Overview

Dataset statistics

Number of variables11
Number of observations332
Missing cells11
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.0 KiB
Average record size in memory92.4 B

Variable types

Numeric4
Text4
Categorical3

Dataset

Description경상남도 김해시 토양오염 관리 시설 현황(신고번호, 사업장명, 업종, 지번주소, 도로명주소, 완공일자, 토양오염물질저장용량 등)에 관한 데이터를 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15013379

Alerts

토양오염도검사해당여부(누출검사) is highly overall correlated with 토양오염도검사해당여부(오염도검사)High correlation
토양오염도검사해당여부(오염도검사) is highly overall correlated with 토양오염도검사해당여부(누출검사)High correlation
토양오염도검사해당여부(오염도검사) is highly imbalanced (56.2%)Imbalance
도로명주소 has 11 (3.3%) missing valuesMissing
신고번호 has unique valuesUnique

Reproduction

Analysis started2024-03-13 00:07:58.196000
Analysis finished2024-03-13 00:08:00.077582
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

신고번호
Real number (ℝ)

UNIQUE 

Distinct332
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean166.5
Minimum1
Maximum332
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-03-13T09:08:00.131406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.55
Q183.75
median166.5
Q3249.25
95-th percentile315.45
Maximum332
Range331
Interquartile range (IQR)165.5

Descriptive statistics

Standard deviation95.984374
Coefficient of variation (CV)0.57648273
Kurtosis-1.2
Mean166.5
Median Absolute Deviation (MAD)83
Skewness0
Sum55278
Variance9213
MonotonicityStrictly increasing
2024-03-13T09:08:00.240606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
230 1
 
0.3%
228 1
 
0.3%
227 1
 
0.3%
226 1
 
0.3%
225 1
 
0.3%
224 1
 
0.3%
223 1
 
0.3%
222 1
 
0.3%
221 1
 
0.3%
Other values (322) 322
97.0%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
332 1
0.3%
331 1
0.3%
330 1
0.3%
329 1
0.3%
328 1
0.3%
327 1
0.3%
326 1
0.3%
325 1
0.3%
324 1
0.3%
323 1
0.3%

사업장명
Text

Distinct325
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-03-13T09:08:00.429273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length7.2710843
Min length2

Characters and Unicode

Total characters2414
Distinct characters311
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique318 ?
Unique (%)95.8%

Sample

1st row영진주유소
2nd row예진주유소
3rd row고속도로관리공단 진영(상)주유소
4th row상동농협직영주유소
5th row동방석유㈜직영 부영주유소
ValueCountFrequency (%)
주식회사 9
 
2.2%
한솔유화㈜ 4
 
1.0%
광신석유㈜ 3
 
0.7%
㈜가온에너지 3
 
0.7%
김해지점 3
 
0.7%
㈜한중유화 2
 
0.5%
유공에너지 2
 
0.5%
한길주유소 2
 
0.5%
진영휴게소 2
 
0.5%
㈜에스엔디유통 2
 
0.5%
Other values (368) 382
92.3%
2024-03-13T09:08:00.968697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 206
 
8.5%
주 174
 
7.2%
소 159
 
6.6%
㈜ 146
 
6.0%
85
 
3.5%
에 52
 
2.2%
대 49
 
2.0%
지 49
 
2.0%
이 41
 
1.7%
동 34
 
1.4%
Other values (301) 1419
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2070
85.7%
Other Symbol 146
 
6.0%
Space Separator 85
 
3.5%
Uppercase Letter 46
 
1.9%
Decimal Number 19
 
0.8%
Open Punctuation 18
 
0.7%
Close Punctuation 18
 
0.7%
Other Punctuation 7
 
0.3%
Lowercase Letter 4
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 206
 
10.0%
주 174
 
8.4%
소 159
 
7.7%
에 52
 
2.5%
대 49
 
2.4%
지 49
 
2.4%
이 41
 
2.0%
동 34
 
1.6%
스 33
 
1.6%
화 31
 
1.5%
Other values (265) 1242
60.0%
Uppercase Letter
ValueCountFrequency (%)
C 10
21.7%
I 6
13.0%
K 5
10.9%
S 5
10.9%
E 4
 
8.7%
R 2
 
4.3%
F 2
 
4.3%
O 2
 
4.3%
Y 1
 
2.2%
D 1
 
2.2%
Other values (8) 8
17.4%
Decimal Number
ValueCountFrequency (%)
2 7
36.8%
1 6
31.6%
7 3
15.8%
0 1
 
5.3%
3 1
 
5.3%
5 1
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
f 1
25.0%
l 1
25.0%
e 1
25.0%
s 1
25.0%
Other Punctuation
ValueCountFrequency (%)
: 3
42.9%
. 2
28.6%
, 2
28.6%
Other Symbol
ValueCountFrequency (%)
㈜ 146
100.0%
Space Separator
ValueCountFrequency (%)
85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2216
91.8%
Common 148
 
6.1%
Latin 50
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 206
 
9.3%
주 174
 
7.9%
소 159
 
7.2%
㈜ 146
 
6.6%
에 52
 
2.3%
대 49
 
2.2%
지 49
 
2.2%
이 41
 
1.9%
동 34
 
1.5%
스 33
 
1.5%
Other values (266) 1273
57.4%
Latin
ValueCountFrequency (%)
C 10
20.0%
I 6
12.0%
K 5
10.0%
S 5
10.0%
E 4
 
8.0%
R 2
 
4.0%
F 2
 
4.0%
O 2
 
4.0%
Y 1
 
2.0%
D 1
 
2.0%
Other values (12) 12
24.0%
Common
ValueCountFrequency (%)
85
57.4%
( 18
 
12.2%
) 18
 
12.2%
2 7
 
4.7%
1 6
 
4.1%
7 3
 
2.0%
: 3
 
2.0%
. 2
 
1.4%
, 2
 
1.4%
0 1
 
0.7%
Other values (3) 3
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2070
85.7%
ASCII 198
 
8.2%
None 146
 
6.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 206
 
10.0%
주 174
 
8.4%
소 159
 
7.7%
에 52
 
2.5%
대 49
 
2.4%
지 49
 
2.4%
이 41
 
2.0%
동 34
 
1.6%
스 33
 
1.6%
화 31
 
1.5%
Other values (265) 1242
60.0%
None
ValueCountFrequency (%)
㈜ 146
100.0%
ASCII
ValueCountFrequency (%)
85
42.9%
( 18
 
9.1%
) 18
 
9.1%
C 10
 
5.1%
2 7
 
3.5%
1 6
 
3.0%
I 6
 
3.0%
K 5
 
2.5%
S 5
 
2.5%
E 4
 
2.0%
Other values (25) 34
 
17.2%

업종
Categorical

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
주유소
165 
산업시설
108 
유해화학물질
36 
기타
23 

Length

Max length6
Median length4
Mean length3.5813253
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주유소 165
49.7%
산업시설 108
32.5%
유해화학물질 36
 
10.8%
기타 23
 
6.9%

Length

2024-03-13T09:08:01.083354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T09:08:01.169348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주유소 165
49.7%
산업시설 108
32.5%
유해화학물질 36
 
10.8%
기타 23
 
6.9%

지번주소
Text

Distinct323
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-03-13T09:08:01.348976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length29
Mean length20.89759
Min length15

Characters and Unicode

Total characters6938
Distinct characters114
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

Unique315 ?
Unique (%)94.9%

Sample

1st row경상남도 김해시 내동 495
2nd row경상남도 김해시 어방동 351-8
3rd row경상남도 김해시 진영읍 우동리 377-2
4th row경상남도 김해시 상동면 매리 93-3
5th row경상남도 김해시 진영읍 진영리 319-121
ValueCountFrequency (%)
경상남도 333
20.5%
김해시 333
20.5%
진영읍 51
 
3.1%
한림면 48
 
3.0%
주촌면 33
 
2.0%
외 31
 
1.9%
생림면 30
 
1.8%
진례면 28
 
1.7%
상동면 25
 
1.5%
어방동 21
 
1.3%
Other values (407) 693
42.6%
2024-03-13T09:08:01.650678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1294
18.7%
상 362
 
5.2%
시 334
 
4.8%
경 333
 
4.8%
남 333
 
4.8%
도 333
 
4.8%
김 333
 
4.8%
해 333
 
4.8%
1 284
 
4.1%
- 249
 
3.6%
Other values (104) 2750
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4032
58.1%
Decimal Number 1353
 
19.5%
Space Separator 1294
 
18.7%
Dash Punctuation 249
 
3.6%
Other Punctuation 7
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 362
 
9.0%
시 334
 
8.3%
경 333
 
8.3%
남 333
 
8.3%
도 333
 
8.3%
김 333
 
8.3%
해 333
 
8.3%
리 226
 
5.6%
면 174
 
4.3%
동 169
 
4.2%
Other values (87) 1102
27.3%
Decimal Number
ValueCountFrequency (%)
1 284
21.0%
2 180
13.3%
3 153
11.3%
4 126
9.3%
0 113
 
8.4%
5 113
 
8.4%
7 100
 
7.4%
9 97
 
7.2%
6 94
 
6.9%
8 93
 
6.9%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
: 1
 
14.3%
Space Separator
ValueCountFrequency (%)
1294
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 249
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4032
58.1%
Common 2905
41.9%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 362
 
9.0%
시 334
 
8.3%
경 333
 
8.3%
남 333
 
8.3%
도 333
 
8.3%
김 333
 
8.3%
해 333
 
8.3%
리 226
 
5.6%
면 174
 
4.3%
동 169
 
4.2%
Other values (87) 1102
27.3%
Common
ValueCountFrequency (%)
1294
44.5%
1 284
 
9.8%
- 249
 
8.6%
2 180
 
6.2%
3 153
 
5.3%
4 126
 
4.3%
0 113
 
3.9%
5 113
 
3.9%
7 100
 
3.4%
9 97
 
3.3%
Other values (6) 196
 
6.7%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4032
58.1%
ASCII 2906
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1294
44.5%
1 284
 
9.8%
- 249
 
8.6%
2 180
 
6.2%
3 153
 
5.3%
4 126
 
4.3%
0 113
 
3.9%
5 113
 
3.9%
7 100
 
3.4%
9 97
 
3.3%
Other values (7) 197
 
6.8%
Hangul
ValueCountFrequency (%)
상 362
 
9.0%
시 334
 
8.3%
경 333
 
8.3%
남 333
 
8.3%
도 333
 
8.3%
김 333
 
8.3%
해 333
 
8.3%
리 226
 
5.6%
면 174
 
4.3%
동 169
 
4.2%
Other values (87) 1102
27.3%

도로명주소
Text

MISSING 

Distinct315
Distinct (%)98.1%
Missing11
Missing (%)3.3%
Memory size2.7 KiB
2024-03-13T09:08:01.882912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length31
Mean length22.934579
Min length14

Characters and Unicode

Total characters7362
Distinct characters113
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

Unique309 ?
Unique (%)96.3%

Sample

1st row경상남도 김해시 금관대로 1279 (내동)
2nd row경상남도 김해시 인제로 145 (어방동)
3rd row경상남도 김해시 진영읍 하계로96번길 44-49
4th row경상남도 김해시 상동면 동북로 481
5th row경상남도 김해시 진영읍 진산대로 187
ValueCountFrequency (%)
경상남도 322
20.2%
김해시 321
20.1%
진영읍 51
 
3.2%
김해대로 46
 
2.9%
한림면 43
 
2.7%
주촌면 30
 
1.9%
서부로 29
 
1.8%
생림면 28
 
1.8%
진례면 26
 
1.6%
상동면 24
 
1.5%
Other values (422) 678
42.4%
2024-03-13T09:08:02.233301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1289
17.5%
해 381
 
5.2%
김 380
 
5.2%
상 363
 
4.9%
경 322
 
4.4%
남 322
 
4.4%
도 322
 
4.4%
시 321
 
4.4%
로 321
 
4.4%
1 256
 
3.5%
Other values (103) 3085
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4449
60.4%
Decimal Number 1371
 
18.6%
Space Separator 1289
 
17.5%
Open Punctuation 87
 
1.2%
Close Punctuation 87
 
1.2%
Dash Punctuation 77
 
1.0%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
해 381
 
8.6%
김 380
 
8.5%
상 363
 
8.2%
경 322
 
7.2%
남 322
 
7.2%
도 322
 
7.2%
시 321
 
7.2%
로 321
 
7.2%
면 160
 
3.6%
동 150
 
3.4%
Other values (87) 1407
31.6%
Decimal Number
ValueCountFrequency (%)
1 256
18.7%
2 190
13.9%
4 142
10.4%
3 138
10.1%
5 131
9.6%
6 126
9.2%
9 121
8.8%
7 94
 
6.9%
0 91
 
6.6%
8 82
 
6.0%
Other Punctuation
ValueCountFrequency (%)
: 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
1289
100.0%
Open Punctuation
ValueCountFrequency (%)
( 87
100.0%
Close Punctuation
ValueCountFrequency (%)
) 87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4449
60.4%
Common 2913
39.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
해 381
 
8.6%
김 380
 
8.5%
상 363
 
8.2%
경 322
 
7.2%
남 322
 
7.2%
도 322
 
7.2%
시 321
 
7.2%
로 321
 
7.2%
면 160
 
3.6%
동 150
 
3.4%
Other values (87) 1407
31.6%
Common
ValueCountFrequency (%)
1289
44.2%
1 256
 
8.8%
2 190
 
6.5%
4 142
 
4.9%
3 138
 
4.7%
5 131
 
4.5%
6 126
 
4.3%
9 121
 
4.2%
7 94
 
3.2%
0 91
 
3.1%
Other values (6) 335
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4449
60.4%
ASCII 2913
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1289
44.2%
1 256
 
8.8%
2 190
 
6.5%
4 142
 
4.9%
3 138
 
4.7%
5 131
 
4.5%
6 126
 
4.3%
9 121
 
4.2%
7 94
 
3.2%
0 91
 
3.1%
Other values (6) 335
 
11.5%
Hangul
ValueCountFrequency (%)
해 381
 
8.6%
김 380
 
8.5%
상 363
 
8.2%
경 322
 
7.2%
남 322
 
7.2%
도 322
 
7.2%
시 321
 
7.2%
로 321
 
7.2%
면 160
 
3.6%
동 150
 
3.4%
Other values (87) 1407
31.6%

완공일자
Text

Distinct311
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-03-13T09:08:02.475186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length10
Mean length10.51506
Min length10

Characters and Unicode

Total characters3491
Distinct characters24
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

Unique292 ?
Unique (%)88.0%

Sample

1st row1995-08-02
2nd row1996-06-14
3rd row1999-11-30
4th row1997-09-11
5th row1994-11-11
ValueCountFrequency (%)
2015-06-25 3
 
0.9%
2000-06-19 3
 
0.9%
2009-10-14 2
 
0.6%
2020-09-22 2
 
0.6%
2011-06-21 2
 
0.6%
2002-05-30 2
 
0.6%
2009-04-01 2
 
0.6%
2007-12-27 2
 
0.6%
2018-01-23 2
 
0.6%
2006-11-27 2
 
0.6%
Other values (315) 327
93.7%
2024-03-13T09:08:02.819915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 859
24.6%
- 688
19.7%
2 551
15.8%
1 486
13.9%
9 242
 
6.9%
3 122
 
3.5%
4 112
 
3.2%
6 106
 
3.0%
8 95
 
2.7%
7 95
 
2.7%
Other values (14) 135
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2760
79.1%
Dash Punctuation 688
 
19.7%
Space Separator 17
 
0.5%
Other Punctuation 12
 
0.3%
Other Letter 10
 
0.3%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 859
31.1%
2 551
20.0%
1 486
17.6%
9 242
 
8.8%
3 122
 
4.4%
4 112
 
4.1%
6 106
 
3.8%
8 95
 
3.4%
7 95
 
3.4%
5 92
 
3.3%
Other Letter
ValueCountFrequency (%)
년 2
20.0%
리 1
10.0%
모 1
10.0%
델 1
10.0%
링 1
10.0%
탱 1
10.0%
크 1
10.0%
신 1
10.0%
설 1
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 688
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3481
99.7%
Hangul 10
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 859
24.7%
- 688
19.8%
2 551
15.8%
1 486
14.0%
9 242
 
7.0%
3 122
 
3.5%
4 112
 
3.2%
6 106
 
3.0%
8 95
 
2.7%
7 95
 
2.7%
Other values (5) 125
 
3.6%
Hangul
ValueCountFrequency (%)
년 2
20.0%
리 1
10.0%
모 1
10.0%
델 1
10.0%
링 1
10.0%
탱 1
10.0%
크 1
10.0%
신 1
10.0%
설 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3481
99.7%
Hangul 10
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 859
24.7%
- 688
19.8%
2 551
15.8%
1 486
14.0%
9 242
 
7.0%
3 122
 
3.5%
4 112
 
3.2%
6 106
 
3.0%
8 95
 
2.7%
7 95
 
2.7%
Other values (5) 125
 
3.6%
Hangul
ValueCountFrequency (%)
년 2
20.0%
리 1
10.0%
모 1
10.0%
델 1
10.0%
링 1
10.0%
탱 1
10.0%
크 1
10.0%
신 1
10.0%
설 1
10.0%

토양오염도검사해당여부(누출검사)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
적용
289 
면제
43 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
적용 289
87.0%
면제 43
 
13.0%

Length

2024-03-13T09:08:02.954487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T09:08:03.049010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적용 289
87.0%
면제 43
 
13.0%

토양오염도검사해당여부(오염도검사)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
적용
302 
면제
 
30

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
적용 302
91.0%
면제 30
 
9.0%

Length

2024-03-13T09:08:03.127127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T09:08:03.199358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적용 302
91.0%
면제 30
 
9.0%

토양오염물질저장용량(L)
Real number (ℝ)

Distinct161
Distinct (%)48.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean291351.72
Minimum20000
Maximum6390000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-03-13T09:08:03.283100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000
5-th percentile27000
Q167800
median200000
Q3300000
95-th percentile807610
Maximum6390000
Range6370000
Interquartile range (IQR)232200

Descriptive statistics

Standard deviation526903.48
Coefficient of variation (CV)1.808479
Kurtosis66.445925
Mean291351.72
Median Absolute Deviation (MAD)108800
Skewness7.0330364
Sum96728772
Variance2.7762728 × 1011
MonotonicityNot monotonic
2024-03-13T09:08:03.395471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200000 25
 
7.5%
300000 23
 
6.9%
250000 17
 
5.1%
40000 11
 
3.3%
160000 10
 
3.0%
150000 10
 
3.0%
350000 9
 
2.7%
400000 8
 
2.4%
20000 8
 
2.4%
100000 7
 
2.1%
Other values (151) 204
61.4%
ValueCountFrequency (%)
20000 8
2.4%
20800 1
 
0.3%
21000 2
 
0.6%
21460 1
 
0.3%
23200 1
 
0.3%
24000 2
 
0.6%
25600 1
 
0.3%
27000 2
 
0.6%
28800 1
 
0.3%
29000 3
 
0.9%
ValueCountFrequency (%)
6390000 1
0.3%
4369000 1
0.3%
2612580 1
0.3%
2246000 1
0.3%
2093552 1
0.3%
1996780 1
0.3%
1854000 1
0.3%
1638000 1
0.3%
1600000 1
0.3%
1536000 1
0.3%

위도
Real number (ℝ)

Distinct321
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.270094
Minimum35.193445
Maximum35.349855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-03-13T09:08:03.504175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.193445
5-th percentile35.217064
Q135.235487
median35.271094
Q335.304434
95-th percentile35.326946
Maximum35.349855
Range0.15640983
Interquartile range (IQR)0.068946252

Descriptive statistics

Standard deviation0.037886649
Coefficient of variation (CV)0.0010741862
Kurtosis-1.2078803
Mean35.270094
Median Absolute Deviation (MAD)0.034749795
Skewness0.12016414
Sum11709.671
Variance0.0014353982
MonotonicityNot monotonic
2024-03-13T09:08:03.627383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.32075517 3
 
0.9%
35.3047555 2
 
0.6%
35.26108265 2
 
0.6%
35.26822801 2
 
0.6%
35.31566205 2
 
0.6%
35.22964258 2
 
0.6%
35.23604236 2
 
0.6%
35.29168897 2
 
0.6%
35.27133219 2
 
0.6%
35.22933633 2
 
0.6%
Other values (311) 311
93.7%
ValueCountFrequency (%)
35.19344484 1
0.3%
35.19402604 1
0.3%
35.20288058 1
0.3%
35.20383514 1
0.3%
35.20421929 1
0.3%
35.2070142 1
0.3%
35.20818165 1
0.3%
35.21034659 1
0.3%
35.21058918 1
0.3%
35.21200846 1
0.3%
ValueCountFrequency (%)
35.34985467 1
0.3%
35.34747808 1
0.3%
35.34647405 1
0.3%
35.34549533 1
0.3%
35.34390374 1
0.3%
35.34385875 1
0.3%
35.34219512 1
0.3%
35.34122518 1
0.3%
35.33994812 1
0.3%
35.33918774 1
0.3%

경도
Real number (ℝ)

Distinct321
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.83822
Minimum128.70782
Maximum129.0028
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-03-13T09:08:03.757947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.70782
5-th percentile128.74367
Q1128.77731
median128.84556
Q3128.88912
95-th percentile128.94573
Maximum129.0028
Range0.2949796
Interquartile range (IQR)0.11181335

Descriptive statistics

Standard deviation0.066050081
Coefficient of variation (CV)0.00051265905
Kurtosis-0.74053041
Mean128.83822
Median Absolute Deviation (MAD)0.05565925
Skewness0.060632508
Sum42774.29
Variance0.0043626132
MonotonicityNot monotonic
2024-03-13T09:08:03.866817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8469882 3
 
0.9%
128.8007593 2
 
0.6%
128.8379914 2
 
0.6%
129.0027962 2
 
0.6%
128.7473975 2
 
0.6%
128.7992942 2
 
0.6%
128.9053886 2
 
0.6%
128.7837103 2
 
0.6%
128.7758308 2
 
0.6%
128.8722472 2
 
0.6%
Other values (311) 311
93.7%
ValueCountFrequency (%)
128.7078166 1
0.3%
128.7086544 1
0.3%
128.7091531 1
0.3%
128.7091755 1
0.3%
128.7102397 1
0.3%
128.7144771 1
0.3%
128.715865 1
0.3%
128.7172309 1
0.3%
128.7174338 1
0.3%
128.7179021 1
0.3%
ValueCountFrequency (%)
129.0027962 2
0.6%
128.9829227 1
0.3%
128.9828842 1
0.3%
128.9808463 1
0.3%
128.974266 1
0.3%
128.971816 1
0.3%
128.9709624 1
0.3%
128.9678716 1
0.3%
128.9669066 1
0.3%
128.9654758 1
0.3%

Interactions

2024-03-13T09:07:59.587362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:58.697456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:58.972891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:59.278338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:59.664067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:58.763452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:59.039575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:59.363705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:59.739475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:58.831451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:59.109681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:59.435407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:59.813323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:58.903573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:59.187126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:07:59.509512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T09:08:03.950166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신고번호업종토양오염도검사해당여부(누출검사)토양오염도검사해당여부(오염도검사)토양오염물질저장용량(L)위도경도
신고번호1.0000.5030.2600.1390.1140.2360.390
업종0.5031.0000.5640.4460.2980.2920.231
토양오염도검사해당여부(누출검사)0.2600.5641.0000.9350.1610.1000.160
토양오염도검사해당여부(오염도검사)0.1390.4460.9351.0000.0000.0000.000
토양오염물질저장용량(L)0.1140.2980.1610.0001.0000.0000.000
위도0.2360.2920.1000.0000.0001.0000.700
경도0.3900.2310.1600.0000.0000.7001.000
2024-03-13T09:08:04.039215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
토양오염도검사해당여부(누출검사)업종토양오염도검사해당여부(오염도검사)
토양오염도검사해당여부(누출검사)1.0000.3850.769
업종0.3851.0000.300
토양오염도검사해당여부(오염도검사)0.7690.3001.000
2024-03-13T09:08:04.113348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신고번호토양오염물질저장용량(L)위도경도업종토양오염도검사해당여부(누출검사)토양오염도검사해당여부(오염도검사)
신고번호1.000-0.0040.038-0.0970.3210.1960.105
토양오염물질저장용량(L)-0.0041.000-0.083-0.0770.2060.1690.000
위도0.038-0.0831.000-0.2770.1770.0750.000
경도-0.097-0.077-0.2771.0000.1410.1210.000
업종0.3210.2060.1770.1411.0000.3850.300
토양오염도검사해당여부(누출검사)0.1960.1690.0750.1210.3851.0000.769
토양오염도검사해당여부(오염도검사)0.1050.0000.0000.0000.3000.7691.000

Missing values

2024-03-13T09:07:59.908195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T09:08:00.026610image/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.

Sample

신고번호사업장명업종지번주소도로명주소완공일자토양오염도검사해당여부(누출검사)토양오염도검사해당여부(오염도검사)토양오염물질저장용량(L)위도경도
01영진주유소주유소경상남도 김해시 내동 495경상남도 김해시 금관대로 1279 (내동)1995-08-02적용적용12000035.239016128.859804
12예진주유소주유소경상남도 김해시 어방동 351-8경상남도 김해시 인제로 145 (어방동)1996-06-14적용적용16000035.241734128.903617
23고속도로관리공단 진영(상)주유소주유소경상남도 김해시 진영읍 우동리 377-2경상남도 김해시 진영읍 하계로96번길 44-491999-11-30적용적용27000035.278886128.714477
34상동농협직영주유소주유소경상남도 김해시 상동면 매리 93-3경상남도 김해시 상동면 동북로 4811997-09-11적용적용10000035.31561128.967872
45동방석유㈜직영 부영주유소주유소경상남도 김해시 진영읍 진영리 319-121경상남도 김해시 진영읍 진산대로 1871994-11-11적용적용19600035.320671128.722709
56해안주유소주유소경상남도 김해시 명법동 202-2경상남도 김해시 금관대로 820-16 (명법동)1993-01-06적용적용16000035.203835128.837918
67보은주유소주유소경상남도 김해시 어방동 1116-3 외 2필지경상남도 김해시 김해대로 2537 (어방동)1993-06-16적용적용15600035.228956128.904409
78송진주유소주유소경상남도 김해시 한림면 신천리 285-2경상남도 김해시 한림면 김해대로 15671987-03-05적용적용13000035.275607128.842725
89현대주유소주유소경상남도 김해시 한림면 명동리 61-1경상남도 김해시 한림면 한림로 1311995-09-07적용적용12000035.304736128.807763
910단감주유소주유소경상남도 김해시 진영읍 진영리 728경상남도 김해시 진영읍 진산대로 2431995-07-14적용적용20000035.323614128.717434
신고번호사업장명업종지번주소도로명주소완공일자토양오염도검사해당여부(누출검사)토양오염도검사해당여부(오염도검사)토양오염물질저장용량(L)위도경도
322323성림엔에스티 주식회사주유소경상남도 김해시 진례면 고모리 545-1경상남도 김해시 진례면 고모로 5362000-06-19적용적용66000035.271729128.775879
323324㈜미다스교역산업시설경상남도 김해시 청천리 299-6경상남도 김해시 진례면 서부로 434-342023-05-16적용적용32000035.261083128.837991
324325㈜디케이메탈산업시설경상남도 김해시 주촌면 내삼리 1050경상남도 김해시 주촌면 서부로1541번안길 862023-11-30적용적용3000035.235912128.808134
325326㈜비알피유해화학물질경상남도 김해시 주촌면 내삼리 836-1경상남도 김해시 주촌면 서부로1409번길 402023-10-13적용적용639000035.227027128.818361
326327우봉이엔티산업시설경상남도 김해시 상동면 우계리 845경상남도 김해시 상동면 상동로 263-202023-10-24적용적용25680035.30327128.899101
327328㈜가온에너지산업시설경상남도 김해시 봉림리 823-2경상남도 김해시 생림면 생림대로 8602024-01-04적용적용70000035.261083128.837991
328329주식회사 에스에이치씨피산업시설경상남도 김해시 대동첨단산업단지 A-14-5<NA>2024-01-08적용적용50100035.255554128.974266
329330㈜이알유해화학물질경상남도 김해시 한림면 안하리 271-3경상남도 김해시 한림면 안하로116번길 462023-12-04적용적용80500035.30941128.828373
330331케이원에너지산업시설경상남도 김해시 진례면 송현리 1045-7<NA>2023-12-27적용적용153600035.241014128.782035
331332㈜페트로뱅크산업시설경상남도 김해시 진례면 산본리 32-1<NA>2023-12-28적용적용88400035.235836128.767263