Overview

Dataset statistics

Number of variables12
Number of observations34
Missing cells36
Missing cells (%)8.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory104.9 B

Variable types

Categorical3
Text5
Unsupported1
Numeric3

Dataset

Description경기도 토양전문기관 및 토양정화업체 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=UB59Y8D2X82TIOGXONRB12806726&infSeq=1

Alerts

집계년도 has constant value ""Constant
시군명 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
연락처정보 has 2 (5.9%) missing valuesMissing
주요점검사항 has 34 (100.0%) missing valuesMissing
주요점검사항 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-16 04:46:40.032937
Analysis finished2024-03-16 04:46:48.324576
Duration8.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023
34 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 34
100.0%

Length

2024-03-16T04:46:48.586224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T04:46:48.903600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 34
100.0%

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
경기도
34 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 34
100.0%

Length

2024-03-16T04:46:49.233186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T04:46:49.577433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 34
100.0%

기관명
Text

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-16T04:46:50.011672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10.5
Mean length8.1470588
Min length4

Characters and Unicode

Total characters277
Distinct characters93
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)88.2%

Sample

1st row(재)한국화학융합시험연구원
2nd row측천산업주식회사
3rd row(재)경기환경과학연구원
4th row(재)한국환경종합연구원
5th row(재)테라환경연구원
ValueCountFrequency (%)
재)테라환경연구원 2
 
5.4%
주식회사 2
 
5.4%
㈜케이에이치이 2
 
5.4%
효림 1
 
2.7%
㈜케이디이엔지 1
 
2.7%
한국환경자원기술㈜ 1
 
2.7%
환경시설관리 1
 
2.7%
해성메탈㈜ 1
 
2.7%
파주공장 1
 
2.7%
㈜대일이앤씨 1
 
2.7%
Other values (24) 24
64.9%
2024-03-16T04:46:51.060664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 21
 
7.6%
이 19
 
6.9%
경 12
 
4.3%
환 11
 
4.0%
( 9
 
3.2%
원 9
 
3.2%
) 9
 
3.2%
에 8
 
2.9%
재 7
 
2.5%
한 7
 
2.5%
Other values (83) 165
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 235
84.8%
Other Symbol 21
 
7.6%
Open Punctuation 9
 
3.2%
Close Punctuation 9
 
3.2%
Space Separator 3
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 19
 
8.1%
경 12
 
5.1%
환 11
 
4.7%
원 9
 
3.8%
에 8
 
3.4%
재 7
 
3.0%
한 7
 
3.0%
연 6
 
2.6%
구 6
 
2.6%
국 6
 
2.6%
Other values (79) 144
61.3%
Other Symbol
ValueCountFrequency (%)
㈜ 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 256
92.4%
Common 21
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 21
 
8.2%
이 19
 
7.4%
경 12
 
4.7%
환 11
 
4.3%
원 9
 
3.5%
에 8
 
3.1%
재 7
 
2.7%
한 7
 
2.7%
연 6
 
2.3%
구 6
 
2.3%
Other values (80) 150
58.6%
Common
ValueCountFrequency (%)
( 9
42.9%
) 9
42.9%
3
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 235
84.8%
None 21
 
7.6%
ASCII 21
 
7.6%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 21
100.0%
Hangul
ValueCountFrequency (%)
이 19
 
8.1%
경 12
 
5.1%
환 11
 
4.7%
원 9
 
3.8%
에 8
 
3.4%
재 7
 
3.0%
한 7
 
3.0%
연 6
 
2.6%
구 6
 
2.6%
국 6
 
2.6%
Other values (79) 144
61.3%
ASCII
ValueCountFrequency (%)
( 9
42.9%
) 9
42.9%
3
 
14.3%

구분명
Categorical

Distinct3
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
토양정화업
24 
토양오염조사기관
6 
누출검사기관
4 

Length

Max length8
Median length5
Mean length5.6470588
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row토양오염조사기관
2nd row토양정화업
3rd row토양오염조사기관
4th row토양오염조사기관
5th row토양오염조사기관

Common Values

ValueCountFrequency (%)
토양정화업 24
70.6%
토양오염조사기관 6
 
17.6%
누출검사기관 4
 
11.8%

Length

2024-03-16T04:46:51.667905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T04:46:52.122541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토양정화업 24
70.6%
토양오염조사기관 6
 
17.6%
누출검사기관 4
 
11.8%

연락처정보
Text

MISSING 

Distinct30
Distinct (%)93.8%
Missing2
Missing (%)5.9%
Memory size404.0 B
2024-03-16T04:46:52.692902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.09375
Min length11

Characters and Unicode

Total characters387
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

Unique28 ?
Unique (%)87.5%

Sample

1st row02-2092-3834
2nd row031-499-8700
3rd row031-699-0131
4th row031-360-2255
5th row031-429-9979
ValueCountFrequency (%)
031-429-9979 2
 
6.2%
031-457-1194 2
 
6.2%
02-2092-3834 1
 
3.1%
031-949-5405 1
 
3.1%
031-986-3838 1
 
3.1%
070-4610-1143 1
 
3.1%
02-6112-3555 1
 
3.1%
031-8091-2244 1
 
3.1%
070-7492-2394 1
 
3.1%
02-3016-9025 1
 
3.1%
Other values (20) 20
62.5%
2024-03-16T04:46:53.795647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 64
16.5%
0 50
12.9%
1 43
11.1%
3 42
10.9%
2 39
10.1%
4 26
6.7%
9 26
6.7%
7 25
 
6.5%
8 22
 
5.7%
5 21
 
5.4%
Other values (2) 29
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 312
80.6%
Dash Punctuation 64
 
16.5%
Other Punctuation 11
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 50
16.0%
1 43
13.8%
3 42
13.5%
2 39
12.5%
4 26
8.3%
9 26
8.3%
7 25
8.0%
8 22
7.1%
5 21
6.7%
6 18
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%
Other Punctuation
ValueCountFrequency (%)
* 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 387
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 64
16.5%
0 50
12.9%
1 43
11.1%
3 42
10.9%
2 39
10.1%
4 26
6.7%
9 26
6.7%
7 25
 
6.5%
8 22
 
5.7%
5 21
 
5.4%
Other values (2) 29
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 387
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 64
16.5%
0 50
12.9%
1 43
11.1%
3 42
10.9%
2 39
10.1%
4 26
6.7%
9 26
6.7%
7 25
 
6.5%
8 22
 
5.7%
5 21
 
5.4%
Other values (2) 29
7.5%

대표자명
Text

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-16T04:46:54.328715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.4117647
Min length3

Characters and Unicode

Total characters116
Distinct characters64
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)88.2%

Sample

1st row김현철
2nd row임성배
3rd row여인홍
4th row김용현
5th row김종민
ValueCountFrequency (%)
김종민 2
 
5.6%
홍병철 2
 
5.6%
이학범 1
 
2.8%
정승훈 1
 
2.8%
강병주 1
 
2.8%
박성오 1
 
2.8%
권지훈 1
 
2.8%
손군환 1
 
2.8%
조성국 1
 
2.8%
김주엽 1
 
2.8%
Other values (24) 24
66.7%
2024-03-16T04:46:55.297347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 11
 
9.5%
철 6
 
5.2%
홍 4
 
3.4%
성 4
 
3.4%
이 4
 
3.4%
현 4
 
3.4%
환 4
 
3.4%
훈 3
 
2.6%
호 3
 
2.6%
종 3
 
2.6%
Other values (54) 70
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111
95.7%
Other Punctuation 3
 
2.6%
Space Separator 2
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 11
 
9.9%
철 6
 
5.4%
홍 4
 
3.6%
성 4
 
3.6%
이 4
 
3.6%
현 4
 
3.6%
환 4
 
3.6%
훈 3
 
2.7%
호 3
 
2.7%
종 3
 
2.7%
Other values (52) 65
58.6%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111
95.7%
Common 5
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 11
 
9.9%
철 6
 
5.4%
홍 4
 
3.6%
성 4
 
3.6%
이 4
 
3.6%
현 4
 
3.6%
환 4
 
3.6%
훈 3
 
2.7%
호 3
 
2.7%
종 3
 
2.7%
Other values (52) 65
58.6%
Common
ValueCountFrequency (%)
, 3
60.0%
2
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111
95.7%
ASCII 5
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 11
 
9.9%
철 6
 
5.4%
홍 4
 
3.6%
성 4
 
3.6%
이 4
 
3.6%
현 4
 
3.6%
환 4
 
3.6%
훈 3
 
2.7%
호 3
 
2.7%
종 3
 
2.7%
Other values (52) 65
58.6%
ASCII
ValueCountFrequency (%)
, 3
60.0%
2
40.0%

주요점검사항
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)100.0%
Memory size438.0 B

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14140.824
Minimum10050
Maximum18554
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-03-16T04:46:55.711804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10050
5-th percentile10990.25
Q113038.25
median13971.5
Q315728.75
95-th percentile17719.3
Maximum18554
Range8504
Interquartile range (IQR)2690.5

Descriptive statistics

Standard deviation2032.7891
Coefficient of variation (CV)0.14375323
Kurtosis-0.043017423
Mean14140.824
Median Absolute Deviation (MAD)1124.5
Skewness0.2492992
Sum480788
Variance4132231.5
MonotonicityNot monotonic
2024-03-16T04:46:56.189225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
11431 2
 
5.9%
15850 2
 
5.9%
15809 2
 
5.9%
13207 2
 
5.9%
13901 1
 
2.9%
14449 1
 
2.9%
12612 1
 
2.9%
18290 1
 
2.9%
13591 1
 
2.9%
13810 1
 
2.9%
Other values (20) 20
58.8%
ValueCountFrequency (%)
10050 1
2.9%
10896 1
2.9%
11041 1
2.9%
11431 2
5.9%
12612 1
2.9%
12767 1
2.9%
12927 1
2.9%
12982 1
2.9%
13207 2
5.9%
13473 1
2.9%
ValueCountFrequency (%)
18554 1
2.9%
18290 1
2.9%
17412 1
2.9%
17086 1
2.9%
16226 1
2.9%
15850 2
5.9%
15809 2
5.9%
15488 1
2.9%
14952 1
2.9%
14449 1
2.9%

소재지지번주소
Text

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-16T04:46:56.840457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length36
Mean length30.147059
Min length15

Characters and Unicode

Total characters1025
Distinct characters151
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)88.2%

Sample

1st row경기도 과천시 중앙동 2번지
2nd row경기도 화성시 서신면 전곡리 140-2
3rd row경기도 하남시 풍산동 618번지 하남테크노파크 U1센터 C동 1410호
4th row경기도 안양시 동안구 평촌동 126-1번지 두산벤처다임 620호
5th row경기도 군포시 당정동 522번지 SK벤티움 102동 1104호
ValueCountFrequency (%)
경기도 34
 
16.0%
성남시 6
 
2.8%
안양시 5
 
2.3%
군포시 4
 
1.9%
동안구 4
 
1.9%
분당구 3
 
1.4%
c동 2
 
0.9%
2층 2
 
0.9%
화성시 2
 
0.9%
관양동 2
 
0.9%
Other values (132) 149
70.0%
2024-03-16T04:46:58.008132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
179
 
17.5%
1 40
 
3.9%
동 39
 
3.8%
도 36
 
3.5%
기 35
 
3.4%
시 35
 
3.4%
경 34
 
3.3%
지 33
 
3.2%
번 32
 
3.1%
2 30
 
2.9%
Other values (141) 532
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 599
58.4%
Decimal Number 211
 
20.6%
Space Separator 179
 
17.5%
Dash Punctuation 23
 
2.2%
Uppercase Letter 11
 
1.1%
Other Punctuation 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 39
 
6.5%
도 36
 
6.0%
기 35
 
5.8%
시 35
 
5.8%
경 34
 
5.7%
지 33
 
5.5%
번 32
 
5.3%
호 19
 
3.2%
구 15
 
2.5%
크 11
 
1.8%
Other values (123) 310
51.8%
Decimal Number
ValueCountFrequency (%)
1 40
19.0%
2 30
14.2%
0 23
10.9%
8 22
10.4%
4 21
10.0%
9 20
9.5%
3 19
9.0%
5 16
 
7.6%
6 16
 
7.6%
7 4
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
K 4
36.4%
S 4
36.4%
C 2
18.2%
U 1
 
9.1%
Space Separator
ValueCountFrequency (%)
179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 599
58.4%
Common 414
40.4%
Latin 12
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 39
 
6.5%
도 36
 
6.0%
기 35
 
5.8%
시 35
 
5.8%
경 34
 
5.7%
지 33
 
5.5%
번 32
 
5.3%
호 19
 
3.2%
구 15
 
2.5%
크 11
 
1.8%
Other values (123) 310
51.8%
Common
ValueCountFrequency (%)
179
43.2%
1 40
 
9.7%
2 30
 
7.2%
- 23
 
5.6%
0 23
 
5.6%
8 22
 
5.3%
4 21
 
5.1%
9 20
 
4.8%
3 19
 
4.6%
5 16
 
3.9%
Other values (3) 21
 
5.1%
Latin
ValueCountFrequency (%)
K 4
33.3%
S 4
33.3%
C 2
16.7%
n 1
 
8.3%
U 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 599
58.4%
ASCII 426
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
179
42.0%
1 40
 
9.4%
2 30
 
7.0%
- 23
 
5.4%
0 23
 
5.4%
8 22
 
5.2%
4 21
 
4.9%
9 20
 
4.7%
3 19
 
4.5%
5 16
 
3.8%
Other values (8) 33
 
7.7%
Hangul
ValueCountFrequency (%)
동 39
 
6.5%
도 36
 
6.0%
기 35
 
5.8%
시 35
 
5.8%
경 34
 
5.7%
지 33
 
5.5%
번 32
 
5.3%
호 19
 
3.2%
구 15
 
2.5%
크 11
 
1.8%
Other values (123) 310
51.8%

소재지도로명주소
Text

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-16T04:46:58.681287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length38
Mean length30.294118
Min length19

Characters and Unicode

Total characters1030
Distinct characters166
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

Unique30 ?
Unique (%)88.2%

Sample

1st row경기도 과천시 교육원로 98(중앙동)
2nd row경기도 화성시 서신면 전곡리 140-2
3rd row경기도 하남시 풍산동 하남대로 947, 하남테크노파크 U1센터 C동 1410호
4th row경기도 안양시 동안구 흥안대로 415, 620호
5th row경기도 군포시 고산로 166 SK벤티움 102동 1104호
ValueCountFrequency (%)
경기도 34
 
15.8%
성남시 6
 
2.8%
안양시 5
 
2.3%
군포시 4
 
1.9%
동안구 4
 
1.9%
분당구 3
 
1.4%
c동 2
 
0.9%
은현면 2
 
0.9%
양주시 2
 
0.9%
124 2
 
0.9%
Other values (135) 151
70.2%
2024-03-16T04:46:59.819118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
181
 
17.6%
1 59
 
5.7%
기 38
 
3.7%
도 36
 
3.5%
시 35
 
3.4%
경 34
 
3.3%
로 31
 
3.0%
0 25
 
2.4%
동 24
 
2.3%
2 23
 
2.2%
Other values (156) 544
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 578
56.1%
Decimal Number 208
 
20.2%
Space Separator 181
 
17.6%
Other Punctuation 19
 
1.8%
Open Punctuation 11
 
1.1%
Close Punctuation 11
 
1.1%
Uppercase Letter 11
 
1.1%
Dash Punctuation 10
 
1.0%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 38
 
6.6%
도 36
 
6.2%
시 35
 
6.1%
경 34
 
5.9%
로 31
 
5.4%
동 24
 
4.2%
호 20
 
3.5%
구 15
 
2.6%
안 14
 
2.4%
남 11
 
1.9%
Other values (136) 320
55.4%
Decimal Number
ValueCountFrequency (%)
1 59
28.4%
0 25
12.0%
2 23
 
11.1%
4 19
 
9.1%
3 18
 
8.7%
5 17
 
8.2%
6 15
 
7.2%
8 14
 
6.7%
7 10
 
4.8%
9 8
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
K 4
36.4%
S 4
36.4%
C 2
18.2%
U 1
 
9.1%
Space Separator
ValueCountFrequency (%)
181
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 578
56.1%
Common 440
42.7%
Latin 12
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 38
 
6.6%
도 36
 
6.2%
시 35
 
6.1%
경 34
 
5.9%
로 31
 
5.4%
동 24
 
4.2%
호 20
 
3.5%
구 15
 
2.6%
안 14
 
2.4%
남 11
 
1.9%
Other values (136) 320
55.4%
Common
ValueCountFrequency (%)
181
41.1%
1 59
 
13.4%
0 25
 
5.7%
2 23
 
5.2%
, 19
 
4.3%
4 19
 
4.3%
3 18
 
4.1%
5 17
 
3.9%
6 15
 
3.4%
8 14
 
3.2%
Other values (5) 50
 
11.4%
Latin
ValueCountFrequency (%)
K 4
33.3%
S 4
33.3%
C 2
16.7%
n 1
 
8.3%
U 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 578
56.1%
ASCII 452
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
181
40.0%
1 59
 
13.1%
0 25
 
5.5%
2 23
 
5.1%
, 19
 
4.2%
4 19
 
4.2%
3 18
 
4.0%
5 17
 
3.8%
6 15
 
3.3%
8 14
 
3.1%
Other values (10) 62
 
13.7%
Hangul
ValueCountFrequency (%)
기 38
 
6.6%
도 36
 
6.2%
시 35
 
6.1%
경 34
 
5.9%
로 31
 
5.4%
동 24
 
4.2%
호 20
 
3.5%
구 15
 
2.6%
안 14
 
2.4%
남 11
 
1.9%
Other values (136) 320
55.4%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.442528
Minimum37.133724
Maximum37.938614
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-03-16T04:47:00.264090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.133724
5-th percentile37.216216
Q137.36212
median37.406395
Q337.460012
95-th percentile37.843458
Maximum37.938614
Range0.80488951
Interquartile range (IQR)0.097892345

Descriptive statistics

Standard deviation0.17755806
Coefficient of variation (CV)0.0047421494
Kurtosis1.7699666
Mean37.442528
Median Absolute Deviation (MAD)0.052499793
Skewness1.2205138
Sum1273.046
Variance0.031526865
MonotonicityNot monotonic
2024-03-16T04:47:00.681998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
37.3484253669 2
 
5.9%
37.3703840127 2
 
5.9%
37.4399480135 2
 
5.9%
37.426159033 1
 
2.9%
37.3857052472 1
 
2.9%
37.8485186545 1
 
2.9%
37.523038582 1
 
2.9%
37.359364993 1
 
2.9%
37.2442822429 1
 
2.9%
37.4447217305 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
37.1337243217 1
2.9%
37.1943331329 1
2.9%
37.2279984922 1
2.9%
37.2442822429 1
2.9%
37.3001940704 1
2.9%
37.3123248192 1
2.9%
37.3484253669 2
5.9%
37.359364993 1
2.9%
37.3703840127 2
5.9%
37.3857052472 1
2.9%
ValueCountFrequency (%)
37.9386138352 1
2.9%
37.8485186545 1
2.9%
37.8407330338 1
2.9%
37.7326978222 1
2.9%
37.6010000043 1
2.9%
37.5518151352 1
2.9%
37.5458667457 1
2.9%
37.523038582 1
2.9%
37.465108881 1
2.9%
37.4447217305 1
2.9%

WGS84경도
Real number (ℝ)

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.01777
Minimum126.57019
Maximum127.65935
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-03-16T04:47:01.231677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.57019
5-th percentile126.74353
Q1126.94275
median126.97594
Q3127.13479
95-th percentile127.309
Maximum127.65935
Range1.0891553
Interquartile range (IQR)0.19204607

Descriptive statistics

Standard deviation0.20779195
Coefficient of variation (CV)0.0016359282
Kurtosis2.358592
Mean127.01777
Median Absolute Deviation (MAD)0.12265826
Skewness0.82685916
Sum4318.6041
Variance0.043177493
MonotonicityNot monotonic
2024-03-16T04:47:01.799896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
126.9525159902 2
 
5.9%
126.9450154484 2
 
5.9%
127.1769873928 2
 
5.9%
126.9782620596 1
 
2.9%
127.125709393 1
 
2.9%
127.0146962306 1
 
2.9%
126.7679446779 1
 
2.9%
127.6593462293 1
 
2.9%
126.9454341281 1
 
2.9%
126.8939899644 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
126.5701909194 1
2.9%
126.7004948955 1
2.9%
126.7667024534 1
2.9%
126.7679446779 1
2.9%
126.7891158509 1
2.9%
126.8492141835 1
2.9%
126.8908893475 1
2.9%
126.8939899644 1
2.9%
126.9419906332 1
2.9%
126.9450154484 2
5.9%
ValueCountFrequency (%)
127.6593462293 1
2.9%
127.4971290552 1
2.9%
127.2076953235 1
2.9%
127.1980722751 1
2.9%
127.1936926063 1
2.9%
127.1769873928 2
5.9%
127.1432975849 1
2.9%
127.1378207406 1
2.9%
127.125709393 1
2.9%
127.1064362241 1
2.9%

Interactions

2024-03-16T04:46:46.557877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:46:44.861428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:46:45.605694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:46:46.800628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:46:45.096669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:46:46.006572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:46:47.150128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:46:45.358979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:46:46.293408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T04:47:02.113672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관명구분명연락처정보대표자명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
기관명1.0000.0001.0001.0001.0001.0001.0001.0001.000
구분명0.0001.0000.0000.0000.6780.0000.0000.2920.000
연락처정보1.0000.0001.0001.0001.0001.0001.0001.0001.000
대표자명1.0000.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호1.0000.6781.0001.0001.0001.0001.0000.9430.749
소재지지번주소1.0000.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0000.0001.0001.0001.0001.0001.0001.0001.000
WGS84위도1.0000.2921.0001.0000.9431.0001.0001.0000.623
WGS84경도1.0000.0001.0001.0000.7491.0001.0000.6231.000
2024-03-16T04:47:02.467784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도구분명
소재지우편번호1.000-0.806-0.2850.354
WGS84위도-0.8061.0000.0090.084
WGS84경도-0.2850.0091.0000.000
구분명0.3540.0840.0001.000

Missing values

2024-03-16T04:46:47.527992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T04:46:48.096491image/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

집계년도시군명기관명구분명연락처정보대표자명주요점검사항소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
02023경기도(재)한국화학융합시험연구원토양오염조사기관02-2092-3834김현철<NA>13810경기도 과천시 중앙동 2번지경기도 과천시 교육원로 98(중앙동)37.426159126.978262
12023경기도측천산업주식회사토양정화업031-499-8700임성배<NA>18554경기도 화성시 서신면 전곡리 140-2경기도 화성시 서신면 전곡리 140-237.194333126.700495
22023경기도(재)경기환경과학연구원토양오염조사기관031-699-0131여인홍<NA>12982경기도 하남시 풍산동 618번지 하남테크노파크 U1센터 C동 1410호경기도 하남시 풍산동 하남대로 947, 하남테크노파크 U1센터 C동 1410호37.545867127.193693
32023경기도(재)한국환경종합연구원토양오염조사기관031-360-2255김용현<NA>14059경기도 안양시 동안구 평촌동 126-1번지 두산벤처다임 620호경기도 안양시 동안구 흥안대로 415, 620호37.391622126.973011
42023경기도(재)테라환경연구원토양오염조사기관031-429-9979김종민<NA>15850경기도 군포시 당정동 522번지 SK벤티움 102동 1104호경기도 군포시 고산로 166 SK벤티움 102동 1104호37.348425126.952516
52023경기도(재)한국환경조사평가원토양오염조사기관031-311-7768지창환<NA>14952경기도 시흥시 신천동 864-4번지 프라임캐슬지식산업센터 801호경기도 시흥시 포도원로 116번길 25 프라임캐슬 지식산업센터 801호37.433754126.789116
62023경기도(주)엔지오스누출검사기관031-484-8835김재명<NA>15488경기도 안산시 상록구 이동 659-8번지 201호경기도 안산시 상록구 송호1길 83-1, 201호37.312325126.849214
72023경기도(재)테라환경연구원누출검사기관031-429-9979김종민<NA>15850경기도 군포시 당정동 522번지 SK벤티움 102동 1104호경기도 군포시 고산로 166 SK벤티움 102동 1104호37.348425126.952516
82023경기도아름다운환경건설㈜토양정화업031-776-2080이종열<NA>13207경기도 성남시 중원구 상대원동 190-1번지 SKn테크노파크 메가동 501호경기도 성남시 중원구 사기막골로 124, SKn테크노파크 메가동 501호37.439948127.176987
92023경기도㈜에코필토양정화업02-3461-5517고성환<NA>11431경기도 양주시 은현면 도하리 296-3번지경기도 양주시 은현면 그루고개로384번길 14137.840733127.0151
집계년도시군명기관명구분명연락처정보대표자명주요점검사항소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
242023경기도㈜케이에이치이누출검사기관031-457-1194홍병철<NA>15809경기도 군포시 금정동 689-28번지 한림테크노빌딩 5층경기도 군포시 공단로 294 한림테크노빌딩 5층37.370384126.945015
252023경기도㈜대일이앤씨토양정화업031-881-4751김주엽<NA>12612경기도 여주시 북내면 외룡리 383-5번지경기도 여주시 북내면 외재로 17637.359365127.659346
262023경기도대보건설㈜토양정화업02-3016-9025권오철<NA>18290경기도 화성시 매송면 천천리 206-2번지 203호경기도 화성시 매송면 매송고색로 375번길 5-1, 203호37.244282126.945434
272023경기도주식회사 효림토양정화업070-7492-2394조성국, 이학범<NA>13591경기도 성남시 분당구 서현동 246-2번지 분당서현신영팰리스타워 1205호경기도 성남시 분당구 황새울로360번길 21, 1205호(서현동, 분당서현신영팰리스타워)37.385705127.125709
282023경기도환경시설관리 주식회사토양정화업031-8091-2244권지훈<NA>13901경기도 안양시 만안구 석수동 859번지 케이타워 본관경기도 안양시 만안구 일직로 88(석수동, 케이타워본관)37.41999126.890889
292023경기도한국환경자원기술㈜토양정화업02-6112-3555박성오<NA>14322경기도 광명시 소하동 1345번지 SK테크노파크 C동 305호경기도 광명시 하안로 60, C동 305호 (소하동, SK테크노파크)37.444722126.89399
302023경기도㈜케이디이엔지토양정화업070-4610-1143강병주<NA>14058경기도 안양시 동안구 관양동 911번지 에이스하이테크시티 평촌1동 8층 815호 및 816호경기도 안양시 동안구 흥안대로 457-27, 에이스하이테크시티 평촌1동 8층 815호 및 816호37.394663126.973611
312023경기도㈜한강이앰피토양정화업031-986-3838정승훈<NA>10050경기도 김포시 대곶면 대벽리 690-88번지경기도 김포시 대곶면 대곶남로 53-15137.601126.570191
322023경기도㈜아이나환경코리아토양정화업<NA>황준영<NA>13473경기도 성남시 분당구 판교동 495번지 훼미리프라자 2층경기도 성남시 분당구 서판교로 164, 훼미리프라자 2층37.400592127.094531
332023경기도(재)한국환경산업연구원토양오염조사기관031-283-6923편서연<NA>16226경기도 수원시 영통구 이의동 1248-3번지 413호경기도 수원시 영통구 대학4로 17, 413호(이의동)37.300194127.046721