Overview

Dataset statistics

Number of variables44
Number of observations26
Missing cells418
Missing cells (%)36.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.8 KiB
Average record size in memory386.1 B

Variable types

Categorical17
Text7
Numeric5
Unsupported12
DateTime2
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author성북구
URLhttps://data.seoul.go.kr/dataList/OA-18459/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
급수시설구분명 has constant value ""Constant
건물소유구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (60.9%)Imbalance
영업상태명 is highly imbalanced (60.9%)Imbalance
상세영업상태코드 is highly imbalanced (60.9%)Imbalance
상세영업상태명 is highly imbalanced (60.9%)Imbalance
소재지면적 is highly imbalanced (60.1%)Imbalance
도로명우편번호 is highly imbalanced (60.1%)Imbalance
데이터갱신구분 is highly imbalanced (76.5%)Imbalance
위생업태명 is highly imbalanced (76.5%)Imbalance
본사종업원수 is highly imbalanced (60.9%)Imbalance
공장사무직종업원수 is highly imbalanced (60.9%)Imbalance
공장판매직종업원수 is highly imbalanced (60.9%)Imbalance
공장생산직종업원수 is highly imbalanced (60.9%)Imbalance
보증액 is highly imbalanced (76.5%)Imbalance
월세액 is highly imbalanced (76.5%)Imbalance
시설총규모 is highly imbalanced (76.5%)Imbalance
인허가취소일자 has 26 (100.0%) missing valuesMissing
폐업일자 has 2 (7.7%) missing valuesMissing
휴업시작일자 has 26 (100.0%) missing valuesMissing
휴업종료일자 has 26 (100.0%) missing valuesMissing
재개업일자 has 26 (100.0%) missing valuesMissing
전화번호 has 19 (73.1%) missing valuesMissing
도로명주소 has 22 (84.6%) missing valuesMissing
좌표정보(X) has 6 (23.1%) missing valuesMissing
좌표정보(Y) has 6 (23.1%) missing valuesMissing
남성종사자수 has 26 (100.0%) missing valuesMissing
여성종사자수 has 26 (100.0%) missing valuesMissing
영업장주변구분명 has 26 (100.0%) missing valuesMissing
등급구분명 has 26 (100.0%) missing valuesMissing
급수시설구분명 has 25 (96.2%) missing valuesMissing
총인원 has 26 (100.0%) missing valuesMissing
건물소유구분명 has 25 (96.2%) missing valuesMissing
다중이용업소여부 has 1 (3.8%) missing valuesMissing
전통업소지정번호 has 26 (100.0%) missing valuesMissing
전통업소주된음식 has 26 (100.0%) missing valuesMissing
홈페이지 has 26 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
지번주소 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
여성종사자수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총인원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 02:12:17.897270
Analysis finished2024-05-11 02:12:18.756698
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
3070000
26 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3070000
2nd row3070000
3rd row3070000
4th row3070000
5th row3070000

Common Values

ValueCountFrequency (%)
3070000 26
100.0%

Length

2024-05-11T02:12:18.973480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:19.278304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3070000 26
100.0%

관리번호
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-05-11T02:12:19.683620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters572
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

Unique26 ?
Unique (%)100.0%

Sample

1st row3070000-111-1973-00001
2nd row3070000-111-1985-00001
3rd row3070000-111-1986-00001
4th row3070000-111-1986-00002
5th row3070000-111-1986-00003
ValueCountFrequency (%)
3070000-111-1973-00001 1
 
3.8%
3070000-111-1985-00001 1
 
3.8%
3070000-111-2002-00009 1
 
3.8%
3070000-111-2002-00008 1
 
3.8%
3070000-111-2002-00007 1
 
3.8%
3070000-111-2002-00006 1
 
3.8%
3070000-111-2002-00005 1
 
3.8%
3070000-111-2002-00004 1
 
3.8%
3070000-111-2002-00003 1
 
3.8%
3070000-111-2002-00002 1
 
3.8%
Other values (16) 16
61.5%
2024-05-11T02:12:20.650654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 246
43.0%
1 102
17.8%
- 78
 
13.6%
3 33
 
5.8%
7 30
 
5.2%
2 26
 
4.5%
9 23
 
4.0%
8 12
 
2.1%
5 11
 
1.9%
6 6
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 494
86.4%
Dash Punctuation 78
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 246
49.8%
1 102
20.6%
3 33
 
6.7%
7 30
 
6.1%
2 26
 
5.3%
9 23
 
4.7%
8 12
 
2.4%
5 11
 
2.2%
6 6
 
1.2%
4 5
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 246
43.0%
1 102
17.8%
- 78
 
13.6%
3 33
 
5.8%
7 30
 
5.2%
2 26
 
4.5%
9 23
 
4.0%
8 12
 
2.1%
5 11
 
1.9%
6 6
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 246
43.0%
1 102
17.8%
- 78
 
13.6%
3 33
 
5.8%
7 30
 
5.2%
2 26
 
4.5%
9 23
 
4.0%
8 12
 
2.1%
5 11
 
1.9%
6 6
 
1.0%

인허가일자
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19862046
Minimum19690602
Maximum20021019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-05-11T02:12:21.021566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19690602
5-th percentile19738447
Q119782808
median19860566
Q319935900
95-th percentile20015446
Maximum20021019
Range330417
Interquartile range (IQR)153092.5

Descriptive statistics

Standard deviation90956.731
Coefficient of variation (CV)0.004579424
Kurtosis-0.76904915
Mean19862046
Median Absolute Deviation (MAD)80359
Skewness0.051661819
Sum5.164132 × 108
Variance8.2731269 × 109
MonotonicityNot monotonic
2024-05-11T02:12:21.477846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
19731229 1
 
3.8%
19950619 1
 
3.8%
20021019 1
 
3.8%
19690602 1
 
3.8%
19810406 1
 
3.8%
19760214 1
 
3.8%
19760101 1
 
3.8%
19760413 1
 
3.8%
19760218 1
 
3.8%
19780306 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
19690602 1
3.8%
19731229 1
3.8%
19760101 1
3.8%
19760214 1
3.8%
19760218 1
3.8%
19760413 1
3.8%
19780306 1
3.8%
19790312 1
3.8%
19810406 1
3.8%
19850530 1
3.8%
ValueCountFrequency (%)
20021019 1
3.8%
20020423 1
3.8%
20000516 1
3.8%
19950619 1
3.8%
19950506 1
3.8%
19950407 1
3.8%
19941024 1
3.8%
19920528 1
3.8%
19890329 1
3.8%
19880616 1
3.8%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
3
24 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 24
92.3%
1 2
 
7.7%

Length

2024-05-11T02:12:21.885765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:22.193140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 24
92.3%
1 2
 
7.7%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
폐업
24 
영업/정상
 
2

Length

Max length5
Median length2
Mean length2.2307692
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 24
92.3%
영업/정상 2
 
7.7%

Length

2024-05-11T02:12:22.523009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:22.843591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 24
92.3%
영업/정상 2
 
7.7%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
2
24 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 24
92.3%
1 2
 
7.7%

Length

2024-05-11T02:12:23.170837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:23.479156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 24
92.3%
1 2
 
7.7%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
폐업
24 
영업
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 24
92.3%
영업 2
 
7.7%

Length

2024-05-11T02:12:23.888309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:24.327927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 24
92.3%
영업 2
 
7.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)37.5%
Missing2
Missing (%)7.7%
Infinite0
Infinite (%)0.0%
Mean20028501
Minimum19970214
Maximum20140519
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-05-11T02:12:24.647677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19970214
5-th percentile19975514
Q120021104
median20021202
Q320021202
95-th percentile20126158
Maximum20140519
Range170305
Interquartile range (IQR)98

Descriptive statistics

Standard deviation40077.075
Coefficient of variation (CV)0.0020010022
Kurtosis3.4997818
Mean20028501
Median Absolute Deviation (MAD)49
Skewness1.7891725
Sum4.8068404 × 108
Variance1.6061719 × 109
MonotonicityNot monotonic
2024-05-11T02:12:25.013417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
20021202 12
46.2%
20021104 5
19.2%
19970214 1
 
3.8%
19971103 1
 
3.8%
20000509 1
 
3.8%
20130612 1
 
3.8%
20010214 1
 
3.8%
20140519 1
 
3.8%
20100920 1
 
3.8%
(Missing) 2
 
7.7%
ValueCountFrequency (%)
19970214 1
 
3.8%
19971103 1
 
3.8%
20000509 1
 
3.8%
20010214 1
 
3.8%
20021104 5
19.2%
20021202 12
46.2%
20100920 1
 
3.8%
20130612 1
 
3.8%
20140519 1
 
3.8%
ValueCountFrequency (%)
20140519 1
 
3.8%
20130612 1
 
3.8%
20100920 1
 
3.8%
20021202 12
46.2%
20021104 5
19.2%
20010214 1
 
3.8%
20000509 1
 
3.8%
19971103 1
 
3.8%
19970214 1
 
3.8%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

전화번호
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing19
Missing (%)73.1%
Memory size340.0 B
2024-05-11T02:12:25.412378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters70
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

Unique7 ?
Unique (%)100.0%

Sample

1st row02 7428183
2nd row02 9432279
3rd row02 9180122
4th row02 7445155
5th row02 9157585
ValueCountFrequency (%)
02 7
50.0%
7428183 1
 
7.1%
9432279 1
 
7.1%
9180122 1
 
7.1%
7445155 1
 
7.1%
9157585 1
 
7.1%
9263313 1
 
7.1%
9153542 1
 
7.1%
2024-05-11T02:12:26.310759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14
20.0%
0 8
11.4%
5 8
11.4%
7
10.0%
1 7
10.0%
3 6
8.6%
9 6
8.6%
4 5
 
7.1%
7 4
 
5.7%
8 4
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
90.0%
Space Separator 7
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14
22.2%
0 8
12.7%
5 8
12.7%
1 7
11.1%
3 6
9.5%
9 6
9.5%
4 5
 
7.9%
7 4
 
6.3%
8 4
 
6.3%
6 1
 
1.6%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 14
20.0%
0 8
11.4%
5 8
11.4%
7
10.0%
1 7
10.0%
3 6
8.6%
9 6
8.6%
4 5
 
7.1%
7 4
 
5.7%
8 4
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14
20.0%
0 8
11.4%
5 8
11.4%
7
10.0%
1 7
10.0%
3 6
8.6%
9 6
8.6%
4 5
 
7.1%
7 4
 
5.7%
8 4
 
5.7%

소재지면적
Categorical

IMBALANCE 

Distinct5
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
22 
24.86
 
1
50.32
 
1
29.0
 
1
0.0
 
1

Length

Max length5
Median length4
Mean length4.0384615
Min length3

Unique

Unique4 ?
Unique (%)15.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 22
84.6%
24.86 1
 
3.8%
50.32 1
 
3.8%
29.0 1
 
3.8%
0.0 1
 
3.8%

Length

2024-05-11T02:12:26.905809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:27.348252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
84.6%
24.86 1
 
3.8%
50.32 1
 
3.8%
29.0 1
 
3.8%
0.0 1
 
3.8%

소재지우편번호
Real number (ℝ)

Distinct24
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean136564
Minimum136034
Maximum136865
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-05-11T02:12:27.819926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum136034
5-th percentile136035
Q1136097.5
median136819
Q3136829.75
95-th percentile136852.75
Maximum136865
Range831
Interquartile range (IQR)732.25

Descriptive statistics

Standard deviation371.46768
Coefficient of variation (CV)0.0027200996
Kurtosis-1.6238276
Mean136564
Median Absolute Deviation (MAD)17
Skewness-0.69566872
Sum3550664
Variance137988.24
MonotonicityNot monotonic
2024-05-11T02:12:28.356347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
136035 2
 
7.7%
136802 2
 
7.7%
136828 1
 
3.8%
136836 1
 
3.8%
136837 1
 
3.8%
136140 1
 
3.8%
136865 1
 
3.8%
136833 1
 
3.8%
136090 1
 
3.8%
136858 1
 
3.8%
Other values (14) 14
53.8%
ValueCountFrequency (%)
136034 1
3.8%
136035 2
7.7%
136041 1
3.8%
136043 1
3.8%
136044 1
3.8%
136090 1
3.8%
136120 1
3.8%
136140 1
3.8%
136802 2
7.7%
136815 1
3.8%
ValueCountFrequency (%)
136865 1
3.8%
136858 1
3.8%
136837 1
3.8%
136836 1
3.8%
136833 1
3.8%
136832 1
3.8%
136830 1
3.8%
136829 1
3.8%
136828 1
3.8%
136827 1
3.8%

지번주소
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-05-11T02:12:28.844775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length20.884615
Min length18

Characters and Unicode

Total characters543
Distinct characters39
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

Unique26 ?
Unique (%)100.0%

Sample

1st row서울특별시 성북구 장위동 66-253
2nd row서울특별시 성북구 상월곡동 57-5
3rd row서울특별시 성북구 석관동 248-24
4th row서울특별시 성북구 동소문동4가 163
5th row서울특별시 성북구 삼선동4가 9
ValueCountFrequency (%)
서울특별시 26
24.8%
성북구 26
24.8%
장위동 10
 
9.5%
석관동 3
 
2.9%
길음동 2
 
1.9%
종암동 2
 
1.9%
동소문동5가 2
 
1.9%
3-75 1
 
1.0%
75-11 1
 
1.0%
삼선동1가 1
 
1.0%
Other values (31) 31
29.5%
2024-05-11T02:12:30.011574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
104
19.2%
동 29
 
5.3%
성 27
 
5.0%
북 27
 
5.0%
서 26
 
4.8%
특 26
 
4.8%
별 26
 
4.8%
시 26
 
4.8%
구 26
 
4.8%
울 26
 
4.8%
Other values (29) 200
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 297
54.7%
Decimal Number 117
 
21.5%
Space Separator 104
 
19.2%
Dash Punctuation 24
 
4.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 29
9.8%
성 27
9.1%
북 27
9.1%
서 26
8.8%
특 26
8.8%
별 26
8.8%
시 26
8.8%
구 26
8.8%
울 26
8.8%
장 10
 
3.4%
Other values (16) 48
16.2%
Decimal Number
ValueCountFrequency (%)
2 20
17.1%
1 20
17.1%
5 14
12.0%
3 14
12.0%
6 12
10.3%
4 10
8.5%
7 9
7.7%
8 9
7.7%
0 6
 
5.1%
9 3
 
2.6%
Space Separator
ValueCountFrequency (%)
104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 297
54.7%
Common 246
45.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 29
9.8%
성 27
9.1%
북 27
9.1%
서 26
8.8%
특 26
8.8%
별 26
8.8%
시 26
8.8%
구 26
8.8%
울 26
8.8%
장 10
 
3.4%
Other values (16) 48
16.2%
Common
ValueCountFrequency (%)
104
42.3%
- 24
 
9.8%
2 20
 
8.1%
1 20
 
8.1%
5 14
 
5.7%
3 14
 
5.7%
6 12
 
4.9%
4 10
 
4.1%
7 9
 
3.7%
8 9
 
3.7%
Other values (3) 10
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 297
54.7%
ASCII 246
45.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
104
42.3%
- 24
 
9.8%
2 20
 
8.1%
1 20
 
8.1%
5 14
 
5.7%
3 14
 
5.7%
6 12
 
4.9%
4 10
 
4.1%
7 9
 
3.7%
8 9
 
3.7%
Other values (3) 10
 
4.1%
Hangul
ValueCountFrequency (%)
동 29
9.8%
성 27
9.1%
북 27
9.1%
서 26
8.8%
특 26
8.8%
별 26
8.8%
시 26
8.8%
구 26
8.8%
울 26
8.8%
장 10
 
3.4%
Other values (16) 48
16.2%

도로명주소
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing22
Missing (%)84.6%
Memory size340.0 B
2024-05-11T02:12:30.708412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length29.25
Min length28

Characters and Unicode

Total characters117
Distinct characters40
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row서울특별시 성북구 동소문로 86-19, 1층 (동소문동5가)
2nd row서울특별시 성북구 보문로29다길 20 (삼선동3가)
3rd row서울특별시 성북구 돌곶이로 149, 1층 (장위동)
4th row서울특별시 성북구 삼선교로10다길 7 (삼선동1가)
ValueCountFrequency (%)
서울특별시 4
18.2%
성북구 4
18.2%
1층 2
 
9.1%
동소문로 1
 
4.5%
86-19 1
 
4.5%
동소문동5가 1
 
4.5%
보문로29다길 1
 
4.5%
20 1
 
4.5%
삼선동3가 1
 
4.5%
돌곶이로 1
 
4.5%
Other values (5) 5
22.7%
2024-05-11T02:12:32.131498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
 
15.4%
1 6
 
5.1%
동 6
 
5.1%
서 4
 
3.4%
구 4
 
3.4%
) 4
 
3.4%
울 4
 
3.4%
로 4
 
3.4%
( 4
 
3.4%
북 4
 
3.4%
Other values (30) 59
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69
59.0%
Decimal Number 19
 
16.2%
Space Separator 18
 
15.4%
Close Punctuation 4
 
3.4%
Open Punctuation 4
 
3.4%
Other Punctuation 2
 
1.7%
Dash Punctuation 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6
 
8.7%
서 4
 
5.8%
구 4
 
5.8%
울 4
 
5.8%
로 4
 
5.8%
북 4
 
5.8%
시 4
 
5.8%
특 4
 
5.8%
별 4
 
5.8%
성 4
 
5.8%
Other values (15) 27
39.1%
Decimal Number
ValueCountFrequency (%)
1 6
31.6%
9 3
15.8%
0 2
 
10.5%
2 2
 
10.5%
4 1
 
5.3%
3 1
 
5.3%
5 1
 
5.3%
6 1
 
5.3%
8 1
 
5.3%
7 1
 
5.3%
Space Separator
ValueCountFrequency (%)
18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69
59.0%
Common 48
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6
 
8.7%
서 4
 
5.8%
구 4
 
5.8%
울 4
 
5.8%
로 4
 
5.8%
북 4
 
5.8%
시 4
 
5.8%
특 4
 
5.8%
별 4
 
5.8%
성 4
 
5.8%
Other values (15) 27
39.1%
Common
ValueCountFrequency (%)
18
37.5%
1 6
 
12.5%
) 4
 
8.3%
( 4
 
8.3%
9 3
 
6.2%
, 2
 
4.2%
0 2
 
4.2%
2 2
 
4.2%
4 1
 
2.1%
3 1
 
2.1%
Other values (5) 5
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69
59.0%
ASCII 48
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
37.5%
1 6
 
12.5%
) 4
 
8.3%
( 4
 
8.3%
9 3
 
6.2%
, 2
 
4.2%
0 2
 
4.2%
2 2
 
4.2%
4 1
 
2.1%
3 1
 
2.1%
Other values (5) 5
 
10.4%
Hangul
ValueCountFrequency (%)
동 6
 
8.7%
서 4
 
5.8%
구 4
 
5.8%
울 4
 
5.8%
로 4
 
5.8%
북 4
 
5.8%
시 4
 
5.8%
특 4
 
5.8%
별 4
 
5.8%
성 4
 
5.8%
Other values (15) 27
39.1%

도로명우편번호
Categorical

IMBALANCE 

Distinct5
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
22 
2846
 
1
2868
 
1
2768
 
1
2867
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique4 ?
Unique (%)15.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 22
84.6%
2846 1
 
3.8%
2868 1
 
3.8%
2768 1
 
3.8%
2867 1
 
3.8%

Length

2024-05-11T02:12:32.809936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:33.300667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
84.6%
2846 1
 
3.8%
2868 1
 
3.8%
2768 1
 
3.8%
2867 1
 
3.8%

사업장명
Text

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-05-11T02:12:33.970076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length3.8076923
Min length2

Characters and Unicode

Total characters99
Distinct characters47
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)92.3%

Sample

1st row문복상회
2nd row동아
3rd row대성어름
4th row양지얼음
5th row삼한사
ValueCountFrequency (%)
장위빙고 2
 
7.7%
문복상회 1
 
3.8%
대성얼음 1
 
3.8%
길음빙고 1
 
3.8%
영신상회 1
 
3.8%
신흥상회 1
 
3.8%
동진상사 1
 
3.8%
태양얼음 1
 
3.8%
보영빙고 1
 
3.8%
신생 1
 
3.8%
Other values (15) 15
57.7%
2024-05-11T02:12:34.977951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
음 7
 
7.1%
빙 6
 
6.1%
고 6
 
6.1%
상 5
 
5.1%
얼 5
 
5.1%
어 4
 
4.0%
름 4
 
4.0%
회 4
 
4.0%
신 4
 
4.0%
성 3
 
3.0%
Other values (37) 51
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
음 7
 
7.1%
빙 6
 
6.1%
고 6
 
6.1%
상 5
 
5.1%
얼 5
 
5.1%
어 4
 
4.0%
름 4
 
4.0%
회 4
 
4.0%
신 4
 
4.0%
성 3
 
3.0%
Other values (37) 51
51.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
음 7
 
7.1%
빙 6
 
6.1%
고 6
 
6.1%
상 5
 
5.1%
얼 5
 
5.1%
어 4
 
4.0%
름 4
 
4.0%
회 4
 
4.0%
신 4
 
4.0%
성 3
 
3.0%
Other values (37) 51
51.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
음 7
 
7.1%
빙 6
 
6.1%
고 6
 
6.1%
상 5
 
5.1%
얼 5
 
5.1%
어 4
 
4.0%
름 4
 
4.0%
회 4
 
4.0%
신 4
 
4.0%
성 3
 
3.0%
Other values (37) 51
51.5%

최종수정일자
Date

Distinct7
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2002-06-10 00:00:00
Maximum2022-06-21 14:58:31
2024-05-11T02:12:35.369145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:12:35.686535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
I
25 
U
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
I 25
96.2%
U 1
 
3.8%

Length

2024-05-11T02:12:36.136665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:36.530293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 25
96.2%
u 1
 
3.8%

데이터갱신일자
Date

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2018-08-31 23:59:59
Maximum2021-12-05 22:03:00
2024-05-11T02:12:36.806163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:12:37.118519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
식용얼음판매업
26 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식용얼음판매업 26
100.0%

Length

2024-05-11T02:12:37.708483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:38.018861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식용얼음판매업 26
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)100.0%
Missing6
Missing (%)23.1%
Infinite0
Infinite (%)0.0%
Mean203067.6
Minimum200002.24
Maximum205097.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-05-11T02:12:38.375674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200002.24
5-th percentile200729
Q1201236.18
median203830.22
Q3204532.48
95-th percentile205013.75
Maximum205097.5
Range5095.2618
Interquartile range (IQR)3296.2986

Descriptive statistics

Standard deviation1781.2433
Coefficient of variation (CV)0.0087716764
Kurtosis-1.648951
Mean203067.6
Median Absolute Deviation (MAD)1111.9444
Skewness-0.43068662
Sum4061352
Variance3172827.6
MonotonicityNot monotonic
2024-05-11T02:12:38.826094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
203667.889459768 1
 
3.8%
203794.050334723 1
 
3.8%
201876.521665604 1
 
3.8%
204587.060050135 1
 
3.8%
201291.362915988 1
 
3.8%
204340.457190229 1
 
3.8%
200002.235318313 1
 
3.8%
200767.249972581 1
 
3.8%
204515.162344206 1
 
3.8%
204584.427414502 1
 
3.8%
Other values (10) 10
38.5%
(Missing) 6
23.1%
ValueCountFrequency (%)
200002.235318313 1
3.8%
200767.249972581 1
3.8%
200882.542886377 1
3.8%
200943.413725984 1
3.8%
201116.246836135 1
3.8%
201276.157731782 1
3.8%
201291.362915988 1
3.8%
201876.521665604 1
3.8%
203667.889459768 1
3.8%
203794.050334723 1
3.8%
ValueCountFrequency (%)
205097.497093266 1
3.8%
205009.342841748 1
3.8%
204874.985010931 1
3.8%
204587.060050135 1
3.8%
204584.427414502 1
3.8%
204515.162344206 1
3.8%
204430.225789311 1
3.8%
204428.767553083 1
3.8%
204340.457190229 1
3.8%
203866.38862167 1
3.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)100.0%
Missing6
Missing (%)23.1%
Infinite0
Infinite (%)0.0%
Mean455812.66
Minimum453617.17
Maximum457648.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-05-11T02:12:39.188527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum453617.17
5-th percentile453751.61
Q1454407.52
median456372.56
Q3456817.11
95-th percentile457466.43
Maximum457648.46
Range4031.297
Interquartile range (IQR)2409.5864

Descriptive statistics

Standard deviation1332.8936
Coefficient of variation (CV)0.0029242136
Kurtosis-1.4353856
Mean455812.66
Median Absolute Deviation (MAD)648.31527
Skewness-0.42470618
Sum9116253.2
Variance1776605.3
MonotonicityNot monotonic
2024-05-11T02:12:39.584333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
456812.978587048 1
 
3.8%
456829.493935701 1
 
3.8%
455664.635302013 1
 
3.8%
457456.845946002 1
 
3.8%
454328.45949244 1
 
3.8%
456755.46483427 1
 
3.8%
454531.932109902 1
 
3.8%
453758.685285761 1
 
3.8%
456961.265841104 1
 
3.8%
456377.08229273 1
 
3.8%
Other values (10) 10
38.5%
(Missing) 6
23.1%
ValueCountFrequency (%)
453617.168015763 1
3.8%
453758.685285761 1
3.8%
454095.061423307 1
3.8%
454328.45949244 1
3.8%
454350.876959968 1
3.8%
454426.402390733 1
3.8%
454531.932109902 1
3.8%
455664.635302013 1
3.8%
455905.345458343 1
3.8%
456368.036293742 1
3.8%
ValueCountFrequency (%)
457648.464999566 1
3.8%
457456.845946002 1
3.8%
456961.265841104 1
3.8%
456920.579497717 1
3.8%
456829.493935701 1
3.8%
456812.978587048 1
3.8%
456788.756896189 1
3.8%
456755.46483427 1
3.8%
456655.668842683 1
3.8%
456377.08229273 1
3.8%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
식용얼음판매업
25 
<NA>
 
1

Length

Max length7
Median length7
Mean length6.8846154
Min length4

Unique

Unique1 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
식용얼음판매업 25
96.2%
<NA> 1
 
3.8%

Length

2024-05-11T02:12:40.053734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:40.372922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식용얼음판매업 25
96.2%
na 1
 
3.8%

남성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

여성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

급수시설구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing25
Missing (%)96.2%
Memory size340.0 B
2024-05-11T02:12:40.638021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row상수도전용
ValueCountFrequency (%)
상수도전용 1
100.0%
2024-05-11T02:12:41.397046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
상 1
20.0%
수 1
20.0%
도 1
20.0%
전 1
20.0%
용 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 1
20.0%
수 1
20.0%
도 1
20.0%
전 1
20.0%
용 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 1
20.0%
수 1
20.0%
도 1
20.0%
전 1
20.0%
용 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
상 1
20.0%
수 1
20.0%
도 1
20.0%
전 1
20.0%
용 1
20.0%

총인원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
24 
0
 
2

Length

Max length4
Median length4
Mean length3.7692308
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> 24
92.3%
0 2
 
7.7%

Length

2024-05-11T02:12:41.817657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:42.135852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
92.3%
0 2
 
7.7%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
24 
0
 
2

Length

Max length4
Median length4
Mean length3.7692308
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> 24
92.3%
0 2
 
7.7%

Length

2024-05-11T02:12:42.494099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:42.819218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
92.3%
0 2
 
7.7%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
24 
0
 
2

Length

Max length4
Median length4
Mean length3.7692308
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> 24
92.3%
0 2
 
7.7%

Length

2024-05-11T02:12:43.158734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:43.685883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
92.3%
0 2
 
7.7%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
24 
0
 
2

Length

Max length4
Median length4
Mean length3.7692308
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> 24
92.3%
0 2
 
7.7%

Length

2024-05-11T02:12:44.028934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:44.431974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
92.3%
0 2
 
7.7%

건물소유구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing25
Missing (%)96.2%
Memory size340.0 B
2024-05-11T02:12:44.623966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row임대
ValueCountFrequency (%)
임대 1
100.0%
2024-05-11T02:12:45.261306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
임 1
50.0%
대 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
임 1
50.0%
대 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
임 1
50.0%
대 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
임 1
50.0%
대 1
50.0%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
25 
0
 
1

Length

Max length4
Median length4
Mean length3.8846154
Min length1

Unique

Unique1 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
96.2%
0 1
 
3.8%

Length

2024-05-11T02:12:45.698531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:46.018726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
96.2%
0 1
 
3.8%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
25 
0
 
1

Length

Max length4
Median length4
Mean length3.8846154
Min length1

Unique

Unique1 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
96.2%
0 1
 
3.8%

Length

2024-05-11T02:12:46.376491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:46.788720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
96.2%
0 1
 
3.8%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)4.0%
Missing1
Missing (%)3.8%
Memory size184.0 B
False
25 
(Missing)
 
1
ValueCountFrequency (%)
False 25
96.2%
(Missing) 1
 
3.8%
2024-05-11T02:12:47.006834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
0
25 
<NA>
 
1

Length

Max length4
Median length1
Mean length1.1153846
Min length1

Unique

Unique1 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 25
96.2%
<NA> 1
 
3.8%

Length

2024-05-11T02:12:47.332990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:47.651572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 25
96.2%
na 1
 
3.8%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030700003070000-111-1973-0000119731229<NA>3폐업2폐업20021202<NA><NA><NA><NA><NA>136828서울특별시 성북구 장위동 66-253<NA><NA>문복상회2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업204584.427415456377.082293식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
130700003070000-111-1985-0000119850530<NA>3폐업2폐업20021202<NA><NA><NA><NA><NA>136120서울특별시 성북구 상월곡동 57-5<NA><NA>동아2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업203866.388622455905.345458식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
230700003070000-111-1986-0000119860226<NA>3폐업2폐업19970214<NA><NA><NA><NA><NA>136818서울특별시 성북구 석관동 248-24<NA><NA>대성어름2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업205097.497093456368.036294식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
330700003070000-111-1986-0000219860408<NA>3폐업2폐업20021202<NA><NA><NA><NA><NA>136034서울특별시 성북구 동소문동4가 163<NA><NA>양지얼음2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업200943.413726454426.402391식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
430700003070000-111-1986-0000319860421<NA>3폐업2폐업20021104<NA><NA><NA>02 7428183<NA>136044서울특별시 성북구 삼선동4가 9<NA><NA>삼한사2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업200882.542886454095.061423식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
530700003070000-111-1986-0000419860712<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.86136035서울특별시 성북구 동소문동5가 56-2서울특별시 성북구 동소문로 86-19, 1층 (동소문동5가)2846한솔얼음2016-06-01 16:58:17I2018-08-31 23:59:59.0식용얼음판매업201276.157732454350.87696식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
630700003070000-111-1987-0000119870603<NA>3폐업2폐업19971103<NA><NA><NA><NA><NA>136832서울특별시 성북구 장위동 166-2<NA><NA>한일상회2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업204430.225789457648.465식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
730700003070000-111-1988-0000119880514<NA>3폐업2폐업20021104<NA><NA><NA>02 9432279<NA>136826서울특별시 성북구 장위동 36-22<NA><NA>부안2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업205009.342842456920.579498식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
830700003070000-111-1988-0000219880616<NA>3폐업2폐업20021202<NA><NA><NA><NA><NA>136815서울특별시 성북구 석관동 320-10<NA><NA>삼성2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업<NA><NA>식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
930700003070000-111-1989-0000119890329<NA>3폐업2폐업20021104<NA><NA><NA><NA><NA>136820서울특별시 성북구 석관동 341-28<NA><NA>삼표어름2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업<NA><NA>식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1630700003070000-111-2002-0000120020423<NA>3폐업2폐업20140519<NA><NA><NA>02 926331329.0136041서울특별시 성북구 삼선동1가 274-11서울특별시 성북구 삼선교로10다길 7 (삼선동1가)2867유공에너지판매2009-06-01 10:10:54I2018-08-31 23:59:59.0식용얼음판매업200767.249973453758.685286식용얼음판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0<NA><NA><NA>
1730700003070000-111-2002-0000219790312<NA>3폐업2폐업20021104<NA><NA><NA><NA><NA>136824서울특별시 성북구 성북동 128-1<NA><NA>신생2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업200002.235318454531.93211식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
1830700003070000-111-2002-0000319780306<NA>3폐업2폐업20021202<NA><NA><NA><NA><NA>136858서울특별시 성북구 종암동 3-75<NA><NA>보영빙고2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업<NA><NA>식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
1930700003070000-111-2002-0000419760218<NA>3폐업2폐업20021202<NA><NA><NA><NA><NA>136090서울특별시 성북구 종암동 3-74 ,75<NA><NA>태양얼음2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업<NA><NA>식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
2030700003070000-111-2002-0000519760413<NA>3폐업2폐업20021104<NA><NA><NA><NA><NA>136833서울특별시 성북구 장위동 238-228<NA><NA>장위빙고2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업204340.45719456755.464834식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
2130700003070000-111-2002-0000619760101<NA>3폐업2폐업20021202<NA><NA><NA><NA><NA>136035서울특별시 성북구 동소문동5가 119-15<NA><NA>동진상사2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업201291.362916454328.459492식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
2230700003070000-111-2002-0000719760214<NA>3폐업2폐업20021202<NA><NA><NA><NA><NA>136865서울특별시 성북구 하월곡동 68-2<NA><NA>신흥상회2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업<NA><NA>식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
2330700003070000-111-2002-0000819810406<NA>3폐업2폐업20021202<NA><NA><NA><NA><NA>136140서울특별시 성북구 장위동 153-16<NA><NA>영신상회2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업204587.06005457456.845946식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
2430700003070000-111-2002-0000919690602<NA>3폐업2폐업20021202<NA><NA><NA><NA><NA>136802서울특별시 성북구 길음동 540-2<NA><NA>길음빙고2002-06-10 00:00:00I2018-08-31 23:59:59.0식용얼음판매업201876.521666455664.635302식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
2530700003070000-111-2002-0001020021019<NA>3폐업2폐업20100920<NA><NA><NA>02 91535420.0136837서울특별시 성북구 장위동 233-398<NA><NA>월드빙고2008-03-20 09:17:59I2018-08-31 23:59:59.0식용얼음판매업203794.050335456829.493936식용얼음판매업<NA><NA><NA><NA>상수도전용<NA>0000임대00N0<NA><NA><NA>