Overview

Dataset statistics

Number of variables27
Number of observations46
Missing cells430
Missing cells (%)34.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.6 KiB
Average record size in memory234.9 B

Variable types

Categorical7
Numeric5
DateTime3
Unsupported8
Text4

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),자본금,거래처
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-19053/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 46 (100.0%) missing valuesMissing
폐업일자 has 22 (47.8%) missing valuesMissing
휴업시작일자 has 46 (100.0%) missing valuesMissing
휴업종료일자 has 46 (100.0%) missing valuesMissing
재개업일자 has 46 (100.0%) missing valuesMissing
소재지면적 has 27 (58.7%) missing valuesMissing
소재지우편번호 has 46 (100.0%) missing valuesMissing
도로명주소 has 5 (10.9%) missing valuesMissing
도로명우편번호 has 46 (100.0%) missing valuesMissing
좌표정보(X) has 4 (8.7%) missing valuesMissing
좌표정보(Y) has 4 (8.7%) missing valuesMissing
자본금 has 46 (100.0%) missing valuesMissing
거래처 has 46 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 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
소재지우편번호 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
자본금 is an unsupported type, check if it needs cleaning or further analysisUnsupported
거래처 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 05:36:35.537294
Analysis finished2024-05-11 05:36:36.107710
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
3010000
46 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 46
100.0%

Length

2024-05-11T14:36:36.228000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:36.375441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 46
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9874967 × 1018
Minimum1.976301 × 1018
Maximum2.009301 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T14:36:36.567652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.976301 × 1018
5-th percentile1.976301 × 1018
Q11.976301 × 1018
median1.986801 × 1018
Q31.994051 × 1018
95-th percentile2.003301 × 1018
Maximum2.009301 × 1018
Range3.3000003 × 1016
Interquartile range (IQR)1.775 × 1016

Descriptive statistics

Standard deviation9.6208561 × 1015
Coefficient of variation (CV)0.0048406905
Kurtosis-0.84081808
Mean1.9874967 × 1018
Median Absolute Deviation (MAD)9 × 1015
Skewness0.3752028
Sum-8.0887404 × 1017
Variance9.2560872 × 1031
MonotonicityStrictly increasing
2024-05-11T14:36:36.824659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1976301007101500002 1
 
2.2%
1995301007101200055 1
 
2.2%
1989301007101200018 1
 
2.2%
1990301007101200048 1
 
2.2%
1991301007101200116 1
 
2.2%
1992301007101200011 1
 
2.2%
1992301007101200115 1
 
2.2%
1992301007101500001 1
 
2.2%
1993301007101500018 1
 
2.2%
1993301007101500019 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
1976301007101500002 1
2.2%
1976301007101500003 1
2.2%
1976301007101500004 1
2.2%
1976301007101500005 1
2.2%
1976301007101500006 1
2.2%
1976301007101500008 1
2.2%
1976301007101500009 1
2.2%
1976301007101500010 1
2.2%
1976301007101500011 1
2.2%
1976301007101500012 1
2.2%
ValueCountFrequency (%)
2009301010001500001 1
2.2%
2006301007101500001 1
2.2%
2003301007101500002 1
2.2%
2003301007101500001 1
2.2%
2000301007101200058 1
2.2%
2000301007101200057 1
2.2%
1999301007101200050 1
2.2%
1997301007101200056 1
2.2%
1996301007101500021 1
2.2%
1995301007101500020 1
2.2%

인허가일자
Date

Distinct37
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum1976-04-28 00:00:00
Maximum2009-01-08 00:00:00
2024-05-11T14:36:37.058524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:37.282363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
3
30 
1
16 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
3 30
65.2%
1 16
34.8%

Length

2024-05-11T14:36:37.458561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:37.629547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 30
65.2%
1 16
34.8%

영업상태명
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
폐업
30 
영업/정상
16 

Length

Max length5
Median length2
Mean length3.0434783
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 30
65.2%
영업/정상 16
34.8%

Length

2024-05-11T14:36:37.810169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:37.977221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 30
65.2%
영업/정상 16
34.8%

상세영업상태코드
Categorical

Distinct4
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
3
30 
1
13 
6
 
2
7
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st row6
2nd row3
3rd row3
4th row6
5th row1

Common Values

ValueCountFrequency (%)
3 30
65.2%
1 13
28.3%
6 2
 
4.3%
7 1
 
2.2%

Length

2024-05-11T14:36:38.146049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:38.320091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 30
65.2%
1 13
28.3%
6 2
 
4.3%
7 1
 
2.2%

상세영업상태명
Categorical

Distinct4
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
폐지
30 
신규등록
13 
휴지사업재개
 
2
영업개시
 
1

Length

Max length6
Median length2
Mean length2.7826087
Min length2

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st row휴지사업재개
2nd row폐지
3rd row폐지
4th row휴지사업재개
5th row신규등록

Common Values

ValueCountFrequency (%)
폐지 30
65.2%
신규등록 13
28.3%
휴지사업재개 2
 
4.3%
영업개시 1
 
2.2%

Length

2024-05-11T14:36:38.535459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:38.716466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐지 30
65.2%
신규등록 13
28.3%
휴지사업재개 2
 
4.3%
영업개시 1
 
2.2%

폐업일자
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)95.8%
Missing22
Missing (%)47.8%
Infinite0
Infinite (%)0.0%
Mean20105208
Minimum20020125
Maximum20210414
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T14:36:38.858835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020125
5-th percentile20022664
Q120040890
median20095558
Q320156100
95-th percentile20200829
Maximum20210414
Range190289
Interquartile range (IQR)115210

Descriptive statistics

Standard deviation64645.331
Coefficient of variation (CV)0.0032153525
Kurtosis-1.3742106
Mean20105208
Median Absolute Deviation (MAD)55083.5
Skewness0.28234917
Sum4.82525 × 108
Variance4.1790188 × 109
MonotonicityNot monotonic
2024-05-11T14:36:39.069023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20080104 2
 
4.3%
20200422 1
 
2.2%
20140324 1
 
2.2%
20060905 1
 
2.2%
20170705 1
 
2.2%
20130802 1
 
2.2%
20111007 1
 
2.2%
20040401 1
 
2.2%
20040429 1
 
2.2%
20151231 1
 
2.2%
Other values (13) 13
28.3%
(Missing) 22
47.8%
ValueCountFrequency (%)
20020125 1
2.2%
20021227 1
2.2%
20030804 1
2.2%
20040401 1
2.2%
20040429 1
2.2%
20040519 1
2.2%
20041013 1
2.2%
20050608 1
2.2%
20060905 1
2.2%
20080104 2
4.3%
ValueCountFrequency (%)
20210414 1
2.2%
20200901 1
2.2%
20200422 1
2.2%
20191218 1
2.2%
20190415 1
2.2%
20170705 1
2.2%
20151231 1
2.2%
20140324 1
2.2%
20130802 1
2.2%
20120904 1
2.2%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

전화번호
Text

Distinct44
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-05-11T14:36:39.396307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length10.608696
Min length8

Characters and Unicode

Total characters488
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)93.5%

Sample

1st row02-2273-5189
2nd row0222679925
3rd row0222655473
4th row02-2279-9965
5th row02-2236-2759
ValueCountFrequency (%)
02 14
 
23.3%
0222675047 3
 
5.0%
02-2275-5150 1
 
1.7%
22661448 1
 
1.7%
0222325152 1
 
1.7%
7787305 1
 
1.7%
2346197 1
 
1.7%
2380793 1
 
1.7%
2724922 1
 
1.7%
0222663088 1
 
1.7%
Other values (35) 35
58.3%
2024-05-11T14:36:39.987206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 142
29.1%
0 69
14.1%
7 48
 
9.8%
5 38
 
7.8%
3 36
 
7.4%
- 30
 
6.1%
6 29
 
5.9%
8 24
 
4.9%
9 23
 
4.7%
4 22
 
4.5%
Other values (2) 27
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 444
91.0%
Dash Punctuation 30
 
6.1%
Space Separator 14
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 142
32.0%
0 69
15.5%
7 48
 
10.8%
5 38
 
8.6%
3 36
 
8.1%
6 29
 
6.5%
8 24
 
5.4%
9 23
 
5.2%
4 22
 
5.0%
1 13
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 488
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 142
29.1%
0 69
14.1%
7 48
 
9.8%
5 38
 
7.8%
3 36
 
7.4%
- 30
 
6.1%
6 29
 
5.9%
8 24
 
4.9%
9 23
 
4.7%
4 22
 
4.5%
Other values (2) 27
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 488
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 142
29.1%
0 69
14.1%
7 48
 
9.8%
5 38
 
7.8%
3 36
 
7.4%
- 30
 
6.1%
6 29
 
5.9%
8 24
 
4.9%
9 23
 
4.7%
4 22
 
4.5%
Other values (2) 27
 
5.5%

소재지면적
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)94.7%
Missing27
Missing (%)58.7%
Infinite0
Infinite (%)0.0%
Mean746.57474
Minimum330.58
Maximum1256.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T14:36:40.220421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum330.58
5-th percentile339.508
Q1466.75
median758.7
Q3978.17
95-th percentile1256.2
Maximum1256.2
Range925.62
Interquartile range (IQR)511.42

Descriptive statistics

Standard deviation309.55425
Coefficient of variation (CV)0.41463263
Kurtosis-1.2523666
Mean746.57474
Median Absolute Deviation (MAD)254.2
Skewness0.060523757
Sum14184.92
Variance95823.833
MonotonicityNot monotonic
2024-05-11T14:36:40.405918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1256.2 2
 
4.3%
372.5 1
 
2.2%
1028.0 1
 
2.2%
758.7 1
 
2.2%
437.6 1
 
2.2%
964.64 1
 
2.2%
661.1 1
 
2.2%
724.0 1
 
2.2%
343.0 1
 
2.2%
504.5 1
 
2.2%
Other values (8) 8
 
17.4%
(Missing) 27
58.7%
ValueCountFrequency (%)
330.58 1
2.2%
340.5 1
2.2%
343.0 1
2.2%
372.5 1
2.2%
437.6 1
2.2%
495.9 1
2.2%
504.5 1
2.2%
661.1 1
2.2%
724.0 1
2.2%
758.7 1
2.2%
ValueCountFrequency (%)
1256.2 2
4.3%
1028.0 1
2.2%
1004.9 1
2.2%
991.7 1
2.2%
964.64 1
2.2%
953.0 1
2.2%
942.1 1
2.2%
819.8 1
2.2%
758.7 1
2.2%
724.0 1
2.2%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

지번주소
Text

Distinct44
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-05-11T14:36:40.793014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length23
Mean length19.76087
Min length15

Characters and Unicode

Total characters909
Distinct characters64
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)91.3%

Sample

1st row서울특별시 중구 필동2가 51-1
2nd row서울특별시 중구 오장동 206-2
3rd row서울특별시 중구 을지로6가 32
4th row서울특별시 중구 장충동1가 31-1
5th row서울특별시 중구 신당동 357-6
ValueCountFrequency (%)
서울특별시 46
24.2%
중구 46
24.2%
신당동 13
 
6.8%
을지로3가 4
 
2.1%
황학동 3
 
1.6%
장충동2가 2
 
1.1%
광희동1가 2
 
1.1%
필동2가 2
 
1.1%
남대문로5가 2
 
1.1%
만리동2가 2
 
1.1%
Other values (65) 68
35.8%
2024-05-11T14:36:41.416317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
175
19.3%
1 52
 
5.7%
서 46
 
5.1%
울 46
 
5.1%
특 46
 
5.1%
별 46
 
5.1%
시 46
 
5.1%
중 46
 
5.1%
구 46
 
5.1%
동 38
 
4.2%
Other values (54) 322
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 493
54.2%
Decimal Number 203
22.3%
Space Separator 175
 
19.3%
Dash Punctuation 37
 
4.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 46
9.3%
울 46
9.3%
특 46
9.3%
별 46
9.3%
시 46
9.3%
중 46
9.3%
구 46
9.3%
동 38
 
7.7%
가 21
 
4.3%
당 13
 
2.6%
Other values (41) 99
20.1%
Decimal Number
ValueCountFrequency (%)
1 52
25.6%
2 36
17.7%
5 24
11.8%
3 18
 
8.9%
6 16
 
7.9%
9 15
 
7.4%
7 13
 
6.4%
4 10
 
4.9%
8 10
 
4.9%
0 9
 
4.4%
Space Separator
ValueCountFrequency (%)
175
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 493
54.2%
Common 415
45.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 46
9.3%
울 46
9.3%
특 46
9.3%
별 46
9.3%
시 46
9.3%
중 46
9.3%
구 46
9.3%
동 38
 
7.7%
가 21
 
4.3%
당 13
 
2.6%
Other values (41) 99
20.1%
Common
ValueCountFrequency (%)
175
42.2%
1 52
 
12.5%
- 37
 
8.9%
2 36
 
8.7%
5 24
 
5.8%
3 18
 
4.3%
6 16
 
3.9%
9 15
 
3.6%
7 13
 
3.1%
4 10
 
2.4%
Other values (2) 19
 
4.6%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 493
54.2%
ASCII 416
45.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
175
42.1%
1 52
 
12.5%
- 37
 
8.9%
2 36
 
8.7%
5 24
 
5.8%
3 18
 
4.3%
6 16
 
3.8%
9 15
 
3.6%
7 13
 
3.1%
4 10
 
2.4%
Other values (3) 20
 
4.8%
Hangul
ValueCountFrequency (%)
서 46
9.3%
울 46
9.3%
특 46
9.3%
별 46
9.3%
시 46
9.3%
중 46
9.3%
구 46
9.3%
동 38
 
7.7%
가 21
 
4.3%
당 13
 
2.6%
Other values (41) 99
20.1%

도로명주소
Text

MISSING 

Distinct40
Distinct (%)97.6%
Missing5
Missing (%)10.9%
Memory size500.0 B
2024-05-11T14:36:41.877242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length24.268293
Min length21

Characters and Unicode

Total characters995
Distinct characters79
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

Unique39 ?
Unique (%)95.1%

Sample

1st row서울특별시 중구 퇴계로 228 (필동2가)
2nd row서울특별시 중구 동호로 335 (오장동)
3rd row서울특별시 중구 을지로 246 (을지로6가)
4th row서울특별시 중구 장충단로 202 (장충동1가)
5th row서울특별시 중구 동호로 203 (신당동)
ValueCountFrequency (%)
서울특별시 41
19.9%
중구 41
19.9%
신당동 12
 
5.8%
을지로3가 4
 
1.9%
동호로 4
 
1.9%
퇴계로 3
 
1.5%
다산로 3
 
1.5%
황학동 3
 
1.5%
34 2
 
1.0%
6 2
 
1.0%
Other values (84) 91
44.2%
2024-05-11T14:36:42.607822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
165
 
16.6%
로 49
 
4.9%
구 42
 
4.2%
서 41
 
4.1%
( 41
 
4.1%
특 41
 
4.1%
별 41
 
4.1%
시 41
 
4.1%
중 41
 
4.1%
울 41
 
4.1%
Other values (69) 452
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 586
58.9%
Space Separator 165
 
16.6%
Decimal Number 156
 
15.7%
Open Punctuation 41
 
4.1%
Close Punctuation 41
 
4.1%
Dash Punctuation 4
 
0.4%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 49
 
8.4%
구 42
 
7.2%
서 41
 
7.0%
특 41
 
7.0%
별 41
 
7.0%
시 41
 
7.0%
중 41
 
7.0%
울 41
 
7.0%
동 38
 
6.5%
길 20
 
3.4%
Other values (54) 191
32.6%
Decimal Number
ValueCountFrequency (%)
1 32
20.5%
3 29
18.6%
2 25
16.0%
4 14
9.0%
5 14
9.0%
0 12
 
7.7%
6 10
 
6.4%
7 9
 
5.8%
9 8
 
5.1%
8 3
 
1.9%
Space Separator
ValueCountFrequency (%)
165
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 586
58.9%
Common 409
41.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 49
 
8.4%
구 42
 
7.2%
서 41
 
7.0%
특 41
 
7.0%
별 41
 
7.0%
시 41
 
7.0%
중 41
 
7.0%
울 41
 
7.0%
동 38
 
6.5%
길 20
 
3.4%
Other values (54) 191
32.6%
Common
ValueCountFrequency (%)
165
40.3%
( 41
 
10.0%
) 41
 
10.0%
1 32
 
7.8%
3 29
 
7.1%
2 25
 
6.1%
4 14
 
3.4%
5 14
 
3.4%
0 12
 
2.9%
6 10
 
2.4%
Other values (5) 26
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 586
58.9%
ASCII 409
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
165
40.3%
( 41
 
10.0%
) 41
 
10.0%
1 32
 
7.8%
3 29
 
7.1%
2 25
 
6.1%
4 14
 
3.4%
5 14
 
3.4%
0 12
 
2.9%
6 10
 
2.4%
Other values (5) 26
 
6.4%
Hangul
ValueCountFrequency (%)
로 49
 
8.4%
구 42
 
7.2%
서 41
 
7.0%
특 41
 
7.0%
별 41
 
7.0%
시 41
 
7.0%
중 41
 
7.0%
울 41
 
7.0%
동 38
 
6.5%
길 20
 
3.4%
Other values (54) 191
32.6%

도로명우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

사업장명
Text

Distinct44
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-05-11T14:36:43.019814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length7.7391304
Min length3

Characters and Unicode

Total characters356
Distinct characters108
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

Unique43 ?
Unique (%)93.5%

Sample

1st rowSK에너지 직영 퇴계로주유소
2nd rowSK네트웍스(주)수도주유소
3rd row(주)SK글로벌(주) 을지로주유소
4th row서울석유(주) 장충주유소
5th row에이치디현대오일뱅크(주)직영장원주유소
ValueCountFrequency (%)
서울석유 3
 
5.1%
직영 2
 
3.4%
주식회사 2
 
3.4%
충무석유 1
 
1.7%
대호에너지 1
 
1.7%
대진석유 1
 
1.7%
약수주유소 1
 
1.7%
일광석유 1
 
1.7%
현대정유(주)직영 1
 
1.7%
버티고개주유소 1
 
1.7%
Other values (45) 45
76.3%
2024-05-11T14:36:43.655216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 40
 
11.2%
주 34
 
9.6%
석 21
 
5.9%
소 18
 
5.1%
) 13
 
3.7%
13
 
3.7%
( 13
 
3.7%
영 9
 
2.5%
지 8
 
2.2%
에 7
 
2.0%
Other values (98) 180
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 309
86.8%
Close Punctuation 13
 
3.7%
Space Separator 13
 
3.7%
Open Punctuation 13
 
3.7%
Uppercase Letter 6
 
1.7%
Decimal Number 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 40
 
12.9%
주 34
 
11.0%
석 21
 
6.8%
소 18
 
5.8%
영 9
 
2.9%
지 8
 
2.6%
에 7
 
2.3%
스 6
 
1.9%
사 6
 
1.9%
서 6
 
1.9%
Other values (92) 154
49.8%
Uppercase Letter
ValueCountFrequency (%)
K 3
50.0%
S 3
50.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Decimal Number
ValueCountFrequency (%)
5 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 309
86.8%
Common 41
 
11.5%
Latin 6
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 40
 
12.9%
주 34
 
11.0%
석 21
 
6.8%
소 18
 
5.8%
영 9
 
2.9%
지 8
 
2.6%
에 7
 
2.3%
스 6
 
1.9%
사 6
 
1.9%
서 6
 
1.9%
Other values (92) 154
49.8%
Common
ValueCountFrequency (%)
) 13
31.7%
13
31.7%
( 13
31.7%
5 2
 
4.9%
Latin
ValueCountFrequency (%)
K 3
50.0%
S 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 309
86.8%
ASCII 47
 
13.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 40
 
12.9%
주 34
 
11.0%
석 21
 
6.8%
소 18
 
5.8%
영 9
 
2.9%
지 8
 
2.6%
에 7
 
2.3%
스 6
 
1.9%
사 6
 
1.9%
서 6
 
1.9%
Other values (92) 154
49.8%
ASCII
ValueCountFrequency (%)
) 13
27.7%
13
27.7%
( 13
27.7%
K 3
 
6.4%
S 3
 
6.4%
5 2
 
4.3%

최종수정일자
Date

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum2009-11-23 15:48:48
Maximum2024-02-29 09:51:20
2024-05-11T14:36:43.917248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:44.133274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
U
23 
I
23 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 23
50.0%
I 23
50.0%

Length

2024-05-11T14:36:44.346987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:44.490548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 23
50.0%
i 23
50.0%

데이터갱신일자
Date

Distinct18
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:02:00
2024-05-11T14:36:44.625833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:44.839245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

업태구분명
Categorical

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
일반판매소
22 
주유소
19 
용제판매소
5 

Length

Max length5
Median length5
Mean length4.173913
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반판매소 22
47.8%
주유소 19
41.3%
용제판매소 5
 
10.9%

Length

2024-05-11T14:36:45.074640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:45.332948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반판매소 22
47.8%
주유소 19
41.3%
용제판매소 5
 
10.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)95.2%
Missing4
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean200110
Minimum196715.27
Maximum202185.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T14:36:45.614027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196715.27
5-th percentile197696.96
Q1199276.6
median200173.19
Q3201106.78
95-th percentile201853.02
Maximum202185.73
Range5470.4541
Interquartile range (IQR)1830.1814

Descriptive statistics

Standard deviation1303.5125
Coefficient of variation (CV)0.0065139796
Kurtosis0.026332111
Mean200110
Median Absolute Deviation (MAD)929.36966
Skewness-0.60551053
Sum8404620.1
Variance1699144.8
MonotonicityNot monotonic
2024-05-11T14:36:45.971647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
199828.382578404 2
 
4.3%
199243.819646237 2
 
4.3%
198171.540570023 1
 
2.2%
200638.900463459 1
 
2.2%
201126.012826602 1
 
2.2%
200029.166732773 1
 
2.2%
200394.851756721 1
 
2.2%
201049.077525203 1
 
2.2%
196715.271566103 1
 
2.2%
201478.507867956 1
 
2.2%
Other values (30) 30
65.2%
(Missing) 4
 
8.7%
ValueCountFrequency (%)
196715.271566103 1
2.2%
197464.65197896 1
2.2%
197683.64947393 1
2.2%
197949.94152054 1
2.2%
198171.540570023 1
2.2%
198744.433228989 1
2.2%
199055.288923974 1
2.2%
199148.237513374 1
2.2%
199166.892140129 1
2.2%
199243.819646237 2
4.3%
ValueCountFrequency (%)
202185.725696826 1
2.2%
202055.803747 1
2.2%
201858.556252796 1
2.2%
201747.820608415 1
2.2%
201675.409021013 1
2.2%
201554.937996539 1
2.2%
201478.507867956 1
2.2%
201380.197665657 1
2.2%
201315.983348988 1
2.2%
201224.308328296 1
2.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)95.2%
Missing4
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean451192.86
Minimum450044.63
Maximum451958.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T14:36:46.279225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450044.63
5-th percentile450421.52
Q1450954.31
median451272.63
Q3451521.4
95-th percentile451779.7
Maximum451958.5
Range1913.865
Interquartile range (IQR)567.09753

Descriptive statistics

Standard deviation444.80829
Coefficient of variation (CV)0.00098584959
Kurtosis0.55664557
Mean451192.86
Median Absolute Deviation (MAD)267.54619
Skewness-0.82698841
Sum18950100
Variance197854.42
MonotonicityNot monotonic
2024-05-11T14:36:46.525007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
451249.574098116 2
 
4.3%
451538.099475916 2
 
4.3%
450729.003374226 1
 
2.2%
450044.630607241 1
 
2.2%
451211.653500506 1
 
2.2%
450895.225466804 1
 
2.2%
451398.897492225 1
 
2.2%
450750.147301284 1
 
2.2%
450052.802445678 1
 
2.2%
451388.207226603 1
 
2.2%
Other values (30) 30
65.2%
(Missing) 4
 
8.7%
ValueCountFrequency (%)
450044.630607241 1
2.2%
450052.802445678 1
2.2%
450415.643708471 1
2.2%
450533.125356615 1
2.2%
450568.695207373 1
2.2%
450678.247827876 1
2.2%
450729.003374226 1
2.2%
450750.147301284 1
2.2%
450831.953962116 1
2.2%
450895.225466804 1
2.2%
ValueCountFrequency (%)
451958.495584927 1
2.2%
451894.126542 1
2.2%
451785.104693077 1
2.2%
451677.065126229 1
2.2%
451650.778853987 1
2.2%
451587.720094494 1
2.2%
451579.319762379 1
2.2%
451575.215089429 1
2.2%
451542.261628625 1
2.2%
451538.099475916 2
4.3%

자본금
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

거래처
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자본금거래처
0301000019763010071015000021976-05-27<NA>1영업/정상6휴지사업재개<NA><NA><NA><NA>02-2273-5189504.5<NA>서울특별시 중구 필동2가 51-1서울특별시 중구 퇴계로 228 (필동2가)<NA>SK에너지 직영 퇴계로주유소2023-12-29 13:35:51U2022-11-01 21:01:00.0주유소199678.424471451047.403802<NA><NA>
13010000197630100710150000319760528<NA>3폐업3폐지20120904<NA><NA><NA>0222679925819.8<NA>서울특별시 중구 오장동 206-2서울특별시 중구 동호로 335 (오장동)<NA>SK네트웍스(주)수도주유소2012-09-04 10:31:27I2018-08-31 23:59:59.0주유소200113.999616451324.026101<NA><NA>
23010000197630100710150000419760527<NA>3폐업3폐지20020125<NA><NA><NA>02226554731004.9<NA>서울특별시 중구 을지로6가 32서울특별시 중구 을지로 246 (을지로6가)<NA>(주)SK글로벌(주) 을지로주유소2012-02-06 15:57:51I2018-08-31 23:59:59.0주유소200406.563572451542.261629<NA><NA>
33010000197630100710150000519760521<NA>1영업/정상6휴지사업재개<NA><NA><NA><NA>02-2279-9965991.7<NA>서울특별시 중구 장충동1가 31-1서울특별시 중구 장충단로 202 (장충동1가)<NA>서울석유(주) 장충주유소2022-01-12 11:07:07U2022-01-14 02:40:00.0주유소200551.866093451166.741475<NA><NA>
4301000019763010071015000061976-04-30<NA>1영업/정상1신규등록<NA><NA><NA><NA>02-2236-2759495.9<NA>서울특별시 중구 신당동 357-6서울특별시 중구 동호로 203 (신당동)<NA>에이치디현대오일뱅크(주)직영장원주유소2023-04-20 10:39:58U2022-12-03 22:02:00.0주유소200751.417159450415.643708<NA><NA>
53010000197630100710150000819760526<NA>3폐업3폐지20120308<NA><NA><NA>0222343451942.1<NA>서울특별시 중구 황학동 938서울특별시 중구 난계로 169 (황학동)<NA>서울석유(주)직영 인창주유소2012-03-08 17:51:08I2018-08-31 23:59:59.0주유소202055.803747451894.126542<NA><NA>
63010000197630100710150000919760428<NA>3폐업3폐지20200901<NA><NA><NA>02226750471256.2<NA>서울특별시 중구 초동 107-12서울특별시 중구 마른내로 31 (초동)<NA>지에스칼텍스(주)초동주유소2020-09-03 10:57:27U2020-09-05 02:40:00.0주유소199148.237513451395.30424<NA><NA>
73010000197630100710150001019760428<NA>3폐업3폐지20080108<NA><NA><NA>0222675047330.58<NA>서울특별시 중구 충무로5가 19-8서울특별시 중구 창경궁로 2-1 (충무로5가)<NA>충무로5가 주유소2012-02-06 14:52:43I2018-08-31 23:59:59.0주유소199823.188147451160.479751<NA><NA>
8301000019763010071015000111976-05-04<NA>3폐업3폐지<NA><NA><NA><NA>02 7526880953.0<NA>서울특별시 중구 남대문로5가 84-17서울특별시 중구 퇴계로 15 (남대문로5가)<NA>지에스칼텍스(주) 직영 역전점2023-09-04 15:59:38U2022-12-09 00:06:00.0주유소197683.649474450533.125357<NA><NA>
9301000019763010071015000121976-05-11<NA>1영업/정상1신규등록<NA><NA><NA><NA>02-2267-8025340.5<NA>서울특별시 중구 필동2가 3-1서울특별시 중구 퇴계로 196 (필동2가)<NA>필동주유소2023-07-06 15:18:47U2022-12-07 00:08:00.0주유소199374.931549450959.464116<NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자본금거래처
363010000199530100710150002019950325<NA>1영업/정상7영업개시<NA><NA><NA><NA>02-2275-5150758.7<NA>서울특별시 중구 장충동2가 186-69서울특별시 중구 동호로 296 (장충동2가)<NA>씨앤에스유통(주) 장충드림주유소2022-01-19 13:59:37U2022-01-21 02:40:00.0주유소200232.378994450952.587691<NA><NA>
37301000019963010071015000211996-03-25<NA>1영업/정상1신규등록<NA><NA><NA><NA>02-2234-34511028.0<NA>서울특별시 중구 신당동 741서울특별시 중구 왕십리로 403 (신당동)<NA>세화주유소2024-02-29 09:51:20U2023-12-03 00:02:00.0주유소202185.725697451383.557088<NA><NA>
38301000019973010071012000561997-11-13<NA>1영업/정상1신규등록<NA><NA><NA><NA>0507-1408-2720<NA><NA>서울특별시 중구 신당동 233-27서울특별시 중구 다산로39길 71-5 (신당동)<NA>엘지석유2023-07-06 15:49:33U2022-12-07 00:08:00.0일반판매소200994.257585451362.27912<NA><NA>
393010000199930100710120005019991228<NA>3폐업3폐지20080104<NA><NA><NA>0222797245<NA><NA>서울특별시 중구 장충동2가 161-15서울특별시 중구 장충단로7길 41 (장충동2가)<NA>금강석유2012-02-08 09:15:12I2018-08-31 23:59:59.0일반판매소200295.735672451124.275659<NA><NA>
40301000020003010071012000572000-06-10<NA>1영업/정상1신규등록<NA><NA><NA><NA>02-2273-5528<NA><NA>서울특별시 중구 신당동 386-125서울특별시 중구 청구로17길 35 (신당동)<NA>동부석유에너지2023-12-21 18:33:16U2022-11-01 22:03:00.0일반판매소200987.4151450831.953962<NA><NA>
413010000200030100710120005820000804<NA>3폐업3폐지<NA><NA><NA><NA>0222761066<NA><NA>서울특별시 중구 예관동 70-19<NA><NA>서울석유2014-01-23 16:33:17I2018-08-31 23:59:59.0일반판매소199828.382578451249.574098<NA><NA>
42301000020033010071015000012003-01-21<NA>1영업/정상1신규등록<NA><NA><NA><NA>0222720071<NA><NA>서울특별시 중구 을지로3가 5-6서울특별시 중구 을지로 109 (을지로3가)<NA>주식회사 영흥화학상사2023-07-06 15:52:45U2022-12-07 00:08:00.0용제판매소199055.288924451579.319762<NA><NA>
433010000200330100710150000220030212<NA>3폐업3폐지<NA><NA><NA><NA>02 7737887<NA><NA>서울특별시 중구 장교동 1서울특별시 중구 삼일대로 363, 1203호 (장교동,장교빌딩)<NA>(주)트래솔2012-05-10 17:01:07I2018-08-31 23:59:59.0용제판매소198744.433229451677.065126<NA><NA>
443010000200630100710150000120060224<NA>3폐업3폐지<NA><NA><NA><NA>0222782890<NA><NA>서울특별시 중구 을지로3가 295-5서울특별시 중구 을지로14길 3 (을지로3가)<NA>한성화학건재(주)2012-02-08 15:40:20I2018-08-31 23:59:59.0용제판매소199243.819646451538.099476<NA><NA>
453010000200930101000150000120090108<NA>3폐업3폐지20140324<NA><NA><NA>22782890<NA><NA>서울특별시 중구 을지로3가 295-5서울특별시 중구 을지로14길 3 (을지로3가)<NA>한성케미탈2014-03-26 17:09:50I2018-08-31 23:59:59.0용제판매소199243.819646451538.099476<NA><NA>