Overview

Dataset statistics

Number of variables33
Number of observations481
Missing cells5140
Missing cells (%)32.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory131.7 KiB
Average record size in memory280.3 B

Variable types

Categorical9
Numeric8
DateTime4
Unsupported5
Text7

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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-19370/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업종구분명 has a high cardinality: 51 distinct valuesHigh cardinality
업종구분명 is highly imbalanced (60.4%)Imbalance
인허가취소일자 has 481 (100.0%) missing valuesMissing
폐업일자 has 207 (43.0%) missing valuesMissing
휴업시작일자 has 481 (100.0%) missing valuesMissing
휴업종료일자 has 481 (100.0%) missing valuesMissing
재개업일자 has 481 (100.0%) missing valuesMissing
전화번호 has 169 (35.1%) missing valuesMissing
소재지면적 has 481 (100.0%) missing valuesMissing
소재지우편번호 has 375 (78.0%) missing valuesMissing
지번주소 has 18 (3.7%) missing valuesMissing
도로명주소 has 49 (10.2%) missing valuesMissing
도로명우편번호 has 316 (65.7%) missing valuesMissing
업태구분명 has 261 (54.3%) missing valuesMissing
좌표정보(X) has 43 (8.9%) missing valuesMissing
좌표정보(Y) has 43 (8.9%) missing valuesMissing
주생산품명 has 470 (97.7%) missing valuesMissing
배출시설조업시간 has 187 (38.9%) missing valuesMissing
배출시설연간가동일수 has 186 (38.7%) missing valuesMissing
방지시설조업시간 has 211 (43.9%) missing valuesMissing
방지시설연간가동일수 has 200 (41.6%) 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
배출시설조업시간 has 162 (33.7%) zerosZeros
배출시설연간가동일수 has 168 (34.9%) zerosZeros
방지시설조업시간 has 179 (37.2%) zerosZeros
방지시설연간가동일수 has 185 (38.5%) zerosZeros

Reproduction

Analysis started2024-05-11 05:54:10.067887
Analysis finished2024-05-11 05:54:11.353584
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
3180000
481 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 481
100.0%

Length

2024-05-11T14:54:11.479702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:11.636091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 481
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct481
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1800002 × 1017
Minimum3.1800002 × 1017
Maximum3.1800002 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-05-11T14:54:11.822838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1800002 × 1017
5-th percentile3.1800002 × 1017
Q13.1800002 × 1017
median3.1800002 × 1017
Q33.1800002 × 1017
95-th percentile3.1800002 × 1017
Maximum3.1800002 × 1017
Range2400000
Interquartile range (IQR)1489984

Descriptive statistics

Standard deviation792422.28
Coefficient of variation (CV)2.4918938 × 10-12
Kurtosis-1.2624153
Mean3.1800002 × 1017
Median Absolute Deviation (MAD)399936
Skewness0.55151479
Sum5.3840576 × 1018
Variance6.2793306 × 1011
MonotonicityStrictly increasing
2024-05-11T14:54:12.095917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
318000021200000001 1
 
0.2%
318000021201500040 1
 
0.2%
318000021201500008 1
 
0.2%
318000021201500007 1
 
0.2%
318000021201500006 1
 
0.2%
318000021201500005 1
 
0.2%
318000021201500004 1
 
0.2%
318000021201500003 1
 
0.2%
318000021201500002 1
 
0.2%
318000021201500001 1
 
0.2%
Other values (471) 471
97.9%
ValueCountFrequency (%)
318000021200000001 1
0.2%
318000021200000002 1
0.2%
318000021200000003 1
0.2%
318000021200000004 1
0.2%
318000021200000005 1
0.2%
318000021200000007 1
0.2%
318000021200000008 1
0.2%
318000021200000009 1
0.2%
318000021200000010 1
0.2%
318000021200000011 1
0.2%
ValueCountFrequency (%)
318000021202400001 1
0.2%
318000021202300003 1
0.2%
318000021202300002 1
0.2%
318000021202300001 1
0.2%
318000021202200016 1
0.2%
318000021202200015 1
0.2%
318000021202200014 1
0.2%
318000021202200013 1
0.2%
318000021202200012 1
0.2%
318000021202200011 1
0.2%

인허가일자
Date

Distinct374
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum1971-01-15 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T14:54:12.327044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:12.558533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing481
Missing (%)100.0%
Memory size4.4 KiB

영업상태코드
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
1
201 
3
198 
4
82 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 201
41.8%
3 198
41.2%
4 82
17.0%

Length

2024-05-11T14:54:12.803691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:12.987132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 201
41.8%
3 198
41.2%
4 82
17.0%

영업상태명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
영업/정상
201 
폐업
198 
취소/말소/만료/정지/중지
82 

Length

Max length14
Median length5
Mean length5.2993763
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 201
41.8%
폐업 198
41.2%
취소/말소/만료/정지/중지 82
17.0%

Length

2024-05-11T14:54:13.208732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:13.399225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 201
41.8%
폐업 198
41.2%
취소/말소/만료/정지/중지 82
17.0%

상세영업상태코드
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
11
201 
2
198 
4
82 

Length

Max length2
Median length1
Mean length1.4178794
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row11
4th row2
5th row4

Common Values

ValueCountFrequency (%)
11 201
41.8%
2 198
41.2%
4 82
17.0%

Length

2024-05-11T14:54:13.695542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:13.862460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 201
41.8%
2 198
41.2%
4 82
17.0%

상세영업상태명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
영업
201 
폐업
198 
폐쇄
82 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 201
41.8%
폐업 198
41.2%
폐쇄 82
17.0%

Length

2024-05-11T14:54:14.044336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:14.204492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 201
41.8%
폐업 198
41.2%
폐쇄 82
17.0%

폐업일자
Date

MISSING 

Distinct184
Distinct (%)67.2%
Missing207
Missing (%)43.0%
Memory size3.9 KiB
Minimum2000-01-08 00:00:00
Maximum2024-04-02 00:00:00
2024-05-11T14:54:14.388307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:14.635760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing481
Missing (%)100.0%
Memory size4.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing481
Missing (%)100.0%
Memory size4.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing481
Missing (%)100.0%
Memory size4.4 KiB

전화번호
Text

MISSING 

Distinct294
Distinct (%)94.2%
Missing169
Missing (%)35.1%
Memory size3.9 KiB
2024-05-11T14:54:15.128509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.6698718
Min length4

Characters and Unicode

Total characters3017
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

Unique276 ?
Unique (%)88.5%

Sample

1st row6788559
2nd row02-2633-1932
3rd row2678-0931
4th row0226794997
5th row0226341317
ValueCountFrequency (%)
679 4
 
1.2%
677 4
 
1.2%
631 3
 
0.9%
02 3
 
0.9%
0226753155 2
 
0.6%
0226339639 2
 
0.6%
633 2
 
0.6%
02-2632-0713 2
 
0.6%
676 2
 
0.6%
0226728560 2
 
0.6%
Other values (295) 311
92.3%
2024-05-11T14:54:15.788051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 496
16.4%
0 391
13.0%
6 383
12.7%
7 315
10.4%
3 291
9.6%
- 258
8.6%
1 230
7.6%
8 179
 
5.9%
9 158
 
5.2%
5 155
 
5.1%
Other values (2) 161
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2734
90.6%
Dash Punctuation 258
 
8.6%
Space Separator 25
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 496
18.1%
0 391
14.3%
6 383
14.0%
7 315
11.5%
3 291
10.6%
1 230
8.4%
8 179
 
6.5%
9 158
 
5.8%
5 155
 
5.7%
4 136
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 258
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3017
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 496
16.4%
0 391
13.0%
6 383
12.7%
7 315
10.4%
3 291
9.6%
- 258
8.6%
1 230
7.6%
8 179
 
5.9%
9 158
 
5.2%
5 155
 
5.1%
Other values (2) 161
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3017
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 496
16.4%
0 391
13.0%
6 383
12.7%
7 315
10.4%
3 291
9.6%
- 258
8.6%
1 230
7.6%
8 179
 
5.9%
9 158
 
5.2%
5 155
 
5.1%
Other values (2) 161
 
5.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing481
Missing (%)100.0%
Memory size4.4 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)18.9%
Missing375
Missing (%)78.0%
Infinite0
Infinite (%)0.0%
Mean150091.37
Minimum150034
Maximum150106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-05-11T14:54:15.985420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150034
5-th percentile150039.25
Q1150093
median150093
Q3150102.75
95-th percentile150104.75
Maximum150106
Range72
Interquartile range (IQR)9.75

Descriptive statistics

Standard deviation17.684713
Coefficient of variation (CV)0.00011782631
Kurtosis4.4277709
Mean150091.37
Median Absolute Deviation (MAD)3
Skewness-2.3214395
Sum15909685
Variance312.74906
MonotonicityNot monotonic
2024-05-11T14:54:16.151649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
150093 34
 
7.1%
150103 17
 
3.5%
150102 9
 
1.9%
150091 7
 
1.5%
150096 6
 
1.2%
150038 5
 
1.0%
150104 4
 
0.8%
150106 3
 
0.6%
150094 3
 
0.6%
150044 3
 
0.6%
Other values (10) 15
 
3.1%
(Missing) 375
78.0%
ValueCountFrequency (%)
150034 1
 
0.2%
150038 5
1.0%
150043 1
 
0.2%
150044 3
0.6%
150073 1
 
0.2%
150081 1
 
0.2%
150082 1
 
0.2%
150090 1
 
0.2%
150091 7
1.5%
150092 1
 
0.2%
ValueCountFrequency (%)
150106 3
 
0.6%
150105 3
 
0.6%
150104 4
 
0.8%
150103 17
3.5%
150102 9
 
1.9%
150101 3
 
0.6%
150096 6
 
1.2%
150095 2
 
0.4%
150094 3
 
0.6%
150093 34
7.1%

지번주소
Text

MISSING 

Distinct375
Distinct (%)81.0%
Missing18
Missing (%)3.7%
Memory size3.9 KiB
2024-05-11T14:54:16.405514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length23.401728
Min length17

Characters and Unicode

Total characters10835
Distinct characters184
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique319 ?
Unique (%)68.9%

Sample

1st row서울특별시 영등포구 영등포동8가 73번지
2nd row서울특별시 영등포구 영등포동8가 73번지
3rd row서울특별시 영등포구 영등포동8가 73
4th row서울특별시 영등포구 영등포동8가 73-0번지
5th row서울특별시 영등포구 영등포동8가 73-0번지
ValueCountFrequency (%)
서울특별시 463
23.6%
영등포구 463
23.6%
여의도동 78
 
4.0%
양평동3가 57
 
2.9%
문래동3가 54
 
2.7%
문래동1가 42
 
2.1%
양평동6가 26
 
1.3%
양평동5가 23
 
1.2%
문래동2가 21
 
1.1%
69 19
 
1.0%
Other values (439) 720
36.6%
2024-05-11T14:54:16.848944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1809
 
16.7%
영 513
 
4.7%
포 511
 
4.7%
등 510
 
4.7%
동 471
 
4.3%
서 470
 
4.3%
울 467
 
4.3%
시 465
 
4.3%
특 463
 
4.3%
별 463
 
4.3%
Other values (174) 4693
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6941
64.1%
Space Separator 1809
 
16.7%
Decimal Number 1746
 
16.1%
Dash Punctuation 295
 
2.7%
Uppercase Letter 37
 
0.3%
Other Punctuation 5
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 513
 
7.4%
포 511
 
7.4%
등 510
 
7.3%
동 471
 
6.8%
서 470
 
6.8%
울 467
 
6.7%
시 465
 
6.7%
특 463
 
6.7%
별 463
 
6.7%
구 463
 
6.7%
Other values (144) 2145
30.9%
Uppercase Letter
ValueCountFrequency (%)
S 9
24.3%
E 4
10.8%
K 4
10.8%
G 3
 
8.1%
A 3
 
8.1%
N 3
 
8.1%
T 2
 
5.4%
U 2
 
5.4%
B 2
 
5.4%
R 2
 
5.4%
Other values (3) 3
 
8.1%
Decimal Number
ValueCountFrequency (%)
1 315
18.0%
3 305
17.5%
2 249
14.3%
4 175
10.0%
6 171
9.8%
5 154
8.8%
7 127
7.3%
8 92
 
5.3%
9 87
 
5.0%
0 71
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 3
60.0%
& 1
 
20.0%
/ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1809
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 295
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6941
64.1%
Common 3857
35.6%
Latin 37
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 513
 
7.4%
포 511
 
7.4%
등 510
 
7.3%
동 471
 
6.8%
서 470
 
6.8%
울 467
 
6.7%
시 465
 
6.7%
특 463
 
6.7%
별 463
 
6.7%
구 463
 
6.7%
Other values (144) 2145
30.9%
Common
ValueCountFrequency (%)
1809
46.9%
1 315
 
8.2%
3 305
 
7.9%
- 295
 
7.6%
2 249
 
6.5%
4 175
 
4.5%
6 171
 
4.4%
5 154
 
4.0%
7 127
 
3.3%
8 92
 
2.4%
Other values (7) 165
 
4.3%
Latin
ValueCountFrequency (%)
S 9
24.3%
E 4
10.8%
K 4
10.8%
G 3
 
8.1%
A 3
 
8.1%
N 3
 
8.1%
T 2
 
5.4%
U 2
 
5.4%
B 2
 
5.4%
R 2
 
5.4%
Other values (3) 3
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6941
64.1%
ASCII 3894
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1809
46.5%
1 315
 
8.1%
3 305
 
7.8%
- 295
 
7.6%
2 249
 
6.4%
4 175
 
4.5%
6 171
 
4.4%
5 154
 
4.0%
7 127
 
3.3%
8 92
 
2.4%
Other values (20) 202
 
5.2%
Hangul
ValueCountFrequency (%)
영 513
 
7.4%
포 511
 
7.4%
등 510
 
7.3%
동 471
 
6.8%
서 470
 
6.8%
울 467
 
6.7%
시 465
 
6.7%
특 463
 
6.7%
별 463
 
6.7%
구 463
 
6.7%
Other values (144) 2145
30.9%

도로명주소
Text

MISSING 

Distinct337
Distinct (%)78.0%
Missing49
Missing (%)10.2%
Memory size3.9 KiB
2024-05-11T14:54:17.255133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length48
Mean length29.958333
Min length22

Characters and Unicode

Total characters12942
Distinct characters219
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique283 ?
Unique (%)65.5%

Sample

1st row서울특별시 영등포구 영중로41길 12 (영등포동8가)
2nd row서울특별시 영등포구 영중로41길 12 (영등포동8가)
3rd row서울특별시 영등포구 영중로41길 12 (영등포동8가)
4th row서울특별시 영등포구 영중로41길 12 (영등포동8가)
5th row서울특별시 영등포구 영중로41길 12 (영등포동8가)
ValueCountFrequency (%)
서울특별시 432
 
18.6%
영등포구 432
 
18.6%
여의도동 85
 
3.7%
선유로 57
 
2.5%
양평동3가 53
 
2.3%
문래동1가 37
 
1.6%
문래동3가 28
 
1.2%
176 26
 
1.1%
양평동6가 26
 
1.1%
양평동5가 20
 
0.9%
Other values (429) 1126
48.5%
2024-05-11T14:54:17.922809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1990
 
15.4%
영 533
 
4.1%
포 504
 
3.9%
등 502
 
3.9%
서 456
 
3.5%
동 447
 
3.5%
울 440
 
3.4%
시 436
 
3.4%
로 434
 
3.4%
구 433
 
3.3%
Other values (209) 6767
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8080
62.4%
Space Separator 1990
 
15.4%
Decimal Number 1759
 
13.6%
Close Punctuation 433
 
3.3%
Open Punctuation 433
 
3.3%
Other Punctuation 143
 
1.1%
Dash Punctuation 56
 
0.4%
Uppercase Letter 48
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 533
 
6.6%
포 504
 
6.2%
등 502
 
6.2%
서 456
 
5.6%
동 447
 
5.5%
울 440
 
5.4%
시 436
 
5.4%
로 434
 
5.4%
구 433
 
5.4%
특 432
 
5.3%
Other values (177) 3463
42.9%
Uppercase Letter
ValueCountFrequency (%)
S 10
20.8%
G 5
10.4%
K 5
10.4%
E 4
 
8.3%
A 4
 
8.3%
T 3
 
6.2%
N 3
 
6.2%
M 3
 
6.2%
U 2
 
4.2%
L 2
 
4.2%
Other values (4) 7
14.6%
Decimal Number
ValueCountFrequency (%)
1 378
21.5%
3 262
14.9%
2 216
12.3%
6 188
10.7%
7 169
9.6%
5 134
 
7.6%
4 133
 
7.6%
8 112
 
6.4%
0 94
 
5.3%
9 73
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 138
96.5%
. 3
 
2.1%
& 1
 
0.7%
/ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
1990
100.0%
Close Punctuation
ValueCountFrequency (%)
) 433
100.0%
Open Punctuation
ValueCountFrequency (%)
( 433
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8080
62.4%
Common 4814
37.2%
Latin 48
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 533
 
6.6%
포 504
 
6.2%
등 502
 
6.2%
서 456
 
5.6%
동 447
 
5.5%
울 440
 
5.4%
시 436
 
5.4%
로 434
 
5.4%
구 433
 
5.4%
특 432
 
5.3%
Other values (177) 3463
42.9%
Common
ValueCountFrequency (%)
1990
41.3%
) 433
 
9.0%
( 433
 
9.0%
1 378
 
7.9%
3 262
 
5.4%
2 216
 
4.5%
6 188
 
3.9%
7 169
 
3.5%
, 138
 
2.9%
5 134
 
2.8%
Other values (8) 473
 
9.8%
Latin
ValueCountFrequency (%)
S 10
20.8%
G 5
10.4%
K 5
10.4%
E 4
 
8.3%
A 4
 
8.3%
T 3
 
6.2%
N 3
 
6.2%
M 3
 
6.2%
U 2
 
4.2%
L 2
 
4.2%
Other values (4) 7
14.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8080
62.4%
ASCII 4862
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1990
40.9%
) 433
 
8.9%
( 433
 
8.9%
1 378
 
7.8%
3 262
 
5.4%
2 216
 
4.4%
6 188
 
3.9%
7 169
 
3.5%
, 138
 
2.8%
5 134
 
2.8%
Other values (22) 521
 
10.7%
Hangul
ValueCountFrequency (%)
영 533
 
6.6%
포 504
 
6.2%
등 502
 
6.2%
서 456
 
5.6%
동 447
 
5.5%
울 440
 
5.4%
시 436
 
5.4%
로 434
 
5.4%
구 433
 
5.4%
특 432
 
5.3%
Other values (177) 3463
42.9%

도로명우편번호
Text

MISSING 

Distinct88
Distinct (%)53.3%
Missing316
Missing (%)65.7%
Memory size3.9 KiB
2024-05-11T14:54:18.340291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1272727
Min length5

Characters and Unicode

Total characters846
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

Unique53 ?
Unique (%)32.1%

Sample

1st row150038
2nd row07371
3rd row150091
4th row07371
5th row150091
ValueCountFrequency (%)
07238 6
 
3.6%
07327 6
 
3.6%
07305 6
 
3.6%
07345 5
 
3.0%
07326 5
 
3.0%
07330 5
 
3.0%
07333 5
 
3.0%
07291 4
 
2.4%
07237 4
 
2.4%
07325 4
 
2.4%
Other values (78) 115
69.7%
2024-05-11T14:54:19.089930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 211
24.9%
7 175
20.7%
3 121
14.3%
2 120
14.2%
5 56
 
6.6%
1 55
 
6.5%
9 30
 
3.5%
4 26
 
3.1%
6 26
 
3.1%
8 25
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 845
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 211
25.0%
7 175
20.7%
3 121
14.3%
2 120
14.2%
5 56
 
6.6%
1 55
 
6.5%
9 30
 
3.6%
4 26
 
3.1%
6 26
 
3.1%
8 25
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 846
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 211
24.9%
7 175
20.7%
3 121
14.3%
2 120
14.2%
5 56
 
6.6%
1 55
 
6.5%
9 30
 
3.5%
4 26
 
3.1%
6 26
 
3.1%
8 25
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 846
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 211
24.9%
7 175
20.7%
3 121
14.3%
2 120
14.2%
5 56
 
6.6%
1 55
 
6.5%
9 30
 
3.5%
4 26
 
3.1%
6 26
 
3.1%
8 25
 
3.0%

사업장명
Text

Distinct430
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-05-11T14:54:19.517637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length8.3284823
Min length2

Characters and Unicode

Total characters4006
Distinct characters352
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique383 ?
Unique (%)79.6%

Sample

1st row한양금속공업사
2nd row서광금속
3rd row광명금속공업사
4th row원광기업사
5th row(주)다영금속
ValueCountFrequency (%)
주식회사 11
 
2.0%
관리단 7
 
1.3%
여의도 5
 
0.9%
유한회사 4
 
0.7%
주)경방 3
 
0.5%
대성공업사 3
 
0.5%
한국터치스크린(주 3
 
0.5%
정성특수 3
 
0.5%
금성정밀금형부식 2
 
0.4%
선창기업사 2
 
0.4%
Other values (458) 508
92.2%
2024-05-11T14:54:20.126272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 182
 
4.5%
( 181
 
4.5%
) 181
 
4.5%
사 121
 
3.0%
업 97
 
2.4%
동 85
 
2.1%
공 84
 
2.1%
스 79
 
2.0%
자 79
 
2.0%
70
 
1.7%
Other values (342) 2847
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3494
87.2%
Open Punctuation 188
 
4.7%
Close Punctuation 188
 
4.7%
Space Separator 70
 
1.7%
Uppercase Letter 40
 
1.0%
Decimal Number 21
 
0.5%
Other Punctuation 2
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 182
 
5.2%
사 121
 
3.5%
업 97
 
2.8%
동 85
 
2.4%
공 84
 
2.4%
스 79
 
2.3%
자 79
 
2.3%
금 65
 
1.9%
이 61
 
1.7%
대 59
 
1.7%
Other values (313) 2582
73.9%
Uppercase Letter
ValueCountFrequency (%)
S 8
20.0%
C 6
15.0%
F 4
10.0%
I 4
10.0%
A 4
10.0%
B 3
 
7.5%
M 3
 
7.5%
V 2
 
5.0%
P 2
 
5.0%
K 1
 
2.5%
Other values (3) 3
 
7.5%
Decimal Number
ValueCountFrequency (%)
1 5
23.8%
2 5
23.8%
5 4
19.0%
4 2
 
9.5%
3 2
 
9.5%
7 1
 
4.8%
6 1
 
4.8%
9 1
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 181
96.3%
[ 7
 
3.7%
Close Punctuation
ValueCountFrequency (%)
) 181
96.3%
] 7
 
3.7%
Space Separator
ValueCountFrequency (%)
70
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3495
87.2%
Common 471
 
11.8%
Latin 40
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 182
 
5.2%
사 121
 
3.5%
업 97
 
2.8%
동 85
 
2.4%
공 84
 
2.4%
스 79
 
2.3%
자 79
 
2.3%
금 65
 
1.9%
이 61
 
1.7%
대 59
 
1.7%
Other values (314) 2583
73.9%
Common
ValueCountFrequency (%)
( 181
38.4%
) 181
38.4%
70
 
14.9%
] 7
 
1.5%
[ 7
 
1.5%
1 5
 
1.1%
2 5
 
1.1%
5 4
 
0.8%
4 2
 
0.4%
3 2
 
0.4%
Other values (5) 7
 
1.5%
Latin
ValueCountFrequency (%)
S 8
20.0%
C 6
15.0%
F 4
10.0%
I 4
10.0%
A 4
10.0%
B 3
 
7.5%
M 3
 
7.5%
V 2
 
5.0%
P 2
 
5.0%
K 1
 
2.5%
Other values (3) 3
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3494
87.2%
ASCII 511
 
12.8%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 182
 
5.2%
사 121
 
3.5%
업 97
 
2.8%
동 85
 
2.4%
공 84
 
2.4%
스 79
 
2.3%
자 79
 
2.3%
금 65
 
1.9%
이 61
 
1.7%
대 59
 
1.7%
Other values (313) 2582
73.9%
ASCII
ValueCountFrequency (%)
( 181
35.4%
) 181
35.4%
70
 
13.7%
S 8
 
1.6%
] 7
 
1.4%
[ 7
 
1.4%
C 6
 
1.2%
1 5
 
1.0%
2 5
 
1.0%
F 4
 
0.8%
Other values (18) 37
 
7.2%
None
ValueCountFrequency (%)
㈜ 1
100.0%

최종수정일자
Date

UNIQUE 

Distinct481
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2000-10-11 11:37:49
Maximum2024-05-02 20:05:25
2024-05-11T14:54:20.374279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:20.677662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
U
263 
I
218 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 263
54.7%
I 218
45.3%

Length

2024-05-11T14:54:20.920672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:21.093865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 263
54.7%
i 218
45.3%

데이터갱신일자
Date

Distinct173
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2018-09-27 23:59:59
Maximum2023-12-05 00:04:00
2024-05-11T14:54:21.270729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:21.558709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Text

MISSING 

Distinct79
Distinct (%)35.9%
Missing261
Missing (%)54.3%
Memory size3.9 KiB
2024-05-11T14:54:22.099199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length8.5227273
Min length2

Characters and Unicode

Total characters1875
Distinct characters136
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

Unique51 ?
Unique (%)23.2%

Sample

1st row도금업
2nd row금속 주조업
3rd row도금업
4th row금속 열처리, 도금 및 기타 금속가공업
5th row도금업
ValueCountFrequency (%)
도금업 41
 
7.5%
및 41
 
7.5%
기타 40
 
7.3%
자동차 39
 
7.1%
제조업 36
 
6.6%
세차업 20
 
3.7%
종합 18
 
3.3%
수리업 18
 
3.3%
부동산업 18
 
3.3%
부동산 15
 
2.7%
Other values (108) 260
47.6%
2024-05-11T14:54:22.841769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
326
 
17.4%
업 211
 
11.3%
금 77
 
4.1%
동 75
 
4.0%
제 67
 
3.6%
차 64
 
3.4%
도 55
 
2.9%
조 53
 
2.8%
기 51
 
2.7%
리 51
 
2.7%
Other values (126) 845
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1545
82.4%
Space Separator 326
 
17.4%
Other Punctuation 3
 
0.2%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 211
 
13.7%
금 77
 
5.0%
동 75
 
4.9%
제 67
 
4.3%
차 64
 
4.1%
도 55
 
3.6%
조 53
 
3.4%
기 51
 
3.3%
리 51
 
3.3%
자 44
 
2.8%
Other values (123) 797
51.6%
Space Separator
ValueCountFrequency (%)
326
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1545
82.4%
Common 330
 
17.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 211
 
13.7%
금 77
 
5.0%
동 75
 
4.9%
제 67
 
4.3%
차 64
 
4.1%
도 55
 
3.6%
조 53
 
3.4%
기 51
 
3.3%
리 51
 
3.3%
자 44
 
2.8%
Other values (123) 797
51.6%
Common
ValueCountFrequency (%)
326
98.8%
, 3
 
0.9%
1 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1545
82.4%
ASCII 330
 
17.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
326
98.8%
, 3
 
0.9%
1 1
 
0.3%
Hangul
ValueCountFrequency (%)
업 211
 
13.7%
금 77
 
5.0%
동 75
 
4.9%
제 67
 
4.3%
차 64
 
4.1%
도 55
 
3.6%
조 53
 
3.4%
기 51
 
3.3%
리 51
 
3.3%
자 44
 
2.8%
Other values (123) 797
51.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct301
Distinct (%)68.7%
Missing43
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean191097.41
Minimum189552.02
Maximum194632.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-05-11T14:54:23.490819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189552.02
5-th percentile189745.95
Q1190304.86
median190522.61
Q3191578.71
95-th percentile193568.35
Maximum194632.53
Range5080.5046
Interquartile range (IQR)1273.8405

Descriptive statistics

Standard deviation1236.4953
Coefficient of variation (CV)0.0064704975
Kurtosis-0.04509083
Mean191097.41
Median Absolute Deviation (MAD)402.09236
Skewness1.1086988
Sum83700668
Variance1528920.7
MonotonicityNot monotonic
2024-05-11T14:54:23.723951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190488.51283629 26
 
5.4%
190538.027786022 14
 
2.9%
190448.157570527 6
 
1.2%
191385.057392247 5
 
1.0%
190394.893240555 5
 
1.0%
191484.795883444 5
 
1.0%
189734.544016734 4
 
0.8%
193326.931018911 4
 
0.8%
190423.161819476 4
 
0.8%
190205.589461995 4
 
0.8%
Other values (291) 361
75.1%
(Missing) 43
 
8.9%
ValueCountFrequency (%)
189552.021760333 1
0.2%
189554.182520551 2
0.4%
189617.235259629 1
0.2%
189621.592266026 2
0.4%
189649.902054728 1
0.2%
189678.939085241 1
0.2%
189682.022243843 1
0.2%
189710.546326777 1
0.2%
189715.276099415 1
0.2%
189720.59056995 1
0.2%
ValueCountFrequency (%)
194632.526367463 1
 
0.2%
194530.535390096 1
 
0.2%
194504.656267957 3
0.6%
194324.398950764 1
 
0.2%
193861.272368256 1
 
0.2%
193844.169062846 1
 
0.2%
193818.18014 1
 
0.2%
193798.948251805 1
 
0.2%
193767.231404334 1
 
0.2%
193726.322806044 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct301
Distinct (%)68.7%
Missing43
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean446786.81
Minimum442751.47
Maximum449085.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-05-11T14:54:24.023837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442751.47
5-th percentile445389.32
Q1446052.98
median446813.84
Q3447425.5
95-th percentile448702.3
Maximum449085.44
Range6333.9727
Interquartile range (IQR)1372.523

Descriptive statistics

Standard deviation1051.4955
Coefficient of variation (CV)0.0023534614
Kurtosis0.42365956
Mean446786.81
Median Absolute Deviation (MAD)611.655
Skewness-0.095341663
Sum1.9569262 × 108
Variance1105642.8
MonotonicityNot monotonic
2024-05-11T14:54:24.259659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447425.498511292 26
 
5.4%
445443.835077233 14
 
2.9%
445389.316055073 6
 
1.2%
446098.555926507 5
 
1.0%
448455.552719091 5
 
1.0%
447424.009075052 5
 
1.0%
446634.254586356 4
 
0.8%
446973.914570276 4
 
0.8%
445550.795371215 4
 
0.8%
448655.273531987 4
 
0.8%
Other values (291) 361
75.1%
(Missing) 43
 
8.9%
ValueCountFrequency (%)
442751.471769958 1
0.2%
443157.388663332 1
0.2%
443231.351977519 1
0.2%
443459.357676774 1
0.2%
444268.836599848 1
0.2%
444750.439497843 1
0.2%
444772.107371737 1
0.2%
444779.980000876 1
0.2%
444797.883766039 1
0.2%
444818.181074076 1
0.2%
ValueCountFrequency (%)
449085.444429773 1
 
0.2%
449058.532372675 1
 
0.2%
448990.816559516 3
0.6%
448925.043878859 3
0.6%
448923.661413114 2
0.4%
448903.4937903 2
0.4%
448871.733893544 2
0.4%
448827.326974942 1
 
0.2%
448788.457554535 1
 
0.2%
448779.57454276 1
 
0.2%

환경업무구분명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
대기배출업소관리
319 
<NA>
162 

Length

Max length8
Median length8
Mean length6.6528067
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대기배출업소관리 319
66.3%
<NA> 162
33.7%

Length

2024-05-11T14:54:24.478767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:24.677981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기배출업소관리 319
66.3%
na 162
33.7%

업종구분명
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct51
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
337 
도금업
35 
자동차 세차업
 
17
조립금속제품 제조업 기계 및 가구 제외
 
8
부동산업
 
6
Other values (46)
78 

Length

Max length21
Median length4
Mean length5.4636175
Min length3

Unique

Unique32 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 337
70.1%
도금업 35
 
7.3%
자동차 세차업 17
 
3.5%
조립금속제품 제조업 기계 및 가구 제외 8
 
1.7%
부동산업 6
 
1.2%
자동차 종합 수리업 6
 
1.2%
자동차 수리업 6
 
1.2%
도장 및 기타 피막처리업 6
 
1.2%
비주거용 부동산 관리업 5
 
1.0%
백화점 3
 
0.6%
Other values (41) 52
 
10.8%

Length

2024-05-11T14:54:24.880379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 337
47.6%
도금업 35
 
4.9%
자동차 32
 
4.5%
및 32
 
4.5%
제조업 29
 
4.1%
기타 25
 
3.5%
세차업 19
 
2.7%
수리업 13
 
1.8%
조립금속제품 11
 
1.6%
종합 9
 
1.3%
Other values (78) 166
23.4%

종별명
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
263 
5종
182 
4종
31 
2종
 
3
3종
 
2

Length

Max length4
Median length4
Mean length3.0935551
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 263
54.7%
5종 182
37.8%
4종 31
 
6.4%
2종 3
 
0.6%
3종 2
 
0.4%

Length

2024-05-11T14:54:25.126544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:25.365373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 263
54.7%
5종 182
37.8%
4종 31
 
6.4%
2종 3
 
0.6%
3종 2
 
0.4%

주생산품명
Text

MISSING 

Distinct10
Distinct (%)90.9%
Missing470
Missing (%)97.7%
Memory size3.9 KiB
2024-05-11T14:54:25.596979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4
Min length2

Characters and Unicode

Total characters44
Distinct characters29
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)81.8%

Sample

1st row금속부품
2nd row금속제품제조
3rd row스텐판, 동판
4th row기계부품
5th row악세사리
ValueCountFrequency (%)
기계부품 2
16.7%
금속부품 1
8.3%
금속제품제조 1
8.3%
스텐판 1
8.3%
동판 1
8.3%
악세사리 1
8.3%
전자부품 1
8.3%
간판 1
8.3%
도장 1
8.3%
서적출판 1
8.3%
2024-05-11T14:54:26.050631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
품 5
 
11.4%
부 4
 
9.1%
판 4
 
9.1%
기 2
 
4.5%
금 2
 
4.5%
속 2
 
4.5%
제 2
 
4.5%
계 2
 
4.5%
서 1
 
2.3%
간 1
 
2.3%
Other values (19) 19
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42
95.5%
Space Separator 1
 
2.3%
Other Punctuation 1
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 5
 
11.9%
부 4
 
9.5%
판 4
 
9.5%
기 2
 
4.8%
금 2
 
4.8%
속 2
 
4.8%
제 2
 
4.8%
계 2
 
4.8%
서 1
 
2.4%
간 1
 
2.4%
Other values (17) 17
40.5%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42
95.5%
Common 2
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 5
 
11.9%
부 4
 
9.5%
판 4
 
9.5%
기 2
 
4.8%
금 2
 
4.8%
속 2
 
4.8%
제 2
 
4.8%
계 2
 
4.8%
서 1
 
2.4%
간 1
 
2.4%
Other values (17) 17
40.5%
Common
ValueCountFrequency (%)
1
50.0%
, 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42
95.5%
ASCII 2
 
4.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
품 5
 
11.9%
부 4
 
9.5%
판 4
 
9.5%
기 2
 
4.8%
금 2
 
4.8%
속 2
 
4.8%
제 2
 
4.8%
계 2
 
4.8%
서 1
 
2.4%
간 1
 
2.4%
Other values (17) 17
40.5%
ASCII
ValueCountFrequency (%)
1
50.0%
, 1
50.0%

배출시설조업시간
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)7.1%
Missing187
Missing (%)38.9%
Infinite0
Infinite (%)0.0%
Mean3.5197279
Minimum0
Maximum24
Zeros162
Zeros (%)33.7%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-05-11T14:54:26.261697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q38
95-th percentile10
Maximum24
Range24
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.8278294
Coefficient of variation (CV)1.3716485
Kurtosis3.4126697
Mean3.5197279
Median Absolute Deviation (MAD)0
Skewness1.6073137
Sum1034.8
Variance23.307937
MonotonicityNot monotonic
2024-05-11T14:54:26.463924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 162
33.7%
8.0 66
 
13.7%
10.0 9
 
1.9%
6.0 8
 
1.7%
2.0 7
 
1.5%
5.0 7
 
1.5%
4.0 7
 
1.5%
3.0 6
 
1.2%
11.0 3
 
0.6%
24.0 3
 
0.6%
Other values (11) 16
 
3.3%
(Missing) 187
38.9%
ValueCountFrequency (%)
0.0 162
33.7%
1.0 1
 
0.2%
1.3 1
 
0.2%
1.5 2
 
0.4%
2.0 7
 
1.5%
3.0 6
 
1.2%
4.0 7
 
1.5%
5.0 7
 
1.5%
6.0 8
 
1.7%
7.0 2
 
0.4%
ValueCountFrequency (%)
24.0 3
 
0.6%
23.0 1
 
0.2%
22.0 1
 
0.2%
20.0 1
 
0.2%
16.0 2
 
0.4%
12.0 3
 
0.6%
11.0 3
 
0.6%
10.0 9
 
1.9%
9.0 1
 
0.2%
8.0 66
13.7%

배출시설연간가동일수
Real number (ℝ)

MISSING  ZEROS 

Distinct35
Distinct (%)11.9%
Missing186
Missing (%)38.7%
Infinite0
Infinite (%)0.0%
Mean104.2678
Minimum0
Maximum365
Zeros168
Zeros (%)34.9%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-05-11T14:54:26.664931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3300
95-th percentile343
Maximum365
Range365
Interquartile range (IQR)300

Descriptive statistics

Standard deviation135.68112
Coefficient of variation (CV)1.3012754
Kurtosis-1.1675384
Mean104.2678
Median Absolute Deviation (MAD)0
Skewness0.76617104
Sum30759
Variance18409.367
MonotonicityNot monotonic
2024-05-11T14:54:26.922669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 168
34.9%
300 59
 
12.3%
365 11
 
2.3%
100 7
 
1.5%
150 6
 
1.2%
102 4
 
0.8%
120 4
 
0.8%
90 3
 
0.6%
360 3
 
0.6%
82 2
 
0.4%
Other values (25) 28
 
5.8%
(Missing) 186
38.7%
ValueCountFrequency (%)
0 168
34.9%
47 1
 
0.2%
53 1
 
0.2%
55 1
 
0.2%
80 2
 
0.4%
82 2
 
0.4%
90 3
 
0.6%
92 2
 
0.4%
95 1
 
0.2%
100 7
 
1.5%
ValueCountFrequency (%)
365 11
 
2.3%
360 3
 
0.6%
350 1
 
0.2%
340 1
 
0.2%
300 59
12.3%
294 1
 
0.2%
270 1
 
0.2%
260 1
 
0.2%
250 1
 
0.2%
249 1
 
0.2%

방지시설조업시간
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)7.0%
Missing211
Missing (%)43.9%
Infinite0
Infinite (%)0.0%
Mean2.7203704
Minimum0
Maximum30
Zeros179
Zeros (%)37.2%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-05-11T14:54:27.159299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile10
Maximum30
Range30
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.588104
Coefficient of variation (CV)1.6865733
Kurtosis6.480034
Mean2.7203704
Median Absolute Deviation (MAD)0
Skewness2.1432803
Sum734.5
Variance21.050699
MonotonicityNot monotonic
2024-05-11T14:54:27.388758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 179
37.2%
8.0 41
 
8.5%
10.0 8
 
1.7%
6.0 8
 
1.7%
5.0 7
 
1.5%
2.0 4
 
0.8%
4.0 4
 
0.8%
11.0 3
 
0.6%
3.0 3
 
0.6%
12.0 2
 
0.4%
Other values (9) 11
 
2.3%
(Missing) 211
43.9%
ValueCountFrequency (%)
0.0 179
37.2%
1.5 2
 
0.4%
2.0 4
 
0.8%
3.0 3
 
0.6%
4.0 4
 
0.8%
5.0 7
 
1.5%
6.0 8
 
1.7%
7.0 1
 
0.2%
7.5 1
 
0.2%
8.0 41
 
8.5%
ValueCountFrequency (%)
30.0 1
 
0.2%
23.0 1
 
0.2%
22.0 1
 
0.2%
20.0 1
 
0.2%
16.0 2
 
0.4%
12.0 2
 
0.4%
11.0 3
 
0.6%
10.0 8
 
1.7%
9.0 1
 
0.2%
8.0 41
8.5%

방지시설연간가동일수
Real number (ℝ)

MISSING  ZEROS 

Distinct29
Distinct (%)10.3%
Missing200
Missing (%)41.6%
Infinite0
Infinite (%)0.0%
Mean82.017794
Minimum0
Maximum365
Zeros185
Zeros (%)38.5%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-05-11T14:54:27.642493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3150
95-th percentile300
Maximum365
Range365
Interquartile range (IQR)150

Descriptive statistics

Standard deviation126.88486
Coefficient of variation (CV)1.5470406
Kurtosis-0.4317514
Mean82.017794
Median Absolute Deviation (MAD)0
Skewness1.1338064
Sum23047
Variance16099.768
MonotonicityNot monotonic
2024-05-11T14:54:27.852192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 185
38.5%
300 42
 
8.7%
365 8
 
1.7%
150 6
 
1.2%
100 5
 
1.0%
102 4
 
0.8%
360 3
 
0.6%
120 3
 
0.6%
92 2
 
0.4%
250 2
 
0.4%
Other values (19) 21
 
4.4%
(Missing) 200
41.6%
ValueCountFrequency (%)
0 185
38.5%
47 1
 
0.2%
53 1
 
0.2%
80 2
 
0.4%
82 1
 
0.2%
92 2
 
0.4%
95 1
 
0.2%
100 5
 
1.0%
102 4
 
0.8%
110 1
 
0.2%
ValueCountFrequency (%)
365 8
 
1.7%
360 3
 
0.6%
350 1
 
0.2%
300 42
8.7%
270 1
 
0.2%
260 1
 
0.2%
250 2
 
0.4%
249 1
 
0.2%
240 2
 
0.4%
236 1
 
0.2%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
0318000031800002120000000119931029<NA>3폐업2폐업20021230<NA><NA><NA><NA><NA>150038서울특별시 영등포구 영등포동8가 73번지서울특별시 영등포구 영중로41길 12 (영등포동8가)<NA>한양금속공업사2002-12-30 17:50:00I2018-10-04 11:12:49.0도금업191484.795883447424.009075대기배출업소관리도금업<NA><NA>0.000.00
1318000031800002120000000219931029<NA>3폐업2폐업20010118<NA><NA><NA><NA><NA>150038서울특별시 영등포구 영등포동8가 73번지서울특별시 영등포구 영중로41길 12 (영등포동8가)<NA>서광금속2001-01-18 13:42:53I2018-10-04 11:12:49.0금속 주조업191484.795883447424.009075대기배출업소관리금속 주조업<NA><NA>0.000.00
2318000031800002120000000319940219<NA>1영업/정상11영업<NA><NA><NA><NA>6788559<NA><NA>서울특별시 영등포구 영등포동8가 73서울특별시 영등포구 영중로41길 12 (영등포동8가)150038광명금속공업사2021-10-20 08:55:24U2021-10-22 02:40:00.0<NA>191484.795883447424.009075대기배출업소관리<NA>4종<NA>8.03008.0300
3318000031800002120000000419741120<NA>3폐업2폐업20091130<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동8가 73-0번지서울특별시 영등포구 영중로41길 12 (영등포동8가)<NA>원광기업사2009-11-30 11:34:35I2018-10-04 11:12:49.0<NA>191484.795883447424.009075대기배출업소관리<NA>5종<NA>0.000.00
4318000031800002120000000519980703<NA>4취소/말소/만료/정지/중지4폐쇄20190809<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동8가 73-0번지서울특별시 영등포구 영중로41길 12 (영등포동8가)<NA>(주)다영금속2019-08-09 11:04:13U2019-08-11 02:40:00.0<NA>191484.795883447424.009075대기배출업소관리<NA>5종<NA>0.000.00
5318000031800002120000000719930924<NA>1영업/정상11영업<NA><NA><NA><NA>02-2633-1932<NA><NA>서울특별시 영등포구 문래동1가 54-2<NA><NA>진성열처리공업(주)2022-01-11 15:17:41U2022-01-13 02:40:00.0<NA><NA><NA>대기배출업소관리<NA>5종<NA>8.03008.0300
6318000031800002120000000819881017<NA>4취소/말소/만료/정지/중지4폐쇄20211201<NA><NA><NA>2678-0931<NA><NA>서울특별시 영등포구 문래동1가 74 106호서울특별시 영등포구 경인로76길 6 (문래동1가, 106호)07371대광특수공업2022-03-19 10:02:52U2022-03-21 02:40:00.0도금업190538.027786445443.835077대기배출업소관리도금업5종<NA>0.000.00
7318000031800002120000000919881017<NA>4취소/말소/만료/정지/중지4폐쇄20220518<NA><NA><NA>0226794997<NA><NA>서울특별시 영등포구 문래동1가 74서울특별시 영등포구 경인로76길 6 (문래동1가)<NA>영일도금2022-05-19 09:01:12U2021-12-04 22:01:00.0금속 열처리, 도금 및 기타 금속가공업190538.027786445443.835077<NA><NA><NA><NA><NA><NA><NA><NA>
8318000031800002120000001019920807<NA>4취소/말소/만료/정지/중지4폐쇄20050620<NA><NA><NA>0226341317<NA>150091서울특별시 영등포구 문래동1가 74번지서울특별시 영등포구 경인로76길 6 (문래동1가)<NA>미래산업2005-06-20 17:29:17I2018-10-04 11:12:49.0도금업190538.027786445443.835077대기배출업소관리도금업<NA><NA>0.000.00
931800003180000212000000111993-08-21<NA>4취소/말소/만료/정지/중지4폐쇄2024-04-02<NA><NA><NA>02-2675-1369<NA><NA>서울특별시 영등포구 문래동1가 74서울특별시 영등포구 경인로76길 6 (문래동1가)<NA>우성열처리2024-04-03 15:20:54U2023-12-04 00:05:00.0기타 금속가공제품 제조업190538.027786445443.835077<NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
47131800003180000212022000112022-12-05<NA>1영업/정상11영업<NA><NA><NA><NA>02-781-1000<NA><NA>서울특별시 영등포구 여의도동 18 한국방송공사서울특별시 영등포구 여의공원로 13, 한국방송공사 (여의도동)07235한국방송공사 (KBS별관)2024-01-02 10:54:20U2023-12-01 00:04:00.0공중파 방송업192538.786642447017.159179<NA><NA><NA><NA><NA><NA><NA><NA>
472318000031800002120220001220221214<NA>1영업/정상11영업<NA><NA><NA><NA>02-2639-6884<NA><NA>서울특별시 영등포구 영등포동7가 94-46 제일빌딩서울특별시 영등포구 버드나루로 84, 제일빌딩 (영등포동7가)07230제일물산주식회사2022-12-15 16:16:01I2021-11-01 23:07:00.0그외 기타 상품 전문 도매업191921.794068447058.097595<NA><NA><NA><NA><NA><NA><NA><NA>
473318000031800002120220001320221215<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 61-5 리버타워서울특별시 영등포구 63로 36 (여의도동, 리버타워)07345리버타워빌딩관리단2022-12-16 15:42:22I2021-11-01 23:08:00.0<NA>194504.656268446355.021492<NA><NA><NA><NA><NA><NA><NA><NA>
47431800003180000212022000142022-12-22<NA>1영업/정상11영업<NA><NA><NA><NA>070-7092-7782<NA><NA>서울특별시 영등포구 당산동3가 2-7 코레일유통 사옥서울특별시 영등포구 국회대로 612, 코레일유통 사옥 (당산동3가)07258코레일유통(주)2023-03-02 11:19:13U2022-12-03 00:04:00.0<NA>191272.120991447064.885775<NA><NA><NA><NA><NA><NA><NA><NA>
475318000031800002120220001520221226<NA>1영업/정상11영업<NA><NA><NA><NA>02-2019-9039<NA><NA>서울특별시 영등포구 당산동4가 38-1 에이원타워 당산서울특별시 영등포구 국회대로 559, 에이원타워 당산 (당산동4가)07219주식회사 엔에이치제3호위탁관리부동산투자회사2023-01-18 16:45:20U2022-11-30 22:00:00.0부동산업190811.867953447351.665282<NA><NA><NA><NA><NA><NA><NA><NA>
47631800003180000212022000162022-12-27<NA>1영업/정상11영업<NA><NA><NA><NA>02-831-8780<NA><NA>서울특별시 영등포구 신길동 1196서울특별시 영등포구 여의대방로 259 (신길동)07355공군항공안전단(공군호텔)2023-08-23 15:43:04U2022-12-07 22:05:00.0<NA>193176.477193445333.479175<NA><NA><NA><NA><NA><NA><NA><NA>
47731800003180000212023000012023-11-15<NA>1영업/정상11영업<NA><NA><NA><NA>02-2069-2064<NA><NA>서울특별시 영등포구 영등포동8가 35-1 리마크빌 영등포서울특별시 영등포구 영중로 119, 리마크빌 영등포 (영등포동8가)07228(주)케이디리빙2023-11-20 17:34:25U2022-10-31 22:02:00.0부동산업191536.037141447172.053366<NA><NA><NA><NA><NA><NA><NA><NA>
47831800003180000212023000022023-12-01<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 14-8 극동브이아이피빌딩서울특별시 영등포구 국회대로70길 15-1, 극동브이아이피빌딩 (여의도동)07238극동VIP빌딩관리단2023-12-01 15:32:54I2022-11-02 00:03:00.0<NA>192883.820839447484.878116<NA><NA><NA><NA><NA><NA><NA><NA>
47931800003180000212023000032023-12-29<NA>1영업/정상11영업<NA><NA><NA><NA>02-785-8196<NA><NA>서울특별시 영등포구 여의도동 13 여의도파라곤서울특별시 영등포구 국회대로 800, 여의도파라곤 (여의도동)07238여의도파라곤 관리단2024-01-02 10:55:36U2023-12-01 00:04:00.0비주거용 부동산 관리업192959.271161447637.656082<NA><NA><NA><NA><NA><NA><NA><NA>
48031800003180000212024000012024-05-02<NA>1영업/정상11영업<NA><NA><NA><NA>02-2670-0703<NA><NA>서울특별시 영등포구 양평동4가 1-1 한국GM주식회사서울특별시 영등포구 선유동2로 51, 한국GM주식회사 (양평동4가)07212한국지엠(주) 서울서비스센터2024-05-02 20:05:25I2023-12-05 00:04:00.0자동차 수리 및 세차업190794.61837447871.264061<NA><NA><NA><NA><NA><NA><NA><NA>