Overview

Dataset statistics

Number of variables26
Number of observations1002
Missing cells6265
Missing cells (%)24.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory210.5 KiB
Average record size in memory215.1 B

Variable types

Numeric6
DateTime5
Categorical7
Text8

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),점포구분명
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16096/S/1/datasetView.do

Alerts

인허가취소일자 has 995 (99.3%) missing valuesMissing
폐업일자 has 822 (82.0%) missing valuesMissing
휴업시작일자 has 983 (98.1%) missing valuesMissing
휴업종료일자 has 983 (98.1%) missing valuesMissing
재개업일자 has 967 (96.5%) missing valuesMissing
전화번호 has 27 (2.7%) missing valuesMissing
소재지면적 has 76 (7.6%) missing valuesMissing
소재지우편번호 has 598 (59.7%) missing valuesMissing
지번주소 has 121 (12.1%) missing valuesMissing
도로명주소 has 175 (17.5%) missing valuesMissing
도로명우편번호 has 354 (35.3%) missing valuesMissing
좌표정보(X) has 82 (8.2%) missing valuesMissing
좌표정보(Y) has 82 (8.2%) missing valuesMissing
관리번호 is highly skewed (γ1 = -21.90363612)Skewed
관리번호 has unique valuesUnique
소재지면적 has 93 (9.3%) zerosZeros

Reproduction

Analysis started2024-05-11 01:02:21.382829
Analysis finished2024-05-11 01:02:23.677248
Duration2.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3126377.2
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-05-11T01:02:23.903969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13060000
median3130000
Q33190000
95-th percentile3240000
Maximum3240000
Range240000
Interquartile range (IQR)130000

Descriptive statistics

Standard deviation76148.216
Coefficient of variation (CV)0.024356695
Kurtosis-1.3097893
Mean3126377.2
Median Absolute Deviation (MAD)70000
Skewness-0.10152184
Sum3.13263 × 109
Variance5.7985509 × 109
MonotonicityNot monotonic
2024-05-11T01:02:24.496989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3010000 74
 
7.4%
3220000 71
 
7.1%
3230000 62
 
6.2%
3070000 60
 
6.0%
3180000 55
 
5.5%
3050000 54
 
5.4%
3160000 53
 
5.3%
3240000 53
 
5.3%
3150000 46
 
4.6%
3110000 42
 
4.2%
Other values (15) 432
43.1%
ValueCountFrequency (%)
3000000 27
 
2.7%
3010000 74
7.4%
3020000 30
3.0%
3030000 31
3.1%
3040000 33
3.3%
3050000 54
5.4%
3060000 20
 
2.0%
3070000 60
6.0%
3080000 31
3.1%
3090000 17
 
1.7%
ValueCountFrequency (%)
3240000 53
5.3%
3230000 62
6.2%
3220000 71
7.1%
3210000 33
3.3%
3200000 31
3.1%
3190000 24
 
2.4%
3180000 55
5.5%
3170000 33
3.3%
3160000 53
5.3%
3150000 46
4.6%

관리번호
Real number (ℝ)

SKEWED  UNIQUE 

Distinct1002
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0031964 × 1018
Minimum1.975308 × 1014
Maximum2.024323 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-05-11T01:02:24.976789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.975308 × 1014
5-th percentile1.9824211 × 1018
Q12.002301 × 1018
median2.0093165 × 1018
Q32.0123218 × 1018
95-th percentile2.021319 × 1018
Maximum2.024323 × 1018
Range2.0241255 × 1018
Interquartile range (IQR)1.0020757 × 1016

Descriptive statistics

Standard deviation9.0226368 × 1016
Coefficient of variation (CV)0.045041198
Kurtosis485.17941
Mean2.0031964 × 1018
Median Absolute Deviation (MAD)4.984501 × 1015
Skewness-21.903636
Sum-3.4922762 × 1018
Variance8.1407974 × 1033
MonotonicityNot monotonic
2024-05-11T01:02:25.541500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2013317014207500002 1
 
0.1%
2007316011707500017 1
 
0.1%
2005316009307500006 1
 
0.1%
1986316007107500001 1
 
0.1%
1998316007107500002 1
 
0.1%
2005316009307500001 1
 
0.1%
2005316009307500002 1
 
0.1%
2005316009307500007 1
 
0.1%
2007316011707500002 1
 
0.1%
2007316011707500005 1
 
0.1%
Other values (992) 992
99.0%
ValueCountFrequency (%)
197530801690752 1
0.1%
200730101300751 1
0.1%
1962303007407500002 1
0.1%
1962303010307500001 1
0.1%
1962316007107500001 1
0.1%
1964301010007500001 1
0.1%
1966308016907500009 1
0.1%
1968301010007500001 1
0.1%
1968307009907500001 1
0.1%
1968316007107500002 1
0.1%
ValueCountFrequency (%)
2024323029107500001 1
0.1%
2024320022507500001 1
0.1%
2024317025707500001 1
0.1%
2024315020007500001 1
0.1%
2024312021907500002 1
0.1%
2024312021907500001 1
0.1%
2024311021707500001 1
0.1%
2024310018407500001 1
0.1%
2024308019007500001 1
0.1%
2024306020207500001 1
0.1%

인허가일자
Date

Distinct789
Distinct (%)78.7%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
Minimum1948-09-21 00:00:00
Maximum2024-05-01 00:00:00
2024-05-11T01:02:26.234562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:02:26.879482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)100.0%
Missing995
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean20149371
Minimum20081107
Maximum20200331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-05-11T01:02:27.384335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20081107
5-th percentile20087047
Q120121009
median20161219
Q320180461
95-th percentile20197416
Maximum20200331
Range119224
Interquartile range (IQR)59452

Descriptive statistics

Standard deviation44634.665
Coefficient of variation (CV)0.002215189
Kurtosis-1.0396523
Mean20149371
Median Absolute Deviation (MAD)29395
Skewness-0.57507468
Sum1.410456 × 108
Variance1.9922533 × 109
MonotonicityNot monotonic
2024-05-11T01:02:27.827986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20190614 1
 
0.1%
20141110 1
 
0.1%
20161219 1
 
0.1%
20170308 1
 
0.1%
20200331 1
 
0.1%
20100908 1
 
0.1%
20081107 1
 
0.1%
(Missing) 995
99.3%
ValueCountFrequency (%)
20081107 1
0.1%
20100908 1
0.1%
20141110 1
0.1%
20161219 1
0.1%
20170308 1
0.1%
20190614 1
0.1%
20200331 1
0.1%
ValueCountFrequency (%)
20200331 1
0.1%
20190614 1
0.1%
20170308 1
0.1%
20161219 1
0.1%
20141110 1
0.1%
20100908 1
0.1%
20081107 1
0.1%

영업상태코드
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
1
731 
3
180 
2
79 
4
 
12

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 (%)
1 731
73.0%
3 180
 
18.0%
2 79
 
7.9%
4 12
 
1.2%

Length

2024-05-11T01:02:28.298871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:02:28.716594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 731
73.0%
3 180
 
18.0%
2 79
 
7.9%
4 12
 
1.2%

영업상태명
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
영업/정상
731 
폐업
180 
휴업
79 
취소/말소/만료/정지/중지
 
12

Length

Max length14
Median length5
Mean length4.3323353
Min length2

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 731
73.0%
폐업 180
 
18.0%
휴업 79
 
7.9%
취소/말소/만료/정지/중지 12
 
1.2%

Length

2024-05-11T01:02:29.103203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:02:29.450152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 731
73.0%
폐업 180
 
18.0%
휴업 79
 
7.9%
취소/말소/만료/정지/중지 12
 
1.2%

상세영업상태코드
Categorical

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
1
708 
3
180 
2
79 
5
 
15
4
 
12

Length

Max length4
Median length1
Mean length1.0239521
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 708
70.7%
3 180
 
18.0%
2 79
 
7.9%
5 15
 
1.5%
4 12
 
1.2%
BBBB 8
 
0.8%

Length

2024-05-11T01:02:29.924172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:02:30.387533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 708
70.7%
3 180
 
18.0%
2 79
 
7.9%
5 15
 
1.5%
4 12
 
1.2%
bbbb 8
 
0.8%

상세영업상태명
Categorical

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
정상영업
708 
폐업처리
180 
휴업처리
79 
영업개시전
 
15
직권취소
 
12

Length

Max length5
Median length4
Mean length4.0149701
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 708
70.7%
폐업처리 180
 
18.0%
휴업처리 79
 
7.9%
영업개시전 15
 
1.5%
직권취소 12
 
1.2%
<NA> 8
 
0.8%

Length

2024-05-11T01:02:30.816525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:02:31.292334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 708
70.7%
폐업처리 180
 
18.0%
휴업처리 79
 
7.9%
영업개시전 15
 
1.5%
직권취소 12
 
1.2%
na 8
 
0.8%

폐업일자
Date

MISSING 

Distinct155
Distinct (%)86.1%
Missing822
Missing (%)82.0%
Memory size8.0 KiB
Minimum1988-08-20 00:00:00
Maximum2024-04-08 00:00:00
2024-05-11T01:02:31.876862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:02:32.331251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Text

MISSING 

Distinct13
Distinct (%)68.4%
Missing983
Missing (%)98.1%
Memory size8.0 KiB
2024-05-11T01:02:32.934972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.2105263
Min length8

Characters and Unicode

Total characters156
Distinct characters10
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

Unique12 ?
Unique (%)63.2%

Sample

1st row2015-05-30
2nd row20220317
3rd row20190701
4th row2024-01-20
5th row11111111
ValueCountFrequency (%)
11111111 7
36.8%
2015-05-30 1
 
5.3%
20220317 1
 
5.3%
20190701 1
 
5.3%
2024-01-20 1
 
5.3%
20100413 1
 
5.3%
20170704 1
 
5.3%
20080529 1
 
5.3%
20211031 1
 
5.3%
20110415 1
 
5.3%
Other values (3) 3
15.8%
2024-05-11T01:02:34.164890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 75
48.1%
0 32
20.5%
2 20
 
12.8%
3 6
 
3.8%
5 5
 
3.2%
7 5
 
3.2%
4 5
 
3.2%
- 4
 
2.6%
9 2
 
1.3%
8 2
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 152
97.4%
Dash Punctuation 4
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 75
49.3%
0 32
21.1%
2 20
 
13.2%
3 6
 
3.9%
5 5
 
3.3%
7 5
 
3.3%
4 5
 
3.3%
9 2
 
1.3%
8 2
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 156
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 75
48.1%
0 32
20.5%
2 20
 
12.8%
3 6
 
3.8%
5 5
 
3.2%
7 5
 
3.2%
4 5
 
3.2%
- 4
 
2.6%
9 2
 
1.3%
8 2
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 75
48.1%
0 32
20.5%
2 20
 
12.8%
3 6
 
3.8%
5 5
 
3.2%
7 5
 
3.2%
4 5
 
3.2%
- 4
 
2.6%
9 2
 
1.3%
8 2
 
1.3%

휴업종료일자
Text

MISSING 

Distinct13
Distinct (%)68.4%
Missing983
Missing (%)98.1%
Memory size8.0 KiB
2024-05-11T01:02:34.576631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.2105263
Min length8

Characters and Unicode

Total characters156
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

Unique12 ?
Unique (%)63.2%

Sample

1st row2015-08-14
2nd row20221231
3rd row20200630
4th row2024-09-05
5th row11111111
ValueCountFrequency (%)
11111111 7
36.8%
2015-08-14 1
 
5.3%
20221231 1
 
5.3%
20200630 1
 
5.3%
2024-09-05 1
 
5.3%
20150430 1
 
5.3%
99991231 1
 
5.3%
20090829 1
 
5.3%
20250430 1
 
5.3%
20140430 1
 
5.3%
Other values (3) 3
15.8%
2024-05-11T01:02:35.659256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 69
44.2%
0 28
17.9%
2 22
 
14.1%
4 9
 
5.8%
9 8
 
5.1%
3 6
 
3.8%
5 5
 
3.2%
- 4
 
2.6%
8 2
 
1.3%
6 2
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 152
97.4%
Dash Punctuation 4
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 69
45.4%
0 28
18.4%
2 22
 
14.5%
4 9
 
5.9%
9 8
 
5.3%
3 6
 
3.9%
5 5
 
3.3%
8 2
 
1.3%
6 2
 
1.3%
7 1
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 156
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 69
44.2%
0 28
17.9%
2 22
 
14.1%
4 9
 
5.8%
9 8
 
5.1%
3 6
 
3.8%
5 5
 
3.2%
- 4
 
2.6%
8 2
 
1.3%
6 2
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 69
44.2%
0 28
17.9%
2 22
 
14.1%
4 9
 
5.8%
9 8
 
5.1%
3 6
 
3.8%
5 5
 
3.2%
- 4
 
2.6%
8 2
 
1.3%
6 2
 
1.3%

재개업일자
Date

MISSING 

Distinct33
Distinct (%)94.3%
Missing967
Missing (%)96.5%
Memory size8.0 KiB
Minimum1962-02-23 00:00:00
Maximum2024-09-06 00:00:00
2024-05-11T01:02:36.260207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:02:36.849968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)

전화번호
Text

MISSING 

Distinct903
Distinct (%)92.6%
Missing27
Missing (%)2.7%
Memory size8.0 KiB
2024-05-11T01:02:37.745646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length10.38359
Min length1

Characters and Unicode

Total characters10124
Distinct characters15
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique859 ?
Unique (%)88.1%

Sample

1st row02-2109-7000
2nd row02-2109-7013
3rd row0226470824
4th row02-2679-3350
5th row02-536-0004
ValueCountFrequency (%)
02 203
 
16.6%
02-2006-2364 8
 
0.7%
02-380-5042 7
 
0.6%
485 7
 
0.6%
2290-5853 7
 
0.6%
9001 6
 
0.5%
5492233 3
 
0.2%
22905853 3
 
0.2%
903-0900 3
 
0.2%
02-2290-5853 3
 
0.2%
Other values (921) 975
79.6%
2024-05-11T01:02:39.213834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1894
18.7%
2 1757
17.4%
- 901
8.9%
5 779
7.7%
3 739
 
7.3%
4 718
 
7.1%
6 711
 
7.0%
1 663
 
6.5%
8 599
 
5.9%
9 541
 
5.3%
Other values (5) 822
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8890
87.8%
Dash Punctuation 901
 
8.9%
Space Separator 315
 
3.1%
Close Punctuation 14
 
0.1%
Other Punctuation 2
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1894
21.3%
2 1757
19.8%
5 779
8.8%
3 739
 
8.3%
4 718
 
8.1%
6 711
 
8.0%
1 663
 
7.5%
8 599
 
6.7%
9 541
 
6.1%
7 489
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 901
100.0%
Space Separator
ValueCountFrequency (%)
315
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10124
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1894
18.7%
2 1757
17.4%
- 901
8.9%
5 779
7.7%
3 739
 
7.3%
4 718
 
7.1%
6 711
 
7.0%
1 663
 
6.5%
8 599
 
5.9%
9 541
 
5.3%
Other values (5) 822
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10124
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1894
18.7%
2 1757
17.4%
- 901
8.9%
5 779
7.7%
3 739
 
7.3%
4 718
 
7.1%
6 711
 
7.0%
1 663
 
6.5%
8 599
 
5.9%
9 541
 
5.3%
Other values (5) 822
8.1%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct780
Distinct (%)84.2%
Missing76
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean7531.9114
Minimum0
Maximum145244.54
Zeros93
Zeros (%)9.3%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-05-11T01:02:39.887845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1323.155
median2979.7
Q39543.5675
95-th percentile32978.338
Maximum145244.54
Range145244.54
Interquartile range (IQR)9220.4125

Descriptive statistics

Standard deviation13665.836
Coefficient of variation (CV)1.8143915
Kurtosis23.743145
Mean7531.9114
Median Absolute Deviation (MAD)2781.15
Skewness4.1245099
Sum6974549.9
Variance1.8675508 × 108
MonotonicityNot monotonic
2024-05-11T01:02:40.609433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 93
 
9.3%
3223.68 6
 
0.6%
10006.0 4
 
0.4%
80.49 3
 
0.3%
10209.0 3
 
0.3%
2837.0 3
 
0.3%
14074.76 3
 
0.3%
2734.89 2
 
0.2%
189.1 2
 
0.2%
2803.0 2
 
0.2%
Other values (770) 805
80.3%
(Missing) 76
 
7.6%
ValueCountFrequency (%)
0.0 93
9.3%
1.0 1
 
0.1%
13.0 1
 
0.1%
80.49 3
 
0.3%
99.0 1
 
0.1%
105.5 1
 
0.1%
106.0 1
 
0.1%
107.8 1
 
0.1%
117.0 1
 
0.1%
120.07 1
 
0.1%
ValueCountFrequency (%)
145244.54 1
0.1%
106290.33 1
0.1%
98983.0 1
0.1%
94319.57 1
0.1%
84573.34 1
0.1%
84471.0 1
0.1%
80038.0 1
0.1%
77670.0 1
0.1%
75439.97 1
0.1%
72582.24 1
0.1%

소재지우편번호
Text

MISSING 

Distinct357
Distinct (%)88.4%
Missing598
Missing (%)59.7%
Memory size8.0 KiB
2024-05-11T01:02:41.643836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2871287
Min length6

Characters and Unicode

Total characters2540
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

Unique321 ?
Unique (%)79.5%

Sample

1st row153-023
2nd row153-801
3rd row158-753
4th row150-723
5th row137-061
ValueCountFrequency (%)
152050 8
 
2.0%
152080 4
 
1.0%
158074 3
 
0.7%
134873 3
 
0.7%
142100 3
 
0.7%
134871 2
 
0.5%
134031 2
 
0.5%
100162 2
 
0.5%
153-023 2
 
0.5%
134832 2
 
0.5%
Other values (347) 373
92.3%
2024-05-11T01:02:43.295414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 631
24.8%
0 371
14.6%
3 300
11.8%
8 264
10.4%
5 217
 
8.5%
2 216
 
8.5%
4 134
 
5.3%
7 125
 
4.9%
- 116
 
4.6%
6 88
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2424
95.4%
Dash Punctuation 116
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 631
26.0%
0 371
15.3%
3 300
12.4%
8 264
10.9%
5 217
 
9.0%
2 216
 
8.9%
4 134
 
5.5%
7 125
 
5.2%
6 88
 
3.6%
9 78
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2540
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 631
24.8%
0 371
14.6%
3 300
11.8%
8 264
10.4%
5 217
 
8.5%
2 216
 
8.5%
4 134
 
5.3%
7 125
 
4.9%
- 116
 
4.6%
6 88
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2540
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 631
24.8%
0 371
14.6%
3 300
11.8%
8 264
10.4%
5 217
 
8.5%
2 216
 
8.5%
4 134
 
5.3%
7 125
 
4.9%
- 116
 
4.6%
6 88
 
3.5%

지번주소
Text

MISSING 

Distinct799
Distinct (%)90.7%
Missing121
Missing (%)12.1%
Memory size8.0 KiB
2024-05-11T01:02:44.553364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length48
Mean length24.015891
Min length7

Characters and Unicode

Total characters21158
Distinct characters316
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique737 ?
Unique (%)83.7%

Sample

1st row서울특별시 금천구 가산동 60번지 22호
2nd row서울특별시 금천구 가산동 60번지 20호
3rd row서울특별시 양천구 목5동 903번지 목동3단지아파트 관리동상가 105호
4th row서울특별시 영등포구 당산동2가 30번지 2호
5th row서울특별시 서초구 방배1동 816번지 1호
ValueCountFrequency (%)
서울특별시 876
 
19.9%
1호 119
 
2.7%
호 65
 
1.5%
강남구 55
 
1.2%
성북구 55
 
1.2%
구로구 53
 
1.2%
동대문구 52
 
1.2%
영등포구 52
 
1.2%
강동구 52
 
1.2%
송파구 50
 
1.1%
Other values (1197) 2975
67.6%
2024-05-11T01:02:46.211411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4011
19.0%
동 1046
 
4.9%
구 980
 
4.6%
서 969
 
4.6%
시 911
 
4.3%
울 879
 
4.2%
특 876
 
4.1%
별 876
 
4.1%
1 839
 
4.0%
지 743
 
3.5%
Other values (306) 9028
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13154
62.2%
Space Separator 4011
 
19.0%
Decimal Number 3817
 
18.0%
Dash Punctuation 77
 
0.4%
Other Punctuation 46
 
0.2%
Uppercase Letter 27
 
0.1%
Math Symbol 9
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1046
 
8.0%
구 980
 
7.5%
서 969
 
7.4%
시 911
 
6.9%
울 879
 
6.7%
특 876
 
6.7%
별 876
 
6.7%
지 743
 
5.6%
호 693
 
5.3%
번 686
 
5.2%
Other values (277) 4495
34.2%
Decimal Number
ValueCountFrequency (%)
1 839
22.0%
2 533
14.0%
3 379
9.9%
5 368
9.6%
6 341
8.9%
4 330
 
8.6%
0 296
 
7.8%
7 258
 
6.8%
9 256
 
6.7%
8 217
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
B 6
22.2%
S 6
22.2%
D 3
11.1%
C 3
11.1%
L 3
11.1%
K 2
 
7.4%
M 2
 
7.4%
A 1
 
3.7%
G 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 44
95.7%
. 2
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
4011
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13154
62.2%
Common 7974
37.7%
Latin 30
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1046
 
8.0%
구 980
 
7.5%
서 969
 
7.4%
시 911
 
6.9%
울 879
 
6.7%
특 876
 
6.7%
별 876
 
6.7%
지 743
 
5.6%
호 693
 
5.3%
번 686
 
5.2%
Other values (277) 4495
34.2%
Common
ValueCountFrequency (%)
4011
50.3%
1 839
 
10.5%
2 533
 
6.7%
3 379
 
4.8%
5 368
 
4.6%
6 341
 
4.3%
4 330
 
4.1%
0 296
 
3.7%
7 258
 
3.2%
9 256
 
3.2%
Other values (7) 363
 
4.6%
Latin
ValueCountFrequency (%)
B 6
20.0%
S 6
20.0%
D 3
10.0%
C 3
10.0%
L 3
10.0%
K 2
 
6.7%
M 2
 
6.7%
Ⅱ 1
 
3.3%
A 1
 
3.3%
G 1
 
3.3%
Other values (2) 2
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13154
62.2%
ASCII 8003
37.8%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4011
50.1%
1 839
 
10.5%
2 533
 
6.7%
3 379
 
4.7%
5 368
 
4.6%
6 341
 
4.3%
4 330
 
4.1%
0 296
 
3.7%
7 258
 
3.2%
9 256
 
3.2%
Other values (18) 392
 
4.9%
Hangul
ValueCountFrequency (%)
동 1046
 
8.0%
구 980
 
7.5%
서 969
 
7.4%
시 911
 
6.9%
울 879
 
6.7%
특 876
 
6.7%
별 876
 
6.7%
지 743
 
5.6%
호 693
 
5.3%
번 686
 
5.2%
Other values (277) 4495
34.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

MISSING 

Distinct757
Distinct (%)91.5%
Missing175
Missing (%)17.5%
Memory size8.0 KiB
2024-05-11T01:02:47.160543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length61
Mean length27.489722
Min length13

Characters and Unicode

Total characters22734
Distinct characters383
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique699 ?
Unique (%)84.5%

Sample

1st row서울특별시 금천구 디지털로 185 (가산동)
2nd row서울특별시 금천구 벚꽃로 266 (가산동)
3rd row서울특별시 양천구 목동서로 100, 105호 (목동,목동3단지아파트 관리동상가)
4th row서울특별시 영등포구 영등포로 109 (당산동2가)
5th row서울특별시 방배로33길 29
ValueCountFrequency (%)
서울특별시 827
 
18.5%
중구 72
 
1.6%
송파구 59
 
1.3%
강남구 59
 
1.3%
영등포구 42
 
0.9%
구로구 39
 
0.9%
성북구 36
 
0.8%
동대문구 36
 
0.8%
마포구 34
 
0.8%
금천구 32
 
0.7%
Other values (1332) 3244
72.4%
2024-05-11T01:02:48.786774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3690
 
16.2%
동 1019
 
4.5%
서 963
 
4.2%
로 930
 
4.1%
구 917
 
4.0%
시 896
 
3.9%
울 830
 
3.7%
) 829
 
3.6%
( 829
 
3.6%
특 828
 
3.6%
Other values (373) 11003
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13936
61.3%
Space Separator 3690
 
16.2%
Decimal Number 3022
 
13.3%
Close Punctuation 830
 
3.7%
Open Punctuation 830
 
3.7%
Other Punctuation 289
 
1.3%
Uppercase Letter 61
 
0.3%
Dash Punctuation 57
 
0.3%
Math Symbol 16
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1019
 
7.3%
서 963
 
6.9%
로 930
 
6.7%
구 917
 
6.6%
시 896
 
6.4%
울 830
 
6.0%
특 828
 
5.9%
별 828
 
5.9%
길 312
 
2.2%
대 210
 
1.5%
Other values (333) 6203
44.5%
Uppercase Letter
ValueCountFrequency (%)
B 9
14.8%
L 7
11.5%
S 7
11.5%
C 6
9.8%
D 6
9.8%
A 6
9.8%
M 5
8.2%
P 3
 
4.9%
E 2
 
3.3%
K 2
 
3.3%
Other values (8) 8
13.1%
Decimal Number
ValueCountFrequency (%)
1 665
22.0%
2 455
15.1%
3 395
13.1%
0 286
9.5%
4 264
 
8.7%
5 237
 
7.8%
6 215
 
7.1%
7 184
 
6.1%
8 171
 
5.7%
9 150
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 829
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 829
99.9%
[ 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 288
99.7%
/ 1
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
p 1
50.0%
a 1
50.0%
Space Separator
ValueCountFrequency (%)
3690
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13936
61.3%
Common 8734
38.4%
Latin 64
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1019
 
7.3%
서 963
 
6.9%
로 930
 
6.7%
구 917
 
6.6%
시 896
 
6.4%
울 830
 
6.0%
특 828
 
5.9%
별 828
 
5.9%
길 312
 
2.2%
대 210
 
1.5%
Other values (333) 6203
44.5%
Latin
ValueCountFrequency (%)
B 9
14.1%
L 7
10.9%
S 7
10.9%
C 6
9.4%
D 6
9.4%
A 6
9.4%
M 5
7.8%
P 3
 
4.7%
E 2
 
3.1%
K 2
 
3.1%
Other values (11) 11
17.2%
Common
ValueCountFrequency (%)
3690
42.2%
) 829
 
9.5%
( 829
 
9.5%
1 665
 
7.6%
2 455
 
5.2%
3 395
 
4.5%
, 288
 
3.3%
0 286
 
3.3%
4 264
 
3.0%
5 237
 
2.7%
Other values (9) 796
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13936
61.3%
ASCII 8797
38.7%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3690
41.9%
) 829
 
9.4%
( 829
 
9.4%
1 665
 
7.6%
2 455
 
5.2%
3 395
 
4.5%
, 288
 
3.3%
0 286
 
3.3%
4 264
 
3.0%
5 237
 
2.7%
Other values (29) 859
 
9.8%
Hangul
ValueCountFrequency (%)
동 1019
 
7.3%
서 963
 
6.9%
로 930
 
6.7%
구 917
 
6.6%
시 896
 
6.4%
울 830
 
6.0%
특 828
 
5.9%
별 828
 
5.9%
길 312
 
2.2%
대 210
 
1.5%
Other values (333) 6203
44.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명우편번호
Text

MISSING 

Distinct577
Distinct (%)89.0%
Missing354
Missing (%)35.3%
Memory size8.0 KiB
2024-05-11T01:02:49.976125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.8996914
Min length5

Characters and Unicode

Total characters3823
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

Unique517 ?
Unique (%)79.8%

Sample

1st row153-801
2nd row150-723
3rd row137-832
4th row02523
5th row135-902
ValueCountFrequency (%)
151015 4
 
0.6%
135926 4
 
0.6%
08608 3
 
0.5%
130826 3
 
0.5%
134873 3
 
0.5%
142876 3
 
0.5%
138916 3
 
0.5%
100804 3
 
0.5%
142100 3
 
0.5%
138-240 2
 
0.3%
Other values (567) 617
95.2%
2024-05-11T01:02:51.666880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 741
19.4%
0 601
15.7%
3 460
12.0%
8 427
11.2%
5 300
7.8%
7 291
 
7.6%
2 272
 
7.1%
4 266
 
7.0%
6 187
 
4.9%
9 160
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3705
96.9%
Dash Punctuation 118
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 741
20.0%
0 601
16.2%
3 460
12.4%
8 427
11.5%
5 300
8.1%
7 291
 
7.9%
2 272
 
7.3%
4 266
 
7.2%
6 187
 
5.0%
9 160
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3823
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 741
19.4%
0 601
15.7%
3 460
12.0%
8 427
11.2%
5 300
7.8%
7 291
 
7.6%
2 272
 
7.1%
4 266
 
7.0%
6 187
 
4.9%
9 160
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3823
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 741
19.4%
0 601
15.7%
3 460
12.0%
8 427
11.2%
5 300
7.8%
7 291
 
7.6%
2 272
 
7.1%
4 266
 
7.0%
6 187
 
4.9%
9 160
 
4.2%

사업장명
Text

Distinct924
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2024-05-11T01:02:52.553685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length22
Mean length9.6706587
Min length2

Characters and Unicode

Total characters9690
Distinct characters414
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique865 ?
Unique (%)86.3%

Sample

1st row마리오아울렛 1관
2nd row마리오아울렛 3관
3rd row롯데슈퍼 목동2점
4th row영등포유통상가
5th row롯데슈퍼 방배2점
ValueCountFrequency (%)
the 36
 
2.2%
fresh 34
 
2.1%
gs 32
 
2.0%
익스프레스 31
 
1.9%
주)지에스리테일 30
 
1.8%
롯데슈퍼 29
 
1.8%
홈플러스(주 27
 
1.6%
홈플러스(주)익스프레스 22
 
1.3%
주)이마트에브리데이 22
 
1.3%
홈플러스 20
 
1.2%
Other values (970) 1357
82.7%
2024-05-11T01:02:54.279584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
639
 
6.6%
점 474
 
4.9%
스 355
 
3.7%
주 280
 
2.9%
( 279
 
2.9%
) 279
 
2.9%
데 233
 
2.4%
시 230
 
2.4%
장 213
 
2.2%
이 213
 
2.2%
Other values (404) 6495
67.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7850
81.0%
Space Separator 639
 
6.6%
Uppercase Letter 522
 
5.4%
Open Punctuation 279
 
2.9%
Close Punctuation 279
 
2.9%
Decimal Number 75
 
0.8%
Lowercase Letter 32
 
0.3%
Dash Punctuation 8
 
0.1%
Other Symbol 4
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 474
 
6.0%
스 355
 
4.5%
주 280
 
3.6%
데 233
 
3.0%
시 230
 
2.9%
장 213
 
2.7%
이 213
 
2.7%
롯 195
 
2.5%
마 162
 
2.1%
상 150
 
1.9%
Other values (354) 5345
68.1%
Uppercase Letter
ValueCountFrequency (%)
S 98
18.8%
E 77
14.8%
H 73
14.0%
G 56
10.7%
T 41
7.9%
R 41
7.9%
F 40
7.7%
A 19
 
3.6%
L 15
 
2.9%
I 9
 
1.7%
Other values (12) 53
10.2%
Lowercase Letter
ValueCountFrequency (%)
a 6
18.8%
e 4
12.5%
o 4
12.5%
k 3
9.4%
r 3
9.4%
l 3
9.4%
t 2
 
6.2%
d 2
 
6.2%
n 1
 
3.1%
z 1
 
3.1%
Other values (3) 3
9.4%
Decimal Number
ValueCountFrequency (%)
2 29
38.7%
9 16
21.3%
3 9
 
12.0%
1 7
 
9.3%
4 5
 
6.7%
6 4
 
5.3%
0 3
 
4.0%
8 1
 
1.3%
5 1
 
1.3%
Space Separator
ValueCountFrequency (%)
639
100.0%
Open Punctuation
ValueCountFrequency (%)
( 279
100.0%
Close Punctuation
ValueCountFrequency (%)
) 279
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7854
81.1%
Common 1282
 
13.2%
Latin 554
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 474
 
6.0%
스 355
 
4.5%
주 280
 
3.6%
데 233
 
3.0%
시 230
 
2.9%
장 213
 
2.7%
이 213
 
2.7%
롯 195
 
2.5%
마 162
 
2.1%
상 150
 
1.9%
Other values (355) 5349
68.1%
Latin
ValueCountFrequency (%)
S 98
17.7%
E 77
13.9%
H 73
13.2%
G 56
10.1%
T 41
7.4%
R 41
7.4%
F 40
7.2%
A 19
 
3.4%
L 15
 
2.7%
I 9
 
1.6%
Other values (25) 85
15.3%
Common
ValueCountFrequency (%)
639
49.8%
( 279
21.8%
) 279
21.8%
2 29
 
2.3%
9 16
 
1.2%
3 9
 
0.7%
- 8
 
0.6%
1 7
 
0.5%
4 5
 
0.4%
6 4
 
0.3%
Other values (4) 7
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7850
81.0%
ASCII 1836
 
18.9%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
639
34.8%
( 279
15.2%
) 279
15.2%
S 98
 
5.3%
E 77
 
4.2%
H 73
 
4.0%
G 56
 
3.1%
T 41
 
2.2%
R 41
 
2.2%
F 40
 
2.2%
Other values (39) 213
 
11.6%
Hangul
ValueCountFrequency (%)
점 474
 
6.0%
스 355
 
4.5%
주 280
 
3.6%
데 233
 
3.0%
시 230
 
2.9%
장 213
 
2.7%
이 213
 
2.7%
롯 195
 
2.5%
마 162
 
2.1%
상 150
 
1.9%
Other values (354) 5345
68.1%
None
ValueCountFrequency (%)
㈜ 4
100.0%

최종수정일자
Date

Distinct892
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
Minimum2007-06-30 10:04:31
Maximum2024-05-09 10:15:49
2024-05-11T01:02:54.828109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:02:55.337509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
I
523 
U
479 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 523
52.2%
U 479
47.8%

Length

2024-05-11T01:02:55.856604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:02:56.543911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 523
52.2%
u 479
47.8%

데이터갱신일자
Date

Distinct296
Distinct (%)29.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T01:02:56.878944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:02:57.521318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct9
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
그 밖의 대규모점포
427 
구분없음
209 
대형마트
112 
시장
82 
쇼핑센터
61 
Other values (4)
111 

Length

Max length10
Median length5
Mean length6.3602794
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row쇼핑센터
2nd row쇼핑센터
3rd row구분없음
4th row그 밖의 대규모점포
5th row대형마트

Common Values

ValueCountFrequency (%)
그 밖의 대규모점포 427
42.6%
구분없음 209
20.9%
대형마트 112
 
11.2%
시장 82
 
8.2%
쇼핑센터 61
 
6.1%
백화점 39
 
3.9%
복합쇼핑몰 37
 
3.7%
전문점 31
 
3.1%
<NA> 4
 
0.4%

Length

2024-05-11T01:02:58.202138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:02:58.598509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
그 427
23.0%
밖의 427
23.0%
대규모점포 427
23.0%
구분없음 209
11.3%
대형마트 112
 
6.0%
시장 82
 
4.4%
쇼핑센터 61
 
3.3%
백화점 39
 
2.1%
복합쇼핑몰 37
 
2.0%
전문점 31
 
1.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct744
Distinct (%)80.9%
Missing82
Missing (%)8.2%
Infinite0
Infinite (%)0.0%
Mean199618.49
Minimum182141.21
Maximum214293.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-05-11T01:02:59.258548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182141.21
5-th percentile187119.95
Q1193239.99
median201133.84
Q3205158.71
95-th percentile211252.74
Maximum214293.09
Range32151.88
Interquartile range (IQR)11918.719

Descriptive statistics

Standard deviation7439.4854
Coefficient of variation (CV)0.037268518
Kurtosis-0.89955858
Mean199618.49
Median Absolute Deviation (MAD)5644.154
Skewness-0.21209619
Sum1.8364901 × 108
Variance55345943
MonotonicityNot monotonic
2024-05-11T01:02:59.825504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
211055.486155787 8
 
0.8%
205396.363734301 7
 
0.7%
188669.484398215 5
 
0.5%
202555.30089577 5
 
0.5%
209074.900840074 5
 
0.5%
206325.349431713 4
 
0.4%
204213.643236507 4
 
0.4%
202485.226490575 4
 
0.4%
192882.837727443 3
 
0.3%
191152.432649234 3
 
0.3%
Other values (734) 872
87.0%
(Missing) 82
 
8.2%
ValueCountFrequency (%)
182141.205465089 1
0.1%
182524.823835629 1
0.1%
182735.786874703 1
0.1%
182944.731406147 1
0.1%
183124.298223484 1
0.1%
183315.556652953 2
0.2%
184102.782470646 1
0.1%
184345.724012817 1
0.1%
184473.320124105 1
0.1%
184498.0 1
0.1%
ValueCountFrequency (%)
214293.085340515 1
0.1%
213700.877714971 2
0.2%
213493.90717524 2
0.2%
213279.781081276 1
0.1%
213247.196130934 1
0.1%
213149.522764117 1
0.1%
213048.692179757 1
0.1%
212800.699970729 1
0.1%
212769.337053978 1
0.1%
212676.162193508 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct745
Distinct (%)81.0%
Missing82
Missing (%)8.2%
Infinite0
Infinite (%)0.0%
Mean449472.76
Minimum437280.57
Maximum464814.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-05-11T01:03:00.390859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437280.57
5-th percentile441986.55
Q1445248.38
median449227.81
Q3452427.38
95-th percentile458835.05
Maximum464814.72
Range27534.143
Interquartile range (IQR)7179.006

Descriptive statistics

Standard deviation5259.6612
Coefficient of variation (CV)0.011701847
Kurtosis-0.40042603
Mean449472.76
Median Absolute Deviation (MAD)3757.9124
Skewness0.34217057
Sum4.1351494 × 108
Variance27664036
MonotonicityNot monotonic
2024-05-11T01:03:01.066498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448786.697371515 8
 
0.8%
455131.683241064 7
 
0.7%
445657.80932984 5
 
0.5%
444010.738380277 5
 
0.5%
456503.066230481 4
 
0.4%
447521.520319158 4
 
0.4%
452184.2101607 4
 
0.4%
444113.028210915 4
 
0.4%
446932.653730601 3
 
0.3%
458333.989216339 3
 
0.3%
Other values (735) 873
87.1%
(Missing) 82
 
8.2%
ValueCountFrequency (%)
437280.574150819 1
 
0.1%
437562.242368734 1
 
0.1%
437914.06299827 1
 
0.1%
437986.940834791 1
 
0.1%
438699.77460936 1
 
0.1%
438701.205634976 1
 
0.1%
438834.378061101 2
0.2%
438865.160717275 3
0.3%
439137.99206467 1
 
0.1%
439247.719038249 1
 
0.1%
ValueCountFrequency (%)
464814.717432497 1
0.1%
464208.305428933 1
0.1%
463573.102150294 1
0.1%
462830.484935873 1
0.1%
462509.638445514 1
0.1%
462495.417040876 1
0.1%
462416.211580109 1
0.1%
462116.40856417 2
0.2%
462113.860476609 1
0.1%
462002.498987713 1
0.1%

점포구분명
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
<NA>
526 
대규모점포
345 
준대규모점포
131 

Length

Max length6
Median length4
Mean length4.6057884
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 526
52.5%
대규모점포 345
34.4%
준대규모점포 131
 
13.1%

Length

2024-05-11T01:03:01.650957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:02.015347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 526
52.5%
대규모점포 345
34.4%
준대규모점포 131
 
13.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
0317000020133170142075000022013-09-06<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2109-700024253.99153-023서울특별시 금천구 가산동 60번지 22호서울특별시 금천구 디지털로 185 (가산동)153-801마리오아울렛 1관2023-02-28 20:56:47U2022-12-03 00:03:00.0쇼핑센터189943.234285441784.247519<NA>
1317000020123170142075000042012-09-13<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2109-701332887.19153-801서울특별시 금천구 가산동 60번지 20호서울특별시 금천구 벚꽃로 266 (가산동)<NA>마리오아울렛 3관2023-02-28 21:05:56U2022-12-03 00:03:00.0쇼핑센터189759.713051441814.115921<NA>
2314000020123140114075000012012-04-05<NA>1영업/정상1정상영업<NA><NA><NA><NA>0226470824496.0158-753서울특별시 양천구 목5동 903번지 목동3단지아파트 관리동상가 105호서울특별시 양천구 목동서로 100, 105호 (목동,목동3단지아파트 관리동상가)<NA>롯데슈퍼 목동2점2023-03-09 09:25:54U2022-12-02 23:01:00.0구분없음188700.85117448020.090999<NA>
3318000020013180076075000291999-05-31<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2679-335041973.81150-723서울특별시 영등포구 당산동2가 30번지 2호서울특별시 영등포구 영등포로 109 (당산동2가)150-723영등포유통상가2023-03-09 15:28:54U2022-12-02 23:01:00.0그 밖의 대규모점포190555.768992446698.814323<NA>
4321000020123210122075000022012-04-24<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-536-00041049.58137-061서울특별시 서초구 방배1동 816번지 1호서울특별시 방배로33길 29137-832롯데슈퍼 방배2점2023-03-13 17:40:32U2022-12-02 23:05:00.0대형마트198984.364832443229.835879<NA>
5305000020233050210075000012023-03-14<NA>1영업/정상5영업개시전<NA><NA><NA><NA>02-2006-2364307.23<NA>서울특별시 동대문구 장안동 310-8 희헌빌딩서울특별시 동대문구 장한로28가길 45, 희헌빌딩 (장안동)02523GS THE FRESH 동대문장안점2023-03-14 09:57:17I2022-12-02 23:06:00.0구분없음206341.538777452530.018812<NA>
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