Overview

Dataset statistics

Number of variables13
Number of observations1359
Missing cells2545
Missing cells (%)14.4%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory144.8 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
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-11433/S/1/datasetView.do

Alerts

점검기관 has constant value ""Constant
점검기관명 has constant value ""Constant
Dataset has 1 (0.1%) duplicate rowsDuplicates
인허가번호 is highly overall correlated with 업종코드High correlation
업종코드 is highly overall correlated with 인허가번호 and 1 other fieldsHigh correlation
업종명 is highly overall correlated with 업종코드High correlation
처분대상여부 is highly imbalanced (92.6%)Imbalance
처분대상여부 has 252 (18.5%) missing valuesMissing
점검결과 has 1359 (100.0%) missing valuesMissing
소재지도로명주소 has 838 (61.7%) missing valuesMissing
소재지주소 has 85 (6.3%) missing valuesMissing
점검결과 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 01:00:57.814065
Analysis finished2024-05-11 01:01:04.386238
Duration6.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체(시설)명
Text

Distinct420
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
2024-05-11T01:01:04.784083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length7.7012509
Min length2

Characters and Unicode

Total characters10466
Distinct characters348
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

Unique144 ?
Unique (%)10.6%

Sample

1st row(주)건양자동차
2nd row(주)우주카독크
3rd row(주)리클린
4th row국립경찰병원
5th row대영운수(주)
ValueCountFrequency (%)
삼광교통(주 18
 
1.2%
승일운수(주 16
 
1.1%
주)잠실에너지 14
 
0.9%
승리상운(주 13
 
0.9%
주)신일씨엠 13
 
0.9%
한국쓰리알환경산업(주 13
 
0.9%
흥덕기업(주 12
 
0.8%
한석교통(주 12
 
0.8%
대산카독크 12
 
0.8%
국립경찰병원 11
 
0.7%
Other values (439) 1346
90.9%
2024-05-11T01:01:06.081102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 656
 
6.3%
) 554
 
5.3%
( 550
 
5.3%
스 294
 
2.8%
차 272
 
2.6%
동 242
 
2.3%
사 229
 
2.2%
업 206
 
2.0%
공 203
 
1.9%
자 199
 
1.9%
Other values (338) 7061
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9089
86.8%
Close Punctuation 554
 
5.3%
Open Punctuation 550
 
5.3%
Space Separator 125
 
1.2%
Uppercase Letter 96
 
0.9%
Decimal Number 33
 
0.3%
Dash Punctuation 13
 
0.1%
Other Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 656
 
7.2%
스 294
 
3.2%
차 272
 
3.0%
동 242
 
2.7%
사 229
 
2.5%
업 206
 
2.3%
공 203
 
2.2%
자 199
 
2.2%
카 188
 
2.1%
유 151
 
1.7%
Other values (312) 6449
71.0%
Uppercase Letter
ValueCountFrequency (%)
S 21
21.9%
K 17
17.7%
T 13
13.5%
M 8
 
8.3%
I 7
 
7.3%
D 6
 
6.2%
C 5
 
5.2%
O 4
 
4.2%
A 3
 
3.1%
H 3
 
3.1%
Other values (5) 9
9.4%
Decimal Number
ValueCountFrequency (%)
2 18
54.5%
4 7
 
21.2%
5 3
 
9.1%
9 3
 
9.1%
3 2
 
6.1%
Other Punctuation
ValueCountFrequency (%)
/ 3
50.0%
. 3
50.0%
Close Punctuation
ValueCountFrequency (%)
) 554
100.0%
Open Punctuation
ValueCountFrequency (%)
( 550
100.0%
Space Separator
ValueCountFrequency (%)
125
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9089
86.8%
Common 1281
 
12.2%
Latin 96
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 656
 
7.2%
스 294
 
3.2%
차 272
 
3.0%
동 242
 
2.7%
사 229
 
2.5%
업 206
 
2.3%
공 203
 
2.2%
자 199
 
2.2%
카 188
 
2.1%
유 151
 
1.7%
Other values (312) 6449
71.0%
Latin
ValueCountFrequency (%)
S 21
21.9%
K 17
17.7%
T 13
13.5%
M 8
 
8.3%
I 7
 
7.3%
D 6
 
6.2%
C 5
 
5.2%
O 4
 
4.2%
A 3
 
3.1%
H 3
 
3.1%
Other values (5) 9
9.4%
Common
ValueCountFrequency (%)
) 554
43.2%
( 550
42.9%
125
 
9.8%
2 18
 
1.4%
- 13
 
1.0%
4 7
 
0.5%
/ 3
 
0.2%
5 3
 
0.2%
. 3
 
0.2%
9 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9089
86.8%
ASCII 1377
 
13.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 656
 
7.2%
스 294
 
3.2%
차 272
 
3.0%
동 242
 
2.7%
사 229
 
2.5%
업 206
 
2.3%
공 203
 
2.2%
자 199
 
2.2%
카 188
 
2.1%
유 151
 
1.7%
Other values (312) 6449
71.0%
ASCII
ValueCountFrequency (%)
) 554
40.2%
( 550
39.9%
125
 
9.1%
S 21
 
1.5%
2 18
 
1.3%
K 17
 
1.2%
- 13
 
0.9%
T 13
 
0.9%
M 8
 
0.6%
4 7
 
0.5%
Other values (16) 51
 
3.7%

인허가번호
Real number (ℝ)

HIGH CORRELATION 

Distinct418
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2300002 × 1017
Minimum3.2300002 × 1017
Maximum3.2300006 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.1 KiB
2024-05-11T01:01:06.746267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2300002 × 1017
5-th percentile3.2300002 × 1017
Q13.2300002 × 1017
median3.2300002 × 1017
Q33.2300002 × 1017
95-th percentile3.2300003 × 1017
Maximum3.2300006 × 1017
Range4.10007 × 1010
Interquartile range (IQR)9.999008 × 108

Descriptive statistics

Standard deviation2.2281151 × 109
Coefficient of variation (CV)6.8981887 × 10-9
Kurtosis161.65966
Mean3.2300002 × 1017
Median Absolute Deviation (MAD)1499840
Skewness10.665666
Sum-3.7648276 × 1018
Variance4.9644969 × 1018
MonotonicityNot monotonic
2024-05-11T01:01:07.232021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
323000022198700021 14
 
1.0%
323000022199300077 14
 
1.0%
323000022200700767 14
 
1.0%
323000022199800269 12
 
0.9%
323000022199300071 12
 
0.9%
323000022199400116 11
 
0.8%
323000022198900003 11
 
0.8%
323000022199900499 11
 
0.8%
323000022201000005 10
 
0.7%
323000021200900002 10
 
0.7%
Other values (408) 1240
91.2%
ValueCountFrequency (%)
323000021200300011 7
0.5%
323000021200400007 6
0.4%
323000021200400008 5
0.4%
323000021200400010 8
0.6%
323000021200400015 5
0.4%
323000021200400016 6
0.4%
323000021200400018 6
0.4%
323000021200400020 6
0.4%
323000021200400031 4
0.3%
323000021200400032 6
0.4%
ValueCountFrequency (%)
323000062201000001 1
0.1%
323000062200800006 1
0.1%
323000034201100086 1
0.1%
323000034201100081 1
0.1%
323000034201100058 1
0.1%
323000034201100047 1
0.1%
323000034201100036 1
0.1%
323000034201100018 1
0.1%
323000034201100017 1
0.1%
323000034201100015 1
0.1%

업종코드
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.961737
Minimum21
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.1 KiB
2024-05-11T01:01:07.704859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile21
Q121
median22
Q322
95-th percentile25
Maximum34
Range13
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.6131844
Coefficient of variation (CV)0.07345432
Kurtosis38.710793
Mean21.961737
Median Absolute Deviation (MAD)0
Skewness5.7452885
Sum29846
Variance2.602364
MonotonicityNot monotonic
2024-05-11T01:01:08.194642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
22 852
62.7%
21 432
31.8%
25 50
 
3.7%
34 17
 
1.3%
23 6
 
0.4%
32 2
 
0.1%
ValueCountFrequency (%)
21 432
31.8%
22 852
62.7%
23 6
 
0.4%
25 50
 
3.7%
32 2
 
0.1%
34 17
 
1.3%
ValueCountFrequency (%)
34 17
 
1.3%
32 2
 
0.1%
25 50
 
3.7%
23 6
 
0.4%
22 852
62.7%
21 432
31.8%

업종명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
폐수배출업소관리
833 
<NA>
283 
대기배출업소관리
239 
소음진동관리
 
4

Length

Max length8
Median length8
Mean length7.1611479
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐수배출업소관리 833
61.3%
<NA> 283
 
20.8%
대기배출업소관리 239
 
17.6%
소음진동관리 4
 
0.3%

Length

2024-05-11T01:01:08.807600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:01:09.330003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐수배출업소관리 833
61.3%
na 283
 
20.8%
대기배출업소관리 239
 
17.6%
소음진동관리 4
 
0.3%

지도점검일자
Real number (ℝ)

Distinct413
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20129836
Minimum20100114
Maximum20171130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.1 KiB
2024-05-11T01:01:09.857820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100114
5-th percentile20100616
Q120110724
median20120920
Q320150901
95-th percentile20170905
Maximum20171130
Range71016
Interquartile range (IQR)40177.5

Descriptive statistics

Standard deviation23767.371
Coefficient of variation (CV)0.0011807036
Kurtosis-1.2170303
Mean20129836
Median Absolute Deviation (MAD)19704
Skewness0.40901373
Sum2.7356447 × 1010
Variance5.6488792 × 108
MonotonicityDecreasing
2024-05-11T01:01:10.393766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161018 17
 
1.3%
20161024 16
 
1.2%
20110922 13
 
1.0%
20120919 13
 
1.0%
20120920 11
 
0.8%
20161019 11
 
0.8%
20161020 11
 
0.8%
20110927 11
 
0.8%
20111115 10
 
0.7%
20110928 10
 
0.7%
Other values (403) 1236
90.9%
ValueCountFrequency (%)
20100114 1
0.1%
20100121 2
0.1%
20100122 2
0.1%
20100127 1
0.1%
20100129 1
0.1%
20100217 2
0.1%
20100304 1
0.1%
20100317 1
0.1%
20100406 2
0.1%
20100407 2
0.1%
ValueCountFrequency (%)
20171130 2
 
0.1%
20171122 2
 
0.1%
20171121 4
0.3%
20171101 1
 
0.1%
20171026 1
 
0.1%
20171024 1
 
0.1%
20171020 2
 
0.1%
20171019 5
0.4%
20171018 3
0.2%
20171017 4
0.3%

점검기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
3230000
1359 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 1359
100.0%

Length

2024-05-11T01:01:10.892938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:01:11.272998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 1359
100.0%

점검기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
서울특별시 송파구
1359 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 송파구 1359
100.0%

Length

2024-05-11T01:01:11.678439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:01:12.210110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 1359
50.0%
송파구 1359
50.0%

지도점검구분
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
정기
942 
수시
216 
합동
175 
기타
 
26

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기 942
69.3%
수시 216
 
15.9%
합동 175
 
12.9%
기타 26
 
1.9%

Length

2024-05-11T01:01:12.627824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:01:13.117578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 942
69.3%
수시 216
 
15.9%
합동 175
 
12.9%
기타 26
 
1.9%

처분대상여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.2%
Missing252
Missing (%)18.5%
Memory size2.8 KiB
False
1097 
True
 
10
(Missing)
252 
ValueCountFrequency (%)
False 1097
80.7%
True 10
 
0.7%
(Missing) 252
 
18.5%
2024-05-11T01:01:13.600697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

점검사항
Text

Distinct204
Distinct (%)15.1%
Missing11
Missing (%)0.8%
Memory size10.7 KiB
2024-05-11T01:01:14.208181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length61
Mean length21.900593
Min length7

Characters and Unicode

Total characters29522
Distinct characters161
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)8.6%

Sample

1st row배출시설 및 방지시설 운영 사항 점검
2nd row배출시설 및 방지시설 적정 운영여부 점검
3rd row배출시설 및 방지시설 적정 운영여부 점검
4th row배출시설 및 방지시설 운영 사항 점검
5th row배출시설 및 방지시설 운영 사항 점검
ValueCountFrequency (%)
및 1257
16.8%
방지시설 1180
15.8%
여부 760
10.2%
폐수배출시설 641
 
8.6%
적정 463
 
6.2%
운영 428
 
5.7%
배출시설 345
 
4.6%
적정운영 288
 
3.8%
대기배출시설 178
 
2.4%
정상가동 150
 
2.0%
Other values (198) 1795
24.0%
2024-05-11T01:01:15.760918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6155
20.8%
설 2442
 
8.3%
시 2427
 
8.2%
및 1295
 
4.4%
지 1228
 
4.2%
배 1225
 
4.1%
출 1224
 
4.1%
방 1208
 
4.1%
정 1144
 
3.9%
여 985
 
3.3%
Other values (151) 10189
34.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23143
78.4%
Space Separator 6155
 
20.8%
Dash Punctuation 116
 
0.4%
Other Punctuation 35
 
0.1%
Close Punctuation 26
 
0.1%
Open Punctuation 26
 
0.1%
Decimal Number 19
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 2442
 
10.6%
시 2427
 
10.5%
및 1295
 
5.6%
지 1228
 
5.3%
배 1225
 
5.3%
출 1224
 
5.3%
방 1208
 
5.2%
정 1144
 
4.9%
여 985
 
4.3%
부 981
 
4.2%
Other values (133) 8984
38.8%
Other Punctuation
ValueCountFrequency (%)
, 18
51.4%
. 8
22.9%
: 3
 
8.6%
？ 2
 
5.7%
% 2
 
5.7%
* 1
 
2.9%
? 1
 
2.9%
Decimal Number
ValueCountFrequency (%)
2 5
26.3%
1 4
21.1%
0 4
21.1%
6 2
 
10.5%
7 2
 
10.5%
3 2
 
10.5%
Space Separator
ValueCountFrequency (%)
6155
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Math Symbol
ValueCountFrequency (%)
→ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23143
78.4%
Common 6379
 
21.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 2442
 
10.6%
시 2427
 
10.5%
및 1295
 
5.6%
지 1228
 
5.3%
배 1225
 
5.3%
출 1224
 
5.3%
방 1208
 
5.2%
정 1144
 
4.9%
여 985
 
4.3%
부 981
 
4.2%
Other values (133) 8984
38.8%
Common
ValueCountFrequency (%)
6155
96.5%
- 116
 
1.8%
) 26
 
0.4%
( 26
 
0.4%
, 18
 
0.3%
. 8
 
0.1%
2 5
 
0.1%
1 4
 
0.1%
0 4
 
0.1%
: 3
 
< 0.1%
Other values (8) 14
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23143
78.4%
ASCII 6375
 
21.6%
None 2
 
< 0.1%
Arrows 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6155
96.5%
- 116
 
1.8%
) 26
 
0.4%
( 26
 
0.4%
, 18
 
0.3%
. 8
 
0.1%
2 5
 
0.1%
1 4
 
0.1%
0 4
 
0.1%
: 3
 
< 0.1%
Other values (6) 10
 
0.2%
Hangul
ValueCountFrequency (%)
설 2442
 
10.6%
시 2427
 
10.5%
및 1295
 
5.6%
지 1228
 
5.3%
배 1225
 
5.3%
출 1224
 
5.3%
방 1208
 
5.2%
정 1144
 
4.9%
여 985
 
4.3%
부 981
 
4.2%
Other values (133) 8984
38.8%
None
ValueCountFrequency (%)
？ 2
100.0%
Arrows
ValueCountFrequency (%)
→ 2
100.0%

점검결과
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1359
Missing (%)100.0%
Memory size12.1 KiB

소재지도로명주소
Text

MISSING 

Distinct274
Distinct (%)52.6%
Missing838
Missing (%)61.7%
Memory size10.7 KiB
2024-05-11T01:01:16.723712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length37
Mean length26.055662
Min length21

Characters and Unicode

Total characters13575
Distinct characters170
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

Unique154 ?
Unique (%)29.6%

Sample

1st row서울특별시 송파구 오금로35길 46 (오금동)
2nd row서울특별시 송파구 동남로24길 17 (오금동)
3rd row서울특별시 송파구 헌릉로 793 (장지동, 송파구 자원순환공원)
4th row서울특별시 송파구 송이로 123 (가락동)
5th row서울특별시 송파구 충민로6길 61-22 (장지동)
ValueCountFrequency (%)
송파구 522
19.3%
서울특별시 521
19.2%
가락동 81
 
3.0%
오금동 79
 
2.9%
방이동 64
 
2.4%
문정동 52
 
1.9%
마천동 45
 
1.7%
중대로 43
 
1.6%
송파동 42
 
1.6%
장지동 32
 
1.2%
Other values (341) 1227
45.3%
2024-05-11T01:01:18.268087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2369
 
17.5%
송 645
 
4.8%
파 606
 
4.5%
동 568
 
4.2%
서 535
 
3.9%
울 533
 
3.9%
구 527
 
3.9%
로 524
 
3.9%
( 522
 
3.8%
) 522
 
3.8%
Other values (160) 6224
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8247
60.8%
Space Separator 2369
 
17.5%
Decimal Number 1741
 
12.8%
Open Punctuation 522
 
3.8%
Close Punctuation 522
 
3.8%
Other Punctuation 104
 
0.8%
Dash Punctuation 58
 
0.4%
Uppercase Letter 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
송 645
 
7.8%
파 606
 
7.3%
동 568
 
6.9%
서 535
 
6.5%
울 533
 
6.5%
구 527
 
6.4%
로 524
 
6.4%
별 521
 
6.3%
시 521
 
6.3%
특 521
 
6.3%
Other values (138) 2746
33.3%
Decimal Number
ValueCountFrequency (%)
1 350
20.1%
2 274
15.7%
3 238
13.7%
4 192
11.0%
5 162
9.3%
6 138
 
7.9%
8 118
 
6.8%
0 104
 
6.0%
9 88
 
5.1%
7 77
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
A 2
16.7%
Y 2
16.7%
M 2
16.7%
C 2
16.7%
G 2
16.7%
S 2
16.7%
Other Punctuation
ValueCountFrequency (%)
, 98
94.2%
. 6
 
5.8%
Space Separator
ValueCountFrequency (%)
2369
100.0%
Open Punctuation
ValueCountFrequency (%)
( 522
100.0%
Close Punctuation
ValueCountFrequency (%)
) 522
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8247
60.8%
Common 5316
39.2%
Latin 12
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
송 645
 
7.8%
파 606
 
7.3%
동 568
 
6.9%
서 535
 
6.5%
울 533
 
6.5%
구 527
 
6.4%
로 524
 
6.4%
별 521
 
6.3%
시 521
 
6.3%
특 521
 
6.3%
Other values (138) 2746
33.3%
Common
ValueCountFrequency (%)
2369
44.6%
( 522
 
9.8%
) 522
 
9.8%
1 350
 
6.6%
2 274
 
5.2%
3 238
 
4.5%
4 192
 
3.6%
5 162
 
3.0%
6 138
 
2.6%
8 118
 
2.2%
Other values (6) 431
 
8.1%
Latin
ValueCountFrequency (%)
A 2
16.7%
Y 2
16.7%
M 2
16.7%
C 2
16.7%
G 2
16.7%
S 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8247
60.8%
ASCII 5328
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2369
44.5%
( 522
 
9.8%
) 522
 
9.8%
1 350
 
6.6%
2 274
 
5.1%
3 238
 
4.5%
4 192
 
3.6%
5 162
 
3.0%
6 138
 
2.6%
8 118
 
2.2%
Other values (12) 443
 
8.3%
Hangul
ValueCountFrequency (%)
송 645
 
7.8%
파 606
 
7.3%
동 568
 
6.9%
서 535
 
6.5%
울 533
 
6.5%
구 527
 
6.4%
로 524
 
6.4%
별 521
 
6.3%
시 521
 
6.3%
특 521
 
6.3%
Other values (138) 2746
33.3%

소재지주소
Text

MISSING 

Distinct343
Distinct (%)26.9%
Missing85
Missing (%)6.3%
Memory size10.7 KiB
2024-05-11T01:01:19.264948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length46
Mean length22.298273
Min length14

Characters and Unicode

Total characters28408
Distinct characters133
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

Unique101 ?
Unique (%)7.9%

Sample

1st row서울특별시 송파구 오금동 39번지
2nd row서울특별시 송파구 오금동 155-10번지
3rd row서울특별시 송파구 장지동 692-2번지
4th row서울특별시 송파구 가락동 58번지
5th row서울특별시 송파구 장지동 863-2번지
ValueCountFrequency (%)
서울특별시 1274
24.1%
송파구 1274
24.1%
가락동 184
 
3.5%
오금동 181
 
3.4%
장지동 167
 
3.2%
방이동 143
 
2.7%
마천동 105
 
2.0%
문정동 103
 
1.9%
송파동 76
 
1.4%
삼전동 75
 
1.4%
Other values (396) 1715
32.4%
2024-05-11T01:01:21.087623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5294
18.6%
지 1507
 
5.3%
파 1355
 
4.8%
송 1350
 
4.8%
동 1306
 
4.6%
구 1290
 
4.5%
시 1287
 
4.5%
서 1276
 
4.5%
울 1276
 
4.5%
특 1274
 
4.5%
Other values (123) 11193
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17275
60.8%
Space Separator 5294
 
18.6%
Decimal Number 4738
 
16.7%
Dash Punctuation 1029
 
3.6%
Other Punctuation 28
 
0.1%
Uppercase Letter 21
 
0.1%
Close Punctuation 10
 
< 0.1%
Open Punctuation 10
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 1507
 
8.7%
파 1355
 
7.8%
송 1350
 
7.8%
동 1306
 
7.6%
구 1290
 
7.5%
시 1287
 
7.5%
서 1276
 
7.4%
울 1276
 
7.4%
특 1274
 
7.4%
별 1274
 
7.4%
Other values (101) 4080
23.6%
Decimal Number
ValueCountFrequency (%)
1 1064
22.5%
2 641
13.5%
3 620
13.1%
6 397
 
8.4%
8 392
 
8.3%
5 389
 
8.2%
4 352
 
7.4%
9 334
 
7.0%
0 301
 
6.4%
7 248
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
A 9
42.9%
B 6
28.6%
L 5
23.8%
D 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 23
82.1%
/ 4
 
14.3%
. 1
 
3.6%
Space Separator
ValueCountFrequency (%)
5294
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1029
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17275
60.8%
Common 11109
39.1%
Latin 24
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 1507
 
8.7%
파 1355
 
7.8%
송 1350
 
7.8%
동 1306
 
7.6%
구 1290
 
7.5%
시 1287
 
7.5%
서 1276
 
7.4%
울 1276
 
7.4%
특 1274
 
7.4%
별 1274
 
7.4%
Other values (101) 4080
23.6%
Common
ValueCountFrequency (%)
5294
47.7%
1 1064
 
9.6%
- 1029
 
9.3%
2 641
 
5.8%
3 620
 
5.6%
6 397
 
3.6%
8 392
 
3.5%
5 389
 
3.5%
4 352
 
3.2%
9 334
 
3.0%
Other values (7) 597
 
5.4%
Latin
ValueCountFrequency (%)
A 9
37.5%
B 6
25.0%
L 5
20.8%
c 3
 
12.5%
D 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17275
60.8%
ASCII 11133
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5294
47.6%
1 1064
 
9.6%
- 1029
 
9.2%
2 641
 
5.8%
3 620
 
5.6%
6 397
 
3.6%
8 392
 
3.5%
5 389
 
3.5%
4 352
 
3.2%
9 334
 
3.0%
Other values (12) 621
 
5.6%
Hangul
ValueCountFrequency (%)
지 1507
 
8.7%
파 1355
 
7.8%
송 1350
 
7.8%
동 1306
 
7.6%
구 1290
 
7.5%
시 1287
 
7.5%
서 1276
 
7.4%
울 1276
 
7.4%
특 1274
 
7.4%
별 1274
 
7.4%
Other values (101) 4080
23.6%

Interactions

2024-05-11T01:01:01.863266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:00:59.943366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:01:00.762699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:01:02.250210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:01:00.206341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:01:01.115594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:01:02.566464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:01:00.502567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:01:01.416553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T01:01:21.463750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업종코드업종명지도점검일자지도점검구분처분대상여부
인허가번호1.0000.8410.0000.2640.3820.163
업종코드0.8411.0001.0000.3550.0870.000
업종명0.0001.0001.0000.3740.1790.000
지도점검일자0.2640.3550.3741.0000.6160.160
지도점검구분0.3820.0870.1790.6161.0000.181
처분대상여부0.1630.0000.0000.1600.1811.000
2024-05-11T01:01:21.947504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분대상여부업종명지도점검구분
처분대상여부1.0000.0000.120
업종명0.0001.0000.169
지도점검구분0.1200.1691.000
2024-05-11T01:01:22.355545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업종코드지도점검일자업종명지도점검구분처분대상여부
인허가번호1.0000.8430.0030.0000.1570.104
업종코드0.8431.000-0.1301.0000.0710.000
지도점검일자0.003-0.1301.0000.2560.3140.133
업종명0.0001.0000.2561.0000.1690.000
지도점검구분0.1570.0710.3140.1691.0000.120
처분대상여부0.1040.0000.1330.0000.1201.000

Missing values

2024-05-11T01:01:03.039385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T01:01:03.733776image/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.
2024-05-11T01:01:04.126006image/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)건양자동차32300002120050000421대기배출업소관리201711303230000서울특별시 송파구수시N배출시설 및 방지시설 운영 사항 점검<NA>서울특별시 송파구 오금로35길 46 (오금동)서울특별시 송파구 오금동 39번지
1(주)우주카독크32300002120030001121대기배출업소관리201711303230000서울특별시 송파구수시N<NA><NA>서울특별시 송파구 동남로24길 17 (오금동)서울특별시 송파구 오금동 155-10번지
2(주)리클린32300002220090000122폐수배출업소관리201711223230000서울특별시 송파구정기N배출시설 및 방지시설 적정 운영여부 점검<NA>서울특별시 송파구 헌릉로 793 (장지동, 송파구 자원순환공원)서울특별시 송파구 장지동 692-2번지
3국립경찰병원32300002219890000322폐수배출업소관리201711223230000서울특별시 송파구정기N배출시설 및 방지시설 적정 운영여부 점검<NA>서울특별시 송파구 송이로 123 (가락동)서울특별시 송파구 가락동 58번지
4대영운수(주)32300002219960020022폐수배출업소관리201711213230000서울특별시 송파구정기N배출시설 및 방지시설 운영 사항 점검<NA>서울특별시 송파구 충민로6길 61-22 (장지동)서울특별시 송파구 장지동 863-2번지
5삼광교통(주)32300002220080000122폐수배출업소관리201711213230000서울특별시 송파구정기N배출시설 및 방지시설 운영 사항 점검<NA>서울특별시 송파구 충민로6길 67 (장지동)서울특별시 송파구 장지동 863-4번지
6승일운수(주)32300002220080000322폐수배출업소관리201711213230000서울특별시 송파구정기N배출시설 및 방지시설 운영 사항 점검<NA>서울특별시 송파구 충민로6길 61-6 (장지동)서울특별시 송파구 장지동 863번지
7(주)신일씨엠32300002219990060222폐수배출업소관리201711213230000서울특별시 송파구정기N배출시설 및 방지시설 운영 사항 점검<NA><NA>서울특별시 송파구 장지동 738-17번지 외 3필지
8돈방자동차공업사32300002220020069922폐수배출업소관리201711013230000서울특별시 송파구정기N배출시설 및 방지시설 적정운영 여부<NA>서울특별시 송파구 송이로30길 31 (문정동)서울특별시 송파구 문정동 91-15번지
9(주)강동모터스32300002120040005521대기배출업소관리201710263230000서울특별시 송파구정기N배출시설 및 방지시설 운영 사항 점검<NA>서울특별시 송파구 백제고분로31길 2-18 (삼전동)서울특별시 송파구 삼전동 133-3번지
업체(시설)명인허가번호업종코드업종명지도점검일자점검기관점검기관명지도점검구분처분대상여부점검사항점검결과소재지도로명주소소재지주소
1349(주)석촌현대자동차서비스32300002120060000221<NA>201003043230000서울특별시 송파구정기<NA>배출시설 및 방지시설 적정운영 여부<NA><NA>서울특별시 송파구 석촌동 183-8번지
1350정우셀프세차장32300002219970022822폐수배출업소관리201002173230000서울특별시 송파구수시N폐수배출시설 및 방지시설 적정운영 여부(행정처분 이행)<NA><NA>서울특별시 송파구 거여동 178-22번지
1351진영주유소32300002219940011622폐수배출업소관리201002173230000서울특별시 송파구수시N행정처분 이행 여부(폐수배출시설 및 방지시설 가동상태)<NA><NA>서울특별시 송파구 거여동 19-4번지
1352준마스타세차32300002219930008722폐수배출업소관리201001293230000서울특별시 송파구수시N폐수배출시설 및 방지시설 가동상태(행정처분 이행상태)<NA><NA>서울특별시 송파구 가락동 171번지
1353문정카32300002219940011922폐수배출업소관리201001273230000서울특별시 송파구수시Y행정처분 사업장 행정처분 이행확인<NA><NA>서울특별시 송파구 문정동 113-5번지
1354(주)리클린32300002120090000121<NA>201001223230000서울특별시 송파구정기<NA>대기배출시설 및 방지시설 적정운영 여부<NA><NA>서울특별시 송파구 가락동 160-9번지 동진빌딩 402호
1355한국지역난방공사 강남지사32300002120080000521대기배출업소관리201001223230000서울특별시 송파구정기N<NA><NA><NA>서울특별시 송파구 장지동 730-1번지
1356제이엔모터스32300002219930007722폐수배출업소관리201001213230000서울특별시 송파구수시Y행정처분 이행확인<NA><NA>서울특별시 송파구 오금동 52-22번지
1357진영주유소32300002219940011622폐수배출업소관리201001213230000서울특별시 송파구기타N폐수배출시설 및 방지시설 가동상태<NA><NA>서울특별시 송파구 거여동 19-4번지
1358정우셀프세차장32300002219970022822폐수배출업소관리201001143230000서울특별시 송파구기타Y폐수배출시설 및 방지시설 가동상태<NA><NA>서울특별시 송파구 거여동 178-22번지

Duplicate rows

Most frequently occurring

업체(시설)명인허가번호업종코드업종명지도점검일자점검기관점검기관명지도점검구분처분대상여부점검사항소재지도로명주소소재지주소# duplicates
0국립경찰병원32300002219890000322폐수배출업소관리201108113230000서울특별시 송파구정기N폐수배출시설 및 방지시설 적정 운영 상태 확인<NA>서울특별시 송파구 가락동 58번지2