Overview

Dataset statistics

Number of variables30
Number of observations45
Missing cells565
Missing cells (%)41.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.5 KiB
Average record size in memory261.9 B

Variable types

Categorical10
Numeric4
Unsupported10
Text4
DateTime2

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),업소구분명,소재지,지정일자,신청일자,항목값1
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-19469/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 has constant value ""Constant
영업상태명 has constant value ""Constant
상세영업상태코드 has constant value ""Constant
상세영업상태명 has constant value ""Constant
최종수정일자 has constant value ""Constant
데이터갱신구분 has constant value ""Constant
데이터갱신일자 has constant value ""Constant
항목값1 has constant value ""Constant
좌표정보(X) is highly imbalanced (77.0%)Imbalance
좌표정보(Y) is highly imbalanced (77.0%)Imbalance
인허가취소일자 has 45 (100.0%) missing valuesMissing
폐업일자 has 45 (100.0%) missing valuesMissing
휴업시작일자 has 45 (100.0%) missing valuesMissing
휴업종료일자 has 45 (100.0%) missing valuesMissing
재개업일자 has 45 (100.0%) missing valuesMissing
전화번호 has 45 (100.0%) missing valuesMissing
소재지면적 has 45 (100.0%) missing valuesMissing
도로명주소 has 42 (93.3%) missing valuesMissing
도로명우편번호 has 45 (100.0%) missing valuesMissing
업태구분명 has 45 (100.0%) missing valuesMissing
소재지 has 36 (80.0%) missing valuesMissing
지정일자 has 45 (100.0%) missing valuesMissing
신청일자 has 37 (82.2%) missing valuesMissing
관리번호 has unique valuesUnique
지번주소 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐업일자 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
전화번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
도로명우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지정일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 06:13:38.776524
Analysis finished2024-05-11 06:13:39.283431
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
3170000
45 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 45
100.0%

Length

2024-05-11T15:13:39.388392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:13:39.547716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 45
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1700001 × 1017
Minimum3.1700001 × 1017
Maximum3.1700001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-05-11T15:13:39.683668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1700001 × 1017
5-th percentile3.1700001 × 1017
Q13.1700001 × 1017
median3.1700001 × 1017
Q33.1700001 × 1017
95-th percentile3.1700001 × 1017
Maximum3.1700001 × 1017
Range45
Interquartile range (IQR)0

Descriptive statistics

Standard deviation129.44637
Coefficient of variation (CV)4.0834816 × 10-16
Kurtosis-2.0952381
Mean3.1700001 × 1017
Median Absolute Deviation (MAD)0
Skewness-1.0348184
Sum-4.1817434 × 1018
Variance16756.364
MonotonicityStrictly increasing
2024-05-11T15:13:39.900192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
317000014200100002 1
 
2.2%
317000014200100037 1
 
2.2%
317000014200100028 1
 
2.2%
317000014200100029 1
 
2.2%
317000014200100030 1
 
2.2%
317000014200100031 1
 
2.2%
317000014200100032 1
 
2.2%
317000014200100033 1
 
2.2%
317000014200100034 1
 
2.2%
317000014200100035 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
317000014200100002 1
2.2%
317000014200100003 1
2.2%
317000014200100004 1
2.2%
317000014200100005 1
2.2%
317000014200100006 1
2.2%
317000014200100007 1
2.2%
317000014200100008 1
2.2%
317000014200100009 1
2.2%
317000014200100010 1
2.2%
317000014200100012 1
2.2%
ValueCountFrequency (%)
317000014200100047 1
2.2%
317000014200100046 1
2.2%
317000014200100045 1
2.2%
317000014200100044 1
2.2%
317000014200100043 1
2.2%
317000014200100042 1
2.2%
317000014200100041 1
2.2%
317000014200100040 1
2.2%
317000014200100039 1
2.2%
317000014200100038 1
2.2%

인허가일자
Real number (ℝ)

Distinct29
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20010635
Minimum20010109
Maximum20011204
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-05-11T15:13:40.142837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010109
5-th percentile20010135
Q120010424
median20010702
Q320010820
95-th percentile20011112
Maximum20011204
Range1095
Interquartile range (IQR)396

Descriptive statistics

Standard deviation294.57031
Coefficient of variation (CV)1.4720688 × 10-5
Kurtosis-0.69922287
Mean20010635
Median Absolute Deviation (MAD)215
Skewness-0.043662406
Sum9.0047855 × 108
Variance86771.665
MonotonicityNot monotonic
2024-05-11T15:13:40.336764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
20010424 4
 
8.9%
20010804 3
 
6.7%
20010407 2
 
4.4%
20010622 2
 
4.4%
20010702 2
 
4.4%
20010706 2
 
4.4%
20010723 2
 
4.4%
20010509 2
 
4.4%
20011112 2
 
4.4%
20010820 2
 
4.4%
Other values (19) 22
48.9%
ValueCountFrequency (%)
20010109 1
 
2.2%
20010119 2
4.4%
20010201 2
4.4%
20010209 1
 
2.2%
20010228 1
 
2.2%
20010327 1
 
2.2%
20010407 2
4.4%
20010424 4
8.9%
20010509 2
4.4%
20010518 1
 
2.2%
ValueCountFrequency (%)
20011204 1
 
2.2%
20011112 2
4.4%
20011110 1
 
2.2%
20011107 1
 
2.2%
20011010 1
 
2.2%
20010920 2
4.4%
20010917 1
 
2.2%
20010829 1
 
2.2%
20010820 2
4.4%
20010804 3
6.7%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

영업상태코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
1
45 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 45
100.0%

Length

2024-05-11T15:13:40.495613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:13:40.628048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 45
100.0%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
영업/정상
45 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 45
100.0%

Length

2024-05-11T15:13:40.758646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:13:40.902826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 45
100.0%

상세영업상태코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
11
45 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row11
3rd row11
4th row11
5th row11

Common Values

ValueCountFrequency (%)
11 45
100.0%

Length

2024-05-11T15:13:41.405591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:13:41.552578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 45
100.0%

상세영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
영업
45 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 45
100.0%

Length

2024-05-11T15:13:41.696723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:13:41.837109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 45
100.0%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

소재지우편번호
Real number (ℝ)

Distinct11
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159039.91
Minimum153011
Maximum423759
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-05-11T15:13:42.001298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum153011
5-th percentile153011.2
Q1153014
median153023
Q3153034
95-th percentile153039
Maximum423759
Range270748
Interquartile range (IQR)20

Descriptive statistics

Standard deviation40358.857
Coefficient of variation (CV)0.25376559
Kurtosis44.999994
Mean159039.91
Median Absolute Deviation (MAD)10
Skewness6.7082032
Sum7156796
Variance1.6288373 × 109
MonotonicityNot monotonic
2024-05-11T15:13:42.197626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
153039 8
17.8%
153023 7
15.6%
153014 7
15.6%
153031 4
8.9%
153013 4
8.9%
153034 4
8.9%
153012 4
8.9%
153011 3
 
6.7%
153019 2
 
4.4%
153035 1
 
2.2%
ValueCountFrequency (%)
153011 3
 
6.7%
153012 4
8.9%
153013 4
8.9%
153014 7
15.6%
153019 2
 
4.4%
153023 7
15.6%
153031 4
8.9%
153034 4
8.9%
153035 1
 
2.2%
153039 8
17.8%
ValueCountFrequency (%)
423759 1
 
2.2%
153039 8
17.8%
153035 1
 
2.2%
153034 4
8.9%
153031 4
8.9%
153023 7
15.6%
153019 2
 
4.4%
153014 7
15.6%
153013 4
8.9%
153012 4
8.9%

지번주소
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2024-05-11T15:13:42.511251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length25
Mean length25.288889
Min length20

Characters and Unicode

Total characters1138
Distinct characters48
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

Unique45 ?
Unique (%)100.0%

Sample

1st row서울특별시 금천구 가산동 345-89번지
2nd row서울특별시 금천구 시흥동 862-14 번지
3rd row서울특별시 금천구 시흥동 908-39 번지
4th row서울특별시 금천구 시흥동 985-2 번지
5th row서울특별시 금천구 독산동 234-27 번지
ValueCountFrequency (%)
서울특별시 44
19.7%
금천구 44
19.7%
번지 41
18.4%
독산동 20
9.0%
시흥동 17
 
7.6%
가산동 7
 
3.1%
169-38 1
 
0.4%
180-47 1
 
0.4%
194-13 1
 
0.4%
1022-117 1
 
0.4%
Other values (46) 46
20.6%
2024-05-11T15:13:43.010581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
276
24.3%
시 62
 
5.4%
동 45
 
4.0%
지 45
 
4.0%
서 44
 
3.9%
특 44
 
3.9%
별 44
 
3.9%
금 44
 
3.9%
천 44
 
3.9%
구 44
 
3.9%
Other values (38) 446
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 600
52.7%
Space Separator 276
24.3%
Decimal Number 220
 
19.3%
Dash Punctuation 42
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 62
10.3%
동 45
 
7.5%
지 45
 
7.5%
서 44
 
7.3%
특 44
 
7.3%
별 44
 
7.3%
금 44
 
7.3%
천 44
 
7.3%
구 44
 
7.3%
울 44
 
7.3%
Other values (26) 140
23.3%
Decimal Number
ValueCountFrequency (%)
1 38
17.3%
8 26
11.8%
0 25
11.4%
9 24
10.9%
3 23
10.5%
4 22
10.0%
2 21
9.5%
5 15
 
6.8%
6 15
 
6.8%
7 11
 
5.0%
Space Separator
ValueCountFrequency (%)
276
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 600
52.7%
Common 538
47.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 62
10.3%
동 45
 
7.5%
지 45
 
7.5%
서 44
 
7.3%
특 44
 
7.3%
별 44
 
7.3%
금 44
 
7.3%
천 44
 
7.3%
구 44
 
7.3%
울 44
 
7.3%
Other values (26) 140
23.3%
Common
ValueCountFrequency (%)
276
51.3%
- 42
 
7.8%
1 38
 
7.1%
8 26
 
4.8%
0 25
 
4.6%
9 24
 
4.5%
3 23
 
4.3%
4 22
 
4.1%
2 21
 
3.9%
5 15
 
2.8%
Other values (2) 26
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 600
52.7%
ASCII 538
47.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
276
51.3%
- 42
 
7.8%
1 38
 
7.1%
8 26
 
4.8%
0 25
 
4.6%
9 24
 
4.5%
3 23
 
4.3%
4 22
 
4.1%
2 21
 
3.9%
5 15
 
2.8%
Other values (2) 26
 
4.8%
Hangul
ValueCountFrequency (%)
시 62
10.3%
동 45
 
7.5%
지 45
 
7.5%
서 44
 
7.3%
특 44
 
7.3%
별 44
 
7.3%
금 44
 
7.3%
천 44
 
7.3%
구 44
 
7.3%
울 44
 
7.3%
Other values (26) 140
23.3%

도로명주소
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing42
Missing (%)93.3%
Memory size492.0 B
2024-05-11T15:13:43.247274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length27.333333
Min length27

Characters and Unicode

Total characters82
Distinct characters28
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

Unique3 ?
Unique (%)100.0%

Sample

1st row서울특별시 금천구 가산디지털2로 62 (가산동)
2nd row서울특별시 금천구 시흥대로140길 18 (독산동)
3rd row서울특별시 금천구 가산디지털1로 24 (가산동)
ValueCountFrequency (%)
서울특별시 3
20.0%
금천구 3
20.0%
가산동 2
13.3%
가산디지털2로 1
 
6.7%
62 1
 
6.7%
시흥대로140길 1
 
6.7%
18 1
 
6.7%
독산동 1
 
6.7%
가산디지털1로 1
 
6.7%
24 1
 
6.7%
2024-05-11T15:13:43.615447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
18.3%
산 5
 
6.1%
시 4
 
4.9%
가 4
 
4.9%
서 3
 
3.7%
울 3
 
3.7%
1 3
 
3.7%
) 3
 
3.7%
동 3
 
3.7%
( 3
 
3.7%
Other values (18) 36
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50
61.0%
Space Separator 15
 
18.3%
Decimal Number 11
 
13.4%
Close Punctuation 3
 
3.7%
Open Punctuation 3
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 5
 
10.0%
시 4
 
8.0%
가 4
 
8.0%
서 3
 
6.0%
울 3
 
6.0%
동 3
 
6.0%
로 3
 
6.0%
구 3
 
6.0%
천 3
 
6.0%
금 3
 
6.0%
Other values (9) 16
32.0%
Decimal Number
ValueCountFrequency (%)
1 3
27.3%
2 3
27.3%
4 2
18.2%
6 1
 
9.1%
0 1
 
9.1%
8 1
 
9.1%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50
61.0%
Common 32
39.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 5
 
10.0%
시 4
 
8.0%
가 4
 
8.0%
서 3
 
6.0%
울 3
 
6.0%
동 3
 
6.0%
로 3
 
6.0%
구 3
 
6.0%
천 3
 
6.0%
금 3
 
6.0%
Other values (9) 16
32.0%
Common
ValueCountFrequency (%)
15
46.9%
1 3
 
9.4%
) 3
 
9.4%
( 3
 
9.4%
2 3
 
9.4%
4 2
 
6.2%
6 1
 
3.1%
0 1
 
3.1%
8 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50
61.0%
ASCII 32
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
46.9%
1 3
 
9.4%
) 3
 
9.4%
( 3
 
9.4%
2 3
 
9.4%
4 2
 
6.2%
6 1
 
3.1%
0 1
 
3.1%
8 1
 
3.1%
Hangul
ValueCountFrequency (%)
산 5
 
10.0%
시 4
 
8.0%
가 4
 
8.0%
서 3
 
6.0%
울 3
 
6.0%
동 3
 
6.0%
로 3
 
6.0%
구 3
 
6.0%
천 3
 
6.0%
금 3
 
6.0%
Other values (9) 16
32.0%

도로명우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

사업장명
Text

Distinct43
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size492.0 B
2024-05-11T15:13:43.961490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.5111111
Min length3

Characters and Unicode

Total characters203
Distinct characters93
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

Unique41 ?
Unique (%)91.1%

Sample

1st row서울금형매점
2nd row소비자유통
3rd row정훈슈퍼
4th row경기상회
5th row진주상회
ValueCountFrequency (%)
관악슈퍼 2
 
4.4%
그랜드마트 2
 
4.4%
똘똘이슈퍼 1
 
2.2%
태광상회 1
 
2.2%
생협슈퍼 1
 
2.2%
대성슈퍼 1
 
2.2%
서울금형매점 1
 
2.2%
정매점 1
 
2.2%
금천두레마트 1
 
2.2%
가산마트 1
 
2.2%
Other values (33) 33
73.3%
2024-05-11T15:13:44.468103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
퍼 19
 
9.4%
슈 17
 
8.4%
마 15
 
7.4%
트 13
 
6.4%
매 5
 
2.5%
상 5
 
2.5%
회 4
 
2.0%
점 4
 
2.0%
유 3
 
1.5%
이 3
 
1.5%
Other values (83) 115
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 201
99.0%
Uppercase Letter 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
퍼 19
 
9.5%
슈 17
 
8.5%
마 15
 
7.5%
트 13
 
6.5%
매 5
 
2.5%
상 5
 
2.5%
회 4
 
2.0%
점 4
 
2.0%
유 3
 
1.5%
이 3
 
1.5%
Other values (81) 113
56.2%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
S 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 201
99.0%
Latin 2
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
퍼 19
 
9.5%
슈 17
 
8.5%
마 15
 
7.5%
트 13
 
6.5%
매 5
 
2.5%
상 5
 
2.5%
회 4
 
2.0%
점 4
 
2.0%
유 3
 
1.5%
이 3
 
1.5%
Other values (81) 113
56.2%
Latin
ValueCountFrequency (%)
P 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 201
99.0%
ASCII 2
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
퍼 19
 
9.5%
슈 17
 
8.5%
마 15
 
7.5%
트 13
 
6.5%
매 5
 
2.5%
상 5
 
2.5%
회 4
 
2.0%
점 4
 
2.0%
유 3
 
1.5%
이 3
 
1.5%
Other values (81) 113
56.2%
ASCII
ValueCountFrequency (%)
P 1
50.0%
S 1
50.0%

최종수정일자
Date

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
Minimum2007-07-07 12:06:16
Maximum2007-07-07 12:06:16
2024-05-11T15:13:44.819750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:13:45.065089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

데이터갱신구분
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
I
45 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 45
100.0%

Length

2024-05-11T15:13:45.323148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:13:45.595428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 45
100.0%

데이터갱신일자
Date

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
Minimum2018-08-31 23:59:59
Maximum2018-08-31 23:59:59
2024-05-11T15:13:45.724339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:13:45.854625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

좌표정보(X)
Categorical

IMBALANCE 

Distinct4
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
42 
189526.335897785
 
1
191033.170537322
 
1
189991.650798406
 
1

Length

Max length16
Median length4
Mean length4.8
Min length4

Unique

Unique3 ?
Unique (%)6.7%

Sample

1st row189526.335897785
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
93.3%
189526.335897785 1
 
2.2%
191033.170537322 1
 
2.2%
189991.650798406 1
 
2.2%

Length

2024-05-11T15:13:46.066885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:13:46.243034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
93.3%
189526.335897785 1
 
2.2%
191033.170537322 1
 
2.2%
189991.650798406 1
 
2.2%

좌표정보(Y)
Categorical

IMBALANCE 

Distinct4
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
42 
441327.817972925
 
1
441266.666695595
 
1
440695.614055984
 
1

Length

Max length16
Median length4
Mean length4.8
Min length4

Unique

Unique3 ?
Unique (%)6.7%

Sample

1st row441327.817972925
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
93.3%
441327.817972925 1
 
2.2%
441266.666695595 1
 
2.2%
440695.614055984 1
 
2.2%

Length

2024-05-11T15:13:46.424736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:13:46.605015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
93.3%
441327.817972925 1
 
2.2%
441266.666695595 1
 
2.2%
440695.614055984 1
 
2.2%

업소구분명
Categorical

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
36 
지정
9 

Length

Max length4
Median length4
Mean length3.6
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
80.0%
지정 9
 
20.0%

Length

2024-05-11T15:13:46.797447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:13:47.030618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
80.0%
지정 9
 
20.0%

소재지
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing36
Missing (%)80.0%
Memory size492.0 B
2024-05-11T15:13:47.286204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.5555556
Min length4

Characters and Unicode

Total characters50
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

Unique9 ?
Unique (%)100.0%

Sample

1st row345-89
2nd row862-14
3rd row908-39
4th row985-2
5th row234-27
ValueCountFrequency (%)
345-89 1
11.1%
862-14 1
11.1%
908-39 1
11.1%
985-2 1
11.1%
234-27 1
11.1%
44-1 1
11.1%
293-1 1
11.1%
987-12 1
11.1%
893-14 1
11.1%
2024-05-11T15:13:47.781279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 9
18.0%
9 7
14.0%
4 6
12.0%
8 6
12.0%
2 6
12.0%
3 5
10.0%
1 5
10.0%
5 2
 
4.0%
7 2
 
4.0%
6 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41
82.0%
Dash Punctuation 9
 
18.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 7
17.1%
4 6
14.6%
8 6
14.6%
2 6
14.6%
3 5
12.2%
1 5
12.2%
5 2
 
4.9%
7 2
 
4.9%
6 1
 
2.4%
0 1
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 9
18.0%
9 7
14.0%
4 6
12.0%
8 6
12.0%
2 6
12.0%
3 5
10.0%
1 5
10.0%
5 2
 
4.0%
7 2
 
4.0%
6 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 9
18.0%
9 7
14.0%
4 6
12.0%
8 6
12.0%
2 6
12.0%
3 5
10.0%
1 5
10.0%
5 2
 
4.0%
7 2
 
4.0%
6 1
 
2.0%

지정일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

신청일자
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)75.0%
Missing37
Missing (%)82.2%
Infinite0
Infinite (%)0.0%
Mean20011015
Minimum20010829
Maximum20011112
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-05-11T15:13:47.955884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010829
5-th percentile20010861
Q120010920
median20011058
Q320011110
95-th percentile20011112
Maximum20011112
Range283
Interquartile range (IQR)190.5

Descriptive statistics

Standard deviation112.7437
Coefficient of variation (CV)5.6340822 × 10-6
Kurtosis-1.3139723
Mean20011015
Median Absolute Deviation (MAD)53.5
Skewness-0.62313369
Sum1.6008812 × 108
Variance12711.143
MonotonicityDecreasing
2024-05-11T15:13:48.104592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20011112 2
 
4.4%
20010920 2
 
4.4%
20011110 1
 
2.2%
20011107 1
 
2.2%
20011010 1
 
2.2%
20010829 1
 
2.2%
(Missing) 37
82.2%
ValueCountFrequency (%)
20010829 1
2.2%
20010920 2
4.4%
20011010 1
2.2%
20011107 1
2.2%
20011110 1
2.2%
20011112 2
4.4%
ValueCountFrequency (%)
20011112 2
4.4%
20011110 1
2.2%
20011107 1
2.2%
20011010 1
2.2%
20010920 2
4.4%
20010829 1
2.2%

항목값1
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
관급봉투
45 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관급봉투 45
100.0%

Length

2024-05-11T15:13:48.320861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:13:48.499112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관급봉투 45
100.0%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업소구분명소재지지정일자신청일자항목값1
0317000031700001420010000220011112<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153023서울특별시 금천구 가산동 345-89번지서울특별시 금천구 가산디지털2로 62 (가산동)<NA>서울금형매점2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA>189526.335898441327.817973지정345-89<NA>20011112관급봉투
1317000031700001420010000320011112<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153039서울특별시 금천구 시흥동 862-14 번지<NA><NA>소비자유통2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA>지정862-14<NA>20011112관급봉투
2317000031700001420010000420011110<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153035서울특별시 금천구 시흥동 908-39 번지<NA><NA>정훈슈퍼2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA>지정908-39<NA>20011110관급봉투
3317000031700001420010000520011107<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153031서울특별시 금천구 시흥동 985-2 번지<NA><NA>경기상회2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA>지정985-2<NA>20011107관급봉투
4317000031700001420010000620011010<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153013서울특별시 금천구 독산동 234-27 번지<NA><NA>진주상회2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA>지정234-27<NA>20011010관급봉투
5317000031700001420010000720010920<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153023서울특별시 금천구 가산동 44-1 번지<NA><NA>늘푸른슈퍼2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA>지정44-1<NA>20010920관급봉투
6317000031700001420010000820010920<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153014서울특별시 금천구 독산동 293-1 번지<NA><NA>잉크마을2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA>지정293-1<NA>20010920관급봉투
7317000031700001420010000920010917<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153019서울특별시 금천구 독산동 987-12 번지<NA><NA>그랜드마트2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA>지정987-12<NA><NA>관급봉투
8317000031700001420010001020010829<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153013서울특별시 금천구 독산동 893-14 번지<NA><NA>와이마트2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA>지정893-14<NA>20010829관급봉투
9317000031700001420010001220010820<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153034서울특별시 금천구 시흥동 820-17 번지<NA><NA>경남마트2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>관급봉투
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업소구분명소재지지정일자신청일자항목값1
35317000031700001420010003820010407<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>423759경기도 광명시 하안동 13단지라상가105호<NA><NA>하안SP2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>관급봉투
36317000031700001420010003920010327<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153039서울특별시 금천구 시흥동 839-49 번지<NA><NA>용화슈퍼2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>관급봉투
37317000031700001420010004020010228<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153014서울특별시 금천구 독산동 1021-53 번지<NA><NA>대성마트2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>관급봉투
38317000031700001420010004120010209<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153023서울특별시 금천구 가산동 664번지서울특별시 금천구 가산디지털1로 24 (가산동)<NA>영상매점2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA>189991.650798440695.614056<NA><NA><NA><NA>관급봉투
39317000031700001420010004220010201<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153012서울특별시 금천구 독산동 1043-2 번지<NA><NA>농산물할인매장2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>관급봉투
40317000031700001420010004320010201<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153014서울특별시 금천구 독산동 198-44 번지<NA><NA>태광상회2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>관급봉투
41317000031700001420010004420010119<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153013서울특별시 금천구 독산동 985-20 번지<NA><NA>똘똘이슈퍼2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>관급봉투
42317000031700001420010004520010119<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153013서울특별시 금천구 독산동 963-6 번지<NA><NA>대성슈퍼2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>관급봉투
43317000031700001420010004620010109<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153039서울특별시 금천구 시흥동 868-35 번지<NA><NA>생협슈퍼2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>관급봉투
44317000031700001420010004720011204<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>153039서울특별시 금천구 시흥동 840-8 번지<NA><NA>한샘마트2007-07-07 12:06:16I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>관급봉투