Overview

Dataset statistics

Number of variables12
Number of observations52
Missing cells156
Missing cells (%)25.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory106.5 B

Variable types

Categorical3
Text3
Unsupported3
Numeric3

Alerts

소재지우편번호 is highly overall correlated with WGS84위도 and 3 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
대기종별구분명 is highly overall correlated with 폐수종별구분명High correlation
폐수종별구분명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
사업자등록번호 has 52 (100.0%) missing valuesMissing
관할기관명 has 52 (100.0%) missing valuesMissing
대표자명 has 52 (100.0%) missing valuesMissing
사업장명 has unique valuesUnique
소재지지번주소 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique
사업자등록번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
관할기관명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
대표자명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 21:46:07.599102
Analysis finished2023-12-10 21:46:09.094398
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
파주시
19 
성남시
6 
안성시
6 
평택시
6 
화성시
4 
Other values (8)
11 

Length

Max length4
Median length3
Mean length3.0384615
Min length3

Unique

Unique6 ?
Unique (%)11.5%

Sample

1st row과천시
2nd row김포시
3rd row김포시
4th row동두천시
5th row부천시

Common Values

ValueCountFrequency (%)
파주시 19
36.5%
성남시 6
 
11.5%
안성시 6
 
11.5%
평택시 6
 
11.5%
화성시 4
 
7.7%
양주시 3
 
5.8%
김포시 2
 
3.8%
과천시 1
 
1.9%
동두천시 1
 
1.9%
부천시 1
 
1.9%
Other values (3) 3
 
5.8%

Length

2023-12-11T06:46:09.149222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
파주시 19
36.5%
성남시 6
 
11.5%
안성시 6
 
11.5%
평택시 6
 
11.5%
화성시 4
 
7.7%
양주시 3
 
5.8%
김포시 2
 
3.8%
과천시 1
 
1.9%
동두천시 1
 
1.9%
부천시 1
 
1.9%
Other values (3) 3
 
5.8%

사업장명
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-11T06:46:09.332268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length7.1923077
Min length3

Characters and Unicode

Total characters374
Distinct characters136
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row과천시맑은물사업소
2nd row㈜두웰
3rd row㈜에스로드화장품
4th row동두천패션칼라사업협동조합
5th row까치울정수장
ValueCountFrequency (%)
과천시맑은물사업소 1
 
1.8%
㈜두웰 1
 
1.8%
전우용사촌㈜파주지점 1
 
1.8%
대산인쇄공사 1
 
1.8%
동광합철㈜ 1
 
1.8%
㈜에스제이씨성전 1
 
1.8%
㈜와이즈산전2공장 1
 
1.8%
새한문화사 1
 
1.8%
㈜코리아피앤피 1
 
1.8%
대일정밀 1
 
1.8%
Other values (46) 46
82.1%
2023-12-11T06:46:09.651896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 22
 
5.9%
) 12
 
3.2%
주 12
 
3.2%
사 11
 
2.9%
( 11
 
2.9%
이 11
 
2.9%
스 10
 
2.7%
장 8
 
2.1%
공 8
 
2.1%
산 7
 
1.9%
Other values (126) 262
70.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 319
85.3%
Other Symbol 22
 
5.9%
Close Punctuation 12
 
3.2%
Open Punctuation 11
 
2.9%
Space Separator 4
 
1.1%
Decimal Number 3
 
0.8%
Uppercase Letter 2
 
0.5%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 12
 
3.8%
사 11
 
3.4%
이 11
 
3.4%
스 10
 
3.1%
장 8
 
2.5%
공 8
 
2.5%
산 7
 
2.2%
업 7
 
2.2%
오 7
 
2.2%
성 7
 
2.2%
Other values (117) 231
72.4%
Decimal Number
ValueCountFrequency (%)
3 2
66.7%
2 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
J 1
50.0%
C 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 341
91.2%
Common 31
 
8.3%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 22
 
6.5%
주 12
 
3.5%
사 11
 
3.2%
이 11
 
3.2%
스 10
 
2.9%
장 8
 
2.3%
공 8
 
2.3%
산 7
 
2.1%
업 7
 
2.1%
오 7
 
2.1%
Other values (118) 238
69.8%
Common
ValueCountFrequency (%)
) 12
38.7%
( 11
35.5%
4
 
12.9%
3 2
 
6.5%
2 1
 
3.2%
, 1
 
3.2%
Latin
ValueCountFrequency (%)
J 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 319
85.3%
ASCII 33
 
8.8%
None 22
 
5.9%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 22
100.0%
ASCII
ValueCountFrequency (%)
) 12
36.4%
( 11
33.3%
4
 
12.1%
3 2
 
6.1%
2 1
 
3.0%
J 1
 
3.0%
C 1
 
3.0%
, 1
 
3.0%
Hangul
ValueCountFrequency (%)
주 12
 
3.8%
사 11
 
3.4%
이 11
 
3.4%
스 10
 
3.1%
장 8
 
2.5%
공 8
 
2.5%
산 7
 
2.2%
업 7
 
2.2%
오 7
 
2.2%
성 7
 
2.2%
Other values (117) 231
72.4%

사업자등록번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

관할기관명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

대표자명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

대기종별구분명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
24 
5
15 
4
10 
3
3 

Length

Max length4
Median length1
Mean length2.3846154
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row5
3rd row<NA>
4th row5
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 24
46.2%
5 15
28.8%
4 10
19.2%
3 3
 
5.8%

Length

2023-12-11T06:46:09.784798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:46:09.900733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
46.2%
5 15
28.8%
4 10
19.2%
3 3
 
5.8%

폐수종별구분명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
5
31 
<NA>
10 
3
5 
4
4 
1
 
1

Length

Max length4
Median length1
Mean length1.5769231
Min length1

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row4
2nd row5
3rd row5
4th row5
5th row3

Common Values

ValueCountFrequency (%)
5 31
59.6%
<NA> 10
 
19.2%
3 5
 
9.6%
4 4
 
7.7%
1 1
 
1.9%
2 1
 
1.9%

Length

2023-12-11T06:46:09.998208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:46:10.092937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 31
59.6%
na 10
 
19.2%
3 5
 
9.6%
4 4
 
7.7%
1 1
 
1.9%
2 1
 
1.9%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13640.712
Minimum10047
Maximum18623
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-11T06:46:10.202643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10047
5-th percentile10858
Q110881
median12449
Q317600.5
95-th percentile18579
Maximum18623
Range8576
Interquartile range (IQR)6719.5

Descriptive statistics

Standard deviation3136.7066
Coefficient of variation (CV)0.22995183
Kurtosis-1.4963836
Mean13640.712
Median Absolute Deviation (MAD)1571
Skewness0.51693251
Sum709317
Variance9838928.3
MonotonicityNot monotonic
2023-12-11T06:46:10.317101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
10881 8
 
15.4%
10878 5
 
9.6%
10858 5
 
9.6%
11410 3
 
5.8%
17605 3
 
5.8%
18579 2
 
3.8%
17749 2
 
3.8%
16037 1
 
1.9%
18623 1
 
1.9%
18608 1
 
1.9%
Other values (21) 21
40.4%
ValueCountFrequency (%)
10047 1
 
1.9%
10049 1
 
1.9%
10858 5
9.6%
10878 5
9.6%
10881 8
15.4%
10949 1
 
1.9%
11303 1
 
1.9%
11410 3
 
5.8%
11781 1
 
1.9%
13117 1
 
1.9%
ValueCountFrequency (%)
18623 1
 
1.9%
18608 1
 
1.9%
18579 2
3.8%
17998 1
 
1.9%
17960 1
 
1.9%
17957 1
 
1.9%
17956 1
 
1.9%
17749 2
3.8%
17605 3
5.8%
17599 1
 
1.9%

소재지지번주소
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-11T06:46:10.536864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length21.326923
Min length17

Characters and Unicode

Total characters1109
Distinct characters88
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row경기도 과천시 갈현동 4-1번지
2nd row경기도 김포시 양촌읍 학운리 2740번지
3rd row경기도 김포시 양촌읍 학운리 897번지
4th row경기도 동두천시 동두천동 534-1번지
5th row경기도 부천시 작동 산60-8번지
ValueCountFrequency (%)
경기도 52
21.7%
파주시 19
 
7.9%
문발동 11
 
4.6%
안성시 6
 
2.5%
평택시 6
 
2.5%
성남시 6
 
2.5%
성동리 5
 
2.1%
탄현면 5
 
2.1%
화성시 4
 
1.7%
중원구 4
 
1.7%
Other values (98) 122
50.8%
2023-12-11T06:46:10.903580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
188
 
17.0%
경 52
 
4.7%
번 52
 
4.7%
도 52
 
4.7%
기 52
 
4.7%
지 52
 
4.7%
시 52
 
4.7%
- 41
 
3.7%
동 36
 
3.2%
5 27
 
2.4%
Other values (78) 505
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 673
60.7%
Decimal Number 207
 
18.7%
Space Separator 188
 
17.0%
Dash Punctuation 41
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 52
 
7.7%
번 52
 
7.7%
도 52
 
7.7%
기 52
 
7.7%
지 52
 
7.7%
시 52
 
7.7%
동 36
 
5.3%
리 26
 
3.9%
성 23
 
3.4%
주 22
 
3.3%
Other values (66) 254
37.7%
Decimal Number
ValueCountFrequency (%)
5 27
13.0%
1 26
12.6%
3 24
11.6%
6 24
11.6%
0 23
11.1%
4 22
10.6%
2 20
9.7%
9 15
7.2%
7 15
7.2%
8 11
5.3%
Space Separator
ValueCountFrequency (%)
188
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 673
60.7%
Common 436
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 52
 
7.7%
번 52
 
7.7%
도 52
 
7.7%
기 52
 
7.7%
지 52
 
7.7%
시 52
 
7.7%
동 36
 
5.3%
리 26
 
3.9%
성 23
 
3.4%
주 22
 
3.3%
Other values (66) 254
37.7%
Common
ValueCountFrequency (%)
188
43.1%
- 41
 
9.4%
5 27
 
6.2%
1 26
 
6.0%
3 24
 
5.5%
6 24
 
5.5%
0 23
 
5.3%
4 22
 
5.0%
2 20
 
4.6%
9 15
 
3.4%
Other values (2) 26
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 673
60.7%
ASCII 436
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
188
43.1%
- 41
 
9.4%
5 27
 
6.2%
1 26
 
6.0%
3 24
 
5.5%
6 24
 
5.5%
0 23
 
5.3%
4 22
 
5.0%
2 20
 
4.6%
9 15
 
3.4%
Other values (2) 26
 
6.0%
Hangul
ValueCountFrequency (%)
경 52
 
7.7%
번 52
 
7.7%
도 52
 
7.7%
기 52
 
7.7%
지 52
 
7.7%
시 52
 
7.7%
동 36
 
5.3%
리 26
 
3.9%
성 23
 
3.4%
주 22
 
3.3%
Other values (66) 254
37.7%

소재지도로명주소
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-11T06:46:11.167696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length19.365385
Min length14

Characters and Unicode

Total characters1007
Distinct characters97
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row경기도 과천시 중앙로 59-92
2nd row경기도 김포시 양촌읍 황금1로 158
3rd row경기도 김포시 양촌읍 학운공단로 2
4th row경기도 동두천시 강변로730번길 25-45
5th row경기도 부천시 길주로 691
ValueCountFrequency (%)
경기도 52
21.7%
파주시 19
 
7.9%
성남시 6
 
2.5%
평택시 6
 
2.5%
안성시 6
 
2.5%
직지길 6
 
2.5%
산업단지길 5
 
2.1%
한록산길 5
 
2.1%
탄현면 5
 
2.1%
화성시 4
 
1.7%
Other values (100) 126
52.5%
2023-12-11T06:46:11.526316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
188
18.7%
기 53
 
5.3%
경 52
 
5.2%
도 52
 
5.2%
시 52
 
5.2%
길 41
 
4.1%
1 41
 
4.1%
3 24
 
2.4%
2 23
 
2.3%
주 23
 
2.3%
Other values (87) 458
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 632
62.8%
Space Separator 188
 
18.7%
Decimal Number 180
 
17.9%
Dash Punctuation 7
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 53
 
8.4%
경 52
 
8.2%
도 52
 
8.2%
시 52
 
8.2%
길 41
 
6.5%
주 23
 
3.6%
로 22
 
3.5%
단 21
 
3.3%
파 19
 
3.0%
성 19
 
3.0%
Other values (75) 278
44.0%
Decimal Number
ValueCountFrequency (%)
1 41
22.8%
3 24
13.3%
2 23
12.8%
8 16
 
8.9%
5 16
 
8.9%
6 15
 
8.3%
4 13
 
7.2%
9 12
 
6.7%
7 11
 
6.1%
0 9
 
5.0%
Space Separator
ValueCountFrequency (%)
188
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 632
62.8%
Common 375
37.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 53
 
8.4%
경 52
 
8.2%
도 52
 
8.2%
시 52
 
8.2%
길 41
 
6.5%
주 23
 
3.6%
로 22
 
3.5%
단 21
 
3.3%
파 19
 
3.0%
성 19
 
3.0%
Other values (75) 278
44.0%
Common
ValueCountFrequency (%)
188
50.1%
1 41
 
10.9%
3 24
 
6.4%
2 23
 
6.1%
8 16
 
4.3%
5 16
 
4.3%
6 15
 
4.0%
4 13
 
3.5%
9 12
 
3.2%
7 11
 
2.9%
Other values (2) 16
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 632
62.8%
ASCII 375
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
188
50.1%
1 41
 
10.9%
3 24
 
6.4%
2 23
 
6.1%
8 16
 
4.3%
5 16
 
4.3%
6 15
 
4.0%
4 13
 
3.5%
9 12
 
3.2%
7 11
 
2.9%
Other values (2) 16
 
4.3%
Hangul
ValueCountFrequency (%)
기 53
 
8.4%
경 52
 
8.2%
도 52
 
8.2%
시 52
 
8.2%
길 41
 
6.5%
주 23
 
3.6%
로 22
 
3.5%
단 21
 
3.3%
파 19
 
3.0%
성 19
 
3.0%
Other values (75) 278
44.0%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.466302
Minimum36.957987
Maximum37.933854
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-11T06:46:11.669343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.957987
5-th percentile36.971391
Q137.090618
median37.555049
Q337.73023
95-th percentile37.865397
Maximum37.933854
Range0.97586754
Interquartile range (IQR)0.63961215

Descriptive statistics

Standard deviation0.32782482
Coefficient of variation (CV)0.008749858
Kurtosis-1.4318037
Mean37.466302
Median Absolute Deviation (MAD)0.20298777
Skewness-0.41268129
Sum1948.2477
Variance0.10746911
MonotonicityNot monotonic
2023-12-11T06:46:11.808971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4207754637 1
 
1.9%
37.7922405713 1
 
1.9%
37.7095790195 1
 
1.9%
37.7930593923 1
 
1.9%
37.7169268066 1
 
1.9%
37.7143299857 1
 
1.9%
37.793973898 1
 
1.9%
37.7304917002 1
 
1.9%
37.7305414027 1
 
1.9%
37.7711442624 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
36.9579866623 1
1.9%
36.970693985 1
1.9%
36.9711813968 1
1.9%
36.9715622764 1
1.9%
36.9724567008 1
1.9%
36.9725596764 1
1.9%
36.9786383316 1
1.9%
36.9814490928 1
1.9%
37.0342262854 1
1.9%
37.0344574797 1
1.9%
ValueCountFrequency (%)
37.933854205 1
1.9%
37.8655830374 1
1.9%
37.8654997601 1
1.9%
37.8653125087 1
1.9%
37.793973898 1
1.9%
37.7930593923 1
1.9%
37.7927181462 1
1.9%
37.7922405713 1
1.9%
37.7915410392 1
1.9%
37.7711442624 1
1.9%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.90853
Minimum126.58224
Maximum127.37856
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-11T06:46:11.931127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.58224
5-th percentile126.68436
Q1126.6918
median126.84385
Q3127.09134
95-th percentile127.26652
Maximum127.37856
Range0.79631538
Interquartile range (IQR)0.39954519

Descriptive statistics

Standard deviation0.2180018
Coefficient of variation (CV)0.0017177869
Kurtosis-1.1698657
Mean126.90853
Median Absolute Deviation (MAD)0.15675055
Skewness0.37547637
Sum6599.2436
Variance0.047524787
MonotonicityNot monotonic
2023-12-11T06:46:12.069369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9856090329 1
 
1.9%
126.6913129243 1
 
1.9%
126.6843613557 1
 
1.9%
126.6924284155 1
 
1.9%
126.6872761741 1
 
1.9%
126.6858182538 1
 
1.9%
126.6917256299 1
 
1.9%
126.7084965573 1
 
1.9%
126.7132282264 1
 
1.9%
126.8392639702 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
126.5822447793 1
1.9%
126.6154093864 1
1.9%
126.6843613557 1
1.9%
126.6843672826 1
1.9%
126.6858182538 1
1.9%
126.6859311995 1
1.9%
126.6860749458 1
1.9%
126.6865315141 1
1.9%
126.6869240595 1
1.9%
126.6872761741 1
1.9%
ValueCountFrequency (%)
127.3785601638 1
1.9%
127.2702961973 1
1.9%
127.2671590874 1
1.9%
127.2660030722 1
1.9%
127.2636061345 1
1.9%
127.1805749797 1
1.9%
127.1744853552 1
1.9%
127.1740755781 1
1.9%
127.1684971572 1
1.9%
127.1595991503 1
1.9%

Interactions

2023-12-11T06:46:08.460540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:46:08.037415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:46:08.264791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:46:08.736699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:46:08.094681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:46:08.332650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:46:08.800137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:46:08.172377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:46:08.389628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:46:12.179597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사업장명대기종별구분명폐수종별구분명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
시군명1.0001.0000.3930.8180.9771.0001.0000.9440.939
사업장명1.0001.0001.0001.0001.0001.0001.0001.0001.000
대기종별구분명0.3931.0001.0000.9230.4031.0001.0000.3020.000
폐수종별구분명0.8181.0000.9231.0000.7771.0001.0000.5540.762
소재지우편번호0.9771.0000.4030.7771.0001.0001.0000.8490.883
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
WGS84위도0.9441.0000.3020.5540.8491.0001.0001.0000.900
WGS84경도0.9391.0000.0000.7620.8831.0001.0000.9001.000
2023-12-11T06:46:12.289805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대기종별구분명폐수종별구분명시군명
대기종별구분명1.0000.6580.224
폐수종별구분명0.6581.0000.566
시군명0.2240.5661.000
2023-12-11T06:46:12.397690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명대기종별구분명폐수종별구분명
소재지우편번호1.000-0.8030.6560.8700.2790.601
WGS84위도-0.8031.000-0.5060.7690.1730.360
WGS84경도0.656-0.5061.0000.7430.0000.383
시군명0.8700.7690.7431.0000.2240.566
대기종별구분명0.2790.1730.0000.2241.0000.658
폐수종별구분명0.6010.3600.3830.5660.6581.000

Missing values

2023-12-11T06:46:08.912456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:46:09.040828image/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

시군명사업장명사업자등록번호관할기관명대표자명대기종별구분명폐수종별구분명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
0과천시과천시맑은물사업소<NA><NA><NA><NA>413841경기도 과천시 갈현동 4-1번지경기도 과천시 중앙로 59-9237.420775126.985609
1김포시㈜두웰<NA><NA><NA>5510047경기도 김포시 양촌읍 학운리 2740번지경기도 김포시 양촌읍 황금1로 15837.62051126.615409
2김포시㈜에스로드화장품<NA><NA><NA><NA>510049경기도 김포시 양촌읍 학운리 897번지경기도 김포시 양촌읍 학운공단로 237.602807126.582245
3동두천시동두천패션칼라사업협동조합<NA><NA><NA>5511303경기도 동두천시 동두천동 534-1번지경기도 동두천시 강변로730번길 25-4537.933854127.051176
4부천시까치울정수장<NA><NA><NA><NA>314477경기도 부천시 작동 산60-8번지경기도 부천시 길주로 69137.507292126.8193
5성남시동성유리<NA><NA><NA><NA>513230경기도 성남시 중원구 상대원동 513-3번지경기도 성남시 중원구 갈마치로 18637.430378127.174485
6성남시CJ씨푸드㈜<NA><NA><NA>3313403경기도 성남시 중원구 상대원동 5449-1번지경기도 성남시 중원구 둔촌대로388번길 3237.430426127.159599
7성남시대웅바이오㈜<NA><NA><NA>4513211경기도 성남시 중원구 상대원동 223-23번지경기도 성남시 중원구 갈마치로 24437.436253127.174076
8성남시한국지역난방공사 분당지사<NA><NA><NA>3413585경기도 성남시 분당구 분당동 186번지경기도 성남시 분당구 분당로 36837.365169127.147014
9성남시성남전기공업㈜<NA><NA><NA>4513220경기도 성남시 중원구 상대원동 150번지경기도 성남시 중원구 사기막골로9번길 1637.434967127.168497
시군명사업장명사업자등록번호관할기관명대표자명대기종별구분명폐수종별구분명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
42평택시(주)아이컴포넌트 3공장<NA><NA><NA>5<NA>17998경기도 평택시 팽성읍 추팔리 397-5번지경기도 평택시 팽성읍 추팔산단1길 7436.957987127.080231
43평택시(주)삼오<NA><NA><NA>5<NA>17749경기도 평택시 칠괴동 575-1번지경기도 평택시 산단로197번길 4537.034457127.091111
44평택시린텍스페셜러티필름코리아(주)<NA><NA><NA>5<NA>17956경기도 평택시 포승읍 원정리 1177번지경기도 평택시 포승읍 포승공단로117번길 3536.981449126.839942
45평택시(주)온이스<NA><NA><NA>4517749경기도 평택시 칠괴동 577-3번지경기도 평택시 산단로197번길 5637.034226127.092034
46평택시현대글로비스(주)<NA><NA><NA>4517957경기도 평택시 포승읍 원정리 1206-5번지경기도 평택시 포승읍 포승공단로 2336.978638126.837011
47평택시한국단자공업(주)평택<NA><NA><NA>5517960경기도 평택시 포승읍 만호리 585번지경기도 평택시 포승읍 평택항로156번길 3636.97256126.84622
48화성시대웅바이오㈜제3공장<NA><NA><NA>3418608경기도 화성시 향남읍 하길리 1404-1번지경기도 화성시 향남읍 제약단지로 2937.091146126.91428
49화성시한국쓰리엠㈜<NA><NA><NA><NA>518579경기도 화성시 장안면 금의리 763-2번지경기도 화성시 장안면 장안공단1길 1837.110352126.841481
50화성시한국우에무라㈜<NA><NA><NA>4518579경기도 화성시 장안면 금의리 761-6번지경기도 화성시 장안면 장안공단6길 4637.112237126.838482
51화성시㈜알피바이오<NA><NA><NA>4518623경기도 화성시 향남읍 상신리 906-6번지경기도 화성시 향남읍 제약공단4길 35-737.089034126.906555