Overview

Dataset statistics

Number of variables33
Number of observations146
Missing cells1403
Missing cells (%)29.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory40.1 KiB
Average record size in memory280.9 B

Variable types

Categorical11
Numeric7
DateTime4
Unsupported5
Text6

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
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-19375/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (51.3%)Imbalance
영업상태명 is highly imbalanced (51.3%)Imbalance
상세영업상태코드 is highly imbalanced (51.3%)Imbalance
상세영업상태명 is highly imbalanced (51.3%)Imbalance
휴업시작일자 is highly imbalanced (94.1%)Imbalance
인허가취소일자 has 146 (100.0%) missing valuesMissing
폐업일자 has 117 (80.1%) missing valuesMissing
휴업종료일자 has 146 (100.0%) missing valuesMissing
재개업일자 has 146 (100.0%) missing valuesMissing
전화번호 has 12 (8.2%) missing valuesMissing
소재지면적 has 146 (100.0%) missing valuesMissing
소재지우편번호 has 146 (100.0%) missing valuesMissing
도로명우편번호 has 32 (21.9%) missing valuesMissing
좌표정보(X) has 2 (1.4%) missing valuesMissing
좌표정보(Y) has 2 (1.4%) missing valuesMissing
주생산품명 has 139 (95.2%) missing valuesMissing
배출시설조업시간 has 100 (68.5%) missing valuesMissing
배출시설연간가동일수 has 72 (49.3%) missing valuesMissing
방지시설조업시간 has 114 (78.1%) missing valuesMissing
방지시설연간가동일수 has 82 (56.2%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 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
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
배출시설연간가동일수 has 29 (19.9%) zerosZeros
방지시설연간가동일수 has 32 (21.9%) zerosZeros

Reproduction

Analysis started2024-04-29 19:54:56.462924
Analysis finished2024-04-29 19:54:57.312549
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3230000
146 

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 146
100.0%

Length

2024-04-30T04:54:57.375770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:54:57.454251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 146
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct146
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2300002 × 1017
Minimum3.2300002 × 1017
Maximum3.2300002 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-30T04:54:57.558253image/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 percentile3.2300002 × 1017
Maximum3.2300002 × 1017
Range1899996
Interquartile range (IQR)1499968

Descriptive statistics

Standard deviation675195.58
Coefficient of variation (CV)2.0903887 × 10-12
Kurtosis-1.6016721
Mean3.2300002 × 1017
Median Absolute Deviation (MAD)600000
Skewness-0.056688823
Sum-8.1822291 × 1018
Variance4.5588907 × 1011
MonotonicityStrictly increasing
2024-04-30T04:54:57.683545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
323000021200300011 1
 
0.7%
323000021202000006 1
 
0.7%
323000021201500032 1
 
0.7%
323000021201500033 1
 
0.7%
323000021201500034 1
 
0.7%
323000021201500035 1
 
0.7%
323000021201600001 1
 
0.7%
323000021201600002 1
 
0.7%
323000021201600003 1
 
0.7%
323000021201700001 1
 
0.7%
Other values (136) 136
93.2%
ValueCountFrequency (%)
323000021200300011 1
0.7%
323000021200400007 1
0.7%
323000021200400008 1
0.7%
323000021200400010 1
0.7%
323000021200400015 1
0.7%
323000021200400016 1
0.7%
323000021200400018 1
0.7%
323000021200400020 1
0.7%
323000021200400031 1
0.7%
323000021200400032 1
0.7%
ValueCountFrequency (%)
323000021202200007 1
0.7%
323000021202200006 1
0.7%
323000021202200005 1
0.7%
323000021202200004 1
0.7%
323000021202200003 1
0.7%
323000021202200002 1
0.7%
323000021202200001 1
0.7%
323000021202100021 1
0.7%
323000021202100020 1
0.7%
323000021202100019 1
0.7%

인허가일자
Date

Distinct119
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1992-09-23 00:00:00
Maximum2022-12-12 00:00:00
2024-04-30T04:54:57.808352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:54:57.914901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing146
Missing (%)100.0%
Memory size1.4 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
1
116 
3
15 
4
14 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
1 116
79.5%
3 15
 
10.3%
4 14
 
9.6%
2 1
 
0.7%

Length

2024-04-30T04:54:58.025436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:54:58.125136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 116
79.5%
3 15
 
10.3%
4 14
 
9.6%
2 1
 
0.7%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
영업/정상
116 
폐업
15 
취소/말소/만료/정지/중지
14 
휴업
 
1

Length

Max length14
Median length5
Mean length5.5342466
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 116
79.5%
폐업 15
 
10.3%
취소/말소/만료/정지/중지 14
 
9.6%
휴업 1
 
0.7%

Length

2024-04-30T04:54:58.226415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:54:58.317403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 116
79.5%
폐업 15
 
10.3%
취소/말소/만료/정지/중지 14
 
9.6%
휴업 1
 
0.7%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
11
116 
2
15 
4
14 
1
 
1

Length

Max length2
Median length2
Mean length1.7945205
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
11 116
79.5%
2 15
 
10.3%
4 14
 
9.6%
1 1
 
0.7%

Length

2024-04-30T04:54:58.417017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:54:58.503914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 116
79.5%
2 15
 
10.3%
4 14
 
9.6%
1 1
 
0.7%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
영업
116 
폐업
15 
폐쇄
14 
휴업
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
영업 116
79.5%
폐업 15
 
10.3%
폐쇄 14
 
9.6%
휴업 1
 
0.7%

Length

2024-04-30T04:54:58.603512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:54:58.710440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 116
79.5%
폐업 15
 
10.3%
폐쇄 14
 
9.6%
휴업 1
 
0.7%

폐업일자
Date

MISSING 

Distinct29
Distinct (%)100.0%
Missing117
Missing (%)80.1%
Memory size1.3 KiB
Minimum2010-11-11 00:00:00
Maximum2024-02-26 00:00:00
2024-04-30T04:54:58.816906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:54:58.924464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
145 
20200528
 
1

Length

Max length8
Median length4
Mean length4.0273973
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 145
99.3%
20200528 1
 
0.7%

Length

2024-04-30T04:54:59.032605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:54:59.135078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 145
99.3%
20200528 1
 
0.7%

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing146
Missing (%)100.0%
Memory size1.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing146
Missing (%)100.0%
Memory size1.4 KiB

전화번호
Text

MISSING 

Distinct132
Distinct (%)98.5%
Missing12
Missing (%)8.2%
Memory size1.3 KiB
2024-04-30T04:54:59.338774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9
Min length7

Characters and Unicode

Total characters1206
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

Unique130 ?
Unique (%)97.0%

Sample

1st row401-1141
2nd row02-402-6358
3rd row473-8313
4th row02 4484178
5th row02 4082939
ValueCountFrequency (%)
02 14
 
9.3%
02-6424-7220 2
 
1.3%
2240-4630 2
 
1.3%
02-2203-8494 1
 
0.7%
02-431-1762 1
 
0.7%
2147-2130 1
 
0.7%
413-2713 1
 
0.7%
02-469-3131 1
 
0.7%
02-412-6514 1
 
0.7%
02-3434-0101 1
 
0.7%
Other values (125) 125
83.3%
2024-04-30T04:54:59.687692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 192
15.9%
0 189
15.7%
2 177
14.7%
1 142
11.8%
- 112
9.3%
3 88
7.3%
6 65
 
5.4%
8 65
 
5.4%
5 64
 
5.3%
7 48
 
4.0%
Other values (2) 64
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1078
89.4%
Dash Punctuation 112
 
9.3%
Space Separator 16
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 192
17.8%
0 189
17.5%
2 177
16.4%
1 142
13.2%
3 88
8.2%
6 65
 
6.0%
8 65
 
6.0%
5 64
 
5.9%
7 48
 
4.5%
9 48
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1206
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 192
15.9%
0 189
15.7%
2 177
14.7%
1 142
11.8%
- 112
9.3%
3 88
7.3%
6 65
 
5.4%
8 65
 
5.4%
5 64
 
5.3%
7 48
 
4.0%
Other values (2) 64
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1206
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 192
15.9%
0 189
15.7%
2 177
14.7%
1 142
11.8%
- 112
9.3%
3 88
7.3%
6 65
 
5.4%
8 65
 
5.4%
5 64
 
5.3%
7 48
 
4.0%
Other values (2) 64
 
5.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing146
Missing (%)100.0%
Memory size1.4 KiB

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing146
Missing (%)100.0%
Memory size1.4 KiB

지번주소
Text

Distinct142
Distinct (%)97.9%
Missing1
Missing (%)0.7%
Memory size1.3 KiB
2024-04-30T04:54:59.912889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length31
Mean length23.896552
Min length16

Characters and Unicode

Total characters3465
Distinct characters213
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

Unique139 ?
Unique (%)95.9%

Sample

1st row서울특별시 송파구 오금동 155-10
2nd row서울특별시 송파구 가락동 156-5
3rd row서울특별시 송파구 가락동 156-2
4th row서울특별시 송파구 가락동 46-15
5th row서울특별시 송파구 풍납동 163-5
ValueCountFrequency (%)
송파구 147
21.5%
서울특별시 145
21.2%
가락동 30
 
4.4%
방이동 26
 
3.8%
신천동 25
 
3.6%
장지동 14
 
2.0%
문정동 11
 
1.6%
잠실동 10
 
1.5%
오금동 9
 
1.3%
마천동 7
 
1.0%
Other values (235) 261
38.1%
2024-04-30T04:55:00.259272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
642
18.5%
파 166
 
4.8%
송 155
 
4.5%
서 153
 
4.4%
동 153
 
4.4%
시 151
 
4.4%
울 151
 
4.4%
구 150
 
4.3%
특 145
 
4.2%
별 145
 
4.2%
Other values (203) 1454
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2209
63.8%
Space Separator 642
 
18.5%
Decimal Number 463
 
13.4%
Dash Punctuation 99
 
2.9%
Uppercase Letter 39
 
1.1%
Other Punctuation 5
 
0.1%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 166
 
7.5%
송 155
 
7.0%
서 153
 
6.9%
동 153
 
6.9%
시 151
 
6.8%
울 151
 
6.8%
구 150
 
6.8%
특 145
 
6.6%
별 145
 
6.6%
가 35
 
1.6%
Other values (173) 805
36.4%
Uppercase Letter
ValueCountFrequency (%)
S 6
15.4%
A 5
12.8%
U 4
10.3%
N 4
10.3%
D 3
7.7%
M 3
7.7%
G 2
 
5.1%
P 2
 
5.1%
I 2
 
5.1%
T 2
 
5.1%
Other values (4) 6
15.4%
Decimal Number
ValueCountFrequency (%)
1 94
20.3%
2 65
14.0%
8 52
11.2%
3 42
9.1%
9 42
9.1%
5 41
8.9%
4 34
 
7.3%
6 34
 
7.3%
7 34
 
7.3%
0 25
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
, 2
40.0%
Space Separator
ValueCountFrequency (%)
642
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2209
63.8%
Common 1217
35.1%
Latin 39
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 166
 
7.5%
송 155
 
7.0%
서 153
 
6.9%
동 153
 
6.9%
시 151
 
6.8%
울 151
 
6.8%
구 150
 
6.8%
특 145
 
6.6%
별 145
 
6.6%
가 35
 
1.6%
Other values (173) 805
36.4%
Common
ValueCountFrequency (%)
642
52.8%
- 99
 
8.1%
1 94
 
7.7%
2 65
 
5.3%
8 52
 
4.3%
3 42
 
3.5%
9 42
 
3.5%
5 41
 
3.4%
4 34
 
2.8%
6 34
 
2.8%
Other values (6) 72
 
5.9%
Latin
ValueCountFrequency (%)
S 6
15.4%
A 5
12.8%
U 4
10.3%
N 4
10.3%
D 3
7.7%
M 3
7.7%
G 2
 
5.1%
P 2
 
5.1%
I 2
 
5.1%
T 2
 
5.1%
Other values (4) 6
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2209
63.8%
ASCII 1256
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
642
51.1%
- 99
 
7.9%
1 94
 
7.5%
2 65
 
5.2%
8 52
 
4.1%
3 42
 
3.3%
9 42
 
3.3%
5 41
 
3.3%
4 34
 
2.7%
6 34
 
2.7%
Other values (20) 111
 
8.8%
Hangul
ValueCountFrequency (%)
파 166
 
7.5%
송 155
 
7.0%
서 153
 
6.9%
동 153
 
6.9%
시 151
 
6.8%
울 151
 
6.8%
구 150
 
6.8%
특 145
 
6.6%
별 145
 
6.6%
가 35
 
1.6%
Other values (173) 805
36.4%

도로명주소
Text

Distinct138
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-30T04:55:00.490843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length38
Mean length30.534247
Min length21

Characters and Unicode

Total characters4458
Distinct characters230
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

Unique130 ?
Unique (%)89.0%

Sample

1st row서울특별시 송파구 동남로24길 17 (오금동)
2nd row서울특별시 송파구 중대로 204 (가락동)
3rd row서울특별시 송파구 중대로 208 (가락동)
4th row서울특별시 송파구 오금로36길 56 (가락동)
5th row서울특별시 송파구 풍성로 53 (풍납동)
ValueCountFrequency (%)
송파구 148
 
17.4%
서울특별시 146
 
17.2%
가락동 29
 
3.4%
신천동 26
 
3.1%
방이동 26
 
3.1%
올림픽로 19
 
2.2%
장지동 14
 
1.6%
문정동 11
 
1.3%
잠실동 10
 
1.2%
중대로 10
 
1.2%
Other values (283) 410
48.3%
2024-04-30T04:55:00.821473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
707
 
15.9%
파 179
 
4.0%
송 176
 
3.9%
동 163
 
3.7%
서 155
 
3.5%
울 153
 
3.4%
시 151
 
3.4%
구 151
 
3.4%
) 150
 
3.4%
( 150
 
3.4%
Other values (220) 2323
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2810
63.0%
Space Separator 707
 
15.9%
Decimal Number 484
 
10.9%
Close Punctuation 150
 
3.4%
Open Punctuation 150
 
3.4%
Other Punctuation 103
 
2.3%
Uppercase Letter 43
 
1.0%
Dash Punctuation 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 179
 
6.4%
송 176
 
6.3%
동 163
 
5.8%
서 155
 
5.5%
울 153
 
5.4%
시 151
 
5.4%
구 151
 
5.4%
특 146
 
5.2%
별 146
 
5.2%
로 146
 
5.2%
Other values (188) 1244
44.3%
Uppercase Letter
ValueCountFrequency (%)
A 6
14.0%
S 6
14.0%
N 4
9.3%
U 4
9.3%
M 3
 
7.0%
D 3
 
7.0%
T 3
 
7.0%
I 2
 
4.7%
F 2
 
4.7%
P 2
 
4.7%
Other values (6) 8
18.6%
Decimal Number
ValueCountFrequency (%)
1 99
20.5%
2 88
18.2%
3 57
11.8%
5 44
9.1%
6 44
9.1%
4 36
 
7.4%
9 35
 
7.2%
8 34
 
7.0%
7 25
 
5.2%
0 22
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 100
97.1%
. 3
 
2.9%
Space Separator
ValueCountFrequency (%)
707
100.0%
Close Punctuation
ValueCountFrequency (%)
) 150
100.0%
Open Punctuation
ValueCountFrequency (%)
( 150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2810
63.0%
Common 1605
36.0%
Latin 43
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 179
 
6.4%
송 176
 
6.3%
동 163
 
5.8%
서 155
 
5.5%
울 153
 
5.4%
시 151
 
5.4%
구 151
 
5.4%
특 146
 
5.2%
별 146
 
5.2%
로 146
 
5.2%
Other values (188) 1244
44.3%
Common
ValueCountFrequency (%)
707
44.0%
) 150
 
9.3%
( 150
 
9.3%
, 100
 
6.2%
1 99
 
6.2%
2 88
 
5.5%
3 57
 
3.6%
5 44
 
2.7%
6 44
 
2.7%
4 36
 
2.2%
Other values (6) 130
 
8.1%
Latin
ValueCountFrequency (%)
A 6
14.0%
S 6
14.0%
N 4
9.3%
U 4
9.3%
M 3
 
7.0%
D 3
 
7.0%
T 3
 
7.0%
I 2
 
4.7%
F 2
 
4.7%
P 2
 
4.7%
Other values (6) 8
18.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2810
63.0%
ASCII 1648
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
707
42.9%
) 150
 
9.1%
( 150
 
9.1%
, 100
 
6.1%
1 99
 
6.0%
2 88
 
5.3%
3 57
 
3.5%
5 44
 
2.7%
6 44
 
2.7%
4 36
 
2.2%
Other values (22) 173
 
10.5%
Hangul
ValueCountFrequency (%)
파 179
 
6.4%
송 176
 
6.3%
동 163
 
5.8%
서 155
 
5.5%
울 153
 
5.4%
시 151
 
5.4%
구 151
 
5.4%
특 146
 
5.2%
별 146
 
5.2%
로 146
 
5.2%
Other values (188) 1244
44.3%

도로명우편번호
Text

MISSING 

Distinct65
Distinct (%)57.0%
Missing32
Missing (%)21.9%
Memory size1.3 KiB
2024-04-30T04:55:01.008485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0350877
Min length5

Characters and Unicode

Total characters574
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

Unique49 ?
Unique (%)43.0%

Sample

1st row138130
2nd row05818
3rd row138121
4th row138-875
5th row05750
ValueCountFrequency (%)
05510 21
 
18.4%
05791 7
 
6.1%
05719 6
 
5.3%
05552 4
 
3.5%
05842 3
 
2.6%
05544 3
 
2.6%
05809 3
 
2.6%
05541 2
 
1.8%
05542 2
 
1.8%
05548 2
 
1.8%
Other values (55) 61
53.5%
2024-04-30T04:55:01.322013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 182
31.7%
0 152
26.5%
1 56
 
9.8%
8 36
 
6.3%
7 34
 
5.9%
4 32
 
5.6%
9 23
 
4.0%
2 21
 
3.7%
6 21
 
3.7%
3 16
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 573
99.8%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 182
31.8%
0 152
26.5%
1 56
 
9.8%
8 36
 
6.3%
7 34
 
5.9%
4 32
 
5.6%
9 23
 
4.0%
2 21
 
3.7%
6 21
 
3.7%
3 16
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 574
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 182
31.7%
0 152
26.5%
1 56
 
9.8%
8 36
 
6.3%
7 34
 
5.9%
4 32
 
5.6%
9 23
 
4.0%
2 21
 
3.7%
6 21
 
3.7%
3 16
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 574
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 182
31.7%
0 152
26.5%
1 56
 
9.8%
8 36
 
6.3%
7 34
 
5.9%
4 32
 
5.6%
9 23
 
4.0%
2 21
 
3.7%
6 21
 
3.7%
3 16
 
2.8%

사업장명
Text

Distinct142
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-30T04:55:01.540950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length19
Mean length10.157534
Min length3

Characters and Unicode

Total characters1483
Distinct characters260
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

Unique138 ?
Unique (%)94.5%

Sample

1st row(주)우주카독크
2nd row주식회사 대림정비공업사
3rd row명진카독크공업주식회사
4th row대신자동차공업사
5th row공신통운(주)
ValueCountFrequency (%)
주식회사 7
 
3.8%
관리단 3
 
1.6%
송파구청 2
 
1.1%
재단법인 2
 
1.1%
기독교한국루터회총회유지재단 2
 
1.1%
옵티멈 2
 
1.1%
한석교통(주 2
 
1.1%
주)엠씨모터스팩토리 1
 
0.5%
서경빌딩 1
 
0.5%
서울시학생체육관 1
 
0.5%
Other values (162) 162
87.6%
2024-04-30T04:55:01.866000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 81
 
5.5%
) 69
 
4.7%
( 69
 
4.7%
사 40
 
2.7%
39
 
2.6%
자 36
 
2.4%
회 34
 
2.3%
동 30
 
2.0%
대 28
 
1.9%
스 27
 
1.8%
Other values (250) 1030
69.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1274
85.9%
Close Punctuation 69
 
4.7%
Open Punctuation 69
 
4.7%
Space Separator 39
 
2.6%
Uppercase Letter 16
 
1.1%
Decimal Number 10
 
0.7%
Dash Punctuation 5
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 81
 
6.4%
사 40
 
3.1%
자 36
 
2.8%
회 34
 
2.7%
동 30
 
2.4%
대 28
 
2.2%
스 27
 
2.1%
공 27
 
2.1%
리 26
 
2.0%
파 26
 
2.0%
Other values (226) 919
72.1%
Uppercase Letter
ValueCountFrequency (%)
A 2
12.5%
E 2
12.5%
O 2
12.5%
I 1
 
6.2%
S 1
 
6.2%
P 1
 
6.2%
C 1
 
6.2%
G 1
 
6.2%
Y 1
 
6.2%
N 1
 
6.2%
Other values (3) 3
18.8%
Decimal Number
ValueCountFrequency (%)
1 3
30.0%
2 3
30.0%
3 1
 
10.0%
9 1
 
10.0%
4 1
 
10.0%
8 1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1274
85.9%
Common 193
 
13.0%
Latin 16
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 81
 
6.4%
사 40
 
3.1%
자 36
 
2.8%
회 34
 
2.7%
동 30
 
2.4%
대 28
 
2.2%
스 27
 
2.1%
공 27
 
2.1%
리 26
 
2.0%
파 26
 
2.0%
Other values (226) 919
72.1%
Latin
ValueCountFrequency (%)
A 2
12.5%
E 2
12.5%
O 2
12.5%
I 1
 
6.2%
S 1
 
6.2%
P 1
 
6.2%
C 1
 
6.2%
G 1
 
6.2%
Y 1
 
6.2%
N 1
 
6.2%
Other values (3) 3
18.8%
Common
ValueCountFrequency (%)
) 69
35.8%
( 69
35.8%
39
20.2%
- 5
 
2.6%
1 3
 
1.6%
2 3
 
1.6%
3 1
 
0.5%
9 1
 
0.5%
4 1
 
0.5%
, 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1274
85.9%
ASCII 209
 
14.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 81
 
6.4%
사 40
 
3.1%
자 36
 
2.8%
회 34
 
2.7%
동 30
 
2.4%
대 28
 
2.2%
스 27
 
2.1%
공 27
 
2.1%
리 26
 
2.0%
파 26
 
2.0%
Other values (226) 919
72.1%
ASCII
ValueCountFrequency (%)
) 69
33.0%
( 69
33.0%
39
18.7%
- 5
 
2.4%
1 3
 
1.4%
2 3
 
1.4%
A 2
 
1.0%
E 2
 
1.0%
O 2
 
1.0%
I 1
 
0.5%
Other values (14) 14
 
6.7%

최종수정일자
Date

UNIQUE 

Distinct146
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2012-11-14 08:48:24
Maximum2024-04-11 14:27:40
2024-04-30T04:55:01.985245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:55:02.109279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
U
127 
I
19 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 127
87.0%
I 19
 
13.0%

Length

2024-04-30T04:55:02.220821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:02.471729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 127
87.0%
i 19
 
13.0%

데이터갱신일자
Date

Distinct111
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2018-10-04 11:12:49
Maximum2023-12-03 23:03:00
2024-04-30T04:55:02.553434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:55:02.687161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct44
Distinct (%)30.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
자동차 수리업
43 
부동산업
18 
택시 운송업
12 
사업시설 유지관리 서비스업
9 
부동산 임대업
8 
Other values (39)
56 

Length

Max length16
Median length15
Mean length7.2054795
Min length2

Unique

Unique27 ?
Unique (%)18.5%

Sample

1st row자동차 수리업
2nd row자동차 수리업
3rd row자동차 수리업
4th row자동차 수리업
5th row택시 운송업

Common Values

ValueCountFrequency (%)
자동차 수리업 43
29.5%
부동산업 18
12.3%
택시 운송업 12
 
8.2%
사업시설 유지관리 서비스업 9
 
6.2%
부동산 임대업 8
 
5.5%
부동산 관리업 5
 
3.4%
주차장 운영업 3
 
2.1%
기타 부동산 임대업 3
 
2.1%
발전업 2
 
1.4%
기독교 단체 2
 
1.4%
Other values (34) 41
28.1%

Length

2024-04-30T04:55:02.824581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
자동차 44
15.0%
수리업 44
15.0%
부동산 20
 
6.8%
부동산업 18
 
6.1%
운송업 15
 
5.1%
서비스업 15
 
5.1%
택시 12
 
4.1%
임대업 12
 
4.1%
사업시설 9
 
3.1%
유지관리 9
 
3.1%
Other values (53) 96
32.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct133
Distinct (%)92.4%
Missing2
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean210281.21
Minimum206383.83
Maximum213657.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-30T04:55:02.949870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206383.83
5-th percentile207672.45
Q1209246.84
median210449.65
Q3211182.92
95-th percentile212537.24
Maximum213657.11
Range7273.279
Interquartile range (IQR)1936.0783

Descriptive statistics

Standard deviation1429.0891
Coefficient of variation (CV)0.0067960854
Kurtosis0.018431564
Mean210281.21
Median Absolute Deviation (MAD)1031.7041
Skewness-0.26467382
Sum30280494
Variance2042295.5
MonotonicityNot monotonic
2024-04-30T04:55:03.061377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
209035.875632195 2
 
1.4%
209338.128679752 2
 
1.4%
211525.928860841 2
 
1.4%
209039.148023482 2
 
1.4%
211928.249894922 2
 
1.4%
208836.192051204 2
 
1.4%
208994.017991356 2
 
1.4%
209309.168083103 2
 
1.4%
211259.909777857 2
 
1.4%
209140.885315651 2
 
1.4%
Other values (123) 124
84.9%
ValueCountFrequency (%)
206383.829438022 1
0.7%
206397.34797252 1
0.7%
206932.357872339 1
0.7%
207025.564276619 1
0.7%
207285.647226547 1
0.7%
207552.148294046 1
0.7%
207553.918225133 1
0.7%
207624.424720682 1
0.7%
207944.598192415 1
0.7%
208233.926974585 1
0.7%
ValueCountFrequency (%)
213657.108454649 1
0.7%
213501.102654244 1
0.7%
213083.85013167 1
0.7%
213022.782000678 1
0.7%
212860.467148542 1
0.7%
212562.616359781 1
0.7%
212562.319086965 1
0.7%
212561.62 1
0.7%
212399.1075575 1
0.7%
212276.350388354 1
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct133
Distinct (%)92.4%
Missing2
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean444619.4
Minimum440696.11
Maximum447989.48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-30T04:55:03.185119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440696.11
5-th percentile442004.81
Q1443542.95
median444912.52
Q3445884.92
95-th percentile446381.99
Maximum447989.48
Range7293.3633
Interquartile range (IQR)2341.9668

Descriptive statistics

Standard deviation1491.2869
Coefficient of variation (CV)0.0033540752
Kurtosis-0.37759858
Mean444619.4
Median Absolute Deviation (MAD)1066.7896
Skewness-0.40261408
Sum64025193
Variance2223936.6
MonotonicityNot monotonic
2024-04-30T04:55:03.312689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445898.643365404 2
 
1.4%
445745.524217446 2
 
1.4%
446381.991026383 2
 
1.4%
446007.966801057 2
 
1.4%
441936.410717522 2
 
1.4%
445807.727388799 2
 
1.4%
445826.545566831 2
 
1.4%
445825.652756192 2
 
1.4%
443711.702922024 2
 
1.4%
446042.592367722 2
 
1.4%
Other values (123) 124
84.9%
ValueCountFrequency (%)
440696.113207812 1
0.7%
440823.229256059 1
0.7%
441446.0 1
0.7%
441477.658542 1
0.7%
441936.410717522 2
1.4%
441969.456994265 1
0.7%
442004.621552314 1
0.7%
442005.874997848 1
0.7%
442007.364271848 1
0.7%
442010.720306467 1
0.7%
ValueCountFrequency (%)
447989.476527322 1
0.7%
447771.722892482 1
0.7%
447682.780497131 1
0.7%
447157.697879202 1
0.7%
447120.577229325 1
0.7%
446539.279382444 2
1.4%
446381.991026383 2
1.4%
446085.121305444 1
0.7%
446067.280052782 1
0.7%
446061.439207259 1
0.7%

환경업무구분명
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
대기배출업소관리
103 
<NA>
43 

Length

Max length8
Median length8
Mean length6.8219178
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대기배출업소관리 103
70.5%
<NA> 43
29.5%

Length

2024-04-30T04:55:03.425788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:03.513614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기배출업소관리 103
70.5%
na 43
29.5%

업종구분명
Categorical

Distinct32
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
44 
자동차 수리업
33 
부동산업
11 
택시 운송업
10 
부동산 임대업
6 
Other values (27)
42 

Length

Max length16
Median length15
Mean length6.1575342
Min length3

Unique

Unique18 ?
Unique (%)12.3%

Sample

1st row자동차 수리업
2nd row<NA>
3rd row자동차 수리업
4th row자동차 수리업
5th row택시 운송업

Common Values

ValueCountFrequency (%)
<NA> 44
30.1%
자동차 수리업 33
22.6%
부동산업 11
 
7.5%
택시 운송업 10
 
6.8%
부동산 임대업 6
 
4.1%
사업시설 유지관리 서비스업 5
 
3.4%
부동산 관리업 4
 
2.7%
주차장 운영업 3
 
2.1%
시내버스 운송업 2
 
1.4%
발전업 2
 
1.4%
Other values (22) 26
17.8%

Length

2024-04-30T04:55:03.605228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 44
17.8%
수리업 34
13.8%
자동차 34
13.8%
부동산 14
 
5.7%
운송업 13
 
5.3%
부동산업 11
 
4.5%
택시 10
 
4.0%
서비스업 9
 
3.6%
임대업 9
 
3.6%
운영업 5
 
2.0%
Other values (38) 64
25.9%

종별명
Categorical

Distinct4
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
5종
84 
<NA>
43 
4종
18 
2종
 
1

Length

Max length4
Median length2
Mean length2.5890411
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
5종 84
57.5%
<NA> 43
29.5%
4종 18
 
12.3%
2종 1
 
0.7%

Length

2024-04-30T04:55:03.731571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:03.846267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5종 84
57.5%
na 43
29.5%
4종 18
 
12.3%
2종 1
 
0.7%

주생산품명
Text

MISSING 

Distinct5
Distinct (%)71.4%
Missing139
Missing (%)95.2%
Memory size1.3 KiB
2024-04-30T04:55:03.951637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.1428571
Min length2

Characters and Unicode

Total characters22
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)57.1%

Sample

1st row분쇄
2nd row보일러
3rd row보일러
4th row자동차도장
5th row보일러
ValueCountFrequency (%)
보일러 3
42.9%
분쇄 1
 
14.3%
자동차도장 1
 
14.3%
도장시설 1
 
14.3%
임대 1
 
14.3%
2024-04-30T04:55:04.156255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 3
13.6%
일 3
13.6%
러 3
13.6%
도 2
9.1%
장 2
9.1%
분 1
 
4.5%
쇄 1
 
4.5%
자 1
 
4.5%
동 1
 
4.5%
차 1
 
4.5%
Other values (4) 4
18.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 3
13.6%
일 3
13.6%
러 3
13.6%
도 2
9.1%
장 2
9.1%
분 1
 
4.5%
쇄 1
 
4.5%
자 1
 
4.5%
동 1
 
4.5%
차 1
 
4.5%
Other values (4) 4
18.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 3
13.6%
일 3
13.6%
러 3
13.6%
도 2
9.1%
장 2
9.1%
분 1
 
4.5%
쇄 1
 
4.5%
자 1
 
4.5%
동 1
 
4.5%
차 1
 
4.5%
Other values (4) 4
18.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 3
13.6%
일 3
13.6%
러 3
13.6%
도 2
9.1%
장 2
9.1%
분 1
 
4.5%
쇄 1
 
4.5%
자 1
 
4.5%
동 1
 
4.5%
차 1
 
4.5%
Other values (4) 4
18.2%

배출시설조업시간
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)26.1%
Missing100
Missing (%)68.5%
Infinite0
Infinite (%)0.0%
Mean6.0326087
Minimum2
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-30T04:55:04.250964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q13.25
median6
Q38
95-th percentile10
Maximum18
Range16
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation3.3836242
Coefficient of variation (CV)0.56088906
Kurtosis2.6640736
Mean6.0326087
Median Absolute Deviation (MAD)2
Skewness1.2001673
Sum277.5
Variance11.448913
MonotonicityNot monotonic
2024-04-30T04:55:04.350339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8.0 14
 
9.6%
2.0 8
 
5.5%
4.0 6
 
4.1%
6.0 5
 
3.4%
3.0 4
 
2.7%
5.0 2
 
1.4%
10.0 2
 
1.4%
7.0 1
 
0.7%
9.0 1
 
0.7%
18.0 1
 
0.7%
Other values (2) 2
 
1.4%
(Missing) 100
68.5%
ValueCountFrequency (%)
2.0 8
5.5%
3.0 4
 
2.7%
4.0 6
4.1%
4.5 1
 
0.7%
5.0 2
 
1.4%
6.0 5
 
3.4%
7.0 1
 
0.7%
8.0 14
9.6%
9.0 1
 
0.7%
10.0 2
 
1.4%
ValueCountFrequency (%)
18.0 1
 
0.7%
15.0 1
 
0.7%
10.0 2
 
1.4%
9.0 1
 
0.7%
8.0 14
9.6%
7.0 1
 
0.7%
6.0 5
 
3.4%
5.0 2
 
1.4%
4.5 1
 
0.7%
4.0 6
4.1%

배출시설연간가동일수
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)29.7%
Missing72
Missing (%)49.3%
Infinite0
Infinite (%)0.0%
Mean145.16216
Minimum0
Maximum365
Zeros29
Zeros (%)19.9%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-30T04:55:04.457293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median107
Q3300
95-th percentile365
Maximum365
Range365
Interquartile range (IQR)300

Descriptive statistics

Standard deviation142.80747
Coefficient of variation (CV)0.98377888
Kurtosis-1.6122407
Mean145.16216
Median Absolute Deviation (MAD)107
Skewness0.29818568
Sum10742
Variance20393.973
MonotonicityNot monotonic
2024-04-30T04:55:04.557282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 29
19.9%
300 14
 
9.6%
365 5
 
3.4%
100 4
 
2.7%
120 2
 
1.4%
360 2
 
1.4%
350 2
 
1.4%
240 2
 
1.4%
114 1
 
0.7%
30 1
 
0.7%
Other values (12) 12
 
8.2%
(Missing) 72
49.3%
ValueCountFrequency (%)
0 29
19.9%
30 1
 
0.7%
60 1
 
0.7%
71 1
 
0.7%
100 4
 
2.7%
104 1
 
0.7%
110 1
 
0.7%
114 1
 
0.7%
120 2
 
1.4%
125 1
 
0.7%
ValueCountFrequency (%)
365 5
 
3.4%
360 2
 
1.4%
350 2
 
1.4%
330 1
 
0.7%
300 14
9.6%
270 1
 
0.7%
250 1
 
0.7%
240 2
 
1.4%
200 1
 
0.7%
183 1
 
0.7%

방지시설조업시간
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)31.2%
Missing114
Missing (%)78.1%
Infinite0
Infinite (%)0.0%
Mean13.1875
Minimum2
Maximum240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-30T04:55:04.657608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q13.75
median6
Q38
95-th percentile12.25
Maximum240
Range238
Interquartile range (IQR)4.25

Descriptive statistics

Standard deviation41.494996
Coefficient of variation (CV)3.14654
Kurtosis31.640136
Mean13.1875
Median Absolute Deviation (MAD)2
Skewness5.610792
Sum422
Variance1721.8347
MonotonicityNot monotonic
2024-04-30T04:55:04.747961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
8 11
 
7.5%
2 6
 
4.1%
4 4
 
2.7%
6 3
 
2.1%
3 2
 
1.4%
5 2
 
1.4%
7 1
 
0.7%
240 1
 
0.7%
15 1
 
0.7%
10 1
 
0.7%
(Missing) 114
78.1%
ValueCountFrequency (%)
2 6
4.1%
3 2
 
1.4%
4 4
 
2.7%
5 2
 
1.4%
6 3
 
2.1%
7 1
 
0.7%
8 11
7.5%
10 1
 
0.7%
15 1
 
0.7%
240 1
 
0.7%
ValueCountFrequency (%)
240 1
 
0.7%
15 1
 
0.7%
10 1
 
0.7%
8 11
7.5%
7 1
 
0.7%
6 3
 
2.1%
5 2
 
1.4%
4 4
 
2.7%
3 2
 
1.4%
2 6
4.1%

방지시설연간가동일수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)25.0%
Missing82
Missing (%)56.2%
Infinite0
Infinite (%)0.0%
Mean134.375
Minimum0
Maximum365
Zeros32
Zeros (%)21.9%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-30T04:55:04.832683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median30
Q3300
95-th percentile365
Maximum365
Range365
Interquartile range (IQR)300

Descriptive statistics

Standard deviation147.39134
Coefficient of variation (CV)1.0968658
Kurtosis-1.703425
Mean134.375
Median Absolute Deviation (MAD)30
Skewness0.35088437
Sum8600
Variance21724.206
MonotonicityNot monotonic
2024-04-30T04:55:04.928936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 32
 
21.9%
300 13
 
8.9%
365 5
 
3.4%
240 2
 
1.4%
180 1
 
0.7%
200 1
 
0.7%
100 1
 
0.7%
350 1
 
0.7%
250 1
 
0.7%
270 1
 
0.7%
Other values (6) 6
 
4.1%
(Missing) 82
56.2%
ValueCountFrequency (%)
0 32
21.9%
60 1
 
0.7%
100 1
 
0.7%
120 1
 
0.7%
125 1
 
0.7%
150 1
 
0.7%
180 1
 
0.7%
200 1
 
0.7%
240 2
 
1.4%
250 1
 
0.7%
ValueCountFrequency (%)
365 5
 
3.4%
350 1
 
0.7%
330 1
 
0.7%
300 13
8.9%
270 1
 
0.7%
260 1
 
0.7%
250 1
 
0.7%
240 2
 
1.4%
200 1
 
0.7%
180 1
 
0.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
0323000032300002120030001120031126<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 송파구 오금동 155-10서울특별시 송파구 동남로24길 17 (오금동)138130(주)우주카독크2021-10-20 09:32:24U2021-10-22 02:40:00.0자동차 수리업212136.079004444133.523606대기배출업소관리자동차 수리업5종<NA><NA>0<NA>0
132300003230000212004000072004-03-23<NA>1영업/정상11영업<NA><NA><NA><NA>401-1141<NA><NA>서울특별시 송파구 가락동 156-5서울특별시 송파구 중대로 204 (가락동)05818주식회사 대림정비공업사2023-05-01 14:18:48U2022-12-05 00:03:00.0자동차 수리업211147.426358444203.537058<NA><NA><NA><NA><NA><NA><NA><NA>
2323000032300002120040000820040323<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 송파구 가락동 156-2서울특별시 송파구 중대로 208 (가락동)<NA>명진카독크공업주식회사2021-12-24 09:49:13U2021-12-26 02:40:00.0자동차 수리업211164.91664444238.069227대기배출업소관리자동차 수리업5종<NA>8.03008300
3323000032300002120040001020040406<NA>1영업/정상11영업<NA><NA><NA><NA>02-402-6358<NA><NA>서울특별시 송파구 가락동 46-15서울특별시 송파구 오금로36길 56 (가락동)<NA>대신자동차공업사2021-11-10 17:48:36U2021-11-12 02:40:00.0자동차 수리업210739.339578444120.262394대기배출업소관리자동차 수리업5종<NA><NA>0<NA>0
4323000032300002120040001520040409<NA>1영업/정상11영업<NA><NA><NA><NA>473-8313<NA><NA>서울특별시 송파구 풍납동 163-5서울특별시 송파구 풍성로 53 (풍납동)<NA>공신통운(주)2021-04-22 17:02:00U2021-04-24 02:40:00.0택시 운송업210394.264588447989.476527대기배출업소관리택시 운송업5종<NA><NA><NA><NA><NA>
5323000032300002120040001620040409<NA>1영업/정상11영업<NA><NA><NA><NA>02 4484178<NA><NA>서울특별시 송파구 오금동 145-13서울특별시 송파구 문정로 231 (오금동)<NA>동서울자동차공업사2021-09-17 11:05:48U2021-09-19 02:40:00.0자동차 수리업212399.107558444098.987653대기배출업소관리자동차 수리업5종<NA><NA>0<NA>0
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7323000032300002120040002020040419<NA>3폐업2폐업20170720<NA><NA><NA><NA><NA><NA>서울특별시 송파구 문정동 83-24번지서울특별시 송파구 새말로 116 (문정동)<NA>서울자동차공업사2019-07-26 16:11:35U2019-07-28 02:40:00.0자동차 수리업211161.760372442283.047494대기배출업소관리자동차 수리업5종<NA><NA><NA><NA><NA>
8323000032300002120040003120040604<NA>3폐업2폐업20130130<NA><NA><NA>9925985<NA><NA>서울특별시 송파구 마천동 8-2번지서울특별시 송파구 성내천로 165 (마천동)<NA>동아상운(주)2013-01-30 16:18:01I2018-10-04 11:12:49.0택시 운송업212860.467149444319.55536대기배출업소관리택시 운송업5종<NA><NA><NA><NA><NA>
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개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
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142323000032300002120220000420220812<NA>1영업/정상11영업<NA><NA><NA><NA>024088509<NA><NA>서울특별시 송파구 가락동 913 헬리오시티서울특별시 송파구 송파대로 345, 상가1-A동 B1층 146호 (가락동, 헬리오시티)05698송파헬리오시티상가관리단 주식회사2022-09-13 10:46:30U2021-12-08 23:05:00.0비주거용 부동산 관리업209416.46996444027.495849<NA><NA><NA><NA><NA><NA><NA><NA>
143323000032300002120220000520221020<NA>1영업/정상11영업<NA><NA><NA><NA>403-7008<NA><NA>서울특별시 송파구 가락동 140 쌍용프라자상가서울특별시 송파구 동남로 189, 쌍용프라자상가 (가락동)05823쌍용프라자상가번영회2022-10-21 09:15:31U2021-10-30 22:03:00.0부동산업211259.909778443711.702922<NA><NA><NA><NA><NA><NA><NA><NA>
144323000032300002120220000620221114<NA>1영업/정상11영업<NA><NA><NA><NA>02-2203-8494<NA><NA>서울특별시 송파구 신천동 7-22서울특별시 송파구 올림픽로 295 (신천동)05510삼성생명(주) 잠실빌딩2022-11-14 17:48:45I2021-10-31 23:06:00.0부동산업209052.28013445853.01154<NA><NA><NA><NA><NA><NA><NA><NA>
145323000032300002120220000720221212<NA>1영업/정상11영업<NA><NA><NA><NA>02-3434-1116<NA><NA>서울특별시 송파구 신천동 7-17 웰리스타워,삼성웰리스아파트서울특별시 송파구 송파대로 562 (신천동, 웰리스타워,삼성웰리스아파트)05510페블스톤전문투자형사모 부동산투자신탁제8호2022-12-19 16:36:02U2021-11-01 22:01:00.0부동산업208730.633457445905.025545<NA><NA><NA><NA><NA><NA><NA><NA>