Overview

Dataset statistics

Number of variables12
Number of observations282
Missing cells854
Missing cells (%)25.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.5 KiB
Average record size in memory103.5 B

Variable types

Categorical3
Text3
Unsupported3
Numeric3

Dataset

Description경기도_대기오염물질 총량관리사업장 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=51849Z55259T4T890V0211771334&infSeq=1

Alerts

집계년도 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
SOX할당대상여부 has 282 (100.0%) missing valuesMissing
NOX할당대상여부 has 282 (100.0%) missing valuesMissing
허가일자 has 282 (100.0%) missing valuesMissing
소재지도로명주소 has 3 (1.1%) missing valuesMissing
업체명 has unique valuesUnique
SOX할당대상여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
NOX할당대상여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
허가일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 21:18:14.283217
Analysis finished2023-12-10 21:18:15.881705
Duration1.6 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2022
282 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 282
100.0%

Length

2023-12-11T06:18:15.948051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:18:16.026608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 282
100.0%

시군명
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
안산시
55 
평택시
33 
양주시
24 
화성시
20 
시흥시
16 
Other values (23)
134 

Length

Max length4
Median length3
Mean length3.0390071
Min length3

Unique

Unique4 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
안산시 55
19.5%
평택시 33
11.7%
양주시 24
 
8.5%
화성시 20
 
7.1%
시흥시 16
 
5.7%
포천시 13
 
4.6%
파주시 12
 
4.3%
이천시 12
 
4.3%
용인시 12
 
4.3%
여주시 10
 
3.5%
Other values (18) 75
26.6%

Length

2023-12-11T06:18:16.112789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안산시 55
19.5%
평택시 33
11.7%
양주시 24
 
8.5%
화성시 20
 
7.1%
시흥시 16
 
5.7%
포천시 13
 
4.6%
파주시 12
 
4.3%
이천시 12
 
4.3%
용인시 12
 
4.3%
여주시 10
 
3.5%
Other values (18) 75
26.6%

업체명
Text

UNIQUE 

Distinct282
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-11T06:18:16.312190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length8.7765957
Min length2

Characters and Unicode

Total characters2475
Distinct characters294
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique282 ?
Unique (%)100.0%

Sample

1st row한국지역난방공사삼송지사
2nd row고양시 환경에너지 시설
3rd row한국동서발전(주) 일산화력본부
4th row한국지역난방공사 중앙지사(난지)
5th row서대문구청(난지물재생센터)
ValueCountFrequency (%)
한국지역난방공사 9
 
2.6%
구 3
 
0.9%
㈜코리아써키트 2
 
0.6%
평택공장 2
 
0.6%
㈜디에이피 2
 
0.6%
주 2
 
0.6%
여주공장 2
 
0.6%
안성공장 2
 
0.6%
㈜단석산업 2
 
0.6%
나래에너지서비스㈜ 2
 
0.6%
Other values (312) 314
91.8%
2023-12-11T06:18:16.904550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 181
 
7.3%
지 75
 
3.0%
) 69
 
2.8%
공 66
 
2.7%
주 64
 
2.6%
스 62
 
2.5%
( 62
 
2.5%
60
 
2.4%
시 51
 
2.1%
에 50
 
2.0%
Other values (284) 1735
70.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2059
83.2%
Other Symbol 181
 
7.3%
Close Punctuation 70
 
2.8%
Open Punctuation 63
 
2.5%
Space Separator 60
 
2.4%
Uppercase Letter 25
 
1.0%
Decimal Number 12
 
0.5%
Lowercase Letter 3
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 75
 
3.6%
공 66
 
3.2%
주 64
 
3.1%
스 62
 
3.0%
시 51
 
2.5%
에 50
 
2.4%
장 47
 
2.3%
업 47
 
2.3%
이 46
 
2.2%
사 36
 
1.7%
Other values (258) 1515
73.6%
Uppercase Letter
ValueCountFrequency (%)
S 6
24.0%
K 3
12.0%
G 3
12.0%
P 2
 
8.0%
L 2
 
8.0%
M 2
 
8.0%
C 1
 
4.0%
D 1
 
4.0%
B 1
 
4.0%
F 1
 
4.0%
Other values (3) 3
12.0%
Decimal Number
ValueCountFrequency (%)
2 9
75.0%
1 2
 
16.7%
4 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
x 1
33.3%
t 1
33.3%
s 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 69
98.6%
] 1
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 62
98.4%
[ 1
 
1.6%
Other Symbol
ValueCountFrequency (%)
㈜ 181
100.0%
Space Separator
ValueCountFrequency (%)
60
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2240
90.5%
Common 207
 
8.4%
Latin 28
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 181
 
8.1%
지 75
 
3.3%
공 66
 
2.9%
주 64
 
2.9%
스 62
 
2.8%
시 51
 
2.3%
에 50
 
2.2%
장 47
 
2.1%
업 47
 
2.1%
이 46
 
2.1%
Other values (259) 1551
69.2%
Latin
ValueCountFrequency (%)
S 6
21.4%
K 3
10.7%
G 3
10.7%
P 2
 
7.1%
L 2
 
7.1%
M 2
 
7.1%
C 1
 
3.6%
D 1
 
3.6%
B 1
 
3.6%
F 1
 
3.6%
Other values (6) 6
21.4%
Common
ValueCountFrequency (%)
) 69
33.3%
( 62
30.0%
60
29.0%
2 9
 
4.3%
. 2
 
1.0%
1 2
 
1.0%
[ 1
 
0.5%
] 1
 
0.5%
4 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2059
83.2%
ASCII 235
 
9.5%
None 181
 
7.3%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 181
100.0%
Hangul
ValueCountFrequency (%)
지 75
 
3.6%
공 66
 
3.2%
주 64
 
3.1%
스 62
 
3.0%
시 51
 
2.5%
에 50
 
2.4%
장 47
 
2.3%
업 47
 
2.3%
이 46
 
2.2%
사 36
 
1.7%
Other values (258) 1515
73.6%
ASCII
ValueCountFrequency (%)
) 69
29.4%
( 62
26.4%
60
25.5%
2 9
 
3.8%
S 6
 
2.6%
K 3
 
1.3%
G 3
 
1.3%
. 2
 
0.9%
P 2
 
0.9%
L 2
 
0.9%
Other values (15) 17
 
7.2%

대기종별구분명
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
1종
179 
2종
83 
3종
20 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1종
2nd row1종
3rd row1종
4th row1종
5th row3종

Common Values

ValueCountFrequency (%)
1종 179
63.5%
2종 83
29.4%
3종 20
 
7.1%

Length

2023-12-11T06:18:17.031334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:18:17.146391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1종 179
63.5%
2종 83
29.4%
3종 20
 
7.1%

SOX할당대상여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing282
Missing (%)100.0%
Memory size2.6 KiB

NOX할당대상여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing282
Missing (%)100.0%
Memory size2.6 KiB

허가일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing282
Missing (%)100.0%
Memory size2.6 KiB

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct202
Distinct (%)72.1%
Missing2
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean14890.586
Minimum10044
Maximum18630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T06:18:17.245325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10044
5-th percentile10845
Q112615
median15419
Q317324.5
95-th percentile18451.85
Maximum18630
Range8586
Interquartile range (IQR)4709.5

Descriptive statistics

Standard deviation2587.4381
Coefficient of variation (CV)0.17376335
Kurtosis-1.2352526
Mean14890.586
Median Absolute Deviation (MAD)2202.5
Skewness-0.2974441
Sum4169364
Variance6694836.1
MonotonicityNot monotonic
2023-12-11T06:18:17.369092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11138 7
 
2.5%
11413 6
 
2.1%
18126 4
 
1.4%
15619 4
 
1.4%
11426 4
 
1.4%
17949 3
 
1.1%
11303 3
 
1.1%
15434 3
 
1.1%
17956 3
 
1.1%
11410 3
 
1.1%
Other values (192) 240
85.1%
ValueCountFrequency (%)
10044 1
 
0.4%
10066 1
 
0.4%
10443 2
0.7%
10542 3
1.1%
10594 1
 
0.4%
10816 1
 
0.4%
10826 1
 
0.4%
10835 1
 
0.4%
10837 1
 
0.4%
10844 1
 
0.4%
ValueCountFrequency (%)
18630 1
0.4%
18626 1
0.4%
18624 1
0.4%
18623 1
0.4%
18571 1
0.4%
18542 2
0.7%
18535 1
0.4%
18527 1
0.4%
18525 1
0.4%
18522 1
0.4%

소재지지번주소
Text

Distinct270
Distinct (%)96.1%
Missing1
Missing (%)0.4%
Memory size2.3 KiB
2023-12-11T06:18:17.612009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length21.177936
Min length15

Characters and Unicode

Total characters5951
Distinct characters173
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique260 ?
Unique (%)92.5%

Sample

1st row경기도 고양시 덕양구 동산동 378번지
2nd row경기도 고양시 일산동구 백석동 1234번지
3rd row경기도 고양시 일산동구 백석동 1143-1번지
4th row경기도 고양시 덕양구 현천동 692-2번지
5th row경기도 고양시 덕양구 현천동 692-2번지
ValueCountFrequency (%)
경기도 281
 
21.0%
안산시 56
 
4.2%
단원구 55
 
4.1%
평택시 31
 
2.3%
성곡동 28
 
2.1%
양주시 24
 
1.8%
화성시 20
 
1.5%
정왕동 16
 
1.2%
시흥시 16
 
1.2%
이천시 13
 
1.0%
Other values (481) 796
59.6%
2023-12-11T06:18:18.019571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1055
 
17.7%
시 307
 
5.2%
지 288
 
4.8%
기 287
 
4.8%
도 286
 
4.8%
경 285
 
4.8%
번 276
 
4.6%
동 192
 
3.2%
1 182
 
3.1%
- 155
 
2.6%
Other values (163) 2638
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3735
62.8%
Space Separator 1055
 
17.7%
Decimal Number 1004
 
16.9%
Dash Punctuation 155
 
2.6%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 307
 
8.2%
지 288
 
7.7%
기 287
 
7.7%
도 286
 
7.7%
경 285
 
7.6%
번 276
 
7.4%
동 192
 
5.1%
리 116
 
3.1%
구 102
 
2.7%
원 90
 
2.4%
Other values (150) 1506
40.3%
Decimal Number
ValueCountFrequency (%)
1 182
18.1%
2 134
13.3%
6 121
12.1%
4 103
10.3%
5 92
9.2%
3 89
8.9%
7 87
8.7%
0 72
 
7.2%
9 67
 
6.7%
8 57
 
5.7%
Space Separator
ValueCountFrequency (%)
1055
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 155
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3735
62.8%
Common 2216
37.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 307
 
8.2%
지 288
 
7.7%
기 287
 
7.7%
도 286
 
7.7%
경 285
 
7.6%
번 276
 
7.4%
동 192
 
5.1%
리 116
 
3.1%
구 102
 
2.7%
원 90
 
2.4%
Other values (150) 1506
40.3%
Common
ValueCountFrequency (%)
1055
47.6%
1 182
 
8.2%
- 155
 
7.0%
2 134
 
6.0%
6 121
 
5.5%
4 103
 
4.6%
5 92
 
4.2%
3 89
 
4.0%
7 87
 
3.9%
0 72
 
3.2%
Other values (3) 126
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3735
62.8%
ASCII 2216
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1055
47.6%
1 182
 
8.2%
- 155
 
7.0%
2 134
 
6.0%
6 121
 
5.5%
4 103
 
4.6%
5 92
 
4.2%
3 89
 
4.0%
7 87
 
3.9%
0 72
 
3.2%
Other values (3) 126
 
5.7%
Hangul
ValueCountFrequency (%)
시 307
 
8.2%
지 288
 
7.7%
기 287
 
7.7%
도 286
 
7.7%
경 285
 
7.6%
번 276
 
7.4%
동 192
 
5.1%
리 116
 
3.1%
구 102
 
2.7%
원 90
 
2.4%
Other values (150) 1506
40.3%

소재지도로명주소
Text

MISSING 

Distinct268
Distinct (%)96.1%
Missing3
Missing (%)1.1%
Memory size2.3 KiB
2023-12-11T06:18:18.282103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length19.935484
Min length14

Characters and Unicode

Total characters5562
Distinct characters210
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique258 ?
Unique (%)92.5%

Sample

1st row경기도 고양시 덕양구 동축로 16
2nd row경기도 고양시 일산동구 경의로 115
3rd row경기도 고양시 일산동구 경의로 201
4th row경기도 고양시 덕양구 대덕로 426
5th row경기도 고양시 덕양구 대덕로 426
ValueCountFrequency (%)
경기도 279
 
21.0%
안산시 56
 
4.2%
단원구 55
 
4.1%
평택시 30
 
2.3%
양주시 24
 
1.8%
화성시 20
 
1.5%
시흥시 16
 
1.2%
이천시 13
 
1.0%
포천시 12
 
0.9%
남면 12
 
0.9%
Other values (486) 810
61.0%
2023-12-11T06:18:18.700447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1048
18.8%
시 303
 
5.4%
기 295
 
5.3%
경 290
 
5.2%
도 283
 
5.1%
로 261
 
4.7%
1 203
 
3.6%
2 140
 
2.5%
3 105
 
1.9%
구 104
 
1.9%
Other values (200) 2530
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3460
62.2%
Space Separator 1048
 
18.8%
Decimal Number 1006
 
18.1%
Dash Punctuation 46
 
0.8%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 303
 
8.8%
기 295
 
8.5%
경 290
 
8.4%
도 283
 
8.2%
로 261
 
7.5%
구 104
 
3.0%
안 94
 
2.7%
단 90
 
2.6%
길 90
 
2.6%
산 83
 
2.4%
Other values (187) 1567
45.3%
Decimal Number
ValueCountFrequency (%)
1 203
20.2%
2 140
13.9%
3 105
10.4%
5 103
10.2%
7 92
9.1%
6 87
8.6%
4 86
8.5%
8 66
 
6.6%
0 64
 
6.4%
9 60
 
6.0%
Space Separator
ValueCountFrequency (%)
1048
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3460
62.2%
Common 2102
37.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 303
 
8.8%
기 295
 
8.5%
경 290
 
8.4%
도 283
 
8.2%
로 261
 
7.5%
구 104
 
3.0%
안 94
 
2.7%
단 90
 
2.6%
길 90
 
2.6%
산 83
 
2.4%
Other values (187) 1567
45.3%
Common
ValueCountFrequency (%)
1048
49.9%
1 203
 
9.7%
2 140
 
6.7%
3 105
 
5.0%
5 103
 
4.9%
7 92
 
4.4%
6 87
 
4.1%
4 86
 
4.1%
8 66
 
3.1%
0 64
 
3.0%
Other values (3) 108
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3460
62.2%
ASCII 2102
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1048
49.9%
1 203
 
9.7%
2 140
 
6.7%
3 105
 
5.0%
5 103
 
4.9%
7 92
 
4.4%
6 87
 
4.1%
4 86
 
4.1%
8 66
 
3.1%
0 64
 
3.0%
Other values (3) 108
 
5.1%
Hangul
ValueCountFrequency (%)
시 303
 
8.8%
기 295
 
8.5%
경 290
 
8.4%
도 283
 
8.2%
로 261
 
7.5%
구 104
 
3.0%
안 94
 
2.7%
단 90
 
2.6%
길 90
 
2.6%
산 83
 
2.4%
Other values (187) 1567
45.3%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct270
Distinct (%)96.1%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean37.396911
Minimum36.955851
Maximum38.049731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T06:18:18.822439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.955851
5-th percentile36.992297
Q137.226486
median37.317602
Q337.551001
95-th percentile37.945045
Maximum38.049731
Range1.0938801
Interquartile range (IQR)0.3245154

Descriptive statistics

Standard deviation0.28737129
Coefficient of variation (CV)0.0076843589
Kurtosis-0.5538164
Mean37.396911
Median Absolute Deviation (MAD)0.12622659
Skewness0.67538316
Sum10508.532
Variance0.082582258
MonotonicityNot monotonic
2023-12-11T06:18:18.942081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5865557413 3
 
1.1%
37.8767440783 2
 
0.7%
37.7371384256 2
 
0.7%
37.1404734573 2
 
0.7%
37.2912367512 2
 
0.7%
37.2942111936 2
 
0.7%
37.9698756561 2
 
0.7%
37.2529797883 2
 
0.7%
37.2286936056 2
 
0.7%
37.0077477207 2
 
0.7%
Other values (260) 260
92.2%
ValueCountFrequency (%)
36.9558508975 1
0.4%
36.9596905456 1
0.4%
36.9625293001 1
0.4%
36.96312043 1
0.4%
36.9641156187 1
0.4%
36.9699198762 1
0.4%
36.974678674 1
0.4%
36.9768651298 1
0.4%
36.9779988613 1
0.4%
36.980883917 1
0.4%
ValueCountFrequency (%)
38.0497310076 1
0.4%
38.0077493853 1
0.4%
38.0069365787 1
0.4%
37.9911661267 1
0.4%
37.9698756561 2
0.7%
37.967634585 1
0.4%
37.9584646161 1
0.4%
37.9542132822 1
0.4%
37.9534345236 1
0.4%
37.9530985921 1
0.4%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct270
Distinct (%)96.1%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean126.98054
Minimum126.5988
Maximum127.7169
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T06:18:19.066716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5988
5-th percentile126.7197
Q1126.77925
median126.95822
Q3127.08843
95-th percentile127.48806
Maximum127.7169
Range1.1180958
Interquartile range (IQR)0.30917417

Descriptive statistics

Standard deviation0.2324766
Coefficient of variation (CV)0.0018308049
Kurtosis0.58833129
Mean126.98054
Median Absolute Deviation (MAD)0.16764842
Skewness0.98557153
Sum35681.532
Variance0.054045371
MonotonicityNot monotonic
2023-12-11T06:18:19.200378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8471495102 3
 
1.1%
127.0073702677 2
 
0.7%
126.7676914345 2
 
0.7%
127.0558595685 2
 
0.7%
127.5046708416 2
 
0.7%
127.4920909297 2
 
0.7%
127.064732998 2
 
0.7%
127.4806834787 2
 
0.7%
127.0830303783 2
 
0.7%
126.7982169096 2
 
0.7%
Other values (260) 260
92.2%
ValueCountFrequency (%)
126.5988021136 1
0.4%
126.6380537927 1
0.4%
126.6947327633 1
0.4%
126.6998349146 1
0.4%
126.7046172017 1
0.4%
126.7064053189 1
0.4%
126.7064860832 1
0.4%
126.7072651919 1
0.4%
126.7090570674 1
0.4%
126.7106215785 1
0.4%
ValueCountFrequency (%)
127.7168978736 1
0.4%
127.7159401627 1
0.4%
127.6582715041 1
0.4%
127.653474376 1
0.4%
127.6438940339 1
0.4%
127.593153731 1
0.4%
127.5771767 1
0.4%
127.536174276 1
0.4%
127.5285081815 1
0.4%
127.5046708416 2
0.7%

Interactions

2023-12-11T06:18:15.263065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:18:14.740036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:18:14.973606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:18:15.337143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:18:14.813739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:18:15.062405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:18:15.413682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:18:14.886474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:18:15.162879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:18:19.309109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명대기종별구분명소재지우편번호WGS84위도WGS84경도
시군명1.0000.1690.9850.9650.934
대기종별구분명0.1691.0000.2820.2460.000
소재지우편번호0.9850.2821.0000.9290.885
WGS84위도0.9650.2460.9291.0000.776
WGS84경도0.9340.0000.8850.7761.000
2023-12-11T06:18:19.410517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명대기종별구분명
시군명1.0000.080
대기종별구분명0.0801.000
2023-12-11T06:18:19.496824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명대기종별구분명
소재지우편번호1.000-0.9150.0530.8680.163
WGS84위도-0.9151.000-0.0950.7760.149
WGS84경도0.053-0.0951.0000.6690.000
시군명0.8680.7760.6691.0000.080
대기종별구분명0.1630.1490.0000.0801.000

Missing values

2023-12-11T06:18:15.533182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:18:15.693707image/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.
2023-12-11T06:18:15.814636image/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

집계년도시군명업체명대기종별구분명SOX할당대상여부NOX할당대상여부허가일자소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
02022고양시한국지역난방공사삼송지사1종<NA><NA><NA>10594경기도 고양시 덕양구 동산동 378번지경기도 고양시 덕양구 동축로 1637.647911126.905173
12022고양시고양시 환경에너지 시설1종<NA><NA><NA>10443경기도 고양시 일산동구 백석동 1234번지경기도 고양시 일산동구 경의로 11537.643322126.796078
22022고양시한국동서발전(주) 일산화력본부1종<NA><NA><NA>10443경기도 고양시 일산동구 백석동 1143-1번지경기도 고양시 일산동구 경의로 20137.645292126.797023
32022고양시한국지역난방공사 중앙지사(난지)1종<NA><NA><NA>10542경기도 고양시 덕양구 현천동 692-2번지경기도 고양시 덕양구 대덕로 42637.586556126.84715
42022고양시서대문구청(난지물재생센터)3종<NA><NA><NA>10542경기도 고양시 덕양구 현천동 692-2번지경기도 고양시 덕양구 대덕로 42637.586556126.84715
52022고양시서울특별시 난지물재생센터1종<NA><NA><NA>10542경기도 고양시 덕양구 현천동 692-2번지경기도 고양시 덕양구 대덕로 42637.586556126.84715
62022과천시과천시자원정화센터1종<NA><NA><NA>13824경기도 과천시 갈현동 205-1번지경기도 과천시 구리안로 17737.407178126.993275
72022광명시광명시자원회수시설1종<NA><NA><NA>14341경기도 광명시 가학동 27번지경기도 광명시 가학로85번길 14237.424668126.863444
82022광명시삼천리(주)1종<NA><NA><NA>14354경기도 광명시 일직동 502번지경기도 광명시 자경로 1737.422526126.890848
92022광명시기아자동차(주)소하리공장1종<NA><NA><NA>14323경기도 광명시 소하동 610-1번지경기도 광명시 기아로 11337.440639126.89417
집계년도시군명업체명대기종별구분명SOX할당대상여부NOX할당대상여부허가일자소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
2722022화성시한밭산업㈜화성공장1종<NA><NA><NA>18630경기도 화성시 양감면 정문리 293-21번지경기도 화성시 양감면 정문송산로 6537.098147126.983581
2732022화성시한국지역난방공사 화성지사(서부지사)1종<NA><NA><NA>18450경기도 화성시 석우동 39번지경기도 화성시 큰재봉길 1637.217776127.079991
2742022화성시신대한정유산업(주)1종<NA><NA><NA>18512경기도 화성시 정남면 고지리 28-1번지경기도 화성시 정남면 가장로 334-1037.161057127.01559
2752022화성시남부산업2종<NA><NA><NA>18624경기도 화성시 향남읍 동오리 82-4번지경기도 화성시 향남읍 서봉로 71437.138699126.956587
2762022화성시기아자동차(주)화성공장1종<NA><NA><NA>18571경기도 화성시 우정읍 매향리 966번지경기도 화성시 우정읍 기아자동차로 9537.039269126.788976
2772022화성시핸즈식스㈜2공장1종<NA><NA><NA>18542경기도 화성시 마도면 쌍송리 682-1번지경기도 화성시 마도면 마도공단로6길 1837.179153126.786484
2782022화성시태형기업㈜1종<NA><NA><NA>18522경기도 화성시 정남면 문학리 719-1번지경기도 화성시 정남면 서봉로755번길 1937.144569126.955216
2792022화성시㈜신성아스콘1종<NA><NA><NA>18527경기도 화성시 팔탄면 구장리 513-5번지경기도 화성시 팔탄면 푸른들판로 57637.160402126.898249
2802022화성시우리아스콘(구 남양아스콘㈜)1종<NA><NA><NA>18535경기도 화성시 팔탄면 하저리 15-1번지경기도 화성시 팔탄면 현대기아로556번길 11137.196814126.862827
2812022화성시일진제강(주)1종<NA><NA><NA>18516경기도 화성시 정남면 괘랑리 446-1번지경기도 화성시 정남면 만년로 905-8037.191376126.995025