Overview

Dataset statistics

Number of variables13
Number of observations1340
Missing cells2015
Missing cells (%)11.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory142.8 KiB
Average record size in memory109.1 B

Variable types

Text4
Numeric3
Categorical4
Boolean1
Unsupported1

Dataset

Description업체(시설)명,인허가번호,업종코드,업종명,지도점검일자,점검기관,점검기관명,지도점검구분,처분대상여부,점검사항,점검결과,소재지도로명주소,소재지주소
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-9970/S/1/datasetView.do

Alerts

점검기관 has constant value ""Constant
점검기관명 has constant value ""Constant
인허가번호 is highly overall correlated with 업종코드 and 1 other fieldsHigh correlation
업종코드 is highly overall correlated with 인허가번호 and 1 other fieldsHigh correlation
업종명 is highly overall correlated with 인허가번호 and 1 other fieldsHigh correlation
업종명 is highly imbalanced (53.1%)Imbalance
지도점검구분 is highly imbalanced (54.5%)Imbalance
처분대상여부 is highly imbalanced (95.3%)Imbalance
점검결과 has 1340 (100.0%) missing valuesMissing
소재지도로명주소 has 647 (48.3%) missing valuesMissing
소재지주소 has 18 (1.3%) missing valuesMissing
점검결과 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 00:50:38.701040
Analysis finished2024-05-11 00:50:49.138486
Duration10.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체(시설)명
Text

Distinct321
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
2024-05-11T00:50:49.455792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length8.3276119
Min length3

Characters and Unicode

Total characters11159
Distinct characters311
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

Unique90 ?
Unique (%)6.7%

Sample

1st row한국지엠강서서비스(주)
2nd row창조모터스
3rd row현대미라클모터스
4th row강서현대서비스
5th row한성모터스
ValueCountFrequency (%)
벽산자동차공업사 26
 
1.8%
현대자동차공업사 25
 
1.8%
영원카독크 24
 
1.7%
마곡자동차써비스 24
 
1.7%
태광자동차 22
 
1.6%
주)광진자동차서비스 21
 
1.5%
주)동부현대자동차 17
 
1.2%
마이스터모터스(주 17
 
1.2%
털보자동차정비 17
 
1.2%
남도자동차공업사 15
 
1.1%
Other values (330) 1200
85.2%
2024-05-11T00:50:50.464320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 622
 
5.6%
동 579
 
5.2%
) 566
 
5.1%
( 561
 
5.0%
차 529
 
4.7%
자 508
 
4.6%
공 397
 
3.6%
업 376
 
3.4%
스 372
 
3.3%
사 371
 
3.3%
Other values (301) 6278
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9815
88.0%
Close Punctuation 566
 
5.1%
Open Punctuation 561
 
5.0%
Uppercase Letter 70
 
0.6%
Space Separator 68
 
0.6%
Lowercase Letter 48
 
0.4%
Decimal Number 21
 
0.2%
Other Punctuation 8
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 622
 
6.3%
동 579
 
5.9%
차 529
 
5.4%
자 508
 
5.2%
공 397
 
4.0%
업 376
 
3.8%
스 372
 
3.8%
사 371
 
3.8%
서 287
 
2.9%
비 278
 
2.8%
Other values (261) 5496
56.0%
Lowercase Letter
ValueCountFrequency (%)
k 6
12.5%
n 5
10.4%
i 5
10.4%
r 5
10.4%
o 4
8.3%
b 4
8.3%
s 4
8.3%
t 3
6.2%
e 3
6.2%
g 2
 
4.2%
Other values (4) 7
14.6%
Uppercase Letter
ValueCountFrequency (%)
K 20
28.6%
N 13
18.6%
T 10
14.3%
S 9
12.9%
E 4
 
5.7%
C 4
 
5.7%
G 3
 
4.3%
M 3
 
4.3%
H 1
 
1.4%
B 1
 
1.4%
Other values (2) 2
 
2.9%
Decimal Number
ValueCountFrequency (%)
5 6
28.6%
7 4
19.0%
6 3
14.3%
0 2
 
9.5%
2 2
 
9.5%
1 2
 
9.5%
3 1
 
4.8%
9 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 6
75.0%
& 2
 
25.0%
Close Punctuation
ValueCountFrequency (%)
) 566
100.0%
Open Punctuation
ValueCountFrequency (%)
( 561
100.0%
Space Separator
ValueCountFrequency (%)
68
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9815
88.0%
Common 1226
 
11.0%
Latin 118
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 622
 
6.3%
동 579
 
5.9%
차 529
 
5.4%
자 508
 
5.2%
공 397
 
4.0%
업 376
 
3.8%
스 372
 
3.8%
사 371
 
3.8%
서 287
 
2.9%
비 278
 
2.8%
Other values (261) 5496
56.0%
Latin
ValueCountFrequency (%)
K 20
16.9%
N 13
 
11.0%
T 10
 
8.5%
S 9
 
7.6%
k 6
 
5.1%
n 5
 
4.2%
i 5
 
4.2%
r 5
 
4.2%
o 4
 
3.4%
b 4
 
3.4%
Other values (16) 37
31.4%
Common
ValueCountFrequency (%)
) 566
46.2%
( 561
45.8%
68
 
5.5%
5 6
 
0.5%
. 6
 
0.5%
7 4
 
0.3%
6 3
 
0.2%
0 2
 
0.2%
2 2
 
0.2%
1 2
 
0.2%
Other values (4) 6
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9815
88.0%
ASCII 1344
 
12.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 622
 
6.3%
동 579
 
5.9%
차 529
 
5.4%
자 508
 
5.2%
공 397
 
4.0%
업 376
 
3.8%
스 372
 
3.8%
사 371
 
3.8%
서 287
 
2.9%
비 278
 
2.8%
Other values (261) 5496
56.0%
ASCII
ValueCountFrequency (%)
) 566
42.1%
( 561
41.7%
68
 
5.1%
K 20
 
1.5%
N 13
 
1.0%
T 10
 
0.7%
S 9
 
0.7%
5 6
 
0.4%
k 6
 
0.4%
. 6
 
0.4%
Other values (30) 79
 
5.9%

인허가번호
Real number (ℝ)

HIGH CORRELATION 

Distinct389
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1500002 × 1017
Minimum3.1500002 × 1017
Maximum3.1500009 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 KiB
2024-05-11T00:50:50.905122image/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 percentile3.1500003 × 1017
Maximum3.1500009 × 1017
Range7.1002 × 1010
Interquartile range (IQR)1.0001254 × 109

Descriptive statistics

Standard deviation2.4110158 × 109
Coefficient of variation (CV)7.6540179 × 10-9
Kurtosis542.44101
Mean3.1500002 × 1017
Median Absolute Deviation (MAD)1800000
Skewness19.674323
Sum-2.1750842 × 1018
Variance5.8129972 × 1018
MonotonicityNot monotonic
2024-05-11T00:50:51.360686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
315000021200800001 24
 
1.8%
315000021200300128 22
 
1.6%
315000021200200128 21
 
1.6%
315000021200300134 17
 
1.3%
315000021200800180 14
 
1.0%
315000021200800181 14
 
1.0%
315000021200400149 14
 
1.0%
315000021200000113 14
 
1.0%
315000021200100119 13
 
1.0%
315000021200200120 13
 
1.0%
Other values (379) 1174
87.6%
ValueCountFrequency (%)
315000021197500034 2
 
0.1%
315000021199100050 3
 
0.2%
315000021199200008 2
 
0.1%
315000021199200027 8
0.6%
315000021199200029 6
0.4%
315000021199200044 4
 
0.3%
315000021199300002 3
 
0.2%
315000021199300030 4
 
0.3%
315000021199300048 11
0.8%
315000021199400001 8
0.6%
ValueCountFrequency (%)
315000092199500006 1
0.1%
315000035200000006 1
0.1%
315000034201000101 1
0.1%
315000034201000072 1
0.1%
315000034200800238 2
0.1%
315000034200700174 1
0.1%
315000034200600018 1
0.1%
315000034200400216 1
0.1%
315000034200400113 1
0.1%
315000034200300324 1
0.1%

업종코드
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.8
Minimum21
Maximum92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 KiB
2024-05-11T00:50:51.869476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile21
Q121
median21
Q322
95-th percentile25
Maximum92
Range71
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.4228807
Coefficient of variation (CV)0.11114132
Kurtosis531.34956
Mean21.8
Median Absolute Deviation (MAD)0
Skewness19.385752
Sum29212
Variance5.870351
MonotonicityNot monotonic
2024-05-11T00:50:52.401218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
21 710
53.0%
22 526
39.3%
25 71
 
5.3%
23 20
 
1.5%
34 10
 
0.7%
28 1
 
0.1%
92 1
 
0.1%
35 1
 
0.1%
ValueCountFrequency (%)
21 710
53.0%
22 526
39.3%
23 20
 
1.5%
25 71
 
5.3%
28 1
 
0.1%
34 10
 
0.7%
35 1
 
0.1%
92 1
 
0.1%
ValueCountFrequency (%)
92 1
 
0.1%
35 1
 
0.1%
34 10
 
0.7%
28 1
 
0.1%
25 71
 
5.3%
23 20
 
1.5%
22 526
39.3%
21 710
53.0%

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
대기배출업소관리
710 
폐수배출업소관리
526 
기타수질오염원관리
 
71
소음진동관리
 
20
지정폐기물배출자관리
 
10
Other values (3)
 
3

Length

Max length16
Median length8
Mean length8.0440299
Min length6

Unique

Unique3 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
대기배출업소관리 710
53.0%
폐수배출업소관리 526
39.3%
기타수질오염원관리 71
 
5.3%
소음진동관리 20
 
1.5%
지정폐기물배출자관리 10
 
0.7%
악취배출업소관리 1
 
0.1%
건설폐기물처리업사업계획(허가) 1
 
0.1%
폐기물처리업관리 1
 
0.1%

Length

2024-05-11T00:50:52.878234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:50:53.293994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기배출업소관리 710
53.0%
폐수배출업소관리 526
39.3%
기타수질오염원관리 71
 
5.3%
소음진동관리 20
 
1.5%
지정폐기물배출자관리 10
 
0.7%
악취배출업소관리 1
 
0.1%
건설폐기물처리업사업계획(허가 1
 
0.1%
폐기물처리업관리 1
 
0.1%

지도점검일자
Real number (ℝ)

Distinct301
Distinct (%)22.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20135754
Minimum20100205
Maximum20170615
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 KiB
2024-05-11T00:50:53.799651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100205
5-th percentile20100415
Q120111108
median20140307
Q320160504
95-th percentile20170406
Maximum20170615
Range70410
Interquartile range (IQR)49396

Descriptive statistics

Standard deviation24189.818
Coefficient of variation (CV)0.0012013366
Kurtosis-1.4159905
Mean20135754
Median Absolute Deviation (MAD)20213
Skewness-0.10923503
Sum2.698191 × 1010
Variance5.8514731 × 108
MonotonicityDecreasing
2024-05-11T00:50:54.319833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120725 16
 
1.2%
20100706 16
 
1.2%
20160405 15
 
1.1%
20110414 15
 
1.1%
20170404 13
 
1.0%
20170614 13
 
1.0%
20170615 12
 
0.9%
20131031 12
 
0.9%
20160907 12
 
0.9%
20100727 12
 
0.9%
Other values (291) 1204
89.9%
ValueCountFrequency (%)
20100205 3
0.2%
20100308 1
 
0.1%
20100309 2
 
0.1%
20100311 1
 
0.1%
20100315 1
 
0.1%
20100317 2
 
0.1%
20100325 3
0.2%
20100401 4
0.3%
20100402 4
0.3%
20100405 7
0.5%
ValueCountFrequency (%)
20170615 12
0.9%
20170614 13
1.0%
20170613 11
0.8%
20170612 12
0.9%
20170526 4
 
0.3%
20170525 4
 
0.3%
20170512 1
 
0.1%
20170511 4
 
0.3%
20170427 2
 
0.1%
20170425 1
 
0.1%

점검기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
3150000
1340 

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 1340
100.0%

Length

2024-05-11T00:50:54.948242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:50:55.282379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 1340
100.0%

점검기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
서울특별시 강서구
1340 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 강서구
2nd row서울특별시 강서구
3rd row서울특별시 강서구
4th row서울특별시 강서구
5th row서울특별시 강서구

Common Values

ValueCountFrequency (%)
서울특별시 강서구 1340
100.0%

Length

2024-05-11T00:50:55.749123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:50:56.202143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 1340
50.0%
강서구 1340
50.0%

지도점검구분
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
정기
1084 
수시
 
94
기타
 
72
합동
 
69
일제
 
21

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기 1084
80.9%
수시 94
 
7.0%
기타 72
 
5.4%
합동 69
 
5.1%
일제 21
 
1.6%

Length

2024-05-11T00:50:56.537794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:50:56.889472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 1084
80.9%
수시 94
 
7.0%
기타 72
 
5.4%
합동 69
 
5.1%
일제 21
 
1.6%

처분대상여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
False
1333 
True
 
7
ValueCountFrequency (%)
False 1333
99.5%
True 7
 
0.5%
2024-05-11T00:50:57.197897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

점검사항
Text

Distinct92
Distinct (%)6.9%
Missing10
Missing (%)0.7%
Memory size10.6 KiB
2024-05-11T00:50:57.708581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length2
Mean length10.029323
Min length2

Characters and Unicode

Total characters13339
Distinct characters87
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)2.4%

Sample

1st row배출시설 및 방지시설 적정관리 여부
2nd row배출시설 및 방지시설 적정관리 여부
3rd row배출시설 및 방지시설 적정관리 여부
4th row배출시설 및 방지시설 적정관리 여부
5th row배출시설 및 방지시설 적정관리 여부
ValueCountFrequency (%)
방지시설 479
13.5%
및 473
13.3%
대기 422
11.9%
여부 339
9.5%
폐수 272
 
7.7%
배출시설 261
 
7.3%
정상가동 176
 
5.0%
폐수배출시설 135
 
3.8%
등 132
 
3.7%
대기배출시설 111
 
3.1%
Other values (77) 753
21.2%
2024-05-11T00:50:59.149304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2223
16.7%
시 1030
 
7.7%
설 1029
 
7.7%
기 579
 
4.3%
부 577
 
4.3%
여 577
 
4.3%
배 572
 
4.3%
출 572
 
4.3%
정 569
 
4.3%
대 537
 
4.0%
Other values (77) 5074
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11108
83.3%
Space Separator 2223
 
16.7%
Other Punctuation 6
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1030
 
9.3%
설 1029
 
9.3%
기 579
 
5.2%
부 577
 
5.2%
여 577
 
5.2%
배 572
 
5.1%
출 572
 
5.1%
정 569
 
5.1%
대 537
 
4.8%
지 503
 
4.5%
Other values (73) 4563
41.1%
Space Separator
ValueCountFrequency (%)
2223
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11108
83.3%
Common 2231
 
16.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1030
 
9.3%
설 1029
 
9.3%
기 579
 
5.2%
부 577
 
5.2%
여 577
 
5.2%
배 572
 
5.1%
출 572
 
5.1%
정 569
 
5.1%
대 537
 
4.8%
지 503
 
4.5%
Other values (73) 4563
41.1%
Common
ValueCountFrequency (%)
2223
99.6%
, 6
 
0.3%
( 1
 
< 0.1%
) 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11108
83.3%
ASCII 2231
 
16.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2223
99.6%
, 6
 
0.3%
( 1
 
< 0.1%
) 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
시 1030
 
9.3%
설 1029
 
9.3%
기 579
 
5.2%
부 577
 
5.2%
여 577
 
5.2%
배 572
 
5.1%
출 572
 
5.1%
정 569
 
5.1%
대 537
 
4.8%
지 503
 
4.5%
Other values (73) 4563
41.1%

점검결과
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

소재지도로명주소
Text

MISSING 

Distinct227
Distinct (%)32.8%
Missing647
Missing (%)48.3%
Memory size10.6 KiB
2024-05-11T00:50:59.853836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length43
Mean length26.542569
Min length21

Characters and Unicode

Total characters18394
Distinct characters106
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

Unique101 ?
Unique (%)14.6%

Sample

1st row서울특별시 강서구 남부순환로 223-19 (외발산동)
2nd row서울특별시 강서구 남부순환로 223-17 (외발산동)
3rd row서울특별시 강서구 남부순환로 223-11 (외발산동)
4th row서울특별시 강서구 남부순환로 223 (외발산동)
5th row서울특별시 강서구 남부순환로 214 (외발산동)
ValueCountFrequency (%)
서울특별시 693
19.9%
강서구 693
19.9%
등촌동 167
 
4.8%
염창동 148
 
4.2%
가양동 114
 
3.3%
양천로 90
 
2.6%
양천로47길 84
 
2.4%
마곡동 63
 
1.8%
외발산동 57
 
1.6%
강서로 48
 
1.4%
Other values (238) 1331
38.2%
2024-05-11T00:51:00.832578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2939
 
16.0%
서 1446
 
7.9%
강 752
 
4.1%
동 706
 
3.8%
시 695
 
3.8%
( 694
 
3.8%
) 694
 
3.8%
울 693
 
3.8%
구 693
 
3.8%
특 693
 
3.8%
Other values (96) 8389
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10661
58.0%
Decimal Number 3073
 
16.7%
Space Separator 2939
 
16.0%
Open Punctuation 694
 
3.8%
Close Punctuation 694
 
3.8%
Dash Punctuation 215
 
1.2%
Other Punctuation 117
 
0.6%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1446
13.6%
강 752
 
7.1%
동 706
 
6.6%
시 695
 
6.5%
울 693
 
6.5%
구 693
 
6.5%
특 693
 
6.5%
별 693
 
6.5%
로 680
 
6.4%
길 437
 
4.1%
Other values (80) 3173
29.8%
Decimal Number
ValueCountFrequency (%)
1 518
16.9%
4 381
12.4%
6 368
12.0%
5 368
12.0%
2 356
11.6%
7 299
9.7%
3 238
7.7%
9 218
7.1%
8 175
 
5.7%
0 152
 
4.9%
Space Separator
ValueCountFrequency (%)
2939
100.0%
Open Punctuation
ValueCountFrequency (%)
( 694
100.0%
Close Punctuation
ValueCountFrequency (%)
) 694
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 215
100.0%
Other Punctuation
ValueCountFrequency (%)
, 117
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10661
58.0%
Common 7732
42.0%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1446
13.6%
강 752
 
7.1%
동 706
 
6.6%
시 695
 
6.5%
울 693
 
6.5%
구 693
 
6.5%
특 693
 
6.5%
별 693
 
6.5%
로 680
 
6.4%
길 437
 
4.1%
Other values (80) 3173
29.8%
Common
ValueCountFrequency (%)
2939
38.0%
( 694
 
9.0%
) 694
 
9.0%
1 518
 
6.7%
4 381
 
4.9%
6 368
 
4.8%
5 368
 
4.8%
2 356
 
4.6%
7 299
 
3.9%
3 238
 
3.1%
Other values (5) 877
 
11.3%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10661
58.0%
ASCII 7733
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2939
38.0%
( 694
 
9.0%
) 694
 
9.0%
1 518
 
6.7%
4 381
 
4.9%
6 368
 
4.8%
5 368
 
4.8%
2 356
 
4.6%
7 299
 
3.9%
3 238
 
3.1%
Other values (6) 878
 
11.4%
Hangul
ValueCountFrequency (%)
서 1446
13.6%
강 752
 
7.1%
동 706
 
6.6%
시 695
 
6.5%
울 693
 
6.5%
구 693
 
6.5%
특 693
 
6.5%
별 693
 
6.5%
로 680
 
6.4%
길 437
 
4.1%
Other values (80) 3173
29.8%

소재지주소
Text

MISSING 

Distinct275
Distinct (%)20.8%
Missing18
Missing (%)1.3%
Memory size10.6 KiB
2024-05-11T00:51:01.773097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length22.829803
Min length14

Characters and Unicode

Total characters30181
Distinct characters92
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

Unique68 ?
Unique (%)5.1%

Sample

1st row서울특별시 강서구 외발산동 230-2번지
2nd row서울특별시 강서구 외발산동 232-2번지
3rd row서울특별시 강서구 외발산동 232번지
4th row서울특별시 강서구 외발산동 233번지
5th row서울특별시 강서구 외발산동 270-2번지
ValueCountFrequency (%)
서울특별시 1322
24.2%
강서구 1322
24.2%
등촌동 367
 
6.7%
염창동 252
 
4.6%
가양동 221
 
4.1%
마곡동 114
 
2.1%
외발산동 113
 
2.1%
방화동 82
 
1.5%
화곡동 77
 
1.4%
20-85번지 44
 
0.8%
Other values (306) 1538
28.2%
2024-05-11T00:51:03.098997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5456
18.1%
서 2644
 
8.8%
지 1343
 
4.4%
동 1330
 
4.4%
구 1326
 
4.4%
시 1325
 
4.4%
특 1322
 
4.4%
별 1322
 
4.4%
강 1322
 
4.4%
울 1322
 
4.4%
Other values (82) 11469
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17571
58.2%
Decimal Number 5835
 
19.3%
Space Separator 5456
 
18.1%
Dash Punctuation 1169
 
3.9%
Other Punctuation 112
 
0.4%
Open Punctuation 12
 
< 0.1%
Close Punctuation 12
 
< 0.1%
Uppercase Letter 11
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 2644
15.0%
지 1343
7.6%
동 1330
7.6%
구 1326
7.5%
시 1325
7.5%
특 1322
7.5%
별 1322
7.5%
강 1322
7.5%
울 1322
7.5%
번 1306
7.4%
Other values (61) 3009
17.1%
Decimal Number
ValueCountFrequency (%)
1 1054
18.1%
2 957
16.4%
6 713
12.2%
3 680
11.7%
4 530
9.1%
5 514
8.8%
9 384
 
6.6%
7 356
 
6.1%
8 332
 
5.7%
0 315
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 5
45.5%
D 4
36.4%
Q 2
 
18.2%
Lowercase Letter
ValueCountFrequency (%)
i 1
33.3%
p 1
33.3%
v 1
33.3%
Space Separator
ValueCountFrequency (%)
5456
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1169
100.0%
Other Punctuation
ValueCountFrequency (%)
, 112
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17571
58.2%
Common 12596
41.7%
Latin 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 2644
15.0%
지 1343
7.6%
동 1330
7.6%
구 1326
7.5%
시 1325
7.5%
특 1322
7.5%
별 1322
7.5%
강 1322
7.5%
울 1322
7.5%
번 1306
7.4%
Other values (61) 3009
17.1%
Common
ValueCountFrequency (%)
5456
43.3%
- 1169
 
9.3%
1 1054
 
8.4%
2 957
 
7.6%
6 713
 
5.7%
3 680
 
5.4%
4 530
 
4.2%
5 514
 
4.1%
9 384
 
3.0%
7 356
 
2.8%
Other values (5) 783
 
6.2%
Latin
ValueCountFrequency (%)
B 5
35.7%
D 4
28.6%
Q 2
 
14.3%
i 1
 
7.1%
p 1
 
7.1%
v 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17571
58.2%
ASCII 12610
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5456
43.3%
- 1169
 
9.3%
1 1054
 
8.4%
2 957
 
7.6%
6 713
 
5.7%
3 680
 
5.4%
4 530
 
4.2%
5 514
 
4.1%
9 384
 
3.0%
7 356
 
2.8%
Other values (11) 797
 
6.3%
Hangul
ValueCountFrequency (%)
서 2644
15.0%
지 1343
7.6%
동 1330
7.6%
구 1326
7.5%
시 1325
7.5%
특 1322
7.5%
별 1322
7.5%
강 1322
7.5%
울 1322
7.5%
번 1306
7.4%
Other values (61) 3009
17.1%

Interactions

2024-05-11T00:50:46.907392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:50:44.911566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:50:46.029532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:50:47.211479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:50:45.336374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:50:46.349726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:50:47.566049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:50:45.729669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:50:46.608995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T00:51:03.515951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업종코드업종명지도점검일자지도점검구분처분대상여부점검사항
인허가번호1.0001.0001.0000.1450.1290.0001.000
업종코드1.0001.0001.0000.1440.1290.0001.000
업종명1.0001.0001.0000.5970.3360.0000.998
지도점검일자0.1450.1440.5971.0000.6290.0970.934
지도점검구분0.1290.1290.3360.6291.0000.0000.940
처분대상여부0.0000.0000.0000.0970.0001.0000.407
점검사항1.0001.0000.9980.9340.9400.4071.000
2024-05-11T00:51:04.072958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분대상여부지도점검구분업종명
처분대상여부1.0000.0000.000
지도점검구분0.0001.0000.213
업종명0.0000.2131.000
2024-05-11T00:51:04.474844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업종코드지도점검일자업종명지도점검구분처분대상여부
인허가번호1.0000.875-0.2830.9980.0970.000
업종코드0.8751.000-0.4140.9980.0970.000
지도점검일자-0.283-0.4141.0000.2350.4480.072
업종명0.9980.9980.2351.0000.2130.000
지도점검구분0.0970.0970.4480.2131.0000.000
처분대상여부0.0000.0000.0720.0000.0001.000

Missing values

2024-05-11T00:50:48.050846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T00:50:48.648236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-11T00:50:49.007937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업체(시설)명인허가번호업종코드업종명지도점검일자점검기관점검기관명지도점검구분처분대상여부점검사항점검결과소재지도로명주소소재지주소
0한국지엠강서서비스(주)31500002120070017521대기배출업소관리201706153150000서울특별시 강서구합동N배출시설 및 방지시설 적정관리 여부<NA>서울특별시 강서구 남부순환로 223-19 (외발산동)서울특별시 강서구 외발산동 230-2번지
1창조모터스31500002120150001121대기배출업소관리201706153150000서울특별시 강서구합동N배출시설 및 방지시설 적정관리 여부<NA>서울특별시 강서구 남부순환로 223-17 (외발산동)서울특별시 강서구 외발산동 232-2번지
2현대미라클모터스31500002120080017521대기배출업소관리201706153150000서울특별시 강서구합동N배출시설 및 방지시설 적정관리 여부<NA>서울특별시 강서구 남부순환로 223-11 (외발산동)서울특별시 강서구 외발산동 232번지
3강서현대서비스31500002120150000821대기배출업소관리201706153150000서울특별시 강서구합동N배출시설 및 방지시설 적정관리 여부<NA>서울특별시 강서구 남부순환로 223 (외발산동)서울특별시 강서구 외발산동 233번지
4한성모터스31500002120150000421대기배출업소관리201706153150000서울특별시 강서구합동N배출시설 및 방지시설 적정관리 여부<NA>서울특별시 강서구 남부순환로 214 (외발산동)서울특별시 강서구 외발산동 270-2번지
5(주)세운모터스31500002120110000621대기배출업소관리201706153150000서울특별시 강서구합동N배출시설 및 방지시설 적정관리 여부<NA>서울특별시 강서구 남부순환로 224-48 (외발산동)서울특별시 강서구 외발산동 274-4번지
6서부현대서비스31500002120110000421대기배출업소관리201706153150000서울특별시 강서구합동N배출시설 및 방지시설 적정관리 여부<NA>서울특별시 강서구 남부순환로 224-40 (외발산동)서울특별시 강서구 외발산동 273번지
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