Overview

Dataset statistics

Number of variables33
Number of observations276
Missing cells2594
Missing cells (%)28.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory75.6 KiB
Average record size in memory280.5 B

Variable types

Categorical13
Numeric4
Text8
Unsupported5
DateTime3

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),환경업무구분명,업종구분명,종별명,주생산품명,배출시설조업시간,배출시설연간가동일수,방지시설조업시간,방지시설연간가동일수
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-19367/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
배출시설조업시간 is highly imbalanced (52.4%)Imbalance
방지시설조업시간 is highly imbalanced (53.4%)Imbalance
인허가취소일자 has 276 (100.0%) missing valuesMissing
폐업일자 has 245 (88.8%) missing valuesMissing
휴업시작일자 has 276 (100.0%) missing valuesMissing
휴업종료일자 has 276 (100.0%) missing valuesMissing
재개업일자 has 276 (100.0%) missing valuesMissing
전화번호 has 105 (38.0%) missing valuesMissing
소재지면적 has 276 (100.0%) missing valuesMissing
소재지우편번호 has 253 (91.7%) missing valuesMissing
도로명주소 has 40 (14.5%) missing valuesMissing
도로명우편번호 has 142 (51.4%) missing valuesMissing
업태구분명 has 83 (30.1%) missing valuesMissing
좌표정보(X) has 36 (13.0%) missing valuesMissing
좌표정보(Y) has 36 (13.0%) missing valuesMissing
주생산품명 has 273 (98.9%) 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
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 00:20:09.376410
Analysis finished2024-05-11 00:20:11.729769
Duration2.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
3150000
276 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 276
100.0%

Length

2024-05-11T00:20:11.963708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:12.396220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 276
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct276
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1500002 × 1017
Minimum3.1500002 × 1017
Maximum3.1500002 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T00:20:12.934783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1500002 × 1017
5-th percentile3.1500002 × 1017
Q13.1500002 × 1017
median3.1500002 × 1017
Q33.1500002 × 1017
95-th percentile3.1500002 × 1017
Maximum3.1500002 × 1017
Range4799987
Interquartile range (IQR)1599872

Descriptive statistics

Standard deviation932458.54
Coefficient of variation (CV)2.9601856 × 10-12
Kurtosis-0.34242891
Mean3.1500002 × 1017
Median Absolute Deviation (MAD)799872
Skewness-0.29255337
Sum-5.2937145 × 1018
Variance8.6947892 × 1011
MonotonicityStrictly increasing
2024-05-11T00:20:13.447014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
315000021197500016 1
 
0.4%
315000021201500007 1
 
0.4%
315000021201500013 1
 
0.4%
315000021201500012 1
 
0.4%
315000021201500011 1
 
0.4%
315000021201500010 1
 
0.4%
315000021201500009 1
 
0.4%
315000021201500008 1
 
0.4%
315000021201500006 1
 
0.4%
315000021201400002 1
 
0.4%
Other values (266) 266
96.4%
ValueCountFrequency (%)
315000021197500016 1
0.4%
315000021197500034 1
0.4%
315000021198800009 1
0.4%
315000021198800047 1
0.4%
315000021199100050 1
0.4%
315000021199200008 1
0.4%
315000021199200022 1
0.4%
315000021199200027 1
0.4%
315000021199200029 1
0.4%
315000021199200043 1
0.4%
ValueCountFrequency (%)
315000021202300003 1
0.4%
315000021202300002 1
0.4%
315000021202300001 1
0.4%
315000021202200006 1
0.4%
315000021202200005 1
0.4%
315000021202200004 1
0.4%
315000021202200003 1
0.4%
315000021202200002 1
0.4%
315000021202200001 1
0.4%
315000021202100014 1
0.4%

인허가일자
Text

Distinct243
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-05-11T00:20:14.223559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.3985507
Min length8

Characters and Unicode

Total characters2318
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

Unique215 ?
Unique (%)77.9%

Sample

1st row20020121
2nd row19750116
3rd row19881101
4th row20010810
5th row19910611
ValueCountFrequency (%)
20151217 4
 
1.4%
2017-11-16 3
 
1.1%
19991029 3
 
1.1%
20160104 3
 
1.1%
20010111 2
 
0.7%
19981112 2
 
0.7%
20151221 2
 
0.7%
2021-04-01 2
 
0.7%
20001018 2
 
0.7%
20000619 2
 
0.7%
Other values (233) 251
90.9%
2024-05-11T00:20:15.598503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 700
30.2%
2 461
19.9%
1 453
19.5%
9 141
 
6.1%
- 110
 
4.7%
8 82
 
3.5%
3 78
 
3.4%
7 75
 
3.2%
6 75
 
3.2%
5 72
 
3.1%
Other values (2) 71
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2206
95.2%
Dash Punctuation 110
 
4.7%
Space Separator 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 700
31.7%
2 461
20.9%
1 453
20.5%
9 141
 
6.4%
8 82
 
3.7%
3 78
 
3.5%
7 75
 
3.4%
6 75
 
3.4%
5 72
 
3.3%
4 69
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 110
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2318
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 700
30.2%
2 461
19.9%
1 453
19.5%
9 141
 
6.1%
- 110
 
4.7%
8 82
 
3.5%
3 78
 
3.4%
7 75
 
3.2%
6 75
 
3.2%
5 72
 
3.1%
Other values (2) 71
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 700
30.2%
2 461
19.9%
1 453
19.5%
9 141
 
6.1%
- 110
 
4.7%
8 82
 
3.5%
3 78
 
3.4%
7 75
 
3.2%
6 75
 
3.2%
5 72
 
3.1%
Other values (2) 71
 
3.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing276
Missing (%)100.0%
Memory size2.6 KiB

영업상태코드
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
1
228 
3
29 
4
 
19

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 228
82.6%
3 29
 
10.5%
4 19
 
6.9%

Length

2024-05-11T00:20:16.027924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:16.340820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 228
82.6%
3 29
 
10.5%
4 19
 
6.9%

영업상태명
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
영업/정상
228 
폐업
29 
취소/말소/만료/정지/중지
 
19

Length

Max length14
Median length5
Mean length5.3043478
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 228
82.6%
폐업 29
 
10.5%
취소/말소/만료/정지/중지 19
 
6.9%

Length

2024-05-11T00:20:16.723078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:17.045269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 228
82.6%
폐업 29
 
10.5%
취소/말소/만료/정지/중지 19
 
6.9%

상세영업상태코드
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
11
228 
2
29 
4
 
19

Length

Max length2
Median length2
Mean length1.826087
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row11
3rd row11
4th row2
5th row11

Common Values

ValueCountFrequency (%)
11 228
82.6%
2 29
 
10.5%
4 19
 
6.9%

Length

2024-05-11T00:20:17.417614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:17.737625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 228
82.6%
2 29
 
10.5%
4 19
 
6.9%

상세영업상태명
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
영업
228 
폐업
29 
폐쇄
 
19

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 228
82.6%
폐업 29
 
10.5%
폐쇄 19
 
6.9%

Length

2024-05-11T00:20:18.080168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:18.375408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 228
82.6%
폐업 29
 
10.5%
폐쇄 19
 
6.9%

폐업일자
Date

MISSING 

Distinct21
Distinct (%)67.7%
Missing245
Missing (%)88.8%
Memory size2.3 KiB
Minimum2001-12-24 00:00:00
Maximum2024-04-26 00:00:00
2024-05-11T00:20:18.685351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:20:19.142657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing276
Missing (%)100.0%
Memory size2.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing276
Missing (%)100.0%
Memory size2.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing276
Missing (%)100.0%
Memory size2.6 KiB

전화번호
Text

MISSING 

Distinct163
Distinct (%)95.3%
Missing105
Missing (%)38.0%
Memory size2.3 KiB
2024-05-11T00:20:19.856800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.134503
Min length8

Characters and Unicode

Total characters1904
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

Unique155 ?
Unique (%)90.6%

Sample

1st row02-2623-9930
2nd row02-3661-3662
3rd row0226012121
4th row02-3663-8888
5th row0236622620
ValueCountFrequency (%)
02-3664-5090 2
 
1.2%
02-2669-3177 2
 
1.2%
0226798797 2
 
1.2%
02-3661-8902 2
 
1.2%
0236644680 2
 
1.2%
02-2659-0808 2
 
1.2%
02-2007-1272 2
 
1.2%
69244860 2
 
1.2%
02-2660-8000 1
 
0.6%
02-2101-1811 1
 
0.6%
Other values (154) 154
89.5%
2024-05-11T00:20:20.821099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 322
16.9%
2 318
16.7%
0 294
15.4%
- 237
12.4%
3 162
8.5%
1 151
7.9%
5 95
 
5.0%
8 89
 
4.7%
4 81
 
4.3%
9 80
 
4.2%
Other values (3) 75
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1664
87.4%
Dash Punctuation 237
 
12.4%
Space Separator 2
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 322
19.4%
2 318
19.1%
0 294
17.7%
3 162
9.7%
1 151
9.1%
5 95
 
5.7%
8 89
 
5.3%
4 81
 
4.9%
9 80
 
4.8%
7 72
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 237
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1904
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 322
16.9%
2 318
16.7%
0 294
15.4%
- 237
12.4%
3 162
8.5%
1 151
7.9%
5 95
 
5.0%
8 89
 
4.7%
4 81
 
4.3%
9 80
 
4.2%
Other values (3) 75
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1904
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 322
16.9%
2 318
16.7%
0 294
15.4%
- 237
12.4%
3 162
8.5%
1 151
7.9%
5 95
 
5.0%
8 89
 
4.7%
4 81
 
4.3%
9 80
 
4.2%
Other values (3) 75
 
3.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing276
Missing (%)100.0%
Memory size2.6 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)56.5%
Missing253
Missing (%)91.7%
Infinite0
Infinite (%)0.0%
Mean157135.7
Minimum157016
Maximum157290
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T00:20:21.193722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum157016
5-th percentile157030.1
Q1157040
median157200
Q3157211.5
95-th percentile157280
Maximum157290
Range274
Interquartile range (IQR)171.5

Descriptive statistics

Standard deviation101.51687
Coefficient of variation (CV)0.00064604592
Kurtosis-1.8298021
Mean157135.7
Median Absolute Deviation (MAD)90
Skewness0.10402256
Sum3614121
Variance10305.676
MonotonicityNot monotonic
2024-05-11T00:20:21.524022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
157040 7
 
2.5%
157031 2
 
0.7%
157203 2
 
0.7%
157201 2
 
0.7%
157280 2
 
0.7%
157200 1
 
0.4%
157230 1
 
0.4%
157202 1
 
0.4%
157290 1
 
0.4%
157016 1
 
0.4%
Other values (3) 3
 
1.1%
(Missing) 253
91.7%
ValueCountFrequency (%)
157016 1
 
0.4%
157030 1
 
0.4%
157031 2
 
0.7%
157040 7
2.5%
157200 1
 
0.4%
157201 2
 
0.7%
157202 1
 
0.4%
157203 2
 
0.7%
157220 1
 
0.4%
157223 1
 
0.4%
ValueCountFrequency (%)
157290 1
 
0.4%
157280 2
 
0.7%
157230 1
 
0.4%
157223 1
 
0.4%
157220 1
 
0.4%
157203 2
 
0.7%
157202 1
 
0.4%
157201 2
 
0.7%
157200 1
 
0.4%
157040 7
2.5%

지번주소
Text

Distinct238
Distinct (%)86.5%
Missing1
Missing (%)0.4%
Memory size2.3 KiB
2024-05-11T00:20:22.010923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length34
Mean length22.749091
Min length14

Characters and Unicode

Total characters6256
Distinct characters197
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

Unique214 ?
Unique (%)77.8%

Sample

1st row서울특별시 강서구 가양동 52-1
2nd row서울특별시 강서구 가양동 92번지
3rd row서울특별시 강서구 염창동 95-1번지
4th row서울특별시 강서구 가양동 110-2번지
5th row서울특별시 강서구 등촌동 64-4
ValueCountFrequency (%)
서울특별시 275
23.1%
강서구 275
23.1%
등촌동 71
 
6.0%
가양동 54
 
4.5%
염창동 36
 
3.0%
외발산동 35
 
2.9%
마곡동 33
 
2.8%
방화동 12
 
1.0%
공항동 10
 
0.8%
화곡동 9
 
0.8%
Other values (290) 381
32.0%
2024-05-11T00:20:23.065232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1112
17.8%
서 567
 
9.1%
강 285
 
4.6%
동 282
 
4.5%
시 281
 
4.5%
울 279
 
4.5%
구 278
 
4.4%
특 275
 
4.4%
별 275
 
4.4%
- 219
 
3.5%
Other values (187) 2403
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3767
60.2%
Decimal Number 1128
 
18.0%
Space Separator 1112
 
17.8%
Dash Punctuation 219
 
3.5%
Other Punctuation 10
 
0.2%
Uppercase Letter 8
 
0.1%
Lowercase Letter 7
 
0.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 567
15.1%
강 285
 
7.6%
동 282
 
7.5%
시 281
 
7.5%
울 279
 
7.4%
구 278
 
7.4%
특 275
 
7.3%
별 275
 
7.3%
지 106
 
2.8%
번 93
 
2.5%
Other values (161) 1046
27.8%
Decimal Number
ValueCountFrequency (%)
1 198
17.6%
2 176
15.6%
6 140
12.4%
3 117
10.4%
7 117
10.4%
4 93
8.2%
5 80
7.1%
0 75
 
6.6%
8 70
 
6.2%
9 62
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
o 2
28.6%
n 2
28.6%
e 1
14.3%
l 1
14.3%
y 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
D 2
25.0%
G 2
25.0%
L 2
25.0%
K 1
12.5%
A 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 9
90.0%
& 1
 
10.0%
Space Separator
ValueCountFrequency (%)
1112
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 219
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3767
60.2%
Common 2474
39.5%
Latin 15
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 567
15.1%
강 285
 
7.6%
동 282
 
7.5%
시 281
 
7.5%
울 279
 
7.4%
구 278
 
7.4%
특 275
 
7.3%
별 275
 
7.3%
지 106
 
2.8%
번 93
 
2.5%
Other values (161) 1046
27.8%
Common
ValueCountFrequency (%)
1112
44.9%
- 219
 
8.9%
1 198
 
8.0%
2 176
 
7.1%
6 140
 
5.7%
3 117
 
4.7%
7 117
 
4.7%
4 93
 
3.8%
5 80
 
3.2%
0 75
 
3.0%
Other values (6) 147
 
5.9%
Latin
ValueCountFrequency (%)
o 2
13.3%
n 2
13.3%
D 2
13.3%
G 2
13.3%
L 2
13.3%
K 1
6.7%
A 1
6.7%
e 1
6.7%
l 1
6.7%
y 1
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3767
60.2%
ASCII 2489
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1112
44.7%
- 219
 
8.8%
1 198
 
8.0%
2 176
 
7.1%
6 140
 
5.6%
3 117
 
4.7%
7 117
 
4.7%
4 93
 
3.7%
5 80
 
3.2%
0 75
 
3.0%
Other values (16) 162
 
6.5%
Hangul
ValueCountFrequency (%)
서 567
15.1%
강 285
 
7.6%
동 282
 
7.5%
시 281
 
7.5%
울 279
 
7.4%
구 278
 
7.4%
특 275
 
7.3%
별 275
 
7.3%
지 106
 
2.8%
번 93
 
2.5%
Other values (161) 1046
27.8%

도로명주소
Text

MISSING 

Distinct208
Distinct (%)88.1%
Missing40
Missing (%)14.5%
Memory size2.3 KiB
2024-05-11T00:20:23.619009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length40
Mean length28.800847
Min length21

Characters and Unicode

Total characters6797
Distinct characters221
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique184 ?
Unique (%)78.0%

Sample

1st row서울특별시 강서구 강서로74길 58 (가양동)
2nd row서울특별시 강서구 양천로 462 (등촌동)
3rd row서울특별시 강서구 공항대로59다길 227 (염창동)
4th row서울특별시 강서구 양천로60길 44 (등촌동)
5th row서울특별시 강서구 강서로74길 50 (가양동)
ValueCountFrequency (%)
서울특별시 236
18.5%
강서구 236
18.5%
등촌동 62
 
4.9%
양천로 39
 
3.1%
가양동 39
 
3.1%
외발산동 31
 
2.4%
염창동 30
 
2.4%
마곡동 29
 
2.3%
남부순환로 20
 
1.6%
방화동 12
 
0.9%
Other values (285) 540
42.4%
2024-05-11T00:20:24.718359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1067
 
15.7%
서 510
 
7.5%
강 266
 
3.9%
동 252
 
3.7%
시 245
 
3.6%
구 240
 
3.5%
울 240
 
3.5%
) 240
 
3.5%
( 239
 
3.5%
특 236
 
3.5%
Other values (211) 3262
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4117
60.6%
Space Separator 1067
 
15.7%
Decimal Number 965
 
14.2%
Close Punctuation 241
 
3.5%
Open Punctuation 240
 
3.5%
Other Punctuation 93
 
1.4%
Dash Punctuation 53
 
0.8%
Uppercase Letter 11
 
0.2%
Lowercase Letter 7
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 510
 
12.4%
강 266
 
6.5%
동 252
 
6.1%
시 245
 
6.0%
구 240
 
5.8%
울 240
 
5.8%
특 236
 
5.7%
별 236
 
5.7%
로 227
 
5.5%
양 127
 
3.1%
Other values (179) 1538
37.4%
Decimal Number
ValueCountFrequency (%)
1 143
14.8%
2 125
13.0%
6 119
12.3%
3 111
11.5%
5 103
10.7%
4 102
10.6%
7 77
8.0%
8 66
6.8%
0 65
6.7%
9 54
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
G 3
27.3%
L 2
18.2%
K 2
18.2%
S 1
 
9.1%
A 1
 
9.1%
B 1
 
9.1%
D 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
o 2
28.6%
n 2
28.6%
y 1
14.3%
e 1
14.3%
l 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 91
97.8%
& 1
 
1.1%
* 1
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 240
99.6%
] 1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 239
99.6%
[ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
1067
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4117
60.6%
Common 2662
39.2%
Latin 18
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 510
 
12.4%
강 266
 
6.5%
동 252
 
6.1%
시 245
 
6.0%
구 240
 
5.8%
울 240
 
5.8%
특 236
 
5.7%
별 236
 
5.7%
로 227
 
5.5%
양 127
 
3.1%
Other values (179) 1538
37.4%
Common
ValueCountFrequency (%)
1067
40.1%
) 240
 
9.0%
( 239
 
9.0%
1 143
 
5.4%
2 125
 
4.7%
6 119
 
4.5%
3 111
 
4.2%
5 103
 
3.9%
4 102
 
3.8%
, 91
 
3.4%
Other values (10) 322
 
12.1%
Latin
ValueCountFrequency (%)
G 3
16.7%
o 2
11.1%
n 2
11.1%
L 2
11.1%
K 2
11.1%
y 1
 
5.6%
e 1
 
5.6%
l 1
 
5.6%
S 1
 
5.6%
A 1
 
5.6%
Other values (2) 2
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4117
60.6%
ASCII 2680
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1067
39.8%
) 240
 
9.0%
( 239
 
8.9%
1 143
 
5.3%
2 125
 
4.7%
6 119
 
4.4%
3 111
 
4.1%
5 103
 
3.8%
4 102
 
3.8%
, 91
 
3.4%
Other values (22) 340
 
12.7%
Hangul
ValueCountFrequency (%)
서 510
 
12.4%
강 266
 
6.5%
동 252
 
6.1%
시 245
 
6.0%
구 240
 
5.8%
울 240
 
5.8%
특 236
 
5.7%
별 236
 
5.7%
로 227
 
5.5%
양 127
 
3.1%
Other values (179) 1538
37.4%

도로명우편번호
Text

MISSING 

Distinct62
Distinct (%)46.3%
Missing142
Missing (%)51.4%
Memory size2.3 KiB
2024-05-11T00:20:25.346866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2164179
Min length5

Characters and Unicode

Total characters699
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

Unique34 ?
Unique (%)25.4%

Sample

1st row07566
2nd row157030
3rd row157862
4th row157859
5th row07505
ValueCountFrequency (%)
07505 10
 
7.5%
07641 8
 
6.0%
07796 7
 
5.2%
07793 6
 
4.5%
07506 5
 
3.7%
157-290 4
 
3.0%
157290 4
 
3.0%
07801 4
 
3.0%
07573 4
 
3.0%
07553 4
 
3.0%
Other values (52) 78
58.2%
2024-05-11T00:20:26.644251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 172
24.6%
0 157
22.5%
5 122
17.5%
6 50
 
7.2%
1 50
 
7.2%
9 33
 
4.7%
4 29
 
4.1%
3 28
 
4.0%
2 27
 
3.9%
8 26
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 694
99.3%
Dash Punctuation 5
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 172
24.8%
0 157
22.6%
5 122
17.6%
6 50
 
7.2%
1 50
 
7.2%
9 33
 
4.8%
4 29
 
4.2%
3 28
 
4.0%
2 27
 
3.9%
8 26
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 699
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 172
24.6%
0 157
22.5%
5 122
17.5%
6 50
 
7.2%
1 50
 
7.2%
9 33
 
4.7%
4 29
 
4.1%
3 28
 
4.0%
2 27
 
3.9%
8 26
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 699
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 172
24.6%
0 157
22.5%
5 122
17.5%
6 50
 
7.2%
1 50
 
7.2%
9 33
 
4.7%
4 29
 
4.1%
3 28
 
4.0%
2 27
 
3.9%
8 26
 
3.7%

사업장명
Text

Distinct259
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-05-11T00:20:27.332416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length9.0942029
Min length2

Characters and Unicode

Total characters2510
Distinct characters303
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

Unique243 ?
Unique (%)88.0%

Sample

1st row대상(주)
2nd row씨제이제일제당(주)김포공장
3rd row서경산업
4th row대하자동차
5th row오신산업(주)
ValueCountFrequency (%)
주식회사 7
 
2.3%
영풍카독크 3
 
1.0%
현준산업 2
 
0.6%
홈플러스(주 2
 
0.6%
서울지역본부 2
 
0.6%
한국가스공사 2
 
0.6%
주)강서자동차정비사업소 2
 
0.6%
주)강서동산정비센터 2
 
0.6%
방화차량사업소 2
 
0.6%
주)대한항공 2
 
0.6%
Other values (270) 284
91.6%
2024-05-11T00:20:28.637065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 141
 
5.6%
) 136
 
5.4%
( 135
 
5.4%
동 92
 
3.7%
스 89
 
3.5%
서 84
 
3.3%
자 83
 
3.3%
공 79
 
3.1%
차 79
 
3.1%
업 69
 
2.7%
Other values (293) 1523
60.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2158
86.0%
Close Punctuation 137
 
5.5%
Open Punctuation 136
 
5.4%
Space Separator 34
 
1.4%
Uppercase Letter 24
 
1.0%
Other Punctuation 9
 
0.4%
Lowercase Letter 9
 
0.4%
Dash Punctuation 2
 
0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 141
 
6.5%
동 92
 
4.3%
스 89
 
4.1%
서 84
 
3.9%
자 83
 
3.8%
공 79
 
3.7%
차 79
 
3.7%
업 69
 
3.2%
사 67
 
3.1%
비 58
 
2.7%
Other values (266) 1317
61.0%
Uppercase Letter
ValueCountFrequency (%)
N 4
16.7%
T 4
16.7%
C 3
12.5%
E 3
12.5%
R 2
8.3%
A 2
8.3%
G 2
8.3%
K 2
8.3%
D 1
 
4.2%
J 1
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
k 2
22.2%
c 1
11.1%
e 1
11.1%
s 1
11.1%
b 1
11.1%
r 1
11.1%
a 1
11.1%
l 1
11.1%
Close Punctuation
ValueCountFrequency (%)
) 136
99.3%
] 1
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 135
99.3%
[ 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 8
88.9%
& 1
 
11.1%
Space Separator
ValueCountFrequency (%)
34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2158
86.0%
Common 319
 
12.7%
Latin 33
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 141
 
6.5%
동 92
 
4.3%
스 89
 
4.1%
서 84
 
3.9%
자 83
 
3.8%
공 79
 
3.7%
차 79
 
3.7%
업 69
 
3.2%
사 67
 
3.1%
비 58
 
2.7%
Other values (266) 1317
61.0%
Latin
ValueCountFrequency (%)
N 4
12.1%
T 4
12.1%
C 3
 
9.1%
E 3
 
9.1%
k 2
 
6.1%
R 2
 
6.1%
A 2
 
6.1%
G 2
 
6.1%
K 2
 
6.1%
D 1
 
3.0%
Other values (8) 8
24.2%
Common
ValueCountFrequency (%)
) 136
42.6%
( 135
42.3%
34
 
10.7%
. 8
 
2.5%
- 2
 
0.6%
[ 1
 
0.3%
& 1
 
0.3%
1 1
 
0.3%
] 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2158
86.0%
ASCII 352
 
14.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 141
 
6.5%
동 92
 
4.3%
스 89
 
4.1%
서 84
 
3.9%
자 83
 
3.8%
공 79
 
3.7%
차 79
 
3.7%
업 69
 
3.2%
사 67
 
3.1%
비 58
 
2.7%
Other values (266) 1317
61.0%
ASCII
ValueCountFrequency (%)
) 136
38.6%
( 135
38.4%
34
 
9.7%
. 8
 
2.3%
N 4
 
1.1%
T 4
 
1.1%
C 3
 
0.9%
E 3
 
0.9%
k 2
 
0.6%
- 2
 
0.6%
Other values (17) 21
 
6.0%

최종수정일자
Date

UNIQUE 

Distinct276
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum2000-09-22 21:05:12
Maximum2024-05-07 16:33:00
2024-05-11T00:20:29.329664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:20:30.026701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
U
187 
I
89 

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 (%)
U 187
67.8%
I 89
32.2%

Length

2024-05-11T00:20:30.577554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:30.979459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 187
67.8%
i 89
32.2%

데이터갱신일자
Date

Distinct128
Distinct (%)46.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum2018-10-04 11:12:49
Maximum2023-12-05 00:09:00
2024-05-11T00:20:31.397804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:20:31.834412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Text

MISSING 

Distinct63
Distinct (%)32.6%
Missing83
Missing (%)30.1%
Memory size2.3 KiB
2024-05-11T00:20:32.601244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length9.6735751
Min length2

Characters and Unicode

Total characters1867
Distinct characters135
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)23.3%

Sample

1st row기타 섬유제품 제조업
2nd row자동차 및 모터사이클 수리업
3rd row자동차 종합 수리업
4th row자동차 종합 수리업
5th row자동차 종합 수리업
ValueCountFrequency (%)
자동차 108
20.1%
수리업 107
20.0%
종합 79
14.7%
및 29
 
5.4%
운송업 17
 
3.2%
모터사이클 16
 
3.0%
기타 15
 
2.8%
제조업 13
 
2.4%
운영업 7
 
1.3%
임대업 6
 
1.1%
Other values (89) 139
25.9%
2024-05-11T00:20:33.666949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
343
18.4%
업 184
 
9.9%
동 116
 
6.2%
리 114
 
6.1%
자 112
 
6.0%
차 110
 
5.9%
수 110
 
5.9%
종 81
 
4.3%
합 80
 
4.3%
및 32
 
1.7%
Other values (125) 585
31.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1515
81.1%
Space Separator 343
 
18.4%
Other Punctuation 8
 
0.4%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 184
 
12.1%
동 116
 
7.7%
리 114
 
7.5%
자 112
 
7.4%
차 110
 
7.3%
수 110
 
7.3%
종 81
 
5.3%
합 80
 
5.3%
및 32
 
2.1%
기 31
 
2.0%
Other values (120) 545
36.0%
Other Punctuation
ValueCountFrequency (%)
, 6
75.0%
; 1
 
12.5%
? 1
 
12.5%
Space Separator
ValueCountFrequency (%)
343
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1515
81.1%
Common 352
 
18.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 184
 
12.1%
동 116
 
7.7%
리 114
 
7.5%
자 112
 
7.4%
차 110
 
7.3%
수 110
 
7.3%
종 81
 
5.3%
합 80
 
5.3%
및 32
 
2.1%
기 31
 
2.0%
Other values (120) 545
36.0%
Common
ValueCountFrequency (%)
343
97.4%
, 6
 
1.7%
; 1
 
0.3%
1 1
 
0.3%
? 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1515
81.1%
ASCII 352
 
18.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
343
97.4%
, 6
 
1.7%
; 1
 
0.3%
1 1
 
0.3%
? 1
 
0.3%
Hangul
ValueCountFrequency (%)
업 184
 
12.1%
동 116
 
7.7%
리 114
 
7.5%
자 112
 
7.4%
차 110
 
7.3%
수 110
 
7.3%
종 81
 
5.3%
합 80
 
5.3%
및 32
 
2.1%
기 31
 
2.0%
Other values (120) 545
36.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct168
Distinct (%)70.0%
Missing36
Missing (%)13.0%
Infinite0
Infinite (%)0.0%
Mean186116.68
Minimum181881.23
Maximum189115.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T00:20:34.244927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum181881.23
5-th percentile183005.6
Q1184475.17
median186109.75
Q3187688.3
95-th percentile188866.35
Maximum189115.55
Range7234.3177
Interquartile range (IQR)3213.1305

Descriptive statistics

Standard deviation1832.246
Coefficient of variation (CV)0.0098446093
Kurtosis-0.90406309
Mean186116.68
Median Absolute Deviation (MAD)1578.5466
Skewness-0.30484338
Sum44668002
Variance3357125.3
MonotonicityNot monotonic
2024-05-11T00:20:34.716298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186095.118991699 6
 
2.2%
187688.30112077 6
 
2.2%
188065.143577087 5
 
1.8%
185102.925888382 5
 
1.8%
184277.922297998 4
 
1.4%
187837.555280582 4
 
1.4%
184882.657508049 3
 
1.1%
188003.276907006 3
 
1.1%
183947.397707356 3
 
1.1%
184488.133116823 3
 
1.1%
Other values (158) 198
71.7%
(Missing) 36
 
13.0%
ValueCountFrequency (%)
181881.234660314 1
0.4%
182086.388313239 1
0.4%
182094.635692564 1
0.4%
182141.205465089 2
0.7%
182524.823835629 2
0.7%
182749.273937321 1
0.4%
182771.965027782 2
0.7%
182974.850127567 2
0.7%
183007.220061564 2
0.7%
183062.31202147 1
0.4%
ValueCountFrequency (%)
189115.552310532 1
 
0.4%
189111.978786699 2
0.7%
189081.889118134 1
 
0.4%
189064.211998511 3
1.1%
189037.964421932 1
 
0.4%
189017.223570684 1
 
0.4%
188998.678607376 1
 
0.4%
188936.952634303 1
 
0.4%
188908.445908283 1
 
0.4%
188864.136677009 1
 
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct168
Distinct (%)70.0%
Missing36
Missing (%)13.0%
Infinite0
Infinite (%)0.0%
Mean450688.98
Minimum447497.71
Maximum453913.48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T00:20:35.303710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447497.71
5-th percentile449281.42
Q1449826.67
median450516.89
Q3451519.71
95-th percentile452428.65
Maximum453913.48
Range6415.7706
Interquartile range (IQR)1693.0437

Descriptive statistics

Standard deviation1118.9161
Coefficient of variation (CV)0.0024826792
Kurtosis0.29335393
Mean450688.98
Median Absolute Deviation (MAD)795.80865
Skewness0.40327863
Sum1.0816535 × 108
Variance1251973.3
MonotonicityNot monotonic
2024-05-11T00:20:35.792681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451646.803088209 6
 
2.2%
450305.395642568 6
 
2.2%
450268.978044735 5
 
1.8%
451165.579794021 5
 
1.8%
449334.46078741 4
 
1.4%
450216.937532533 4
 
1.4%
451017.300748614 3
 
1.1%
450156.394650622 3
 
1.1%
449281.423645259 3
 
1.1%
449384.239839898 3
 
1.1%
Other values (158) 198
71.7%
(Missing) 36
 
13.0%
ValueCountFrequency (%)
447497.707318051 2
0.7%
448443.351824015 1
 
0.4%
448885.127575942 2
0.7%
448899.500159804 1
 
0.4%
448956.995895795 1
 
0.4%
449251.768967194 1
 
0.4%
449255.516548861 2
0.7%
449280.015511343 1
 
0.4%
449281.423645259 3
1.1%
449281.883608257 1
 
0.4%
ValueCountFrequency (%)
453913.477874055 1
0.4%
453746.128937024 1
0.4%
453742.437420801 1
0.4%
453649.980004095 2
0.7%
453328.069853808 1
0.4%
453199.505906493 1
0.4%
453174.899157458 1
0.4%
453136.448166169 1
0.4%
453130.815651695 1
0.4%
452436.506555308 2
0.7%

환경업무구분명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
대기배출업소관리
191 
<NA>
85 

Length

Max length8
Median length8
Mean length6.7681159
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대기배출업소관리 191
69.2%
<NA> 85
30.8%

Length

2024-05-11T00:20:36.601866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:36.978556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기배출업소관리 191
69.2%
na 85
30.8%

업종구분명
Categorical

Distinct47
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
151 
자동차 종합 수리업
47 
자동차 및 모터사이클 수리업
 
11
자동차 수리업
 
11
기타 스포츠시설 운영업
 
4
Other values (42)
52 

Length

Max length21
Median length4
Mean length6.4818841
Min length2

Unique

Unique36 ?
Unique (%)13.0%

Sample

1st row<NA>
2nd row<NA>
3rd row기타 섬유제품 제조업
4th row<NA>
5th row자동차 및 모터사이클 수리업

Common Values

ValueCountFrequency (%)
<NA> 151
54.7%
자동차 종합 수리업 47
 
17.0%
자동차 및 모터사이클 수리업 11
 
4.0%
자동차 수리업 11
 
4.0%
기타 스포츠시설 운영업 4
 
1.4%
택시 운송업 4
 
1.4%
도장및기타피막처리업 3
 
1.1%
부동산 임대업 3
 
1.1%
종합 병원 2
 
0.7%
육상 여객 운송업 2
 
0.7%
Other values (37) 38
 
13.8%

Length

2024-05-11T00:20:37.456111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 151
30.9%
수리업 70
14.3%
자동차 70
14.3%
종합 50
 
10.2%
및 18
 
3.7%
운송업 12
 
2.5%
모터사이클 11
 
2.3%
제조업 8
 
1.6%
기타 6
 
1.2%
운영업 5
 
1.0%
Other values (59) 87
17.8%

종별명
Categorical

Distinct6
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
5종
156 
<NA>
86 
4종
31 
1종
 
1
2종
 
1

Length

Max length4
Median length2
Mean length2.6231884
Min length2

Unique

Unique3 ?
Unique (%)1.1%

Sample

1st row<NA>
2nd row4종
3rd row5종
4th row5종
5th row5종

Common Values

ValueCountFrequency (%)
5종 156
56.5%
<NA> 86
31.2%
4종 31
 
11.2%
1종 1
 
0.4%
2종 1
 
0.4%
3종 1
 
0.4%

Length

2024-05-11T00:20:37.917845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:38.364741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5종 156
56.5%
na 86
31.2%
4종 31
 
11.2%
1종 1
 
0.4%
2종 1
 
0.4%
3종 1
 
0.4%

주생산품명
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing273
Missing (%)98.9%
Memory size2.3 KiB
2024-05-11T00:20:38.749807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.3333333
Min length2

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row메탄
2nd row전력
3rd row보일러
ValueCountFrequency (%)
메탄 1
33.3%
전력 1
33.3%
보일러 1
33.3%
2024-05-11T00:20:40.087610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
메 1
14.3%
탄 1
14.3%
전 1
14.3%
력 1
14.3%
보 1
14.3%
일 1
14.3%
러 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
메 1
14.3%
탄 1
14.3%
전 1
14.3%
력 1
14.3%
보 1
14.3%
일 1
14.3%
러 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
메 1
14.3%
탄 1
14.3%
전 1
14.3%
력 1
14.3%
보 1
14.3%
일 1
14.3%
러 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
메 1
14.3%
탄 1
14.3%
전 1
14.3%
력 1
14.3%
보 1
14.3%
일 1
14.3%
러 1
14.3%

배출시설조업시간
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
198 
8
40 
0
34 
24
 
2
5
 
1

Length

Max length4
Median length4
Mean length3.1630435
Min length1

Unique

Unique2 ?
Unique (%)0.7%

Sample

1st row<NA>
2nd row24
3rd row0
4th row8
5th row8

Common Values

ValueCountFrequency (%)
<NA> 198
71.7%
8 40
 
14.5%
0 34
 
12.3%
24 2
 
0.7%
5 1
 
0.4%
10 1
 
0.4%

Length

2024-05-11T00:20:40.663403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:41.068178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 198
71.7%
8 40
 
14.5%
0 34
 
12.3%
24 2
 
0.7%
5 1
 
0.4%
10 1
 
0.4%

배출시설연간가동일수
Categorical

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
161 
0
73 
300
41 
350
 
1

Length

Max length4
Median length4
Mean length3.0543478
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row<NA>
2nd row350
3rd row0
4th row300
5th row300

Common Values

ValueCountFrequency (%)
<NA> 161
58.3%
0 73
26.4%
300 41
 
14.9%
350 1
 
0.4%

Length

2024-05-11T00:20:41.447825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:41.962668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 161
58.3%
0 73
26.4%
300 41
 
14.9%
350 1
 
0.4%

방지시설조업시간
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
201 
8
36 
0
35 
24
 
2
5
 
1

Length

Max length4
Median length4
Mean length3.192029
Min length1

Unique

Unique2 ?
Unique (%)0.7%

Sample

1st row<NA>
2nd row24
3rd row0
4th row8
5th row8

Common Values

ValueCountFrequency (%)
<NA> 201
72.8%
8 36
 
13.0%
0 35
 
12.7%
24 2
 
0.7%
5 1
 
0.4%
3 1
 
0.4%

Length

2024-05-11T00:20:42.571180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:43.252349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 201
72.8%
8 36
 
13.0%
0 35
 
12.7%
24 2
 
0.7%
5 1
 
0.4%
3 1
 
0.4%

방지시설연간가동일수
Categorical

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
156 
0
70 
300
48 
350
 
1
9
 
1

Length

Max length4
Median length4
Mean length3.0507246
Min length1

Unique

Unique2 ?
Unique (%)0.7%

Sample

1st row<NA>
2nd row350
3rd row0
4th row300
5th row300

Common Values

ValueCountFrequency (%)
<NA> 156
56.5%
0 70
25.4%
300 48
 
17.4%
350 1
 
0.4%
9 1
 
0.4%

Length

2024-05-11T00:20:43.771194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:44.224986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 156
56.5%
0 70
25.4%
300 48
 
17.4%
350 1
 
0.4%
9 1
 
0.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
0315000031500002119750001620020121<NA>1영업/정상11영업<NA><NA><NA><NA>02-2623-9930<NA><NA>서울특별시 강서구 가양동 52-1<NA><NA>대상(주)2022-11-14 19:40:23U2021-10-31 23:06:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1315000031500002119750003419750116<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 가양동 92번지<NA><NA>씨제이제일제당(주)김포공장2015-12-22 16:48:19I2018-10-04 11:12:49.0<NA><NA><NA>대기배출업소관리<NA>4종<NA>2435024350
2315000031500002119880000919881101<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>157040서울특별시 강서구 염창동 95-1번지<NA><NA>서경산업2000-11-22 16:55:57I2018-10-04 11:12:49.0기타 섬유제품 제조업<NA><NA>대기배출업소관리기타 섬유제품 제조업5종<NA>0000
3315000031500002119880004720010810<NA>3폐업2폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 가양동 110-2번지서울특별시 강서구 강서로74길 58 (가양동)<NA>대하자동차2008-10-07 16:43:11I2018-10-04 11:12:49.0<NA>186164.97503451539.175318대기배출업소관리<NA>5종<NA>83008300
4315000031500002119910005019910611<NA>1영업/정상11영업<NA><NA><NA><NA>02-3661-3662<NA><NA>서울특별시 강서구 등촌동 64-4서울특별시 강서구 양천로 462 (등촌동)<NA>오신산업(주)2022-01-14 10:14:39U2022-01-16 02:40:00.0자동차 및 모터사이클 수리업186846.838493451117.714955대기배출업소관리자동차 및 모터사이클 수리업5종<NA>83008300
5315000031500002119920000819920402<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 염창동 263-13번지서울특별시 강서구 공항대로59다길 227 (염창동)<NA>신성카독크2009-03-27 14:48:58I2018-10-04 11:12:49.0<NA>188864.136677449587.813043대기배출업소관리<NA>5종<NA>0000
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7315000031500002119920002720141209<NA>1영업/정상11영업<NA><NA><NA><NA>02-3663-8888<NA><NA>서울특별시 강서구 등촌동 638-11서울특별시 강서구 양천로60길 44 (등촌동)07566경성모터스2022-01-14 10:17:09U2022-01-16 02:40:00.0자동차 종합 수리업187386.206337450535.532471대기배출업소관리자동차 종합 수리업5종<NA>0000
8315000031500002119920002920020529<NA>3폐업2폐업<NA><NA><NA><NA>0236622620<NA><NA>서울특별시 강서구 가양동 115-6번지서울특별시 강서구 강서로74길 50 (가양동)<NA>신원카독크2019-03-18 09:10:11U2019-03-20 02:40:00.0<NA>186124.389979451594.170002대기배출업소관리<NA>5종<NA>83008300
9315000031500002119920004319920616<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>157031서울특별시 강서구 등촌동 629-6번지서울특별시 강서구 양천로 530 (등촌동)157030남영자동차공업(주)2011-10-30 15:16:14I2018-10-04 11:12:49.0<NA>187416.57314450738.07756대기배출업소관리<NA>5종<NA>83008300
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
266315000031500002120210001420211203<NA>1영업/정상11영업<NA><NA><NA><NA>02)6987-7906<NA><NA>서울특별시 강서구 마곡동 770-1 LG사이언스파크서울특별시 강서구 마곡중앙10로 30, LG사이언스파크 (마곡동)07796(주)엘지에너지솔루션2021-12-07 15:56:51U2021-12-09 02:40:00.0물리, 화학 및 생물학 연구개발업<NA><NA>대기배출업소관리물리, 화학 및 생물학 연구개발업5종<NA><NA>0<NA>0
26731500003150000212022000012022-06-10<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 781-8서울특별시 강서구 마곡중앙8로3길 63 (마곡동)07793(주)제놀루션2023-05-23 16:27:29U2022-12-04 22:05:00.0의학 및 약학 연구 개발업185596.136722451617.359623<NA><NA><NA><NA><NA><NA><NA><NA>
268315000031500002120220000220221115<NA>1영업/정상11영업<NA><NA><NA><NA>02-6147-1563<NA><NA>서울특별시 강서구 화곡동 1135-12 새마을금고아이티센터서울특별시 강서구 공항대로 390, 새마을금고아이티센터 (화곡동)07648새마을금고중앙회2022-11-17 17:25:44U2021-10-31 23:09:00.0금융업186804.069137450738.570601<NA><NA><NA><NA><NA><NA><NA><NA>
26931500003150000212022000032022-11-23<NA>1영업/정상11영업<NA><NA><NA><NA>02-3664-7185<NA><NA>서울특별시 강서구 마곡동 771-2 희성엘티빌딩서울특별시 강서구 마곡중앙8로 20, 희성엘티빌딩 (마곡동)07801엘티소재(주)2023-12-11 15:54:59U2022-11-01 23:03:00.0전기?전자공학 연구개발업184882.657508451017.300749<NA><NA><NA><NA><NA><NA><NA><NA>
270315000031500002120220000420221221<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 등촌동 653-25 등촌동KAL빌딩서울특별시 강서구 공항대로 453, 등촌동KAL빌딩 (등촌동)07570(주)대한항공(등촌동 인력개발원)2022-12-08 18:02:14I2021-11-01 23:00:00.0항공 운송업187352.843019450261.240349<NA><NA><NA><NA><NA><NA><NA><NA>
271315000031500002120220000520221213<NA>1영업/정상11영업<NA><NA><NA><NA>02-2669-9022<NA><NA>서울특별시 강서구 외발산동 424 수협공판장서울특별시 강서구 발산로 24, 수협공판장 (외발산동)07644수협강서공판장2022-12-14 07:57:52I2021-11-01 23:06:00.0<NA>183914.93831450085.014573<NA><NA><NA><NA><NA><NA><NA><NA>
272315000031500002120220000620221226<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 등촌동 639-11 홈플러스강서점앤본사사옥서울특별시 강서구 화곡로 398, 홈플러스강서점앤본사사옥 (등촌동)07567홈플러스(주) 본사사옥2022-12-27 15:42:49I2021-11-01 22:09:00.0기타 산업 회사본부187119.948166450691.593174<NA><NA><NA><NA><NA><NA><NA><NA>
273315000031500002120230000120230119<NA>1영업/정상11영업<NA><NA><NA><NA>080-617-1399<NA><NA>서울특별시 강서구 등촌동 633서울특별시 강서구 양천로66길 5, 3층 (등촌동)07553테슬라코리아 유한회사 서울강서점2023-01-19 16:16:12I2022-11-30 22:02:00.0자동차 종합 수리업188065.143577450268.978045<NA><NA><NA><NA><NA><NA><NA><NA>
27431500003150000212023000022023-06-09<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 781-5서울특별시 강서구 마곡동로8길 28 (마곡동)07793한국카본2023-06-09 17:52:49I2022-12-05 23:01:00.0<NA>185506.975214451515.898009<NA><NA><NA><NA><NA><NA><NA><NA>
27531500003150000212023000032023-09-06<NA>1영업/정상11영업<NA><NA><NA><NA>02-1800-8991<NA><NA>서울특별시 강서구 마곡동 780-2서울특별시 강서구 마곡동로 124 (마곡동)[*미고시]07793(주)이랜드건설[이랜드글로벌 R&D센터]2023-09-22 16:09:24U2022-12-08 22:04:00.0기타 산업 회사본부185393.024174451531.147412<NA><NA><NA><NA><NA><NA><NA><NA>