Overview

Dataset statistics

Number of variables11
Number of observations55
Missing cells57
Missing cells (%)9.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory96.4 B

Variable types

Categorical3
Text3
Unsupported1
Numeric4

Dataset

Description수질 기본배출 부과금 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=55SM64H11859W4K3DS3011654138&infSeq=1

Alerts

시군명 has constant value ""Constant
집계년도 is highly overall correlated with 반기구분명High correlation
반기구분명 is highly overall correlated with 집계년도High correlation
부과금액(원) is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with 부과금액(원) and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 부과금액(원) and 1 other fieldsHigh correlation
납부자실명번호 has 55 (100.0%) missing valuesMissing
소재지우편번호 has 2 (3.6%) missing valuesMissing
부과금액(원) has unique valuesUnique
납부자실명번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 21:53:30.084523
Analysis finished2023-12-10 21:53:32.504967
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023
39 
2022
16 

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 39
70.9%
2022 16
29.1%

Length

2023-12-11T06:53:32.563177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:53:32.650602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 39
70.9%
2022 16
29.1%

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size572.0 B
경기도
55 

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 55
100.0%

Length

2023-12-11T06:53:32.747259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:53:32.828720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 55
100.0%

사업장명
Text

Distinct46
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-11T06:53:33.050889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length8.4727273
Min length3

Characters and Unicode

Total characters466
Distinct characters107
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)69.1%

Sample

1st row우원개발(주)
2nd row인그리디언코리아(유) 이천공장
3rd row동원시스템즈(주) 이천사업장
4th row동방에프티엘(주)1공장
5th row대원제약(주)
ValueCountFrequency (%)
금풍건설이엔씨(주 3
 
4.8%
이천공장 3
 
4.8%
샘표식품(주)이천공장 2
 
3.2%
코스맥스(주 2
 
3.2%
동원시스템즈(주 2
 
3.2%
서천건설㈜ 2
 
3.2%
영풍제지(주 2
 
3.2%
광혁건설(주 2
 
3.2%
삼정펄프(주 2
 
3.2%
인그리디언코리아(유 2
 
3.2%
Other values (40) 41
65.1%
2023-12-11T06:53:33.425406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 49
 
10.5%
) 49
 
10.5%
주 48
 
10.3%
이 16
 
3.4%
장 16
 
3.4%
제 13
 
2.8%
공 12
 
2.6%
천 12
 
2.6%
건 11
 
2.4%
설 11
 
2.4%
Other values (97) 229
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 354
76.0%
Open Punctuation 49
 
10.5%
Close Punctuation 49
 
10.5%
Space Separator 8
 
1.7%
Other Symbol 4
 
0.9%
Decimal Number 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 48
 
13.6%
이 16
 
4.5%
장 16
 
4.5%
제 13
 
3.7%
공 12
 
3.4%
천 12
 
3.4%
건 11
 
3.1%
설 11
 
3.1%
약 10
 
2.8%
원 9
 
2.5%
Other values (91) 196
55.4%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 358
76.8%
Common 108
 
23.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 48
 
13.4%
이 16
 
4.5%
장 16
 
4.5%
제 13
 
3.6%
공 12
 
3.4%
천 12
 
3.4%
건 11
 
3.1%
설 11
 
3.1%
약 10
 
2.8%
원 9
 
2.5%
Other values (92) 200
55.9%
Common
ValueCountFrequency (%)
( 49
45.4%
) 49
45.4%
8
 
7.4%
1 1
 
0.9%
2 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 354
76.0%
ASCII 108
 
23.2%
None 4
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 49
45.4%
) 49
45.4%
8
 
7.4%
1 1
 
0.9%
2 1
 
0.9%
Hangul
ValueCountFrequency (%)
주 48
 
13.6%
이 16
 
4.5%
장 16
 
4.5%
제 13
 
3.7%
공 12
 
3.4%
천 12
 
3.4%
건 11
 
3.1%
설 11
 
3.1%
약 10
 
2.8%
원 9
 
2.5%
Other values (91) 196
55.4%
None
ValueCountFrequency (%)
㈜ 4
100.0%

납부자실명번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing55
Missing (%)100.0%
Memory size627.0 B

반기구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
상반기
39 
하반기
16 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상반기 39
70.9%
하반기 16
29.1%

Length

2023-12-11T06:53:33.565554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:53:33.656074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상반기 39
70.9%
하반기 16
29.1%

부과금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3310973.3
Minimum3450
Maximum54309170
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-11T06:53:33.773092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3450
5-th percentile5754
Q115290
median115410
Q31833545
95-th percentile13921629
Maximum54309170
Range54305720
Interquartile range (IQR)1818255

Descriptive statistics

Standard deviation9191512.9
Coefficient of variation (CV)2.7760758
Kurtosis20.863853
Mean3310973.3
Median Absolute Deviation (MAD)110090
Skewness4.3913444
Sum1.8210353 × 108
Variance8.448391 × 1013
MonotonicityNot monotonic
2023-12-11T06:53:33.923538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2732070 1
 
1.8%
38190100 1
 
1.8%
12310 1
 
1.8%
9310 1
 
1.8%
373820 1
 
1.8%
1174320 1
 
1.8%
322300 1
 
1.8%
4400 1
 
1.8%
5940 1
 
1.8%
60570 1
 
1.8%
Other values (45) 45
81.8%
ValueCountFrequency (%)
3450 1
1.8%
4400 1
1.8%
5320 1
1.8%
5940 1
1.8%
6570 1
1.8%
6610 1
1.8%
7730 1
1.8%
8790 1
1.8%
9310 1
1.8%
9650 1
1.8%
ValueCountFrequency (%)
54309170 1
1.8%
38190100 1
1.8%
16706320 1
1.8%
12728190 1
1.8%
9394620 1
1.8%
7876500 1
1.8%
6592360 1
1.8%
5899020 1
1.8%
5614380 1
1.8%
3826020 1
1.8%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct30
Distinct (%)56.6%
Missing2
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean16343.566
Minimum10216
Maximum18626
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-11T06:53:34.051407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10216
5-th percentile10436.8
Q115207
median17342
Q318622
95-th percentile18622.4
Maximum18626
Range8410
Interquartile range (IQR)3415

Descriptive statistics

Standard deviation2777.6729
Coefficient of variation (CV)0.16995513
Kurtosis0.21614939
Mean16343.566
Median Absolute Deviation (MAD)1280
Skewness-1.2753584
Sum866209
Variance7715466.5
MonotonicityNot monotonic
2023-12-11T06:53:34.179345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
18622 12
21.8%
17326 3
 
5.5%
17342 3
 
5.5%
17714 3
 
5.5%
11413 2
 
3.6%
17706 2
 
3.6%
17396 2
 
3.6%
17820 2
 
3.6%
18623 2
 
3.6%
15207 2
 
3.6%
Other values (20) 20
36.4%
(Missing) 2
 
3.6%
ValueCountFrequency (%)
10216 1
1.8%
10430 1
1.8%
10435 1
1.8%
10438 1
1.8%
10456 1
1.8%
11168 1
1.8%
11192 1
1.8%
11413 2
3.6%
14324 1
1.8%
14935 1
1.8%
ValueCountFrequency (%)
18626 1
 
1.8%
18623 2
 
3.6%
18622 12
21.8%
18365 1
 
1.8%
17957 1
 
1.8%
17820 2
 
3.6%
17714 3
 
5.5%
17706 2
 
3.6%
17396 2
 
3.6%
17342 3
 
5.5%

소재지지번주소
Text

Distinct47
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-11T06:53:34.439779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length21.781818
Min length15

Characters and Unicode

Total characters1198
Distinct characters91
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

Unique40 ?
Unique (%)72.7%

Sample

1st row경기도 시흥시 하중동 867-12번지
2nd row경기도 이천시 부발읍 마암리 234-17번지
3rd row경기도 이천시 대월면 사동리 8번지
4th row경기도 화성시 향남읍 상신리 904-5번지
5th row경기도 화성시 향남읍 상신리 903-1번지
ValueCountFrequency (%)
경기도 55
20.4%
화성시 16
 
5.9%
상신리 14
 
5.2%
향남읍 14
 
5.2%
이천시 10
 
3.7%
평택시 8
 
3.0%
부발읍 5
 
1.9%
고양시 5
 
1.9%
진위면 5
 
1.9%
시흥시 5
 
1.9%
Other values (97) 133
49.3%
2023-12-11T06:53:34.821988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
215
 
17.9%
시 60
 
5.0%
경 57
 
4.8%
도 56
 
4.7%
기 55
 
4.6%
번 45
 
3.8%
지 45
 
3.8%
리 39
 
3.3%
- 36
 
3.0%
1 33
 
2.8%
Other values (81) 557
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 736
61.4%
Space Separator 215
 
17.9%
Decimal Number 209
 
17.4%
Dash Punctuation 36
 
3.0%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 60
 
8.2%
경 57
 
7.7%
도 56
 
7.6%
기 55
 
7.5%
번 45
 
6.1%
지 45
 
6.1%
리 39
 
5.3%
읍 22
 
3.0%
동 22
 
3.0%
화 17
 
2.3%
Other values (68) 318
43.2%
Decimal Number
ValueCountFrequency (%)
1 33
15.8%
0 29
13.9%
2 28
13.4%
3 27
12.9%
9 22
10.5%
4 17
8.1%
7 17
8.1%
8 14
6.7%
5 12
 
5.7%
6 10
 
4.8%
Space Separator
ValueCountFrequency (%)
215
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 736
61.4%
Common 462
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 60
 
8.2%
경 57
 
7.7%
도 56
 
7.6%
기 55
 
7.5%
번 45
 
6.1%
지 45
 
6.1%
리 39
 
5.3%
읍 22
 
3.0%
동 22
 
3.0%
화 17
 
2.3%
Other values (68) 318
43.2%
Common
ValueCountFrequency (%)
215
46.5%
- 36
 
7.8%
1 33
 
7.1%
0 29
 
6.3%
2 28
 
6.1%
3 27
 
5.8%
9 22
 
4.8%
4 17
 
3.7%
7 17
 
3.7%
8 14
 
3.0%
Other values (3) 24
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 736
61.4%
ASCII 462
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
215
46.5%
- 36
 
7.8%
1 33
 
7.1%
0 29
 
6.3%
2 28
 
6.1%
3 27
 
5.8%
9 22
 
4.8%
4 17
 
3.7%
7 17
 
3.7%
8 14
 
3.0%
Other values (3) 24
 
5.2%
Hangul
ValueCountFrequency (%)
시 60
 
8.2%
경 57
 
7.7%
도 56
 
7.6%
기 55
 
7.5%
번 45
 
6.1%
지 45
 
6.1%
리 39
 
5.3%
읍 22
 
3.0%
동 22
 
3.0%
화 17
 
2.3%
Other values (68) 318
43.2%

소재지도로명주소
Text

Distinct47
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-11T06:53:35.099673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length21.2
Min length15

Characters and Unicode

Total characters1166
Distinct characters96
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

Unique40 ?
Unique (%)72.7%

Sample

1st row경기도 시흥시 연성로29번길 14-1
2nd row경기도 이천시 부발읍 중부대로 1346
3rd row경기도 이천시 대월면 경충대로 1885-16
4th row경기도 화성시 향남읍 제약공단4길 78
5th row경기도 화성시 향남읍 제약공단1길 24
ValueCountFrequency (%)
경기도 55
 
20.4%
화성시 16
 
5.9%
향남읍 14
 
5.2%
이천시 10
 
3.7%
평택시 8
 
3.0%
시흥시 5
 
1.9%
제약공단2길 5
 
1.9%
진위면 5
 
1.9%
고양시 5
 
1.9%
부발읍 5
 
1.9%
Other values (100) 142
52.6%
2023-12-11T06:53:35.557618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
215
 
18.4%
시 60
 
5.1%
경 59
 
5.1%
도 56
 
4.8%
기 55
 
4.7%
1 38
 
3.3%
로 30
 
2.6%
2 28
 
2.4%
3 26
 
2.2%
길 25
 
2.1%
Other values (86) 574
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 719
61.7%
Space Separator 215
 
18.4%
Decimal Number 213
 
18.3%
Dash Punctuation 17
 
1.5%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 60
 
8.3%
경 59
 
8.2%
도 56
 
7.8%
기 55
 
7.6%
로 30
 
4.2%
길 25
 
3.5%
읍 22
 
3.1%
화 17
 
2.4%
성 17
 
2.4%
면 17
 
2.4%
Other values (73) 361
50.2%
Decimal Number
ValueCountFrequency (%)
1 38
17.8%
2 28
13.1%
3 26
12.2%
7 22
10.3%
5 20
9.4%
8 20
9.4%
6 18
8.5%
4 18
8.5%
0 12
 
5.6%
9 11
 
5.2%
Space Separator
ValueCountFrequency (%)
215
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 719
61.7%
Common 447
38.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 60
 
8.3%
경 59
 
8.2%
도 56
 
7.8%
기 55
 
7.6%
로 30
 
4.2%
길 25
 
3.5%
읍 22
 
3.1%
화 17
 
2.4%
성 17
 
2.4%
면 17
 
2.4%
Other values (73) 361
50.2%
Common
ValueCountFrequency (%)
215
48.1%
1 38
 
8.5%
2 28
 
6.3%
3 26
 
5.8%
7 22
 
4.9%
5 20
 
4.5%
8 20
 
4.5%
6 18
 
4.0%
4 18
 
4.0%
- 17
 
3.8%
Other values (3) 25
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 719
61.7%
ASCII 447
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
215
48.1%
1 38
 
8.5%
2 28
 
6.3%
3 26
 
5.8%
7 22
 
4.9%
5 20
 
4.5%
8 20
 
4.5%
6 18
 
4.0%
4 18
 
4.0%
- 17
 
3.8%
Other values (3) 25
 
5.6%
Hangul
ValueCountFrequency (%)
시 60
 
8.3%
경 59
 
8.2%
도 56
 
7.8%
기 55
 
7.6%
로 30
 
4.2%
길 25
 
3.5%
읍 22
 
3.1%
화 17
 
2.4%
성 17
 
2.4%
면 17
 
2.4%
Other values (73) 361
50.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct49
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.284767
Minimum36.986503
Maximum38.105129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-11T06:53:35.715021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.986503
5-th percentile37.06795
Q137.093731
median37.238144
Q337.379559
95-th percentile37.848521
Maximum38.105129
Range1.1186256
Interquartile range (IQR)0.28582831

Descriptive statistics

Standard deviation0.24965564
Coefficient of variation (CV)0.0066959152
Kurtosis1.7524938
Mean37.284767
Median Absolute Deviation (MAD)0.14404411
Skewness1.4592928
Sum2050.6622
Variance0.062327937
MonotonicityNot monotonic
2023-12-11T06:53:35.852625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
37.23814415 3
 
5.5%
37.27068031 2
 
3.6%
37.02150953 2
 
3.6%
37.33834132 2
 
3.6%
37.21182101 2
 
3.6%
37.08785355 1
 
1.8%
37.09264112 1
 
1.8%
37.09190179 1
 
1.8%
37.09240573 1
 
1.8%
37.39335285 1
 
1.8%
Other values (39) 39
70.9%
ValueCountFrequency (%)
36.9865031 1
1.8%
37.02150953 2
3.6%
37.08785355 1
1.8%
37.08841779 1
1.8%
37.09083141 1
1.8%
37.09097589 1
1.8%
37.09190179 1
1.8%
37.09192314 1
1.8%
37.09196584 1
1.8%
37.09240573 1
1.8%
ValueCountFrequency (%)
38.10512873 1
1.8%
37.85909609 1
1.8%
37.85856612 1
1.8%
37.84421633 1
1.8%
37.77008456 1
1.8%
37.68028585 1
1.8%
37.64797138 1
1.8%
37.63272288 1
1.8%
37.43471724 1
1.8%
37.40810003 1
1.8%

WGS84경도
Real number (ℝ)

Distinct49
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.05373
Minimum126.73647
Maximum127.70395
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-11T06:53:36.004009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.73647
5-th percentile126.79565
Q1126.90038
median126.95931
Q3127.19095
95-th percentile127.50422
Maximum127.70395
Range0.9674821
Interquartile range (IQR)0.29057085

Descriptive statistics

Standard deviation0.24767719
Coefficient of variation (CV)0.0019493893
Kurtosis-0.16738023
Mean127.05373
Median Absolute Deviation (MAD)0.1039315
Skewness1.0115748
Sum6987.9554
Variance0.06134399
MonotonicityNot monotonic
2023-12-11T06:53:36.161178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
127.5042166 3
 
5.5%
127.4669636 2
 
3.6%
127.018152 2
 
3.6%
126.8553821 2
 
3.6%
127.394307 2
 
3.6%
126.9053416 1
 
1.8%
126.909043 1
 
1.8%
126.9039058 1
 
1.8%
126.9030863 1
 
1.8%
126.867647 1
 
1.8%
Other values (39) 39
70.9%
ValueCountFrequency (%)
126.7364716 1
1.8%
126.7421028 1
1.8%
126.7705514 1
1.8%
126.8064114 1
1.8%
126.8116179 1
1.8%
126.8242181 1
1.8%
126.8313374 1
1.8%
126.8553821 2
3.6%
126.8618491 1
1.8%
126.8643856 1
1.8%
ValueCountFrequency (%)
127.7039537 1
 
1.8%
127.5042166 3
5.5%
127.4944234 1
 
1.8%
127.4866509 1
 
1.8%
127.472469 1
 
1.8%
127.4669636 2
3.6%
127.394307 2
3.6%
127.2385705 1
 
1.8%
127.2161731 1
 
1.8%
127.2046228 1
 
1.8%

Interactions

2023-12-11T06:53:31.909805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:30.649973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:31.013263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:31.593384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:31.998828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:30.745221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:31.104202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:31.674916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:32.068201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:30.823658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:31.187499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:31.750422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:32.140301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:30.925826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:31.279647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:31.827594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:53:36.251488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집계년도사업장명반기구분명부과금액(원)소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
집계년도1.0000.0000.9980.2020.3360.0000.0000.1720.416
사업장명0.0001.0000.0000.0000.9830.9970.9970.9440.988
반기구분명0.9980.0001.0000.2020.3360.0000.0000.1720.416
부과금액(원)0.2020.0000.2021.0000.4430.0000.0000.7290.671
소재지우편번호0.3360.9830.3360.4431.0001.0001.0000.9780.688
소재지지번주소0.0000.9970.0000.0001.0001.0001.0001.0001.000
소재지도로명주소0.0000.9970.0000.0001.0001.0001.0001.0001.000
WGS84위도0.1720.9440.1720.7290.9781.0001.0001.0000.926
WGS84경도0.4160.9880.4160.6710.6881.0001.0000.9261.000
2023-12-11T06:53:36.389114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집계년도반기구분명
집계년도1.0000.955
반기구분명0.9551.000
2023-12-11T06:53:36.489692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과금액(원)소재지우편번호WGS84위도WGS84경도집계년도반기구분명
부과금액(원)1.000-0.6680.5930.0430.1420.142
소재지우편번호-0.6681.000-0.931-0.0470.2420.242
WGS84위도0.593-0.9311.0000.0000.1520.152
WGS84경도0.043-0.0470.0001.0000.3850.385
집계년도0.1420.2420.1520.3851.0000.955
반기구분명0.1420.2420.1520.3850.9551.000

Missing values

2023-12-11T06:53:32.248020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:53:32.424292image/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

집계년도시군명사업장명납부자실명번호반기구분명부과금액(원)소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
02023경기도우원개발(주)<NA>상반기273207014976경기도 시흥시 하중동 867-12번지경기도 시흥시 연성로29번길 14-137.391978126.806411
12023경기도인그리디언코리아(유) 이천공장<NA>상반기3819010017326경기도 이천시 부발읍 마암리 234-17번지경기도 이천시 부발읍 중부대로 134637.27068127.466964
22023경기도동원시스템즈(주) 이천사업장<NA>상반기151310017342경기도 이천시 대월면 사동리 8번지경기도 이천시 대월면 경충대로 1885-1637.238144127.504217
32023경기도동방에프티엘(주)1공장<NA>상반기1410018622경기도 화성시 향남읍 상신리 904-5번지경기도 화성시 향남읍 제약공단4길 7837.090976126.901094
42023경기도대원제약(주)<NA>상반기1198018622경기도 화성시 향남읍 상신리 903-1번지경기도 화성시 향남읍 제약공단1길 2437.094107126.904852
52023경기도금풍건설이엔씨(주)<NA>상반기382602015207경기도 안산시 상록구 부곡동 156-3경기도 안산시 상록구 부곡동 156-337.338341126.855382
62023경기도금풍건설이엔씨(주)<NA>상반기11364010430경기도 고양시 일산동구 장항동 903번지경기도 고양시 일산동구 노루목로 1037.647971126.770551
72023경기도광혁건설(주)<NA>상반기310045010456경기도 고양시 덕양구 대장동 390번지경기도 고양시 덕양구 대주로107번길 71-6937.632723126.811618
82023경기도광혁건설(주)<NA>상반기215399010438경기도 고양시 덕양구 대장동 435-3경기도 고양시 덕양구 대장동 435-337.377103127.060187
92023경기도강릉건설(주)<NA>상반기589902014324경기도 광명시 소하동 700-32,1209,702-27경기도 광명시 소하동 700-32,1209,702-2737.434717126.898079
집계년도시군명사업장명납부자실명번호반기구분명부과금액(원)소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
452022경기도(주)알엠 화성공장<NA>하반기1648018626경기도 화성시 양감면 사창리 775-7번지경기도 화성시 양감면 사격장길 88-5137.0941126.959314
462022경기도(주)매일유업<NA>하반기7979017714경기도 평택시 진위면 가곡리 480번지경기도 평택시 진위면 진위서로 6337.108721127.069395
472022경기도(주)대원<NA>하반기7115017342경기도 이천시 대월면 사동리 8번지경기도 이천시 대월면 경충대로 1885-1637.238144127.504217
482022경기도(주)대련건설<NA>하반기1670632010435경기도 고양시 일산동구 백석동 487-3경기도 고양시 일산동구 백석동 487-338.105129127.703954
492022경기도해창개발(주)<NA>하반기5402011192경기도 포천시 내촌면 음현리 산39경기도 포천시 내촌면 음현리 산3937.770085127.23857
502022경기도인그리디언코리아(유) 이천공장<NA>하반기5430917017326경기도 이천시 부발읍 마암리 234-17번지경기도 이천시 부발읍 중부대로 134637.27068127.466964
512022경기도용인정수장<NA>하반기18371017031경기도 용인시 처인구 모현읍 매산리 310-2번지경기도 용인시 처인구 모현읍 곡현로619번길 7737.335259127.216173
522022경기도오비맥주(주)이천공장<NA>하반기659236017326경기도 이천시 부발읍 신하리 27번지경기도 이천시 부발읍 경충대로 231437.267247127.472469
532022경기도영풍제지(주)<NA>하반기11541017706경기도 평택시 진위면 견산리 571-6번지경기도 평택시 진위면 서탄로 937.103485127.0622
542022경기도샘표식품(주)이천공장<NA>하반기59227017396경기도 이천시 호법면 매곡리 231번지경기도 이천시 호법면 이섭대천로 5837.211821127.394307