Overview

Dataset statistics

Number of variables13
Number of observations508
Missing cells836
Missing cells (%)12.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory54.2 KiB
Average record size in memory109.3 B

Variable types

Text4
Numeric3
Categorical4
Boolean1
Unsupported1

Dataset

Description업체(시설)명,인허가번호,업종코드,업종명,지도점검일자,점검기관,점검기관명,지도점검구분,처분대상여부,점검사항,점검결과,소재지도로명주소,소재지주소
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-10278/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
지도점검구분 is highly imbalanced (84.7%)Imbalance
처분대상여부 is highly imbalanced (84.8%)Imbalance
처분대상여부 has 51 (10.0%) missing valuesMissing
점검결과 has 508 (100.0%) missing valuesMissing
소재지도로명주소 has 274 (53.9%) missing valuesMissing
점검결과 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 06:18:28.421637
Analysis finished2024-05-11 06:18:31.944133
Duration3.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체(시설)명
Text

Distinct165
Distinct (%)32.5%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-05-11T15:18:32.291960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length7.9724409
Min length3

Characters and Unicode

Total characters4050
Distinct characters209
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

Unique52 ?
Unique (%)10.2%

Sample

1st row(주)한국교통
2nd row대성세차장
3rd row성주교통
4th row중앙교통(주)
5th row경서운수(주)
ValueCountFrequency (%)
대일차사랑자동차(주 16
 
2.9%
주식회사 16
 
2.9%
경서운수(주 12
 
2.2%
덕수콜택시(주 12
 
2.2%
북부운수(주 11
 
2.0%
국제콜택시(주 9
 
1.6%
연산교통(주 9
 
1.6%
주)중랑현대공업사 8
 
1.4%
남양상운(주 8
 
1.4%
대광운수(주 8
 
1.4%
Other values (166) 443
80.3%
2024-05-11T15:18:32.886965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 329
 
8.1%
) 228
 
5.6%
( 228
 
5.6%
차 177
 
4.4%
사 100
 
2.5%
동 99
 
2.4%
소 87
 
2.1%
대 86
 
2.1%
장 85
 
2.1%
세 77
 
1.9%
Other values (199) 2554
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3480
85.9%
Close Punctuation 228
 
5.6%
Open Punctuation 228
 
5.6%
Uppercase Letter 47
 
1.2%
Space Separator 44
 
1.1%
Lowercase Letter 12
 
0.3%
Decimal Number 9
 
0.2%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 329
 
9.5%
차 177
 
5.1%
사 100
 
2.9%
동 99
 
2.8%
소 87
 
2.5%
대 86
 
2.5%
장 85
 
2.4%
세 77
 
2.2%
자 75
 
2.2%
유 73
 
2.1%
Other values (177) 2292
65.9%
Uppercase Letter
ValueCountFrequency (%)
S 14
29.8%
K 9
19.1%
D 7
14.9%
E 7
14.9%
O 3
 
6.4%
T 2
 
4.3%
A 2
 
4.3%
V 2
 
4.3%
G 1
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
r 2
16.7%
s 2
16.7%
e 2
16.7%
t 2
16.7%
m 2
16.7%
o 2
16.7%
Decimal Number
ValueCountFrequency (%)
4 3
33.3%
2 3
33.3%
3 3
33.3%
Close Punctuation
ValueCountFrequency (%)
) 228
100.0%
Open Punctuation
ValueCountFrequency (%)
( 228
100.0%
Space Separator
ValueCountFrequency (%)
44
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3480
85.9%
Common 511
 
12.6%
Latin 59
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 329
 
9.5%
차 177
 
5.1%
사 100
 
2.9%
동 99
 
2.8%
소 87
 
2.5%
대 86
 
2.5%
장 85
 
2.4%
세 77
 
2.2%
자 75
 
2.2%
유 73
 
2.1%
Other values (177) 2292
65.9%
Latin
ValueCountFrequency (%)
S 14
23.7%
K 9
15.3%
D 7
11.9%
E 7
11.9%
O 3
 
5.1%
r 2
 
3.4%
s 2
 
3.4%
e 2
 
3.4%
T 2
 
3.4%
t 2
 
3.4%
Other values (5) 9
15.3%
Common
ValueCountFrequency (%)
) 228
44.6%
( 228
44.6%
44
 
8.6%
4 3
 
0.6%
2 3
 
0.6%
3 3
 
0.6%
& 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3480
85.9%
ASCII 570
 
14.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 329
 
9.5%
차 177
 
5.1%
사 100
 
2.9%
동 99
 
2.8%
소 87
 
2.5%
대 86
 
2.5%
장 85
 
2.4%
세 77
 
2.2%
자 75
 
2.2%
유 73
 
2.1%
Other values (177) 2292
65.9%
ASCII
ValueCountFrequency (%)
) 228
40.0%
( 228
40.0%
44
 
7.7%
S 14
 
2.5%
K 9
 
1.6%
D 7
 
1.2%
E 7
 
1.2%
4 3
 
0.5%
2 3
 
0.5%
3 3
 
0.5%
Other values (12) 24
 
4.2%

인허가번호
Real number (ℝ)

HIGH CORRELATION 

Distinct165
Distinct (%)32.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0600002 × 1017
Minimum3.0600002 × 1017
Maximum3.0600006 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-05-11T15:18:33.188336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0600002 × 1017
5-th percentile3.0600002 × 1017
Q13.0600002 × 1017
median3.0600002 × 1017
Q33.0600002 × 1017
95-th percentile3.0600003 × 1017
Maximum3.0600006 × 1017
Range4.10019 × 1010
Interquartile range (IQR)9.9889997 × 108

Descriptive statistics

Standard deviation3.3658289 × 109
Coefficient of variation (CV)1.099944 × 10-8
Kurtosis52.021254
Mean3.0600002 × 1017
Median Absolute Deviation (MAD)1099968
Skewness6.4250374
Sum7.8740589 × 1018
Variance1.1328804 × 1019
MonotonicityNot monotonic
2024-05-11T15:18:33.440163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
306000021199800001 16
 
3.1%
306000021199800006 12
 
2.4%
306000022200600002 9
 
1.8%
306000021200200001 9
 
1.8%
306000022199100005 8
 
1.6%
306000021199800004 8
 
1.6%
306000021200400005 8
 
1.6%
306000022198100001 7
 
1.4%
306000022199500008 7
 
1.4%
306000022199200002 7
 
1.4%
Other values (155) 417
82.1%
ValueCountFrequency (%)
306000021199800001 16
3.1%
306000021199800002 4
 
0.8%
306000021199800003 3
 
0.6%
306000021199800004 8
1.6%
306000021199800006 12
2.4%
306000021199900012 4
 
0.8%
306000021199900013 3
 
0.6%
306000021200200001 9
1.8%
306000021200200004 4
 
0.8%
306000021200200005 4
 
0.8%
ValueCountFrequency (%)
306000062201700001 1
0.2%
306000042201100003 1
0.2%
306000042201100002 1
0.2%
306000042201100001 1
0.2%
306000042201000002 1
0.2%
306000042200800001 1
0.2%
306000042199800002 1
0.2%
306000035200700002 1
0.2%
306000035200500004 1
0.2%
306000035200500003 1
0.2%

업종코드
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.305118
Minimum21
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-05-11T15:18:33.662123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile21
Q121
median22
Q322
95-th percentile25
Maximum42
Range21
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.8609135
Coefficient of variation (CV)0.12826265
Kurtosis29.738114
Mean22.305118
Median Absolute Deviation (MAD)0
Skewness5.2922619
Sum11331
Variance8.1848258
MonotonicityNot monotonic
2024-05-11T15:18:33.835980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
22 345
67.9%
21 134
 
26.4%
25 9
 
1.8%
31 7
 
1.4%
42 6
 
1.2%
35 6
 
1.2%
23 1
 
0.2%
ValueCountFrequency (%)
21 134
 
26.4%
22 345
67.9%
23 1
 
0.2%
25 9
 
1.8%
31 7
 
1.4%
35 6
 
1.2%
42 6
 
1.2%
ValueCountFrequency (%)
42 6
 
1.2%
35 6
 
1.2%
31 7
 
1.4%
25 9
 
1.8%
23 1
 
0.2%
22 345
67.9%
21 134
 
26.4%

업종명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
폐수배출업소관리
304 
대기배출업소관리
127 
<NA>
50 
기타수질오염원관리
 
7
폐기물배출자(1호)
 
7
Other values (3)
 
13

Length

Max length10
Median length8
Mean length7.6437008
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
폐수배출업소관리 304
59.8%
대기배출업소관리 127
25.0%
<NA> 50
 
9.8%
기타수질오염원관리 7
 
1.4%
폐기물배출자(1호) 7
 
1.4%
유독물판매업관리 6
 
1.2%
폐기물처리업관리 6
 
1.2%
소음진동관리 1
 
0.2%

Length

2024-05-11T15:18:34.020556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:34.312344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐수배출업소관리 304
59.8%
대기배출업소관리 127
25.0%
na 50
 
9.8%
기타수질오염원관리 7
 
1.4%
폐기물배출자(1호 7
 
1.4%
유독물판매업관리 6
 
1.2%
폐기물처리업관리 6
 
1.2%
소음진동관리 1
 
0.2%

지도점검일자
Real number (ℝ)

Distinct164
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20131296
Minimum20100111
Maximum20170629
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-05-11T15:18:34.615020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100111
5-th percentile20101115
Q120111202
median20130614
Q320150824
95-th percentile20170411
Maximum20170629
Range70518
Interquartile range (IQR)39622.25

Descriptive statistics

Standard deviation21827.513
Coefficient of variation (CV)0.0010842577
Kurtosis-1.1691905
Mean20131296
Median Absolute Deviation (MAD)19688
Skewness0.17438841
Sum1.0226699 × 1010
Variance4.7644032 × 108
MonotonicityDecreasing
2024-05-11T15:18:34.891721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121025 14
 
2.8%
20110930 9
 
1.8%
20101230 9
 
1.8%
20121026 9
 
1.8%
20110926 8
 
1.6%
20101122 8
 
1.6%
20120928 8
 
1.6%
20121030 7
 
1.4%
20101229 7
 
1.4%
20101228 7
 
1.4%
Other values (154) 422
83.1%
ValueCountFrequency (%)
20100111 2
 
0.4%
20100113 1
 
0.2%
20100213 1
 
0.2%
20100430 2
 
0.4%
20100830 2
 
0.4%
20100927 4
0.8%
20100928 4
0.8%
20100930 6
1.2%
20101004 1
 
0.2%
20101115 3
0.6%
ValueCountFrequency (%)
20170629 4
0.8%
20170622 6
1.2%
20170621 4
0.8%
20170615 4
0.8%
20170613 4
0.8%
20170413 3
0.6%
20170411 3
0.6%
20170328 3
0.6%
20161125 1
 
0.2%
20161104 1
 
0.2%

점검기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
3060000
508 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3060000
2nd row3060000
3rd row3060000
4th row3060000
5th row3060000

Common Values

ValueCountFrequency (%)
3060000 508
100.0%

Length

2024-05-11T15:18:35.129551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:35.310227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 508
100.0%

점검기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
서울특별시 중랑구
508 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 중랑구 508
100.0%

Length

2024-05-11T15:18:35.456738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:35.644502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 508
50.0%
중랑구 508
50.0%

지도점검구분
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
정기
478 
수시
 
23
<NA>
 
3
기타
 
2
일제
 
1

Length

Max length4
Median length2
Mean length2.011811
Min length2

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
정기 478
94.1%
수시 23
 
4.5%
<NA> 3
 
0.6%
기타 2
 
0.4%
일제 1
 
0.2%
합동 1
 
0.2%

Length

2024-05-11T15:18:35.873669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:36.090917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 478
94.1%
수시 23
 
4.5%
na 3
 
0.6%
기타 2
 
0.4%
일제 1
 
0.2%
합동 1
 
0.2%

처분대상여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.4%
Missing51
Missing (%)10.0%
Memory size1.1 KiB
False
447 
True
 
10
(Missing)
51 
ValueCountFrequency (%)
False 447
88.0%
True 10
 
2.0%
(Missing) 51
 
10.0%
2024-05-11T15:18:36.230698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

점검사항
Text

Distinct75
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-05-11T15:18:36.542193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length51
Mean length29.718504
Min length6

Characters and Unicode

Total characters15097
Distinct characters94
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)6.7%

Sample

1st row배출시설 점검
2nd row배출시설 점검
3rd row배출시설 점검
4th row배출시설 점검
5th row배출시설 점검
ValueCountFrequency (%)
여부 321
 
9.0%
사항 269
 
7.5%
배출시설 262
 
7.4%
및 235
 
6.6%
폐수배출시설 207
 
5.8%
등 198
 
5.6%
방지시설 197
 
5.5%
운영 123
 
3.5%
기록 121
 
3.4%
운영일지 114
 
3.2%
Other values (93) 1516
42.5%
2024-05-11T15:18:37.297101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3069
20.3%
설 917
 
6.1%
시 811
 
5.4%
부 587
 
3.9%
출 575
 
3.8%
배 569
 
3.8%
여 541
 
3.6%
, 473
 
3.1%
운 467
 
3.1%
영 467
 
3.1%
Other values (84) 6621
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11489
76.1%
Space Separator 3069
 
20.3%
Other Punctuation 473
 
3.1%
Close Punctuation 31
 
0.2%
Open Punctuation 31
 
0.2%
Decimal Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 917
 
8.0%
시 811
 
7.1%
부 587
 
5.1%
출 575
 
5.0%
배 569
 
5.0%
여 541
 
4.7%
운 467
 
4.1%
영 467
 
4.1%
지 418
 
3.6%
사 372
 
3.2%
Other values (77) 5765
50.2%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
0 1
25.0%
1 1
25.0%
Space Separator
ValueCountFrequency (%)
3069
100.0%
Other Punctuation
ValueCountFrequency (%)
, 473
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11489
76.1%
Common 3608
 
23.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 917
 
8.0%
시 811
 
7.1%
부 587
 
5.1%
출 575
 
5.0%
배 569
 
5.0%
여 541
 
4.7%
운 467
 
4.1%
영 467
 
4.1%
지 418
 
3.6%
사 372
 
3.2%
Other values (77) 5765
50.2%
Common
ValueCountFrequency (%)
3069
85.1%
, 473
 
13.1%
) 31
 
0.9%
( 31
 
0.9%
2 2
 
0.1%
0 1
 
< 0.1%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11489
76.1%
ASCII 3608
 
23.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3069
85.1%
, 473
 
13.1%
) 31
 
0.9%
( 31
 
0.9%
2 2
 
0.1%
0 1
 
< 0.1%
1 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
설 917
 
8.0%
시 811
 
7.1%
부 587
 
5.1%
출 575
 
5.0%
배 569
 
5.0%
여 541
 
4.7%
운 467
 
4.1%
영 467
 
4.1%
지 418
 
3.6%
사 372
 
3.2%
Other values (77) 5765
50.2%

점검결과
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing508
Missing (%)100.0%
Memory size4.6 KiB

소재지도로명주소
Text

MISSING 

Distinct124
Distinct (%)53.0%
Missing274
Missing (%)53.9%
Memory size4.1 KiB
2024-05-11T15:18:37.732082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length33
Mean length24.252137
Min length21

Characters and Unicode

Total characters5675
Distinct characters80
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)26.9%

Sample

1st row서울특별시 중랑구 신내로14길 70 (신내동)
2nd row서울특별시 중랑구 봉화산로 99 (중화동)
3rd row서울특별시 중랑구 용마산로117길 29 (망우동)
4th row서울특별시 중랑구 망우로 429 (망우동)
5th row서울특별시 중랑구 겸재로 261 (망우동)
ValueCountFrequency (%)
서울특별시 234
19.9%
중랑구 234
19.9%
망우로 55
 
4.7%
면목동 54
 
4.6%
중화동 51
 
4.3%
망우동 42
 
3.6%
상봉동 37
 
3.1%
신내동 31
 
2.6%
중랑천로 25
 
2.1%
용마산로 22
 
1.9%
Other values (141) 392
33.3%
2024-05-11T15:18:38.416425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1006
17.7%
중 323
 
5.7%
랑 267
 
4.7%
동 265
 
4.7%
서 236
 
4.2%
구 235
 
4.1%
울 235
 
4.1%
시 234
 
4.1%
( 234
 
4.1%
별 234
 
4.1%
Other values (70) 2406
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3464
61.0%
Space Separator 1006
 
17.7%
Decimal Number 723
 
12.7%
Open Punctuation 234
 
4.1%
Close Punctuation 234
 
4.1%
Other Punctuation 11
 
0.2%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 323
 
9.3%
랑 267
 
7.7%
동 265
 
7.7%
서 236
 
6.8%
구 235
 
6.8%
울 235
 
6.8%
시 234
 
6.8%
별 234
 
6.8%
특 234
 
6.8%
로 234
 
6.8%
Other values (55) 967
27.9%
Decimal Number
ValueCountFrequency (%)
1 136
18.8%
2 81
11.2%
7 79
10.9%
9 77
10.7%
3 73
10.1%
4 72
10.0%
5 70
9.7%
6 52
 
7.2%
0 51
 
7.1%
8 32
 
4.4%
Space Separator
ValueCountFrequency (%)
1006
100.0%
Open Punctuation
ValueCountFrequency (%)
( 234
100.0%
Close Punctuation
ValueCountFrequency (%)
) 234
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3464
61.0%
Common 2211
39.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 323
 
9.3%
랑 267
 
7.7%
동 265
 
7.7%
서 236
 
6.8%
구 235
 
6.8%
울 235
 
6.8%
시 234
 
6.8%
별 234
 
6.8%
특 234
 
6.8%
로 234
 
6.8%
Other values (55) 967
27.9%
Common
ValueCountFrequency (%)
1006
45.5%
( 234
 
10.6%
) 234
 
10.6%
1 136
 
6.2%
2 81
 
3.7%
7 79
 
3.6%
9 77
 
3.5%
3 73
 
3.3%
4 72
 
3.3%
5 70
 
3.2%
Other values (5) 149
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3464
61.0%
ASCII 2211
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1006
45.5%
( 234
 
10.6%
) 234
 
10.6%
1 136
 
6.2%
2 81
 
3.7%
7 79
 
3.6%
9 77
 
3.5%
3 73
 
3.3%
4 72
 
3.3%
5 70
 
3.2%
Other values (5) 149
 
6.7%
Hangul
ValueCountFrequency (%)
중 323
 
9.3%
랑 267
 
7.7%
동 265
 
7.7%
서 236
 
6.8%
구 235
 
6.8%
울 235
 
6.8%
시 234
 
6.8%
별 234
 
6.8%
특 234
 
6.8%
로 234
 
6.8%
Other values (55) 967
27.9%

소재지주소
Text

Distinct146
Distinct (%)28.9%
Missing3
Missing (%)0.6%
Memory size4.1 KiB
2024-05-11T15:18:38.830511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length22.261386
Min length19

Characters and Unicode

Total characters11242
Distinct characters50
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)8.1%

Sample

1st row서울특별시 중랑구 신내동 448-2번지
2nd row서울특별시 중랑구 중화동 11-107번지
3rd row서울특별시 중랑구 망우동 487-6번지
4th row서울특별시 중랑구 망우동 487-1번지
5th row서울특별시 중랑구 망우동 526-2번지
ValueCountFrequency (%)
서울특별시 505
24.6%
중랑구 505
24.6%
면목동 140
 
6.8%
상봉동 98
 
4.8%
중화동 89
 
4.3%
망우동 78
 
3.8%
신내동 69
 
3.4%
묵동 31
 
1.5%
209-2번지 16
 
0.8%
210번지 14
 
0.7%
Other values (153) 512
24.9%
2024-05-11T15:18:39.604853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2064
18.4%
중 596
 
5.3%
지 524
 
4.7%
서 505
 
4.5%
구 505
 
4.5%
번 505
 
4.5%
동 505
 
4.5%
울 505
 
4.5%
랑 505
 
4.5%
시 505
 
4.5%
Other values (40) 4523
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6613
58.8%
Decimal Number 2129
 
18.9%
Space Separator 2064
 
18.4%
Dash Punctuation 430
 
3.8%
Other Punctuation 5
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 596
9.0%
지 524
 
7.9%
서 505
 
7.6%
구 505
 
7.6%
번 505
 
7.6%
동 505
 
7.6%
울 505
 
7.6%
랑 505
 
7.6%
시 505
 
7.6%
별 505
 
7.6%
Other values (26) 1453
22.0%
Decimal Number
ValueCountFrequency (%)
1 430
20.2%
2 342
16.1%
4 209
9.8%
3 191
9.0%
0 180
8.5%
9 174
8.2%
8 165
 
7.8%
5 164
 
7.7%
6 140
 
6.6%
7 134
 
6.3%
Space Separator
ValueCountFrequency (%)
2064
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 430
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6613
58.8%
Common 4628
41.2%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 596
9.0%
지 524
 
7.9%
서 505
 
7.6%
구 505
 
7.6%
번 505
 
7.6%
동 505
 
7.6%
울 505
 
7.6%
랑 505
 
7.6%
시 505
 
7.6%
별 505
 
7.6%
Other values (26) 1453
22.0%
Common
ValueCountFrequency (%)
2064
44.6%
- 430
 
9.3%
1 430
 
9.3%
2 342
 
7.4%
4 209
 
4.5%
3 191
 
4.1%
0 180
 
3.9%
9 174
 
3.8%
8 165
 
3.6%
5 164
 
3.5%
Other values (3) 279
 
6.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6613
58.8%
ASCII 4629
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2064
44.6%
- 430
 
9.3%
1 430
 
9.3%
2 342
 
7.4%
4 209
 
4.5%
3 191
 
4.1%
0 180
 
3.9%
9 174
 
3.8%
8 165
 
3.6%
5 164
 
3.5%
Other values (4) 280
 
6.0%
Hangul
ValueCountFrequency (%)
중 596
9.0%
지 524
 
7.9%
서 505
 
7.6%
구 505
 
7.6%
번 505
 
7.6%
동 505
 
7.6%
울 505
 
7.6%
랑 505
 
7.6%
시 505
 
7.6%
별 505
 
7.6%
Other values (26) 1453
22.0%

Interactions

2024-05-11T15:18:30.595433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:29.398335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:30.025339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:30.775851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:29.544808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:30.197122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:30.960937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:29.775015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:30.376822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:18:39.740736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업종코드업종명지도점검일자지도점검구분처분대상여부점검사항
인허가번호1.0000.9120.8860.2880.5250.0000.994
업종코드0.9121.0001.0000.3330.5570.0431.000
업종명0.8861.0001.0000.4180.3760.0641.000
지도점검일자0.2880.3330.4181.0000.0680.2780.922
지도점검구분0.5250.5570.3760.0681.0000.2640.950
처분대상여부0.0000.0430.0640.2780.2641.0000.402
점검사항0.9941.0001.0000.9220.9500.4021.000
2024-05-11T15:18:39.931931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분대상여부업종명지도점검구분
처분대상여부1.0000.0680.321
업종명0.0681.0000.251
지도점검구분0.3210.2511.000
2024-05-11T15:18:40.449512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업종코드지도점검일자업종명지도점검구분처분대상여부
인허가번호1.0000.817-0.0630.7710.2540.000
업종코드0.8171.000-0.2010.9980.2360.052
지도점검일자-0.063-0.2011.0000.2380.0420.208
업종명0.7710.9980.2381.0000.2510.068
지도점검구분0.2540.2360.0420.2511.0000.321
처분대상여부0.0000.0520.2080.0680.3211.000

Missing values

2024-05-11T15:18:31.268759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:18:31.578610image/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.
2024-05-11T15:18:31.804006image/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
0(주)한국교통30600002219980003122폐수배출업소관리201706293060000서울특별시 중랑구정기N배출시설 점검<NA>서울특별시 중랑구 신내로14길 70 (신내동)서울특별시 중랑구 신내동 448-2번지
1대성세차장30600002220030001622폐수배출업소관리201706293060000서울특별시 중랑구정기N배출시설 점검<NA>서울특별시 중랑구 봉화산로 99 (중화동)서울특별시 중랑구 중화동 11-107번지
2성주교통30600002220030002122폐수배출업소관리201706293060000서울특별시 중랑구정기N배출시설 점검<NA>서울특별시 중랑구 용마산로117길 29 (망우동)서울특별시 중랑구 망우동 487-6번지
3중앙교통(주)30600002219950000822폐수배출업소관리201706293060000서울특별시 중랑구정기N배출시설 점검<NA>서울특별시 중랑구 망우로 429 (망우동)서울특별시 중랑구 망우동 487-1번지
4경서운수(주)30600002219950000722폐수배출업소관리201706223060000서울특별시 중랑구정기N배출시설 점검<NA>서울특별시 중랑구 겸재로 261 (망우동)서울특별시 중랑구 망우동 526-2번지
5(주)대성택시30600002220080000122폐수배출업소관리201706223060000서울특별시 중랑구정기N배출시설 점검<NA>서울특별시 중랑구 겸재로 114 (면목동)서울특별시 중랑구 면목동 151-1번지
6연산교통(주)30600002219950000622폐수배출업소관리201706223060000서울특별시 중랑구정기N배출시설 점검<NA>서울특별시 중랑구 겸재로 140 (면목동)서울특별시 중랑구 면목동 149-7번지
7부광통상(주)30600002120070000521<NA>201706223060000서울특별시 중랑구정기<NA>대기배출시설 및 방지시설 정기 점검<NA>서울특별시 중랑구 동일로120길 127 (상봉동)서울특별시 중랑구 상봉동 190-102번지
8정오교통(주)30600002219950002222폐수배출업소관리201706223060000서울특별시 중랑구정기N배출시설 점검<NA>서울특별시 중랑구 망우로 259 (상봉동)서울특별시 중랑구 상봉동 116-27번지
9평화교통(주)30600002219960000322폐수배출업소관리201706223060000서울특별시 중랑구정기N배출시설 점검<NA>서울특별시 중랑구 겸재로 69 (면목동)서울특별시 중랑구 면목동 193-64번지
업체(시설)명인허가번호업종코드업종명지도점검일자점검기관점검기관명지도점검구분처분대상여부점검사항점검결과소재지도로명주소소재지주소
498한인주유소세차장30600002219940001522폐수배출업소관리201009273060000서울특별시 중랑구정기N폐수배출시설 적정운영 여부<NA><NA>서울특별시 중랑구 상봉동 137-8번지
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