Overview

Dataset statistics

Number of variables27
Number of observations2813
Missing cells24096
Missing cells (%)31.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory621.0 KiB
Average record size in memory226.0 B

Variable types

Categorical7
Numeric4
Text7
DateTime6
Unsupported3

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),지정일자,민원종류명
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-19919/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
상세영업상태코드 is highly imbalanced (50.6%)Imbalance
상세영업상태명 is highly imbalanced (50.6%)Imbalance
인허가취소일자 has 2651 (94.2%) missing valuesMissing
폐업일자 has 825 (29.3%) missing valuesMissing
휴업시작일자 has 2747 (97.7%) missing valuesMissing
휴업종료일자 has 2748 (97.7%) missing valuesMissing
재개업일자 has 2813 (100.0%) missing valuesMissing
전화번호 has 1196 (42.5%) missing valuesMissing
소재지면적 has 2813 (100.0%) missing valuesMissing
소재지우편번호 has 2062 (73.3%) missing valuesMissing
도로명주소 has 193 (6.9%) missing valuesMissing
도로명우편번호 has 1813 (64.5%) missing valuesMissing
업태구분명 has 2813 (100.0%) missing valuesMissing
좌표정보(X) has 148 (5.3%) missing valuesMissing
좌표정보(Y) has 148 (5.3%) missing valuesMissing
지정일자 has 1115 (39.6%) missing valuesMissing
관리번호 has unique valuesUnique
재개업일자 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
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 05:48:20.440764
Analysis finished2024-05-11 05:48:22.212125
Duration1.77 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
3170000
2813 

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 2813
100.0%

Length

2024-05-11T14:48:22.324163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:22.487854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 2813
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct2813
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0085367 × 1018
Minimum1.995317 × 1018
Maximum2.024317 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T14:48:22.652447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.995317 × 1018
5-th percentile2.001317 × 1018
Q12.001317 × 1018
median2.007317 × 1018
Q32.014317 × 1018
95-th percentile2.021317 × 1018
Maximum2.024317 × 1018
Range2.9000019 × 1016
Interquartile range (IQR)1.3000007 × 1016

Descriptive statistics

Standard deviation6.9760931 × 1015
Coefficient of variation (CV)0.0034732216
Kurtosis-0.93642868
Mean2.0085367 × 1018
Median Absolute Deviation (MAD)6.0000038 × 1015
Skewness0.57546532
Sum5.3100674 × 1018
Variance4.8665875 × 1031
MonotonicityStrictly increasing
2024-05-11T14:48:22.885507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1995317006705631000 1
 
< 0.1%
2011317014205600235 1
 
< 0.1%
2011317014205600227 1
 
< 0.1%
2011317014205600228 1
 
< 0.1%
2011317014205600229 1
 
< 0.1%
2011317014205600230 1
 
< 0.1%
2011317014205600231 1
 
< 0.1%
2011317014205600232 1
 
< 0.1%
2011317014205600233 1
 
< 0.1%
2011317014205600234 1
 
< 0.1%
Other values (2803) 2803
99.6%
ValueCountFrequency (%)
1995317006705631000 1
< 0.1%
1995317006705654170 1
< 0.1%
1997317010505600424 1
< 0.1%
1998317006705600190 1
< 0.1%
1998317006705620780 1
< 0.1%
1998317006705643700 1
< 0.1%
1998317006705657930 1
< 0.1%
1998317009405602548 1
< 0.1%
1998317009405605851 1
< 0.1%
1998317014205675649 1
< 0.1%
ValueCountFrequency (%)
2024317025705600018 1
< 0.1%
2024317025705600017 1
< 0.1%
2024317025705600016 1
< 0.1%
2024317025705600015 1
< 0.1%
2024317025705600014 1
< 0.1%
2024317025705600013 1
< 0.1%
2024317025705600012 1
< 0.1%
2024317025705600011 1
< 0.1%
2024317025705600010 1
< 0.1%
2024317025705600009 1
< 0.1%
Distinct1866
Distinct (%)66.3%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
2024-05-11T14:48:23.402308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.1286882
Min length8

Characters and Unicode

Total characters22866
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

Unique1296 ?
Unique (%)46.1%

Sample

1st row19950331
2nd row19950331
3rd row19970410
4th row19981116
5th row19981216
ValueCountFrequency (%)
20010102 20
 
0.7%
19950301 18
 
0.6%
19981216 15
 
0.5%
19981217 13
 
0.5%
19981209 12
 
0.4%
20010302 10
 
0.4%
19981207 10
 
0.4%
19981223 8
 
0.3%
19981203 8
 
0.3%
20031022 8
 
0.3%
Other values (1856) 2691
95.7%
2024-05-11T14:48:24.253155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7283
31.9%
2 4507
19.7%
1 4330
18.9%
9 1669
 
7.3%
3 962
 
4.2%
8 930
 
4.1%
4 736
 
3.2%
7 710
 
3.1%
5 709
 
3.1%
6 650
 
2.8%
Other values (2) 380
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22486
98.3%
Dash Punctuation 362
 
1.6%
Space Separator 18
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7283
32.4%
2 4507
20.0%
1 4330
19.3%
9 1669
 
7.4%
3 962
 
4.3%
8 930
 
4.1%
4 736
 
3.3%
7 710
 
3.2%
5 709
 
3.2%
6 650
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 362
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22866
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7283
31.9%
2 4507
19.7%
1 4330
18.9%
9 1669
 
7.3%
3 962
 
4.2%
8 930
 
4.1%
4 736
 
3.2%
7 710
 
3.1%
5 709
 
3.1%
6 650
 
2.8%
Other values (2) 380
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22866
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7283
31.9%
2 4507
19.7%
1 4330
18.9%
9 1669
 
7.3%
3 962
 
4.2%
8 930
 
4.1%
4 736
 
3.2%
7 710
 
3.1%
5 709
 
3.1%
6 650
 
2.8%
Other values (2) 380
 
1.7%

인허가취소일자
Date

MISSING 

Distinct71
Distinct (%)43.8%
Missing2651
Missing (%)94.2%
Memory size22.1 KiB
Minimum2001-10-16 00:00:00
Maximum2024-03-15 00:00:00
2024-05-11T14:48:24.514705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:24.734851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
3
1988 
1
647 
4
 
172
2
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row3
3rd row3
4th row3
5th row1

Common Values

ValueCountFrequency (%)
3 1988
70.7%
1 647
 
23.0%
4 172
 
6.1%
2 6
 
0.2%

Length

2024-05-11T14:48:24.944432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:25.127445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1988
70.7%
1 647
 
23.0%
4 172
 
6.1%
2 6
 
0.2%

영업상태명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
폐업
1988 
영업/정상
647 
취소/말소/만료/정지/중지
 
172
휴업
 
6

Length

Max length14
Median length2
Mean length3.4237469
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row취소/말소/만료/정지/중지
2nd row폐업
3rd row폐업
4th row폐업
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 1988
70.7%
영업/정상 647
 
23.0%
취소/말소/만료/정지/중지 172
 
6.1%
휴업 6
 
0.2%

Length

2024-05-11T14:48:25.307679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:25.463908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1988
70.7%
영업/정상 647
 
23.0%
취소/말소/만료/정지/중지 172
 
6.1%
휴업 6
 
0.2%

상세영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
2
1988 
0
647 
3
 
142
5
 
30
1
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row2
3rd row2
4th row2
5th row0

Common Values

ValueCountFrequency (%)
2 1988
70.7%
0 647
 
23.0%
3 142
 
5.0%
5 30
 
1.1%
1 6
 
0.2%

Length

2024-05-11T14:48:25.630250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:25.802786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1988
70.7%
0 647
 
23.0%
3 142
 
5.0%
5 30
 
1.1%
1 6
 
0.2%

상세영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
폐업처리
1988 
정상영업
647 
직권취소
 
142
지정취소
 
30
휴업처리
 
6

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 1988
70.7%
정상영업 647
 
23.0%
직권취소 142
 
5.0%
지정취소 30
 
1.1%
휴업처리 6
 
0.2%

Length

2024-05-11T14:48:25.981307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:26.160844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 1988
70.7%
정상영업 647
 
23.0%
직권취소 142
 
5.0%
지정취소 30
 
1.1%
휴업처리 6
 
0.2%

폐업일자
Date

MISSING 

Distinct1576
Distinct (%)79.3%
Missing825
Missing (%)29.3%
Memory size22.1 KiB
Minimum2000-12-29 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T14:48:26.407657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:26.669059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct64
Distinct (%)97.0%
Missing2747
Missing (%)97.7%
Memory size22.1 KiB
Minimum2001-03-05 00:00:00
Maximum2024-01-02 00:00:00
2024-05-11T14:48:26.891952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:27.152258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업종료일자
Date

MISSING 

Distinct63
Distinct (%)96.9%
Missing2748
Missing (%)97.7%
Memory size22.1 KiB
Minimum2001-04-03 00:00:00
Maximum2024-01-28 00:00:00
2024-05-11T14:48:27.384481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:27.601346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2813
Missing (%)100.0%
Memory size24.9 KiB

전화번호
Text

MISSING 

Distinct1402
Distinct (%)86.7%
Missing1196
Missing (%)42.5%
Memory size22.1 KiB
2024-05-11T14:48:28.037095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length9.7272727
Min length2

Characters and Unicode

Total characters15729
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1257 ?
Unique (%)77.7%

Sample

1st row02-805-1832
2nd row02 8037015
3rd row0232814883
4th row02 8941689
5th row02 8020906
ValueCountFrequency (%)
02 1086
40.2%
0226361723 14
 
0.5%
1577-0711 7
 
0.3%
8067884 4
 
0.1%
8916184 4
 
0.1%
8305758 4
 
0.1%
8067309 4
 
0.1%
8541781 4
 
0.1%
8948521 4
 
0.1%
8095333 4
 
0.1%
Other values (1395) 1568
58.0%
2024-05-11T14:48:28.730017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2676
17.0%
8 2344
14.9%
2 2268
14.4%
5 1130
7.2%
1090
6.9%
6 1064
 
6.8%
3 1015
 
6.5%
9 945
 
6.0%
4 880
 
5.6%
7 843
 
5.4%
Other values (3) 1474
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14004
89.0%
Space Separator 1090
 
6.9%
Dash Punctuation 634
 
4.0%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2676
19.1%
8 2344
16.7%
2 2268
16.2%
5 1130
8.1%
6 1064
 
7.6%
3 1015
 
7.2%
9 945
 
6.7%
4 880
 
6.3%
7 843
 
6.0%
1 839
 
6.0%
Space Separator
ValueCountFrequency (%)
1090
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 634
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15729
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2676
17.0%
8 2344
14.9%
2 2268
14.4%
5 1130
7.2%
1090
6.9%
6 1064
 
6.8%
3 1015
 
6.5%
9 945
 
6.0%
4 880
 
5.6%
7 843
 
5.4%
Other values (3) 1474
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15729
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2676
17.0%
8 2344
14.9%
2 2268
14.4%
5 1130
7.2%
1090
6.9%
6 1064
 
6.8%
3 1015
 
6.5%
9 945
 
6.0%
4 880
 
5.6%
7 843
 
5.4%
Other values (3) 1474
9.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2813
Missing (%)100.0%
Memory size24.9 KiB

소재지우편번호
Text

MISSING 

Distinct104
Distinct (%)13.8%
Missing2062
Missing (%)73.3%
Memory size22.1 KiB
2024-05-11T14:48:29.078703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0173103
Min length6

Characters and Unicode

Total characters4519
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

Unique39 ?
Unique (%)5.2%

Sample

1st row153857
2nd row153835
3rd row153810
4th row153800
5th row153808
ValueCountFrequency (%)
153023 99
 
13.2%
153010 86
 
11.5%
153030 82
 
10.9%
153801 32
 
4.3%
153825 22
 
2.9%
153857 20
 
2.7%
153864 20
 
2.7%
153829 16
 
2.1%
153806 15
 
2.0%
153803 15
 
2.0%
Other values (94) 344
45.8%
2024-05-11T14:48:29.924208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 1044
23.1%
1 995
22.0%
5 878
19.4%
0 607
13.4%
8 418
9.2%
2 217
 
4.8%
6 119
 
2.6%
7 116
 
2.6%
4 61
 
1.3%
9 48
 
1.1%
Other values (2) 16
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4503
99.6%
Dash Punctuation 13
 
0.3%
Space Separator 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1044
23.2%
1 995
22.1%
5 878
19.5%
0 607
13.5%
8 418
9.3%
2 217
 
4.8%
6 119
 
2.6%
7 116
 
2.6%
4 61
 
1.4%
9 48
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4519
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1044
23.1%
1 995
22.0%
5 878
19.4%
0 607
13.4%
8 418
9.2%
2 217
 
4.8%
6 119
 
2.6%
7 116
 
2.6%
4 61
 
1.3%
9 48
 
1.1%
Other values (2) 16
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4519
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1044
23.1%
1 995
22.0%
5 878
19.4%
0 607
13.4%
8 418
9.2%
2 217
 
4.8%
6 119
 
2.6%
7 116
 
2.6%
4 61
 
1.3%
9 48
 
1.1%
Other values (2) 16
 
0.4%
Distinct2330
Distinct (%)83.2%
Missing11
Missing (%)0.4%
Memory size22.1 KiB
2024-05-11T14:48:30.434983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length48
Mean length25.895789
Min length9

Characters and Unicode

Total characters72560
Distinct characters303
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1976 ?
Unique (%)70.5%

Sample

1st row서울특별시 금천구 독산동 1088번지 1호 주공13단지아파트
2nd row서울특별시 금천구 독산동 1108호
3rd row서울특별시 금천구 시흥동 885번지 5호
4th row서울특별시 금천구 가산동 459번지 18호
5th row서울특별시 금천구 가산동 237번지 23호
ValueCountFrequency (%)
서울특별시 2802
18.5%
금천구 2802
18.5%
독산동 976
 
6.4%
시흥동 910
 
6.0%
가산동 660
 
4.4%
472
 
3.1%
1호 136
 
0.9%
1층 81
 
0.5%
2호 81
 
0.5%
4호 79
 
0.5%
Other values (1580) 6150
40.6%
2024-05-11T14:48:31.250828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15266
21.0%
3886
 
5.4%
1 3123
 
4.3%
2878
 
4.0%
2823
 
3.9%
2821
 
3.9%
2814
 
3.9%
2812
 
3.9%
2807
 
3.9%
2802
 
3.9%
Other values (293) 30528
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42209
58.2%
Space Separator 15266
 
21.0%
Decimal Number 14470
 
19.9%
Dash Punctuation 287
 
0.4%
Uppercase Letter 241
 
0.3%
Other Punctuation 45
 
0.1%
Lowercase Letter 14
 
< 0.1%
Open Punctuation 13
 
< 0.1%
Close Punctuation 13
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3886
 
9.2%
2878
 
6.8%
2823
 
6.7%
2821
 
6.7%
2814
 
6.7%
2812
 
6.7%
2807
 
6.7%
2802
 
6.6%
2802
 
6.6%
2695
 
6.4%
Other values (245) 13069
31.0%
Uppercase Letter
ValueCountFrequency (%)
B 47
19.5%
A 36
14.9%
T 29
12.0%
I 19
7.9%
C 18
 
7.5%
G 11
 
4.6%
K 11
 
4.6%
S 10
 
4.1%
E 10
 
4.1%
L 9
 
3.7%
Other values (13) 41
17.0%
Decimal Number
ValueCountFrequency (%)
1 3123
21.6%
9 1557
10.8%
2 1539
10.6%
0 1435
9.9%
3 1378
9.5%
8 1328
9.2%
4 1241
 
8.6%
5 1023
 
7.1%
7 970
 
6.7%
6 876
 
6.1%
Lowercase Letter
ValueCountFrequency (%)
a 4
28.6%
b 3
21.4%
i 3
21.4%
e 2
14.3%
h 1
 
7.1%
g 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 36
80.0%
. 6
 
13.3%
/ 2
 
4.4%
# 1
 
2.2%
Space Separator
ValueCountFrequency (%)
15266
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 287
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42209
58.2%
Common 30094
41.5%
Latin 257
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3886
 
9.2%
2878
 
6.8%
2823
 
6.7%
2821
 
6.7%
2814
 
6.7%
2812
 
6.7%
2807
 
6.7%
2802
 
6.6%
2802
 
6.6%
2695
 
6.4%
Other values (245) 13069
31.0%
Latin
ValueCountFrequency (%)
B 47
18.3%
A 36
14.0%
T 29
11.3%
I 19
 
7.4%
C 18
 
7.0%
G 11
 
4.3%
K 11
 
4.3%
S 10
 
3.9%
E 10
 
3.9%
L 9
 
3.5%
Other values (20) 57
22.2%
Common
ValueCountFrequency (%)
15266
50.7%
1 3123
 
10.4%
9 1557
 
5.2%
2 1539
 
5.1%
0 1435
 
4.8%
3 1378
 
4.6%
8 1328
 
4.4%
4 1241
 
4.1%
5 1023
 
3.4%
7 970
 
3.2%
Other values (8) 1234
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42207
58.2%
ASCII 30349
41.8%
Number Forms 2
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15266
50.3%
1 3123
 
10.3%
9 1557
 
5.1%
2 1539
 
5.1%
0 1435
 
4.7%
3 1378
 
4.5%
8 1328
 
4.4%
4 1241
 
4.1%
5 1023
 
3.4%
7 970
 
3.2%
Other values (37) 1489
 
4.9%
Hangul
ValueCountFrequency (%)
3886
 
9.2%
2878
 
6.8%
2823
 
6.7%
2821
 
6.7%
2814
 
6.7%
2812
 
6.7%
2807
 
6.7%
2802
 
6.6%
2802
 
6.6%
2695
 
6.4%
Other values (244) 13067
31.0%
Number Forms
ValueCountFrequency (%)
2
100.0%
Compat Jamo
ValueCountFrequency (%)
2
100.0%

도로명주소
Text

MISSING 

Distinct1811
Distinct (%)69.1%
Missing193
Missing (%)6.9%
Memory size22.1 KiB
2024-05-11T14:48:31.765707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length53
Mean length29.314885
Min length18

Characters and Unicode

Total characters76805
Distinct characters326
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1337 ?
Unique (%)51.0%

Sample

1st row서울특별시 금천구 한내로 69-15, 1316동 104-105호 (독산동, 주공13단지아파트)
2nd row서울특별시 금천구 금하로1라길 32 (독산동)
3rd row서울특별시 금천구 금하로 648 (시흥동)
4th row서울특별시 금천구 가산디지털2로 151 (가산동)
5th row서울특별시 금천구 두산로3길 60 (가산동)
ValueCountFrequency (%)
서울특별시 2620
17.8%
금천구 2613
17.7%
독산동 968
 
6.6%
시흥동 855
 
5.8%
가산동 499
 
3.4%
1층 382
 
2.6%
시흥대로 252
 
1.7%
독산로 197
 
1.3%
가산디지털1로 158
 
1.1%
금하로 93
 
0.6%
Other values (1443) 6090
41.4%
2024-05-11T14:48:32.573378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12117
 
15.8%
4365
 
5.7%
1 3411
 
4.4%
2888
 
3.8%
2820
 
3.7%
2748
 
3.6%
2658
 
3.5%
2637
 
3.4%
2634
 
3.4%
) 2630
 
3.4%
Other values (316) 37897
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45463
59.2%
Decimal Number 12131
 
15.8%
Space Separator 12117
 
15.8%
Close Punctuation 2630
 
3.4%
Open Punctuation 2630
 
3.4%
Other Punctuation 1313
 
1.7%
Uppercase Letter 256
 
0.3%
Dash Punctuation 248
 
0.3%
Lowercase Letter 13
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4365
 
9.6%
2888
 
6.4%
2820
 
6.2%
2748
 
6.0%
2658
 
5.8%
2637
 
5.8%
2634
 
5.8%
2620
 
5.8%
2620
 
5.8%
2617
 
5.8%
Other values (266) 16856
37.1%
Uppercase Letter
ValueCountFrequency (%)
B 58
22.7%
A 40
15.6%
T 28
10.9%
I 20
 
7.8%
C 16
 
6.2%
G 13
 
5.1%
S 12
 
4.7%
K 11
 
4.3%
E 10
 
3.9%
L 10
 
3.9%
Other values (13) 38
14.8%
Decimal Number
ValueCountFrequency (%)
1 3411
28.1%
2 1569
12.9%
3 1225
 
10.1%
0 1220
 
10.1%
4 1029
 
8.5%
5 815
 
6.7%
6 789
 
6.5%
8 749
 
6.2%
7 719
 
5.9%
9 605
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
23.1%
i 3
23.1%
a 2
15.4%
b 2
15.4%
o 1
 
7.7%
g 1
 
7.7%
h 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 1301
99.1%
. 9
 
0.7%
/ 2
 
0.2%
# 1
 
0.1%
Space Separator
ValueCountFrequency (%)
12117
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2630
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2630
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 248
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45463
59.2%
Common 31071
40.5%
Latin 271
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4365
 
9.6%
2888
 
6.4%
2820
 
6.2%
2748
 
6.0%
2658
 
5.8%
2637
 
5.8%
2634
 
5.8%
2620
 
5.8%
2620
 
5.8%
2617
 
5.8%
Other values (266) 16856
37.1%
Latin
ValueCountFrequency (%)
B 58
21.4%
A 40
14.8%
T 28
10.3%
I 20
 
7.4%
C 16
 
5.9%
G 13
 
4.8%
S 12
 
4.4%
K 11
 
4.1%
E 10
 
3.7%
L 10
 
3.7%
Other values (21) 53
19.6%
Common
ValueCountFrequency (%)
12117
39.0%
1 3411
 
11.0%
) 2630
 
8.5%
( 2630
 
8.5%
2 1569
 
5.0%
, 1301
 
4.2%
3 1225
 
3.9%
0 1220
 
3.9%
4 1029
 
3.3%
5 815
 
2.6%
Other values (9) 3124
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45461
59.2%
ASCII 31340
40.8%
Compat Jamo 2
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12117
38.7%
1 3411
 
10.9%
) 2630
 
8.4%
( 2630
 
8.4%
2 1569
 
5.0%
, 1301
 
4.2%
3 1225
 
3.9%
0 1220
 
3.9%
4 1029
 
3.3%
5 815
 
2.6%
Other values (39) 3393
 
10.8%
Hangul
ValueCountFrequency (%)
4365
 
9.6%
2888
 
6.4%
2820
 
6.2%
2748
 
6.0%
2658
 
5.8%
2637
 
5.8%
2634
 
5.8%
2620
 
5.8%
2620
 
5.8%
2617
 
5.8%
Other values (265) 16854
37.1%
Compat Jamo
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
2
100.0%

도로명우편번호
Text

MISSING 

Distinct226
Distinct (%)22.6%
Missing1813
Missing (%)64.5%
Memory size22.1 KiB
2024-05-11T14:48:33.124847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.349
Min length5

Characters and Unicode

Total characters5349
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

Unique54 ?
Unique (%)5.4%

Sample

1st row08598
2nd row08519
3rd row153835
4th row153868
5th row153810
ValueCountFrequency (%)
153801 29
 
2.9%
08639 19
 
1.9%
153864 15
 
1.5%
153813 13
 
1.3%
08608 13
 
1.3%
153825 13
 
1.3%
153857 13
 
1.3%
153829 13
 
1.3%
08505 13
 
1.3%
153803 12
 
1.2%
Other values (216) 847
84.7%
2024-05-11T14:48:33.981032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 1078
20.2%
5 992
18.5%
0 938
17.5%
1 622
11.6%
3 548
10.2%
6 388
 
7.3%
2 252
 
4.7%
4 200
 
3.7%
7 173
 
3.2%
9 150
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5341
99.9%
Dash Punctuation 8
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 1078
20.2%
5 992
18.6%
0 938
17.6%
1 622
11.6%
3 548
10.3%
6 388
 
7.3%
2 252
 
4.7%
4 200
 
3.7%
7 173
 
3.2%
9 150
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5349
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 1078
20.2%
5 992
18.5%
0 938
17.5%
1 622
11.6%
3 548
10.2%
6 388
 
7.3%
2 252
 
4.7%
4 200
 
3.7%
7 173
 
3.2%
9 150
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5349
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 1078
20.2%
5 992
18.5%
0 938
17.5%
1 622
11.6%
3 548
10.2%
6 388
 
7.3%
2 252
 
4.7%
4 200
 
3.7%
7 173
 
3.2%
9 150
 
2.8%
Distinct2109
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
2024-05-11T14:48:34.423458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length6.5570565
Min length2

Characters and Unicode

Total characters18445
Distinct characters584
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1727 ?
Unique (%)61.4%

Sample

1st row임마누엘슈퍼
2nd row독산유통
3rd row대명가방(속초식당)
4th row운동장매점
5th row공주슈퍼
ValueCountFrequency (%)
씨유 140
 
3.9%
gs25 102
 
2.9%
세븐일레븐 81
 
2.3%
미니스톱 34
 
1.0%
이마트24 33
 
0.9%
지에스25 29
 
0.8%
주)코리아세븐 24
 
0.7%
제일슈퍼 15
 
0.4%
현대슈퍼 13
 
0.4%
지에스(gs)25 12
 
0.3%
Other values (2150) 3064
86.4%
2024-05-11T14:48:35.060135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
789
 
4.3%
737
 
4.0%
561
 
3.0%
533
 
2.9%
516
 
2.8%
487
 
2.6%
441
 
2.4%
326
 
1.8%
2 319
 
1.7%
295
 
1.6%
Other values (574) 13441
72.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15845
85.9%
Decimal Number 757
 
4.1%
Space Separator 737
 
4.0%
Uppercase Letter 646
 
3.5%
Open Punctuation 194
 
1.1%
Close Punctuation 194
 
1.1%
Lowercase Letter 52
 
0.3%
Other Punctuation 16
 
0.1%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
789
 
5.0%
561
 
3.5%
533
 
3.4%
516
 
3.3%
487
 
3.1%
441
 
2.8%
326
 
2.1%
295
 
1.9%
282
 
1.8%
271
 
1.7%
Other values (511) 11344
71.6%
Uppercase Letter
ValueCountFrequency (%)
G 218
33.7%
S 216
33.4%
C 40
 
6.2%
L 24
 
3.7%
U 22
 
3.4%
K 22
 
3.4%
E 11
 
1.7%
M 10
 
1.5%
D 10
 
1.5%
N 9
 
1.4%
Other values (14) 64
 
9.9%
Lowercase Letter
ValueCountFrequency (%)
e 8
15.4%
i 6
11.5%
a 5
9.6%
t 5
9.6%
l 4
 
7.7%
r 4
 
7.7%
o 3
 
5.8%
s 3
 
5.8%
y 3
 
5.8%
u 1
 
1.9%
Other values (10) 10
19.2%
Decimal Number
ValueCountFrequency (%)
2 319
42.1%
5 271
35.8%
4 53
 
7.0%
3 30
 
4.0%
1 26
 
3.4%
6 16
 
2.1%
8 15
 
2.0%
7 13
 
1.7%
9 8
 
1.1%
0 6
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 6
37.5%
& 4
25.0%
. 4
25.0%
? 1
 
6.2%
/ 1
 
6.2%
Space Separator
ValueCountFrequency (%)
737
100.0%
Open Punctuation
ValueCountFrequency (%)
( 194
100.0%
Close Punctuation
ValueCountFrequency (%)
) 194
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15845
85.9%
Common 1902
 
10.3%
Latin 698
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
789
 
5.0%
561
 
3.5%
533
 
3.4%
516
 
3.3%
487
 
3.1%
441
 
2.8%
326
 
2.1%
295
 
1.9%
282
 
1.8%
271
 
1.7%
Other values (511) 11344
71.6%
Latin
ValueCountFrequency (%)
G 218
31.2%
S 216
30.9%
C 40
 
5.7%
L 24
 
3.4%
U 22
 
3.2%
K 22
 
3.2%
E 11
 
1.6%
M 10
 
1.4%
D 10
 
1.4%
N 9
 
1.3%
Other values (34) 116
16.6%
Common
ValueCountFrequency (%)
737
38.7%
2 319
16.8%
5 271
 
14.2%
( 194
 
10.2%
) 194
 
10.2%
4 53
 
2.8%
3 30
 
1.6%
1 26
 
1.4%
6 16
 
0.8%
8 15
 
0.8%
Other values (9) 47
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15845
85.9%
ASCII 2600
 
14.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
789
 
5.0%
561
 
3.5%
533
 
3.4%
516
 
3.3%
487
 
3.1%
441
 
2.8%
326
 
2.1%
295
 
1.9%
282
 
1.8%
271
 
1.7%
Other values (511) 11344
71.6%
ASCII
ValueCountFrequency (%)
737
28.3%
2 319
12.3%
5 271
 
10.4%
G 218
 
8.4%
S 216
 
8.3%
( 194
 
7.5%
) 194
 
7.5%
4 53
 
2.0%
C 40
 
1.5%
3 30
 
1.2%
Other values (53) 328
12.6%
Distinct1989
Distinct (%)70.7%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
Minimum2007-07-10 09:39:32
Maximum2024-05-07 13:43:42
2024-05-11T14:48:35.294705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:35.599518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
I
2232 
U
581 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2232
79.3%
U 581
 
20.7%

Length

2024-05-11T14:48:35.819797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:35.973689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2232
79.3%
u 581
 
20.7%
Distinct525
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:48:36.144702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:36.375647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2813
Missing (%)100.0%
Memory size24.9 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1207
Distinct (%)45.3%
Missing148
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean190956.92
Minimum188808.52
Maximum192754.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T14:48:36.581354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum188808.52
5-th percentile189417.68
Q1190413.85
median191191.87
Q3191497.59
95-th percentile191936.21
Maximum192754.35
Range3945.8246
Interquartile range (IQR)1083.7406

Descriptive statistics

Standard deviation785.82345
Coefficient of variation (CV)0.0041151871
Kurtosis-0.25823478
Mean190956.92
Median Absolute Deviation (MAD)425.69686
Skewness-0.66294365
Sum5.0890018 × 108
Variance617518.49
MonotonicityNot monotonic
2024-05-11T14:48:36.811125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
191226.287379467 36
 
1.3%
191390.785127877 16
 
0.6%
189720.13564195 14
 
0.5%
189669.316805063 13
 
0.5%
189538.020935968 12
 
0.4%
192754.34619252 11
 
0.4%
191601.031218762 10
 
0.4%
191688.801345744 10
 
0.4%
191919.012705941 9
 
0.3%
191218.125319193 9
 
0.3%
Other values (1197) 2525
89.8%
(Missing) 148
 
5.3%
ValueCountFrequency (%)
188808.521556281 1
< 0.1%
188870.636085641 1
< 0.1%
188882.169962717 1
< 0.1%
188887.197646973 1
< 0.1%
188927.953883941 1
< 0.1%
188951.946721795 1
< 0.1%
188968.189711073 2
0.1%
188974.800556597 2
0.1%
188979.225789508 1
< 0.1%
188981.555267121 2
0.1%
ValueCountFrequency (%)
192754.34619252 11
0.4%
192742.326147617 2
 
0.1%
192584.164515811 4
 
0.1%
192513.506810363 3
 
0.1%
192480.368331844 2
 
0.1%
192458.273299314 1
 
< 0.1%
192434.31669691 4
 
0.1%
192368.43764933 1
 
< 0.1%
192355.210265686 1
 
< 0.1%
192350.237217477 5
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1207
Distinct (%)45.3%
Missing148
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean440324.68
Minimum436888.77
Maximum442636.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T14:48:37.039157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436888.77
5-th percentile437914.06
Q1439187.46
median440552.31
Q3441504.23
95-th percentile442043.59
Maximum442636.32
Range5747.5466
Interquartile range (IQR)2316.7757

Descriptive statistics

Standard deviation1340.6704
Coefficient of variation (CV)0.0030447315
Kurtosis-0.75386333
Mean440324.68
Median Absolute Deviation (MAD)1075.5892
Skewness-0.4575264
Sum1.1734653 × 109
Variance1797397.1
MonotonicityNot monotonic
2024-05-11T14:48:37.269648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
437914.06299827 36
 
1.3%
437280.574150819 16
 
0.6%
440711.695061423 14
 
0.5%
440921.514797121 13
 
0.5%
441982.427934953 12
 
0.4%
438827.143732711 11
 
0.4%
441761.98349337 10
 
0.4%
441962.652912411 10
 
0.4%
440127.175851359 9
 
0.3%
441476.941407818 9
 
0.3%
Other values (1197) 2525
89.8%
(Missing) 148
 
5.3%
ValueCountFrequency (%)
436888.773525926 6
0.2%
436897.466167682 1
 
< 0.1%
436925.910122707 3
0.1%
436946.358720615 4
0.1%
436991.446935421 3
0.1%
436999.258171772 3
0.1%
437033.621043602 2
 
0.1%
437099.172901614 1
 
< 0.1%
437150.06550978 4
0.1%
437188.189860689 2
 
0.1%
ValueCountFrequency (%)
442636.320100968 3
0.1%
442585.933234852 7
0.2%
442569.300676147 5
0.2%
442562.722742062 3
0.1%
442553.141302572 1
 
< 0.1%
442545.885794533 1
 
< 0.1%
442542.727581637 1
 
< 0.1%
442520.64227331 1
 
< 0.1%
442497.377672482 2
 
0.1%
442493.020182986 5
0.2%

지정일자
Real number (ℝ)

MISSING 

Distinct1208
Distinct (%)71.1%
Missing1115
Missing (%)39.6%
Infinite0
Infinite (%)0.0%
Mean20094205
Minimum19830914
Maximum20220307
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T14:48:37.509485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19830914
5-th percentile19981223
Q120050650
median20091203
Q320141128
95-th percentile20192563
Maximum20220307
Range389393
Interquartile range (IQR)90478.5

Descriptive statistics

Standard deviation64483.342
Coefficient of variation (CV)0.0032090516
Kurtosis-0.43776517
Mean20094205
Median Absolute Deviation (MAD)49826.5
Skewness-0.19973121
Sum3.411996 × 1010
Variance4.1581014 × 109
MonotonicityNot monotonic
2024-05-11T14:48:37.810599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20010102 20
 
0.7%
20010302 9
 
0.3%
20010502 7
 
0.2%
19981216 7
 
0.2%
20010201 6
 
0.2%
20010601 5
 
0.2%
20070215 5
 
0.2%
20080808 5
 
0.2%
20141128 5
 
0.2%
20090219 4
 
0.1%
Other values (1198) 1625
57.8%
(Missing) 1115
39.6%
ValueCountFrequency (%)
19830914 1
 
< 0.1%
19851002 1
 
< 0.1%
19870710 1
 
< 0.1%
19870727 1
 
< 0.1%
19880727 1
 
< 0.1%
19891115 1
 
< 0.1%
19930818 1
 
< 0.1%
19940613 1
 
< 0.1%
19950301 3
0.1%
19950329 1
 
< 0.1%
ValueCountFrequency (%)
20220307 1
< 0.1%
20220228 1
< 0.1%
20220225 1
< 0.1%
20220217 1
< 0.1%
20220209 1
< 0.1%
20220124 1
< 0.1%
20220121 1
< 0.1%
20220105 1
< 0.1%
20211129 1
< 0.1%
20211125 1
< 0.1%

민원종류명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
<NA>
1115 
2009년11월법개정전자료
832 
제7조의3제2항에따른경우
789 
제7조의3제3항에따른경우
 
77

Length

Max length14
Median length13
Mean length9.7284038
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2009년11월법개정전자료
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row2009년11월법개정전자료

Common Values

ValueCountFrequency (%)
<NA> 1115
39.6%
2009년11월법개정전자료 832
29.6%
제7조의3제2항에따른경우 789
28.0%
제7조의3제3항에따른경우 77
 
2.7%

Length

2024-05-11T14:48:38.123836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:38.300564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1115
39.6%
2009년11월법개정전자료 832
29.6%
제7조의3제2항에따른경우 789
28.0%
제7조의3제3항에따른경우 77
 
2.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)지정일자민원종류명
03170000199531700670563100019950331202003094취소/말소/만료/정지/중지5지정취소<NA>2020020120200229<NA>02-805-1832<NA><NA>서울특별시 금천구 독산동 1088번지 1호 주공13단지아파트서울특별시 금천구 한내로 69-15, 1316동 104-105호 (독산동, 주공13단지아파트)08598임마누엘슈퍼2020-03-09 09:27:52U2020-03-11 02:40:00.0<NA>189920.5409439526.232038199503312009년11월법개정전자료
13170000199531700670565417019950331<NA>3폐업2폐업처리20060704<NA><NA><NA>02 8037015<NA><NA>서울특별시 금천구 독산동 1108호서울특별시 금천구 금하로1라길 32 (독산동)<NA>독산유통2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>190258.160768439066.093039<NA><NA>
23170000199731701050560042419970410<NA>3폐업2폐업처리20070221<NA><NA><NA><NA><NA><NA>서울특별시 금천구 시흥동 885번지 5호서울특별시 금천구 금하로 648 (시흥동)<NA>대명가방(속초식당)2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>191318.554666439106.410952<NA><NA>
33170000199831700670560019019981116<NA>3폐업2폐업처리20021231<NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 459번지 18호서울특별시 금천구 가산디지털2로 151 (가산동)<NA>운동장매점2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>189089.545931442157.416525<NA><NA>
43170000199831700670562078019981216<NA>1영업/정상0정상영업<NA><NA><NA><NA>0232814883<NA><NA>서울특별시 금천구 가산동 237번지 23호서울특별시 금천구 두산로3길 60 (가산동)08519공주슈퍼2019-07-04 10:27:59U2019-07-06 02:40:00.0<NA>190098.999971441226.22005199812162009년11월법개정전자료
53170000199831700670564370019981209<NA>1영업/정상0정상영업<NA><NA><NA><NA>02 8941689<NA><NA>서울특별시 금천구 시흥동 888번지 19 호서울특별시 금천구 시흥대로58길 18 (시흥동)<NA>마마방2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>191282.675561439059.863014<NA><NA>
63170000199831700670565793019981221<NA>3폐업2폐업처리20040611<NA><NA><NA>02 8020906<NA><NA>서울특별시 금천구 시흥동 853번지 26호서울특별시 금천구 독산로39길 42 (시흥동)<NA>K마트2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>191381.526238439539.510157<NA><NA>
73170000199831700940560254819981222<NA>3폐업2폐업처리20060929<NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 호 148-36<NA><NA>고씨네갈비집2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA>
83170000199831700940560585119981117<NA>3폐업2폐업처리20051221<NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 959번지 23호서울특별시 금천구 독산로 359 (독산동)<NA>현대슈퍼2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>191399.035388441861.462958<NA><NA>
93170000199831701420567564919981114<NA>3폐업2폐업처리20121016<NA><NA><NA><NA><NA>153857서울특별시 금천구 시흥1동 856번지 23호서울특별시 금천구 독산로 137 (시흥동)<NA>한양식품2012-10-16 16:48:15I2018-08-31 23:59:59.0<NA>191502.674094439719.54339199811142009년11월법개정전자료
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)지정일자민원종류명
2803317000020243170257056000092024-03-12<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 60-4 코오롱테크노밸리서울특별시 금천구 디지털로9길 56, 코오롱테크노밸리 1층 101(일부)호 (가산동)08512가산내차례복권2024-03-12 11:13:08I2023-12-02 23:04:00.0<NA>189917.493331442031.656022<NA><NA>
2804317000020243170257056000102024-03-15<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 345-2서울특별시 금천구 가산디지털1로 100, 115호 (가산동)08590지에스25 가산골드타워2024-03-15 15:55:11I2023-12-02 23:07:00.0<NA>189744.930421441398.745566<NA><NA>
2805317000020243170257056000112024-03-26<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 881-11서울특별시 금천구 독산로106길 37, 1층 (독산동)08547이마트24 독산센터점2024-04-23 10:41:21U2023-12-03 22:05:00.0<NA>191601.031219441761.983493<NA><NA>
2806317000020243170257056000122024-03-29<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 152-8서울특별시 금천구 시흥대로 427 (독산동)08535(주)코리아세븐 금천독산점2024-03-29 17:00:24I2023-12-02 21:01:00.0<NA>190887.148805441064.093087<NA><NA>
2807317000020243170257056000132024-04-05<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 459-24서울특별시 금천구 가산디지털2로 169-16, o207호 (가산동)08500골프살롱2024-04-05 16:22:12I2023-12-04 00:07:00.0<NA>189016.465808442320.784167<NA><NA>
2808317000020243170257056000142024-04-17<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 219-5 가산테라타워서울특별시 금천구 디지털로10길 78, 가산테라타워 1층 114호 (가산동)08517지에스25 가산테라타워2024-04-17 18:04:58I2023-12-03 23:09:00.0<NA>190185.054136441381.452927<NA><NA>
2809317000020243170257056000152024-04-29<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 147-25서울특별시 금천구 남부순환로112길 15 (가산동)08529GS25 가산본점2024-04-29 18:05:00I2023-12-05 00:01:00.0<NA>190645.544979441751.642807<NA><NA>
2810317000020243170257056000162024-04-30<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 962-28서울특별시 금천구 독산로 335-1 (독산동)08538(주)코리아세븐 독산본점2024-04-30 09:19:25I2023-12-05 00:02:00.0<NA>191386.912755441627.9038<NA><NA>
2811317000020243170257056000172024-04-30<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 60-26서울특별시 금천구 디지털로 178, 143호 (가산동)08513씨유 퍼블릭가산2호점2024-04-30 13:55:00I2023-12-05 00:02:00.0<NA>189930.507904441616.46071<NA><NA>
2812317000020243170257056000182024-05-02<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 1133 진도아파트서울특별시 금천구 두산로 36, 102,103호 (독산동, 진도아파트)08583지에스(GS)25독산두산로점2024-05-02 17:59:11I2023-12-05 00:04:00.0<NA>190395.63669440875.914368<NA><NA>