 
9.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 96
60.8%
56
35.4%
. 2
 
1.3%
( 2
 
1.3%
) 2
 
1.3%
Hangul
ValueCountFrequency (%)
탕 62
 
4.0%
비 48
 
3.1%
이 47
 
3.1%
국 45
 
2.9%
갈 44
 
2.9%
구 43
 
2.8%
수 35
 
2.3%
스 35
 
2.3%
지 34
 
2.2%
삼 33
 
2.2%
Other values (179) 1108
72.2%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION 

Distinct343
Distinct (%)75.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean195.44698
Minimum0
Maximum3261.23
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-05-11T15:41:59.443345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile52.648
Q197.5
median132
Q3202
95-th percentile499.8
Maximum3261.23
Range3261.23
Interquartile range (IQR)104.5

Descriptive statistics

Standard deviation260.2623
Coefficient of variation (CV)1.3316261
Kurtosis68.843441
Mean195.44698
Median Absolute Deviation (MAD)44.64
Skewness7.1741726
Sum89319.27
Variance67736.466
MonotonicityNot monotonic
2024-05-11T15:41:59.708136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 11
 
2.4%
132.0 5
 
1.1%
82.5 5
 
1.1%
115.0 4
 
0.9%
146.02 4
 
0.9%
100.0 4
 
0.9%
120.0 4
 
0.9%
52.8 4
 
0.9%
171.72 4
 
0.9%
102.3 3
 
0.7%
Other values (333) 409
89.5%
ValueCountFrequency (%)
0.0 1
0.2%
20.0 1
0.2%
23.0 1
0.2%
30.0 1
0.2%
32.0 1
0.2%
32.01 1
0.2%
32.39 1
0.2%
33.0 1
0.2%
33.54 2
0.4%
39.8 1
0.2%
ValueCountFrequency (%)
3261.23 1
0.2%
2815.37 1
0.2%
1822.07 1
0.2%
1334.06 2
0.4%
1193.39 1
0.2%
933.9 1
0.2%
902.52 1
0.2%
853.62 1
0.2%
843.25 1
0.2%
806.59 2
0.4%

행정동명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
방이1동
53 
잠실본동
50 
문정1동
48 
방이2동
47 
가락본동
41 
Other values (20)
218 

Length

Max length4
Median length4
Mean length3.8118162
Min length3

Unique

Unique3 ?
Unique (%)0.7%

Sample

1st row방이1동
2nd row풍납1동
3rd row풍납1동
4th row오금동
5th row거여1동

Common Values

ValueCountFrequency (%)
방이1동 53
11.6%
잠실본동 50
10.9%
문정1동 48
10.5%
방이2동 47
10.3%
가락본동 41
9.0%
석촌동 37
8.1%
송파1동 31
 
6.8%
오금동 25
 
5.5%
삼전동 22
 
4.8%
잠실6동 15
 
3.3%
Other values (15) 88
19.3%

Length

2024-05-11T15:41:59.926975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
방이1동 53
11.6%
잠실본동 50
10.9%
문정1동 48
10.5%
방이2동 47
10.3%
가락본동 41
9.0%
석촌동 37
8.1%
송파1동 31
 
6.8%
오금동 25
 
5.5%
삼전동 22
 
4.8%
잠실6동 15
 
3.3%
Other values (15) 88
19.3%

급수시설구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
310 
상수도전용
147 

Length

Max length5
Median length4
Mean length4.321663
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row상수도전용

Common Values

ValueCountFrequency (%)
<NA> 310
67.8%
상수도전용 147
32.2%

Length

2024-05-11T15:42:00.092527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:00.224247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 310
67.8%
상수도전용 147
32.2%

Interactions

2024-05-11T15:41:46.292349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:38.560076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:40.002619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:41.565285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:43.020889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:44.916612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:46.572521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:38.762248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:40.197119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:41.777583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:43.348892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:45.174807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:46.832433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:38.952386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:40.478811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:42.031404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:43.799720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:45.423791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:47.611281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:39.159604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:40.840262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:42.308224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:44.083650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:45.681445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:47.920808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:39.389544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:41.094435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:42.554240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:44.435888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:45.861498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:48.172822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:39.676701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:41.349319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:42.782810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:44.692438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:41:46.052949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:42:00.322752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정년도지정번호신청일자지정일자취소일자업태명영업장면적(㎡)행정동명
지정년도1.0000.9150.9991.0000.6160.0850.0000.569
지정번호0.9151.0000.8310.8250.2910.0000.0000.638
신청일자0.9990.8311.0001.0000.7130.0000.0000.548
지정일자1.0000.8251.0001.0000.6770.0000.0000.559
취소일자0.6160.2910.7130.6771.0000.4430.0000.614
업태명0.0850.0000.0000.0000.4431.0000.5880.241
영업장면적(㎡)0.0000.0000.0000.0000.0000.5881.0000.581
행정동명0.5690.6380.5480.5590.6140.2410.5811.000
2024-05-11T15:42:00.803173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동명불가일자업태명급수시설구분
행정동명1.0001.0000.0731.000
불가일자1.0001.0001.000NaN
업태명0.0731.0001.0001.000
급수시설구분1.000NaN1.0001.000
2024-05-11T15:42:00.972856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정년도지정번호신청일자지정일자취소일자영업장면적(㎡)불가일자업태명행정동명급수시설구분
지정년도1.000-0.2370.9920.9990.459-0.1100.0000.0000.2301.000
지정번호-0.2371.000-0.206-0.2340.0960.1630.0000.0000.2771.000
신청일자0.992-0.2061.0000.9920.448-0.1131.0000.0000.2231.000
지정일자0.999-0.2340.9921.0000.466-0.1100.0000.0000.2281.000
취소일자0.4590.0960.4480.4661.0000.0790.0000.2170.2581.000
영업장면적(㎡)-0.1100.163-0.113-0.1100.0791.0001.0000.2960.2691.000
불가일자0.0000.0001.0000.0000.0001.0001.0001.0001.0000.000
업태명0.0000.0000.0000.0000.2170.2961.0001.0000.0731.000
행정동명0.2300.2770.2230.2280.2580.2691.0000.0731.0001.000
급수시설구분1.0001.0001.0001.0001.0001.0000.0001.0001.0001.000

Missing values

2024-05-11T15:41:48.712548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:41:49.807178image/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.
2024-05-11T15:41:50.333829image/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

시군구코드지정년도지정번호신청일자지정일자취소일자불가일자업소명소재지도로명소재지지번허가(신고)번호업태명주된음식영업장면적(㎡)행정동명급수시설구분
032300002023222023091520231107<NA><NA>크래버대게나라 잠실점서울특별시 송파구 위례성대로 92, (방이동,1층)서울특별시 송파구 방이동 165번지 4호 1층3230000-101-2005-00531한식대게, 킹크랩307.14방이1동<NA>
132300002023172023091520231107<NA><NA>풍납주먹고기서울특별시 송파구 토성로15길 3-3, 경원빌딩 1층 101호, 102호 (풍납동)서울특별시 송파구 풍납동 405번지 2호 경원빌딩3230000-101-2004-00621한식구이86.0풍납1동<NA>
232300002023182023091520231107<NA><NA>청진동해장국서울특별시 송파구 풍성로 77, C동 지상1층 (풍납동)서울특별시 송파구 풍납동 497번지 C 지상1층3230000-101-2010-00283한식해장국96.0풍납1동<NA>
332300002023102023091520231107<NA><NA>나고야서울특별시 송파구 중대로25길 10, (오금동)서울특별시 송파구 오금동 48번지 11호3230000-101-2001-16908일식회115.0오금동<NA>
432300002023212023091520231107<NA><NA>진진 가마솥 설렁탕서울특별시 송파구 거마로 12, (거여동)서울특별시 송파구 거여동 42번지 13호3230000-101-1993-11843분식설렁탕122.88거여1동상수도전용
53230000202322023091520231107<NA><NA>완도산회 특급포차 가락본점서울특별시 송파구 중대로9길 42, 지상1층 (가락동)서울특별시 송파구 가락동 83번지 10호 지상1층3230000-101-2013-00406한식회92.56가락본동<NA>
63230000202332023091520231107<NA><NA>완도산회 송파 별관서울특별시 송파구 백제고분로 395, 상주황씨대종회빌딩 1층 (송파동)서울특별시 송파구 송파동 20번지 2호 상주황씨대종회빌딩3230000-101-2023-00494한식회128.0송파1동<NA>
732300002023142023091520231107<NA><NA>황규복, 김춘자의 해주냉면서울특별시 송파구 백제고분로7길 8-16, 남광빌딩 1층 102호 (잠실동)서울특별시 송파구 잠실동 195번지 9호 남광빌딩3230000-101-2019-00019한식냉면105.6잠실본동<NA>
83230000202362023091520231107<NA><NA>소풍서울특별시 송파구 마천로 250, 1층 3호 (거여동)서울특별시 송파구 거여동 1번지 1호3230000-101-2019-00220한식한정식232.01거여1동<NA>
93230000202312023091520231107<NA><NA>완도산회포장마차서울특별시 송파구 백제고분로41길 10, (송파동)서울특별시 송파구 송파동 22번지 2호3230000-101-2002-17444한식회99.0송파1동<NA>
시군구코드지정년도지정번호신청일자지정일자취소일자불가일자업소명소재지도로명소재지지번허가(신고)번호업태명주된음식영업장면적(㎡)행정동명급수시설구분
447323000020071812007101620071019<NA><NA>전주국밥서울특별시 송파구 오금로27길 4, (방이동)서울특별시 송파구 방이동 226번지 1호3230000-101-2001-16179분식국수120.0방이2동<NA>
44832300002007142007092820071019<NA><NA>유한회사 성전일식서울특별시 송파구 양재대로 932, 가락동 농수산물도매시장 가락몰4관 1층 (가락동)서울특별시 송파구 가락동 600번지 가락동 농수산물도매시장3230000-101-1985-07935일식일식128.85가락본동상수도전용
44932300002007252007092820071019<NA><NA>유한가락마당서울특별시 송파구 양재대로 932, 가락동 농수산물도매시장 가락몰 4관 3층 002-1호 (가락동)서울특별시 송파구 가락동 600번지 가락동 농수산물도매시장3230000-101-1993-13936한식생태아구찌게156.11가락본동상수도전용
45032300002007152007092820071019<NA><NA>유한회사 유정씨푸드서울특별시 송파구 양재대로 932, 가락동 농수산물도매시장 가락몰 4관 3층 1-1호 (가락동)서울특별시 송파구 가락동 600번지 가락동 농수산물도매시장3230000-101-1987-07936한식정식174.72가락본동상수도전용
45132300002007112007092820071019<NA><NA>연화산서울특별시 송파구 오금로46길 34, (가락동)서울특별시 송파구 가락동 191번지 9호3230000-101-1996-10059중국식자장면198.9가락2동상수도전용
45232300002007262007092820071019<NA><NA>명동찌개마을서울특별시 송파구 송이로 102, 지상1층 (가락동)서울특별시 송파구 가락동 72번지 6호 지상1층3230000-101-2002-17277한식돼지갈비172.64가락본동<NA>
4533230000200782007092820071019<NA><NA>제주흑돈본가서울특별시 송파구 오금로46길 5, 지상1층 (가락동)서울특별시 송파구 가락동 175번지 12호 지상1층3230000-101-1991-12336일식정식127.9가락본동상수도전용
454323000020076200709282007101920231107<NA>남도서울특별시 송파구 오금로44길 5, (가락동)서울특별시 송파구 가락동 174번지 12호3230000-101-1991-07932일식초밥84.64가락2동상수도전용
45532300002007202007092820071019<NA><NA>아구세상서울특별시 송파구 양재대로62길 8, 지상1층 (가락동)서울특별시 송파구 가락동 93번지 지상1층3230000-101-2003-00463한식수제비132.0가락본동<NA>
4563230000200712007092820071019<NA><NA>발리서울특별시 송파구 동남로 133, (가락동)서울특별시 송파구 가락동 108번지 8호3230000-101-1995-08572경양식파스타273.6가락본동상수도전용