Overview

Dataset statistics

Number of variables26
Number of observations30
Missing cells78
Missing cells (%)10.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.7 KiB
Average record size in memory228.4 B

Variable types

Numeric8
Categorical9
Text7
Unsupported1
Boolean1

Dataset

Description시군구코드,업종코드,년도,업소일련번호,업종명,신고일자,업소명,영업장면적(㎡),소재지전화번호,영업자시작일,법인명,소재지시작일,행정동명,폐업일자,업태명,위생교육수료일자,객실수,한실수,양실수,의자수,욕실수,발한실,세탁기수,허가(신고)번호,소재지도로명,소재지지번
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-20882/S/1/datasetView.do

Alerts

업종코드 has constant value ""Constant
업종명 has constant value ""Constant
업태명 has constant value ""Constant
객실수 has constant value ""Constant
발한실 has constant value ""Constant
한실수 is highly imbalanced (53.1%)Imbalance
양실수 is highly imbalanced (53.1%)Imbalance
의자수 is highly imbalanced (53.1%)Imbalance
욕실수 is highly imbalanced (53.1%)Imbalance
소재지전화번호 has 3 (10.0%) missing valuesMissing
법인명 has 18 (60.0%) missing valuesMissing
폐업일자 has 6 (20.0%) missing valuesMissing
위생교육수료일자 has 30 (100.0%) missing valuesMissing
발한실 has 1 (3.3%) missing valuesMissing
소재지도로명 has 20 (66.7%) missing valuesMissing
소재지시작일 has unique valuesUnique
허가(신고)번호 has unique valuesUnique
소재지지번 has unique valuesUnique
위생교육수료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장면적(㎡) has 8 (26.7%) zerosZeros

Reproduction

Analysis started2024-05-10 23:26:27.339924
Analysis finished2024-05-10 23:26:28.157968
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Real number (ℝ)

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3143666.7
Minimum3010000
Maximum3230000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-10T23:26:28.269970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3010000
5-th percentile3014500
Q13105000
median3160000
Q33187500
95-th percentile3230000
Maximum3230000
Range220000
Interquartile range (IQR)82500

Descriptive statistics

Standard deviation67847.869
Coefficient of variation (CV)0.021582399
Kurtosis-0.49992243
Mean3143666.7
Median Absolute Deviation (MAD)35000
Skewness-0.81207002
Sum94310000
Variance4.6033333 × 109
MonotonicityIncreasing
2024-05-10T23:26:28.487266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3160000 5
16.7%
3170000 3
10.0%
3180000 3
10.0%
3230000 3
10.0%
3010000 2
 
6.7%
3040000 2
 
6.7%
3150000 2
 
6.7%
3190000 2
 
6.7%
3210000 2
 
6.7%
3020000 1
 
3.3%
Other values (5) 5
16.7%
ValueCountFrequency (%)
3010000 2
 
6.7%
3020000 1
 
3.3%
3040000 2
 
6.7%
3060000 1
 
3.3%
3070000 1
 
3.3%
3100000 1
 
3.3%
3120000 1
 
3.3%
3150000 2
 
6.7%
3160000 5
16.7%
3170000 3
10.0%
ValueCountFrequency (%)
3230000 3
10.0%
3210000 2
 
6.7%
3200000 1
 
3.3%
3190000 2
 
6.7%
3180000 3
10.0%
3170000 3
10.0%
3160000 5
16.7%
3150000 2
 
6.7%
3120000 1
 
3.3%
3100000 1
 
3.3%

업종코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
208
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row208
2nd row208
3rd row208
4th row208
5th row208

Common Values

ValueCountFrequency (%)
208 30
100.0%

Length

2024-05-10T23:26:28.824330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:26:29.127308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
208 30
100.0%

년도
Real number (ℝ)

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2004.1
Minimum1991
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-10T23:26:29.426778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1991
5-th percentile1991.9
Q11996.5
median2002
Q32010
95-th percentile2017
Maximum2018
Range27
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.8681919
Coefficient of variation (CV)0.0044250246
Kurtosis-1.3469235
Mean2004.1
Median Absolute Deviation (MAD)7.5
Skewness0.096134479
Sum60123
Variance78.644828
MonotonicityNot monotonic
2024-05-10T23:26:29.812222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1993 3
 
10.0%
2009 3
 
10.0%
2017 3
 
10.0%
1991 2
 
6.7%
2010 2
 
6.7%
2008 2
 
6.7%
2002 2
 
6.7%
2001 2
 
6.7%
1999 2
 
6.7%
1995 1
 
3.3%
Other values (8) 8
26.7%
ValueCountFrequency (%)
1991 2
6.7%
1993 3
10.0%
1994 1
 
3.3%
1995 1
 
3.3%
1996 1
 
3.3%
1998 1
 
3.3%
1999 2
6.7%
2000 1
 
3.3%
2001 2
6.7%
2002 2
6.7%
ValueCountFrequency (%)
2018 1
 
3.3%
2017 3
10.0%
2016 1
 
3.3%
2014 1
 
3.3%
2013 1
 
3.3%
2010 2
6.7%
2009 3
10.0%
2008 2
6.7%
2002 2
6.7%
2001 2
6.7%

업소일련번호
Real number (ℝ)

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean748.03333
Minimum1
Maximum2874
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-10T23:26:30.163157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31782.75
95-th percentile2323.55
Maximum2874
Range2873
Interquartile range (IQR)1781.75

Descriptive statistics

Standard deviation1021.1895
Coefficient of variation (CV)1.3651657
Kurtosis-1.2751112
Mean748.03333
Median Absolute Deviation (MAD)0
Skewness0.74100099
Sum22441
Variance1042828
MonotonicityNot monotonic
2024-05-10T23:26:30.528717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 18
60.0%
1782 1
 
3.3%
1783 1
 
3.3%
1754 1
 
3.3%
1953 1
 
3.3%
1954 1
 
3.3%
2450 1
 
3.3%
2874 1
 
3.3%
1590 1
 
3.3%
2145 1
 
3.3%
Other values (3) 3
 
10.0%
ValueCountFrequency (%)
1 18
60.0%
2 1
 
3.3%
1590 1
 
3.3%
1754 1
 
3.3%
1782 1
 
3.3%
1783 1
 
3.3%
1953 1
 
3.3%
1954 1
 
3.3%
1967 1
 
3.3%
2145 1
 
3.3%
ValueCountFrequency (%)
2874 1
3.3%
2450 1
3.3%
2169 1
3.3%
2145 1
3.3%
1967 1
3.3%
1954 1
3.3%
1953 1
3.3%
1783 1
3.3%
1782 1
3.3%
1754 1
3.3%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
세척제제조업
30 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세척제제조업 30
100.0%

Length

2024-05-10T23:26:30.938898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:26:31.254458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세척제제조업 30
100.0%

신고일자
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20041604
Minimum19910302
Maximum20180315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-10T23:26:31.584289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19910302
5-th percentile19919367
Q119965943
median20020971
Q320100195
95-th percentile20171077
Maximum20180315
Range270013
Interquartile range (IQR)134252.5

Descriptive statistics

Standard deviation88619.356
Coefficient of variation (CV)0.0044217697
Kurtosis-1.3417739
Mean20041604
Median Absolute Deviation (MAD)74501.5
Skewness0.097252858
Sum6.0124812 × 108
Variance7.8533903 × 109
MonotonicityNot monotonic
2024-05-10T23:26:32.017411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
20090421 2
 
6.7%
19910302 1
 
3.3%
20090225 1
 
3.3%
20170207 1
 
3.3%
20140418 1
 
3.3%
20021119 1
 
3.3%
20010907 1
 
3.3%
19931130 1
 
3.3%
20100112 1
 
3.3%
20080325 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
19910302 1
3.3%
19910322 1
3.3%
19930423 1
3.3%
19931130 1
3.3%
19931229 1
3.3%
19940307 1
3.3%
19951109 1
3.3%
19961014 1
3.3%
19980729 1
3.3%
19990408 1
3.3%
ValueCountFrequency (%)
20180315 1
3.3%
20171201 1
3.3%
20170925 1
3.3%
20170207 1
3.3%
20160510 1
3.3%
20140418 1
3.3%
20131223 1
3.3%
20100223 1
3.3%
20100112 1
3.3%
20090421 2
6.7%

업소명
Text

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-05-10T23:26:32.448210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9.5
Mean length6.1333333
Min length3

Characters and Unicode

Total characters184
Distinct characters88
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)86.7%

Sample

1st row(주)합동세제
2nd row경남화학
3rd row일광유지
4th row(주)지텍바이오메디컬
5th row옥소코리어
ValueCountFrequency (%)
대신엠씨(주 2
 
6.5%
바이언스 2
 
6.5%
이피아 1
 
3.2%
주)합동세제 1
 
3.2%
바이오에스(bio-s 1
 
3.2%
템스케미칼 1
 
3.2%
주)영동케미칼 1
 
3.2%
주)클린연구소 1
 
3.2%
웅진산업 1
 
3.2%
주식회사-큰우물 1
 
3.2%
Other values (19) 19
61.3%
2024-05-10T23:26:33.036503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 14
 
7.6%
( 13
 
7.1%
) 13
 
7.1%
이 7
 
3.8%
미 4
 
2.2%
스 4
 
2.2%
코 4
 
2.2%
산 4
 
2.2%
사 4
 
2.2%
업 4
 
2.2%
Other values (78) 113
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151
82.1%
Open Punctuation 13
 
7.1%
Close Punctuation 13
 
7.1%
Uppercase Letter 4
 
2.2%
Dash Punctuation 2
 
1.1%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 14
 
9.3%
이 7
 
4.6%
미 4
 
2.6%
스 4
 
2.6%
코 4
 
2.6%
산 4
 
2.6%
사 4
 
2.6%
업 4
 
2.6%
바 4
 
2.6%
씨 4
 
2.6%
Other values (70) 98
64.9%
Uppercase Letter
ValueCountFrequency (%)
B 1
25.0%
I 1
25.0%
O 1
25.0%
S 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151
82.1%
Common 29
 
15.8%
Latin 4
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 14
 
9.3%
이 7
 
4.6%
미 4
 
2.6%
스 4
 
2.6%
코 4
 
2.6%
산 4
 
2.6%
사 4
 
2.6%
업 4
 
2.6%
바 4
 
2.6%
씨 4
 
2.6%
Other values (70) 98
64.9%
Common
ValueCountFrequency (%)
( 13
44.8%
) 13
44.8%
- 2
 
6.9%
1
 
3.4%
Latin
ValueCountFrequency (%)
B 1
25.0%
I 1
25.0%
O 1
25.0%
S 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151
82.1%
ASCII 33
 
17.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 14
 
9.3%
이 7
 
4.6%
미 4
 
2.6%
스 4
 
2.6%
코 4
 
2.6%
산 4
 
2.6%
사 4
 
2.6%
업 4
 
2.6%
바 4
 
2.6%
씨 4
 
2.6%
Other values (70) 98
64.9%
ASCII
ValueCountFrequency (%)
( 13
39.4%
) 13
39.4%
- 2
 
6.1%
B 1
 
3.0%
I 1
 
3.0%
O 1
 
3.0%
S 1
 
3.0%
1
 
3.0%

영업장면적(㎡)
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.265
Minimum0
Maximum423.84
Zeros8
Zeros (%)26.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-10T23:26:33.360258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112.5
median61.88
Q3124.9675
95-th percentile359.67
Maximum423.84
Range423.84
Interquartile range (IQR)112.4675

Descriptive statistics

Standard deviation113.60005
Coefficient of variation (CV)1.132998
Kurtosis2.8411977
Mean100.265
Median Absolute Deviation (MAD)61.88
Skewness1.7249284
Sum3007.95
Variance12904.971
MonotonicityNot monotonic
2024-05-10T23:26:33.720521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 8
26.7%
423.84 2
 
6.7%
165.3 1
 
3.3%
105.1 1
 
3.3%
94.0 1
 
3.3%
124.87 1
 
3.3%
203.06 1
 
3.3%
131.89 1
 
3.3%
63.9 1
 
3.3%
59.7 1
 
3.3%
Other values (12) 12
40.0%
ValueCountFrequency (%)
0.0 8
26.7%
50.0 1
 
3.3%
50.84 1
 
3.3%
51.0 1
 
3.3%
51.85 1
 
3.3%
57.33 1
 
3.3%
59.7 1
 
3.3%
59.86 1
 
3.3%
63.9 1
 
3.3%
66.0 1
 
3.3%
ValueCountFrequency (%)
423.84 2
6.7%
281.24 1
3.3%
230.09 1
3.3%
203.06 1
3.3%
165.3 1
3.3%
131.89 1
3.3%
125.0 1
3.3%
124.87 1
3.3%
107.13 1
3.3%
105.1 1
3.3%

소재지전화번호
Text

MISSING 

Distinct24
Distinct (%)88.9%
Missing3
Missing (%)10.0%
Memory size372.0 B
2024-05-10T23:26:34.071774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.5925926
Min length6

Characters and Unicode

Total characters259
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

Unique21 ?
Unique (%)77.8%

Sample

1st row02 2721638
2nd row0202358543
3rd row02 7026926
4th row02 4563674
5th row02 4772322
ValueCountFrequency (%)
02 15
34.1%
5220847 2
 
4.5%
15889709 2
 
4.5%
0226759671 2
 
4.5%
7045890 1
 
2.3%
2721638 1
 
2.3%
1322 1
 
2.3%
413 1
 
2.3%
5717652 1
 
2.3%
4737736 1
 
2.3%
Other values (17) 17
38.6%
2024-05-10T23:26:34.700697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 47
18.1%
0 38
14.7%
7 27
10.4%
6 22
8.5%
8 21
8.1%
3 21
8.1%
20
7.7%
1 18
 
6.9%
4 17
 
6.6%
5 16
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 239
92.3%
Space Separator 20
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 47
19.7%
0 38
15.9%
7 27
11.3%
6 22
9.2%
8 21
8.8%
3 21
8.8%
1 18
 
7.5%
4 17
 
7.1%
5 16
 
6.7%
9 12
 
5.0%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 259
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 47
18.1%
0 38
14.7%
7 27
10.4%
6 22
8.5%
8 21
8.1%
3 21
8.1%
20
7.7%
1 18
 
6.9%
4 17
 
6.6%
5 16
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 259
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 47
18.1%
0 38
14.7%
7 27
10.4%
6 22
8.5%
8 21
8.1%
3 21
8.1%
20
7.7%
1 18
 
6.9%
4 17
 
6.6%
5 16
 
6.2%

영업자시작일
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20049955
Minimum19940616
Maximum20180315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-10T23:26:35.117000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19940616
5-th percentile19955162
Q119980777
median20020971
Q320100195
95-th percentile20171077
Maximum20180315
Range239699
Interquartile range (IQR)119418

Descriptive statistics

Standard deviation78444.672
Coefficient of variation (CV)0.0039124613
Kurtosis-1.3639696
Mean20049955
Median Absolute Deviation (MAD)60353
Skewness0.32457967
Sum6.0149865 × 108
Variance6.1535666 × 109
MonotonicityNot monotonic
2024-05-10T23:26:35.525144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
20090421 2
 
6.7%
19980922 1
 
3.3%
20090225 1
 
3.3%
20170207 1
 
3.3%
20140418 1
 
3.3%
20021119 1
 
3.3%
20010907 1
 
3.3%
19970825 1
 
3.3%
20100112 1
 
3.3%
20080325 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
19940616 1
3.3%
19951018 1
3.3%
19960227 1
3.3%
19961009 1
3.3%
19970522 1
3.3%
19970825 1
3.3%
19980324 1
3.3%
19980729 1
3.3%
19980922 1
3.3%
19990408 1
3.3%
ValueCountFrequency (%)
20180315 1
3.3%
20171201 1
3.3%
20170925 1
3.3%
20170207 1
3.3%
20160510 1
3.3%
20140418 1
3.3%
20131223 1
3.3%
20100223 1
3.3%
20100112 1
3.3%
20090421 2
6.7%

법인명
Text

MISSING 

Distinct10
Distinct (%)83.3%
Missing18
Missing (%)60.0%
Memory size372.0 B
2024-05-10T23:26:35.892291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.5
Min length6

Characters and Unicode

Total characters90
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)66.7%

Sample

1st row박홍양(원성욱)
2nd row주식회사 에코웰
3rd row아니코(주)
4th row주식회사 이피아
5th row대신엠씨(주)
ValueCountFrequency (%)
주식회사 3
20.0%
대신엠씨(주 2
13.3%
주)큰우물 2
13.3%
박홍양(원성욱 1
 
6.7%
에코웰 1
 
6.7%
아니코(주 1
 
6.7%
이피아 1
 
6.7%
주)마이티워터 1
 
6.7%
주)클린연구소 1
 
6.7%
템스케미칼 1
 
6.7%
2024-05-10T23:26:36.653655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 11
 
12.2%
( 9
 
10.0%
) 9
 
10.0%
씨 4
 
4.4%
식 3
 
3.3%
엠 3
 
3.3%
3
 
3.3%
사 3
 
3.3%
회 3
 
3.3%
대 2
 
2.2%
Other values (33) 40
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69
76.7%
Open Punctuation 9
 
10.0%
Close Punctuation 9
 
10.0%
Space Separator 3
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 11
 
15.9%
씨 4
 
5.8%
식 3
 
4.3%
엠 3
 
4.3%
사 3
 
4.3%
회 3
 
4.3%
대 2
 
2.9%
이 2
 
2.9%
아 2
 
2.9%
신 2
 
2.9%
Other values (30) 34
49.3%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69
76.7%
Common 21
 
23.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 11
 
15.9%
씨 4
 
5.8%
식 3
 
4.3%
엠 3
 
4.3%
사 3
 
4.3%
회 3
 
4.3%
대 2
 
2.9%
이 2
 
2.9%
아 2
 
2.9%
신 2
 
2.9%
Other values (30) 34
49.3%
Common
ValueCountFrequency (%)
( 9
42.9%
) 9
42.9%
3
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69
76.7%
ASCII 21
 
23.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 11
 
15.9%
씨 4
 
5.8%
식 3
 
4.3%
엠 3
 
4.3%
사 3
 
4.3%
회 3
 
4.3%
대 2
 
2.9%
이 2
 
2.9%
아 2
 
2.9%
신 2
 
2.9%
Other values (30) 34
49.3%
ASCII
ValueCountFrequency (%)
( 9
42.9%
) 9
42.9%
3
 
14.3%

소재지시작일
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20052594
Minimum19940616
Maximum20180315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-10T23:26:37.057700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19940616
5-th percentile19955162
Q119980777
median20020971
Q320125246
95-th percentile20171077
Maximum20180315
Range239699
Interquartile range (IQR)144468.75

Descriptive statistics

Standard deviation80252.778
Coefficient of variation (CV)0.0040021145
Kurtosis-1.524652
Mean20052594
Median Absolute Deviation (MAD)65049.5
Skewness0.24758513
Sum6.0157783 × 108
Variance6.4405084 × 109
MonotonicityNot monotonic
2024-05-10T23:26:37.621488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
19980922 1
 
3.3%
20090326 1
 
3.3%
20170207 1
 
3.3%
20140418 1
 
3.3%
20021119 1
 
3.3%
20010907 1
 
3.3%
19970825 1
 
3.3%
20100112 1
 
3.3%
20080325 1
 
3.3%
19970522 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
19940616 1
3.3%
19951018 1
3.3%
19960227 1
3.3%
19961009 1
3.3%
19970522 1
3.3%
19970825 1
3.3%
19980324 1
3.3%
19980729 1
3.3%
19980922 1
3.3%
19990408 1
3.3%
ValueCountFrequency (%)
20180315 1
3.3%
20171201 1
3.3%
20170925 1
3.3%
20170207 1
3.3%
20160510 1
3.3%
20140418 1
3.3%
20131223 1
3.3%
20130222 1
3.3%
20110318 1
3.3%
20100507 1
3.3%

행정동명
Text

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-05-10T23:26:38.114874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5.5
Mean length4.3
Min length2

Characters and Unicode

Total characters129
Distinct characters43
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)70.0%

Sample

1st row필동
2nd row신당동
3rd row원효로제1동
4th row화양동
5th row구의제3동
ValueCountFrequency (%)
구로제3동 5
 
16.7%
가산동 2
 
6.7%
문정1동 2
 
6.7%
영등포동 1
 
3.3%
화양동 1
 
3.3%
당산제1동 1
 
3.3%
방이1동 1
 
3.3%
양재제2동 1
 
3.3%
서초제1동 1
 
3.3%
보라매동 1
 
3.3%
Other values (14) 14
46.7%
2024-05-10T23:26:39.135000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 30
23.3%
제 16
12.4%
1 9
 
7.0%
3 8
 
6.2%
구 6
 
4.7%
로 6
 
4.7%
양 5
 
3.9%
당 4
 
3.1%
가 4
 
3.1%
산 4
 
3.1%
Other values (33) 37
28.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 110
85.3%
Decimal Number 19
 
14.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 30
27.3%
제 16
14.5%
구 6
 
5.5%
로 6
 
5.5%
양 5
 
4.5%
당 4
 
3.6%
가 4
 
3.6%
산 4
 
3.6%
사 2
 
1.8%
본 2
 
1.8%
Other values (29) 31
28.2%
Decimal Number
ValueCountFrequency (%)
1 9
47.4%
3 8
42.1%
2 1
 
5.3%
5 1
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 110
85.3%
Common 19
 
14.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 30
27.3%
제 16
14.5%
구 6
 
5.5%
로 6
 
5.5%
양 5
 
4.5%
당 4
 
3.6%
가 4
 
3.6%
산 4
 
3.6%
사 2
 
1.8%
본 2
 
1.8%
Other values (29) 31
28.2%
Common
ValueCountFrequency (%)
1 9
47.4%
3 8
42.1%
2 1
 
5.3%
5 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 110
85.3%
ASCII 19
 
14.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 30
27.3%
제 16
14.5%
구 6
 
5.5%
로 6
 
5.5%
양 5
 
4.5%
당 4
 
3.6%
가 4
 
3.6%
산 4
 
3.6%
사 2
 
1.8%
본 2
 
1.8%
Other values (29) 31
28.2%
ASCII
ValueCountFrequency (%)
1 9
47.4%
3 8
42.1%
2 1
 
5.3%
5 1
 
5.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)95.8%
Missing6
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean20052314
Minimum19940205
Maximum20180329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-10T23:26:39.562523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19940205
5-th percentile19950880
Q119987734
median20051030
Q320110344
95-th percentile20169160
Maximum20180329
Range240124
Interquartile range (IQR)122609

Descriptive statistics

Standard deviation73342.027
Coefficient of variation (CV)0.0036575343
Kurtosis-1.0200193
Mean20052314
Median Absolute Deviation (MAD)60107.5
Skewness0.11986245
Sum4.8125554 × 108
Variance5.379053 × 109
MonotonicityNot monotonic
2024-05-10T23:26:39.992294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20051229 2
 
6.7%
20090723 1
 
3.3%
20080221 1
 
3.3%
20031117 1
 
3.3%
19990205 1
 
3.3%
20160324 1
 
3.3%
20110420 1
 
3.3%
19970521 1
 
3.3%
20180329 1
 
3.3%
20140521 1
 
3.3%
Other values (13) 13
43.3%
(Missing) 6
20.0%
ValueCountFrequency (%)
19940205 1
3.3%
19950818 1
3.3%
19951231 1
3.3%
19960905 1
3.3%
19970521 1
3.3%
19980323 1
3.3%
19990205 1
3.3%
20010508 1
3.3%
20030923 1
3.3%
20031117 1
3.3%
ValueCountFrequency (%)
20180329 1
3.3%
20170719 1
3.3%
20160324 1
3.3%
20140521 1
3.3%
20120712 1
3.3%
20110420 1
3.3%
20110318 1
3.3%
20090723 1
3.3%
20080221 1
3.3%
20071109 1
3.3%

업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
세척제제조업
30 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세척제제조업 30
100.0%

Length

2024-05-10T23:26:40.394362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:26:40.727382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세척제제조업 30
100.0%

위생교육수료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

객실수
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 30
100.0%

Length

2024-05-10T23:26:41.095847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:26:41.488121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

한실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
27 
<NA>
3 

Length

Max length4
Median length1
Mean length1.3
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 27
90.0%
<NA> 3
 
10.0%

Length

2024-05-10T23:26:41.826347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:26:42.176535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 27
90.0%
na 3
 
10.0%

양실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
27 
<NA>
3 

Length

Max length4
Median length1
Mean length1.3
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 27
90.0%
<NA> 3
 
10.0%

Length

2024-05-10T23:26:42.541736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:26:42.879345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 27
90.0%
na 3
 
10.0%

의자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
27 
<NA>
3 

Length

Max length4
Median length1
Mean length1.3
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 27
90.0%
<NA> 3
 
10.0%

Length

2024-05-10T23:26:43.290061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:26:43.669645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 27
90.0%
na 3
 
10.0%

욕실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
27 
<NA>
3 

Length

Max length4
Median length1
Mean length1.3
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 27
90.0%
<NA> 3
 
10.0%

Length

2024-05-10T23:26:44.186221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:26:44.585344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 27
90.0%
na 3
 
10.0%

발한실
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)3.4%
Missing1
Missing (%)3.3%
Memory size192.0 B
False
29 
(Missing)
 
1
ValueCountFrequency (%)
False 29
96.7%
(Missing) 1
 
3.3%
2024-05-10T23:26:45.011415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

세탁기수
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
16 
0
14 

Length

Max length4
Median length4
Mean length2.6
Min length1

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> 16
53.3%
0 14
46.7%

Length

2024-05-10T23:26:45.441206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:26:45.753598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 16
53.3%
0 14
46.7%

허가(신고)번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-05-10T23:26:46.228291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters660
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

Unique30 ?
Unique (%)100.0%

Sample

1st row3010000-208-1991-01782
2nd row3010000-208-1993-01783
3rd row3020000-208-1991-01754
4th row3040000-208-1999-01953
5th row3040000-208-2000-01954
ValueCountFrequency (%)
3010000-208-1991-01782 1
 
3.3%
3010000-208-1993-01783 1
 
3.3%
3230000-208-2014-00001 1
 
3.3%
3230000-208-2002-00001 1
 
3.3%
3210000-208-2001-00001 1
 
3.3%
3210000-208-1993-02169 1
 
3.3%
3200000-208-2010-00001 1
 
3.3%
3190000-208-2008-00001 1
 
3.3%
3190000-208-1996-01967 1
 
3.3%
3180000-208-2017-00001 1
 
3.3%
Other values (20) 20
66.7%
2024-05-10T23:26:47.756172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 280
42.4%
- 90
 
13.6%
1 72
 
10.9%
2 65
 
9.8%
8 40
 
6.1%
3 39
 
5.9%
9 34
 
5.2%
7 12
 
1.8%
6 10
 
1.5%
5 9
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 570
86.4%
Dash Punctuation 90
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 280
49.1%
1 72
 
12.6%
2 65
 
11.4%
8 40
 
7.0%
3 39
 
6.8%
9 34
 
6.0%
7 12
 
2.1%
6 10
 
1.8%
5 9
 
1.6%
4 9
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 660
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 280
42.4%
- 90
 
13.6%
1 72
 
10.9%
2 65
 
9.8%
8 40
 
6.1%
3 39
 
5.9%
9 34
 
5.2%
7 12
 
1.8%
6 10
 
1.5%
5 9
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 660
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 280
42.4%
- 90
 
13.6%
1 72
 
10.9%
2 65
 
9.8%
8 40
 
6.1%
3 39
 
5.9%
9 34
 
5.2%
7 12
 
1.8%
6 10
 
1.5%
5 9
 
1.4%

소재지도로명
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing20
Missing (%)66.7%
Memory size372.0 B
2024-05-10T23:26:48.423430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length35.7
Min length29

Characters and Unicode

Total characters357
Distinct characters87
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)100.0%

Sample

1st row서울특별시 서대문구 북아현로 93, 2층 (북아현동, 혜전빌딩)
2nd row서울특별시 강서구 양천로 551-17, 1107호 (가양동, 한화비즈메트로1차 )
3rd row서울특별시 구로구 디지털로31길 19, 에이스테크노타워Ⅱ 810호 (구로동)
4th row서울특별시 금천구 범안로16길 29, 지상1층 (독산동)
5th row서울특별시 영등포구 당산로27길 17, 1층 (당산동3가)
ValueCountFrequency (%)
서울특별시 10
 
15.6%
영등포구 3
 
4.7%
2층 2
 
3.1%
문정동 2
 
3.1%
송파구 2
 
3.1%
북아현로 1
 
1.6%
봉천로 1
 
1.6%
당산동3가 1
 
1.6%
버드나루로12나길 1
 
1.6%
48 1
 
1.6%
Other values (40) 40
62.5%
2024-05-10T23:26:49.644795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
 
15.1%
1 21
 
5.9%
, 15
 
4.2%
동 14
 
3.9%
로 13
 
3.6%
구 12
 
3.4%
서 12
 
3.4%
별 10
 
2.8%
특 10
 
2.8%
시 10
 
2.8%
Other values (77) 186
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 205
57.4%
Decimal Number 58
 
16.2%
Space Separator 54
 
15.1%
Other Punctuation 15
 
4.2%
Open Punctuation 10
 
2.8%
Close Punctuation 10
 
2.8%
Dash Punctuation 3
 
0.8%
Uppercase Letter 1
 
0.3%
Letter Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 14
 
6.8%
로 13
 
6.3%
구 12
 
5.9%
서 12
 
5.9%
별 10
 
4.9%
특 10
 
4.9%
시 10
 
4.9%
울 10
 
4.9%
층 6
 
2.9%
길 4
 
2.0%
Other values (60) 104
50.7%
Decimal Number
ValueCountFrequency (%)
1 21
36.2%
2 10
17.2%
3 6
 
10.3%
7 6
 
10.3%
8 3
 
5.2%
0 3
 
5.2%
9 3
 
5.2%
4 2
 
3.4%
5 2
 
3.4%
6 2
 
3.4%
Space Separator
ValueCountFrequency (%)
54
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 205
57.4%
Common 150
42.0%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 14
 
6.8%
로 13
 
6.3%
구 12
 
5.9%
서 12
 
5.9%
별 10
 
4.9%
특 10
 
4.9%
시 10
 
4.9%
울 10
 
4.9%
층 6
 
2.9%
길 4
 
2.0%
Other values (60) 104
50.7%
Common
ValueCountFrequency (%)
54
36.0%
1 21
 
14.0%
, 15
 
10.0%
2 10
 
6.7%
( 10
 
6.7%
) 10
 
6.7%
3 6
 
4.0%
7 6
 
4.0%
8 3
 
2.0%
0 3
 
2.0%
Other values (5) 12
 
8.0%
Latin
ValueCountFrequency (%)
B 1
50.0%
Ⅱ 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 205
57.4%
ASCII 151
42.3%
Number Forms 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54
35.8%
1 21
 
13.9%
, 15
 
9.9%
2 10
 
6.6%
( 10
 
6.6%
) 10
 
6.6%
3 6
 
4.0%
7 6
 
4.0%
8 3
 
2.0%
0 3
 
2.0%
Other values (6) 13
 
8.6%
Hangul
ValueCountFrequency (%)
동 14
 
6.8%
로 13
 
6.3%
구 12
 
5.9%
서 12
 
5.9%
별 10
 
4.9%
특 10
 
4.9%
시 10
 
4.9%
울 10
 
4.9%
층 6
 
2.9%
길 4
 
2.0%
Other values (60) 104
50.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지지번
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-05-10T23:26:50.396604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length39
Mean length29.433333
Min length22

Characters and Unicode

Total characters883
Distinct characters108
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row서울특별시 중구 필동3가 16번지 3호
2nd row서울특별시 중구 신당동 304번지 281호
3rd row서울특별시 용산구 문배동 40번지 47호
4th row서울특별시 광진구 화양동 393번지 1호 건국대학교축산대학구관202호
5th row서울특별시 광진구 구의동 217번지 6호
ValueCountFrequency (%)
서울특별시 30
 
18.0%
7호 6
 
3.6%
구로동 5
 
3.0%
구로구 5
 
3.0%
송파구 3
 
1.8%
197번지 3
 
1.8%
영등포구 3
 
1.8%
금천구 3
 
1.8%
10호 2
 
1.2%
광진구 2
 
1.2%
Other values (95) 105
62.9%
2024-05-10T23:26:51.434458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
213
24.1%
구 42
 
4.8%
서 36
 
4.1%
1 36
 
4.1%
동 34
 
3.9%
지 32
 
3.6%
시 31
 
3.5%
번 30
 
3.4%
특 30
 
3.4%
별 30
 
3.4%
Other values (98) 369
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 506
57.3%
Space Separator 213
24.1%
Decimal Number 159
 
18.0%
Dash Punctuation 4
 
0.5%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 42
 
8.3%
서 36
 
7.1%
동 34
 
6.7%
지 32
 
6.3%
시 31
 
6.1%
번 30
 
5.9%
특 30
 
5.9%
별 30
 
5.9%
울 30
 
5.9%
호 30
 
5.9%
Other values (85) 181
35.8%
Decimal Number
ValueCountFrequency (%)
1 36
22.6%
2 22
13.8%
7 19
11.9%
0 17
10.7%
3 14
 
8.8%
4 13
 
8.2%
9 13
 
8.2%
6 11
 
6.9%
8 8
 
5.0%
5 6
 
3.8%
Space Separator
ValueCountFrequency (%)
213
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 506
57.3%
Common 376
42.6%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 42
 
8.3%
서 36
 
7.1%
동 34
 
6.7%
지 32
 
6.3%
시 31
 
6.1%
번 30
 
5.9%
특 30
 
5.9%
별 30
 
5.9%
울 30
 
5.9%
호 30
 
5.9%
Other values (85) 181
35.8%
Common
ValueCountFrequency (%)
213
56.6%
1 36
 
9.6%
2 22
 
5.9%
7 19
 
5.1%
0 17
 
4.5%
3 14
 
3.7%
4 13
 
3.5%
9 13
 
3.5%
6 11
 
2.9%
8 8
 
2.1%
Other values (2) 10
 
2.7%
Latin
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 506
57.3%
ASCII 376
42.6%
Number Forms 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
213
56.6%
1 36
 
9.6%
2 22
 
5.9%
7 19
 
5.1%
0 17
 
4.5%
3 14
 
3.7%
4 13
 
3.5%
9 13
 
3.5%
6 11
 
2.9%
8 8
 
2.1%
Other values (2) 10
 
2.7%
Hangul
ValueCountFrequency (%)
구 42
 
8.3%
서 36
 
7.1%
동 34
 
6.7%
지 32
 
6.3%
시 31
 
6.1%
번 30
 
5.9%
특 30
 
5.9%
별 30
 
5.9%
울 30
 
5.9%
호 30
 
5.9%
Other values (85) 181
35.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

Sample

시군구코드업종코드년도업소일련번호업종명신고일자업소명영업장면적(㎡)소재지전화번호영업자시작일법인명소재지시작일행정동명폐업일자업태명위생교육수료일자객실수한실수양실수의자수욕실수발한실세탁기수허가(신고)번호소재지도로명소재지지번
0301000020819911782세척제제조업19910302(주)합동세제165.302 272163819980922<NA>19980922필동20050831세척제제조업<NA>00000N<NA>3010000-208-1991-01782<NA>서울특별시 중구 필동3가 16번지 3호
1301000020819931783세척제제조업19930423경남화학0.0020235854319940616<NA>19940616신당동19940205세척제제조업<NA>00000N<NA>3010000-208-1993-01783<NA>서울특별시 중구 신당동 304번지 281호
2302000020819911754세척제제조업19910322일광유지51.8502 702692619961009<NA>19961009원효로제1동19960905세척제제조업<NA>00000N<NA>3020000-208-1991-01754<NA>서울특별시 용산구 문배동 40번지 47호
3304000020819991953세척제제조업19991213(주)지텍바이오메디컬107.1302 456367419991213박홍양(원성욱)19991213화양동20051229세척제제조업<NA>00000N<NA>3040000-208-1999-01953<NA>서울특별시 광진구 화양동 393번지 1호 건국대학교축산대학구관202호
4304000020820001954세척제제조업20000112옥소코리어0.002 477232220000112<NA>20000112구의제3동20051229세척제제조업<NA>00000N<NA>3040000-208-2000-01954<NA>서울특별시 광진구 구의동 217번지 6호
5306000020819942450세척제제조업19940307제일기업57.3302 209263419951018<NA>19951018망우본동19950818세척제제조업<NA>00000N<NA>3060000-208-1994-02450<NA>서울특별시 중랑구 망우동 506번지 13호
6307000020819932874세척제제조업19931229미보산업0.002 915584419980324<NA>19980324종암동19980323세척제제조업<NA>00000N<NA>3070000-208-1993-02874<NA>서울특별시 성북구 종암동 92번지 7호
7310000020819981590세척제제조업19980729미보산업사0.002 931887719980729<NA>19980729중계본동20010508세척제제조업<NA>00000N<NA>3100000-208-1998-01590<NA>서울특별시 노원구 중계동 61번지 9호
8312000020820171세척제제조업20171201고은재51.0<NA>20171201<NA>20171201충현동<NA>세척제제조업<NA>00000N03120000-208-2017-00001서울특별시 서대문구 북아현로 93, 2층 (북아현동, 혜전빌딩)서울특별시 서대문구 북아현동 187번지 10호 혜전빌딩2층
9315000020819991세척제제조업19990408(주)한켐0.0023662218819990408<NA>19990408가양제1동20030923세척제제조업<NA>00000N<NA>3150000-208-1999-00001<NA>서울특별시 강서구 마곡동 7번지 8호
시군구코드업종코드년도업소일련번호업종명신고일자업소명영업장면적(㎡)소재지전화번호영업자시작일법인명소재지시작일행정동명폐업일자업태명위생교육수료일자객실수한실수양실수의자수욕실수발한실세탁기수허가(신고)번호소재지도로명소재지지번
20318000020820101세척제제조업20100223장애인고용봉사회105.1022633448320100223<NA>20100223영등포동20180329세척제제조업<NA>00000N03180000-208-2010-00001서울특별시 영등포구 버드나루로12나길 48, (영등포동2가,동우빌딩 2층)서울특별시 영등포구 영등포동2가 94번지 30호 동우빌딩 2층
21318000020820171세척제제조업20170925(주)마이티워터50.002 2637100820170925(주)마이티워터20170925양평제1동<NA>세척제제조업<NA>00000N03180000-208-2017-00001서울특별시 영등포구 선유동1로 31-2, (양평동3가)서울특별시 영등포구 양평동3가 2번지 3호
22319000020819961967세척제제조업19961014서진환경82.1102 532042119970522<NA>19970522사당제3동19970521세척제제조업<NA>00000N<NA>3190000-208-1996-01967<NA>서울특별시 동작구 사당동 167번지 23호
23319000020820081세척제제조업20080325(주)큰우물59.7522084720080325(주)큰우물20080325사당제5동20110420세척제제조업<NA>00000<NA>03190000-208-2008-00001<NA>서울특별시 동작구 사당동 232번지 7호
24320000020820101세척제제조업20100112주식회사-큰우물63.9522084720100112(주)큰우물20100112보라매동20160324세척제제조업<NA>00000N03200000-208-2010-00001서울특별시 관악구 봉천로 287-1, (봉천동,2층)서울특별시 관악구 봉천동 968번지 19호 2층
25321000020819932169세척제제조업19931130웅진산업0.002 473773619970825<NA>19970825서초제1동19990205세척제제조업<NA>00000N<NA>3210000-208-1993-02169<NA>서울특별시 서초구 서초동 1617번지 14호
26321000020820011세척제제조업20010907(주)클린연구소131.8902 571765220010907(주)클린연구소20010907양재제2동20031117세척제제조업<NA>0<NA><NA><NA><NA>N<NA>3210000-208-2001-00001<NA>서울특별시 서초구 양재동 265번지 29호 3층
27323000020820021세척제제조업20021119(주)영동케미칼203.0602 413 132220021119<NA>20021119방이1동20080221세척제제조업<NA>0<NA><NA><NA><NA>N<NA>3230000-208-2002-00001<NA>서울특별시 송파구 방이동 129번지 2호
28323000020820141세척제제조업20140418템스케미칼124.8702 3401774020140418주식회사 템스케미칼20140418문정1동<NA>세척제제조업<NA>00000N03230000-208-2014-00001서울특별시 송파구 동남로 132, 지하1층 (문정동)서울특별시 송파구 문정동 4번지 8호 지하1층
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