Overview

Dataset statistics

Number of variables9
Number of observations65
Missing cells12
Missing cells (%)2.1%
Duplicate rows1
Duplicate rows (%)1.5%
Total size in memory4.8 KiB
Average record size in memory76.0 B

Variable types

Text4
DateTime2
Categorical1
Numeric2

Dataset

Description전북특별자치도 전주시 내 저수조청소업을 제공하며, 사업장명, 인허가일자, 영업상태명, 소재지전화번호, 도로명주소 등을 제공합니다항목 : 사업장명, 인허가일자, 영업상태명, 소재지전화번호, 도로명주소, 지번주소, 위도, 경도제공부서 : 맑은물사업소 급수과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15083126/fileData.do

Alerts

영업상태명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 1 (1.5%) duplicate rowsDuplicates
소재지전화 has 12 (18.5%) missing valuesMissing

Reproduction

Analysis started2024-03-15 01:50:18.149980
Analysis finished2024-03-15 01:50:21.433990
Duration3.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct63
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size648.0 B
2024-03-15T10:50:22.235164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length7.0923077
Min length3

Characters and Unicode

Total characters461
Distinct characters128
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)93.8%

Sample

1st row(유) 아름다운환경
2nd row(유)HR하누리
3rd row(유)개미환경위생
4th row(유)국민종합주택관리
5th row(유)깨끗한세상
ValueCountFrequency (%)
유)세영환경 2
 
2.9%
주식회사에코유 2
 
2.9%
한국환경방역공사 1
 
1.5%
유 1
 
1.5%
아름다운환경 1
 
1.5%
ok시스템 1
 
1.5%
늘푸른환경 1
 
1.5%
나눔종합관리 1
 
1.5%
주)우리 1
 
1.5%
국제환경 1
 
1.5%
Other values (56) 56
82.4%
2024-03-15T10:50:23.398736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 43
 
9.3%
) 43
 
9.3%
유 36
 
7.8%
환 26
 
5.6%
경 26
 
5.6%
주 16
 
3.5%
리 10
 
2.2%
사 9
 
2.0%
에 7
 
1.5%
한 7
 
1.5%
Other values (118) 238
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 365
79.2%
Open Punctuation 43
 
9.3%
Close Punctuation 43
 
9.3%
Uppercase Letter 6
 
1.3%
Space Separator 3
 
0.7%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 36
 
9.9%
환 26
 
7.1%
경 26
 
7.1%
주 16
 
4.4%
리 10
 
2.7%
사 9
 
2.5%
에 7
 
1.9%
한 7
 
1.9%
업 7
 
1.9%
스 7
 
1.9%
Other values (108) 214
58.6%
Uppercase Letter
ValueCountFrequency (%)
O 1
16.7%
K 1
16.7%
A 1
16.7%
B 1
16.7%
R 1
16.7%
H 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 365
79.2%
Common 90
 
19.5%
Latin 6
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 36
 
9.9%
환 26
 
7.1%
경 26
 
7.1%
주 16
 
4.4%
리 10
 
2.7%
사 9
 
2.5%
에 7
 
1.9%
한 7
 
1.9%
업 7
 
1.9%
스 7
 
1.9%
Other values (108) 214
58.6%
Latin
ValueCountFrequency (%)
O 1
16.7%
K 1
16.7%
A 1
16.7%
B 1
16.7%
R 1
16.7%
H 1
16.7%
Common
ValueCountFrequency (%)
( 43
47.8%
) 43
47.8%
3
 
3.3%
& 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 365
79.2%
ASCII 96
 
20.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 43
44.8%
) 43
44.8%
3
 
3.1%
O 1
 
1.0%
K 1
 
1.0%
A 1
 
1.0%
B 1
 
1.0%
& 1
 
1.0%
R 1
 
1.0%
H 1
 
1.0%
Hangul
ValueCountFrequency (%)
유 36
 
9.9%
환 26
 
7.1%
경 26
 
7.1%
주 16
 
4.4%
리 10
 
2.7%
사 9
 
2.5%
에 7
 
1.9%
한 7
 
1.9%
업 7
 
1.9%
스 7
 
1.9%
Other values (108) 214
58.6%

인허가일자
Date

Distinct58
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size648.0 B
Minimum1997-03-22 00:00:00
Maximum2023-04-05 00:00:00
2024-03-15T10:50:23.812757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:50:24.221860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size648.0 B
영업/정상
65 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 65
100.0%

Length

2024-03-15T10:50:24.626089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:50:24.936891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 65
100.0%

소재지전화
Text

MISSING 

Distinct52
Distinct (%)98.1%
Missing12
Missing (%)18.5%
Memory size648.0 B
2024-03-15T10:50:25.751100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.037736
Min length12

Characters and Unicode

Total characters638
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)96.2%

Sample

1st row063-232-8382
2nd row070-7530-1960
3rd row063-253-0762
4th row063-286-3348
5th row063-223-2365
ValueCountFrequency (%)
063-277-7479 2
 
3.8%
063-246-7377 1
 
1.9%
063-214-4999 1
 
1.9%
063-232-8382 1
 
1.9%
063-224-7004 1
 
1.9%
063-241-8439 1
 
1.9%
063-243-7629 1
 
1.9%
063-224-1114 1
 
1.9%
063-282-1004 1
 
1.9%
063-288-1333 1
 
1.9%
Other values (42) 42
79.2%
2024-03-15T10:50:27.010360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 106
16.6%
2 90
14.1%
0 89
13.9%
3 88
13.8%
6 75
11.8%
7 38
 
6.0%
4 37
 
5.8%
8 35
 
5.5%
1 30
 
4.7%
5 29
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 532
83.4%
Dash Punctuation 106
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 90
16.9%
0 89
16.7%
3 88
16.5%
6 75
14.1%
7 38
7.1%
4 37
7.0%
8 35
 
6.6%
1 30
 
5.6%
5 29
 
5.5%
9 21
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 638
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 106
16.6%
2 90
14.1%
0 89
13.9%
3 88
13.8%
6 75
11.8%
7 38
 
6.0%
4 37
 
5.8%
8 35
 
5.5%
1 30
 
4.7%
5 29
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 638
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 106
16.6%
2 90
14.1%
0 89
13.9%
3 88
13.8%
6 75
11.8%
7 38
 
6.0%
4 37
 
5.8%
8 35
 
5.5%
1 30
 
4.7%
5 29
 
4.5%

도로명주소
Text

Distinct58
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size648.0 B
2024-03-15T10:50:28.015745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length24.046154
Min length22

Characters and Unicode

Total characters1563
Distinct characters95
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

Unique51 ?
Unique (%)78.5%

Sample

1st row전북특별자치도 전주시 덕진구 실리1길 40
2nd row전북특별자치도 전주시 완산구 전주객사3길 62
3rd row전북특별자치도 전주시 완산구 서신천변15길 15-9
4th row전북특별자치도 전주시 덕진구 과학로 238
5th row전북특별자치도 전주시 완산구 천잠로 205
ValueCountFrequency (%)
전북특별자치도 65
20.0%
전주시 65
20.0%
완산구 40
 
12.3%
덕진구 25
 
7.7%
서곡4길 3
 
0.9%
18 3
 
0.9%
명주5길 2
 
0.6%
성지산로 2
 
0.6%
62 2
 
0.6%
36 2
 
0.6%
Other values (96) 116
35.7%
2024-03-15T10:50:29.499323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
260
16.6%
전 132
 
8.4%
주 70
 
4.5%
시 66
 
4.2%
북 66
 
4.2%
치 65
 
4.2%
구 65
 
4.2%
자 65
 
4.2%
별 65
 
4.2%
특 65
 
4.2%
Other values (85) 644
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1070
68.5%
Space Separator 260
 
16.6%
Decimal Number 207
 
13.2%
Dash Punctuation 26
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 132
 
12.3%
주 70
 
6.5%
시 66
 
6.2%
북 66
 
6.2%
치 65
 
6.1%
구 65
 
6.1%
자 65
 
6.1%
별 65
 
6.1%
특 65
 
6.1%
도 65
 
6.1%
Other values (73) 346
32.3%
Decimal Number
ValueCountFrequency (%)
1 42
20.3%
3 31
15.0%
2 27
13.0%
5 21
10.1%
4 18
8.7%
6 17
8.2%
7 14
 
6.8%
8 13
 
6.3%
9 12
 
5.8%
0 12
 
5.8%
Space Separator
ValueCountFrequency (%)
260
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1070
68.5%
Common 493
31.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 132
 
12.3%
주 70
 
6.5%
시 66
 
6.2%
북 66
 
6.2%
치 65
 
6.1%
구 65
 
6.1%
자 65
 
6.1%
별 65
 
6.1%
특 65
 
6.1%
도 65
 
6.1%
Other values (73) 346
32.3%
Common
ValueCountFrequency (%)
260
52.7%
1 42
 
8.5%
3 31
 
6.3%
2 27
 
5.5%
- 26
 
5.3%
5 21
 
4.3%
4 18
 
3.7%
6 17
 
3.4%
7 14
 
2.8%
8 13
 
2.6%
Other values (2) 24
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1070
68.5%
ASCII 493
31.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
260
52.7%
1 42
 
8.5%
3 31
 
6.3%
2 27
 
5.5%
- 26
 
5.3%
5 21
 
4.3%
4 18
 
3.7%
6 17
 
3.4%
7 14
 
2.8%
8 13
 
2.6%
Other values (2) 24
 
4.9%
Hangul
ValueCountFrequency (%)
전 132
 
12.3%
주 70
 
6.5%
시 66
 
6.2%
북 66
 
6.2%
치 65
 
6.1%
구 65
 
6.1%
자 65
 
6.1%
별 65
 
6.1%
특 65
 
6.1%
도 65
 
6.1%
Other values (73) 346
32.3%

지번주소
Text

Distinct58
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size648.0 B
2024-03-15T10:50:30.449985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length29
Mean length26.892308
Min length22

Characters and Unicode

Total characters1748
Distinct characters61
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

Unique51 ?
Unique (%)78.5%

Sample

1st row전북특별자치도 전주시 덕진구 반월동 391-6
2nd row전북특별자치도 전주시 완산구 고사동 389-4
3rd row전북특별자치도 전주시 완산구 서신동 799-16
4th row전북특별자치도 전주시 덕진구 전미동1가 1095-27
5th row전북특별자치도 전주시 완산구 효자동2가 709
ValueCountFrequency (%)
전북특별자치도 65
20.1%
전주시 65
20.1%
완산구 40
12.3%
덕진구 25
 
7.7%
효자동1가 12
 
3.7%
중화산동2가 8
 
2.5%
삼천동1가 6
 
1.9%
효자동3가 4
 
1.2%
인후동2가 3
 
0.9%
1441-3 2
 
0.6%
Other values (83) 94
29.0%
2024-03-15T10:50:32.087296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
259
 
14.8%
전 132
 
7.6%
자 83
 
4.7%
1 78
 
4.5%
동 67
 
3.8%
북 66
 
3.8%
특 65
 
3.7%
별 65
 
3.7%
치 65
 
3.7%
도 65
 
3.7%
Other values (51) 803
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1101
63.0%
Decimal Number 329
 
18.8%
Space Separator 259
 
14.8%
Dash Punctuation 59
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 132
 
12.0%
자 83
 
7.5%
동 67
 
6.1%
북 66
 
6.0%
특 65
 
5.9%
별 65
 
5.9%
치 65
 
5.9%
도 65
 
5.9%
주 65
 
5.9%
시 65
 
5.9%
Other values (39) 363
33.0%
Decimal Number
ValueCountFrequency (%)
1 78
23.7%
2 41
12.5%
3 33
10.0%
4 33
10.0%
9 31
 
9.4%
6 31
 
9.4%
5 29
 
8.8%
7 20
 
6.1%
8 17
 
5.2%
0 16
 
4.9%
Space Separator
ValueCountFrequency (%)
259
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1101
63.0%
Common 647
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 132
 
12.0%
자 83
 
7.5%
동 67
 
6.1%
북 66
 
6.0%
특 65
 
5.9%
별 65
 
5.9%
치 65
 
5.9%
도 65
 
5.9%
주 65
 
5.9%
시 65
 
5.9%
Other values (39) 363
33.0%
Common
ValueCountFrequency (%)
259
40.0%
1 78
 
12.1%
- 59
 
9.1%
2 41
 
6.3%
3 33
 
5.1%
4 33
 
5.1%
9 31
 
4.8%
6 31
 
4.8%
5 29
 
4.5%
7 20
 
3.1%
Other values (2) 33
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1101
63.0%
ASCII 647
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
259
40.0%
1 78
 
12.1%
- 59
 
9.1%
2 41
 
6.3%
3 33
 
5.1%
4 33
 
5.1%
9 31
 
4.8%
6 31
 
4.8%
5 29
 
4.5%
7 20
 
3.1%
Other values (2) 33
 
5.1%
Hangul
ValueCountFrequency (%)
전 132
 
12.0%
자 83
 
7.5%
동 67
 
6.1%
북 66
 
6.0%
특 65
 
5.9%
별 65
 
5.9%
치 65
 
5.9%
도 65
 
5.9%
주 65
 
5.9%
시 65
 
5.9%
Other values (39) 363
33.0%

위도
Real number (ℝ)

Distinct58
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.82672
Minimum35.767077
Maximum35.890212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size713.0 B
2024-03-15T10:50:32.589091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.767077
5-th percentile35.796114
Q135.808039
median35.822267
Q335.842483
95-th percentile35.873535
Maximum35.890212
Range0.12313488
Interquartile range (IQR)0.03444387

Descriptive statistics

Standard deviation0.025763855
Coefficient of variation (CV)0.00071912401
Kurtosis0.0426918
Mean35.82672
Median Absolute Deviation (MAD)0.01551415
Skewness0.46255966
Sum2328.7368
Variance0.0006637762
MonotonicityNot monotonic
2024-03-15T10:50:33.086765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.83295603 2
 
3.1%
35.82338344 2
 
3.1%
35.83481427 2
 
3.1%
35.89021195 2
 
3.1%
35.80803871 2
 
3.1%
35.8122059 2
 
3.1%
35.80704603 2
 
3.1%
35.85786898 1
 
1.5%
35.84964176 1
 
1.5%
35.79640704 1
 
1.5%
Other values (48) 48
73.8%
ValueCountFrequency (%)
35.76707707 1
1.5%
35.77822101 1
1.5%
35.79473361 1
1.5%
35.79604128 1
1.5%
35.79640704 1
1.5%
35.79714295 1
1.5%
35.79750047 1
1.5%
35.80128124 1
1.5%
35.80215396 1
1.5%
35.80239303 1
1.5%
ValueCountFrequency (%)
35.89021195 2
3.1%
35.87690846 1
1.5%
35.87375013 1
1.5%
35.87267479 1
1.5%
35.86434378 1
1.5%
35.86345658 1
1.5%
35.86053852 1
1.5%
35.85786898 1
1.5%
35.85456891 1
1.5%
35.85215167 1
1.5%

경도
Real number (ℝ)

Distinct58
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.12137
Minimum127.05799
Maximum127.17876
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size713.0 B
2024-03-15T10:50:33.631858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.05799
5-th percentile127.07937
Q1127.1127
median127.12101
Q3127.12919
95-th percentile127.1622
Maximum127.17876
Range0.1207749
Interquartile range (IQR)0.0164872

Descriptive statistics

Standard deviation0.023983455
Coefficient of variation (CV)0.00018866581
Kurtosis0.57094922
Mean127.12137
Median Absolute Deviation (MAD)0.0083055
Skewness-0.013651296
Sum8262.889
Variance0.00057520614
MonotonicityNot monotonic
2024-03-15T10:50:34.130728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1720412 2
 
3.1%
127.1213564 2
 
3.1%
127.1032309 2
 
3.1%
127.1291917 2
 
3.1%
127.1219281 2
 
3.1%
127.1184804 2
 
3.1%
127.1181631 2
 
3.1%
127.1248513 1
 
1.5%
127.1016328 1
 
1.5%
127.12101 1
 
1.5%
Other values (48) 48
73.8%
ValueCountFrequency (%)
127.0579855 1
1.5%
127.0679175 1
1.5%
127.0768963 1
1.5%
127.0789414 1
1.5%
127.0810851 1
1.5%
127.0887394 1
1.5%
127.0901922 1
1.5%
127.0960108 1
1.5%
127.0989558 1
1.5%
127.1006947 1
1.5%
ValueCountFrequency (%)
127.1787604 1
1.5%
127.1720412 2
3.1%
127.164431 1
1.5%
127.153286 1
1.5%
127.1520679 1
1.5%
127.1518489 1
1.5%
127.1514859 1
1.5%
127.1511249 1
1.5%
127.1492749 1
1.5%
127.1485989 1
1.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size648.0 B
Minimum2024-01-18 00:00:00
Maximum2024-01-18 00:00:00
2024-03-15T10:50:34.553643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:50:34.829768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T10:50:19.968592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:50:19.578688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:50:20.316858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:50:19.722725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:50:34.968903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명인허가일자소재지전화도로명주소지번주소위도경도
사업장명1.0001.0001.0000.9960.9960.9921.000
인허가일자1.0001.0001.0000.9900.9900.9000.952
소재지전화1.0001.0001.0000.9870.9870.9701.000
도로명주소0.9960.9900.9871.0001.0001.0001.000
지번주소0.9960.9900.9871.0001.0001.0001.000
위도0.9920.9000.9701.0001.0001.0000.702
경도1.0000.9521.0001.0001.0000.7021.000
2024-03-15T10:50:35.290178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.146
경도-0.1461.000

Missing values

2024-03-15T10:50:20.719889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:50:21.312281image/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

사업장명인허가일자영업상태명소재지전화도로명주소지번주소위도경도데이터기준일자
0(유) 아름다운환경2018-10-25영업/정상063-232-8382전북특별자치도 전주시 덕진구 실리1길 40전북특별자치도 전주시 덕진구 반월동 391-635.87375127.0679172024-01-18
1(유)HR하누리2019-05-28영업/정상070-7530-1960전북특별자치도 전주시 완산구 전주객사3길 62전북특별자치도 전주시 완산구 고사동 389-435.819976127.1420372024-01-18
2(유)개미환경위생2012-11-15영업/정상063-253-0762전북특별자치도 전주시 완산구 서신천변15길 15-9전북특별자치도 전주시 완산구 서신동 799-1635.831236127.1127052024-01-18
3(유)국민종합주택관리2012-10-12영업/정상063-286-3348전북특별자치도 전주시 덕진구 과학로 238전북특별자치도 전주시 덕진구 전미동1가 1095-2735.890212127.1291922024-01-18
4(유)깨끗한세상2021-09-29영업/정상063-223-2365전북특별자치도 전주시 완산구 천잠로 205전북특별자치도 전주시 완산구 효자동2가 70935.805284127.0960112024-01-18
5(유)나래트렌드2021-12-30영업/정상063-276-3338전북특별자치도 전주시 덕진구 과학로 238전북특별자치도 전주시 덕진구 전미동1가 1095-2735.890212127.1291922024-01-18
6(유)나운2013-08-26영업/정상063-254-3020전북특별자치도 전주시 덕진구 안덕원로 106-3전북특별자치도 전주시 덕진구 진북동 320-3735.82957127.1419112024-01-18
7(유)다온환경2023-04-05영업/정상063-277-0552전북특별자치도 전주시 완산구 서곡4길 29전북특별자치도 전주시 완산구 효자동3가1446-435.833941127.1038472024-01-18
8(유)대양환경2007-06-25영업/정상063-227-1033전북특별자치도 전주시 완산구 용머리로 73전북특별자치도 전주시 완산구 효자동1가 296-17535.807046127.1181632024-01-18
9(유)대호개발2010-07-01영업/정상063-224-8222전북특별자치도 전주시 완산구 인정4길 12-8전북특별자치도 전주시 완산구 중화산동2가 582-335.820006127.1213132024-01-18
사업장명인허가일자영업상태명소재지전화도로명주소지번주소위도경도데이터기준일자
55유한회사 가은환경2019-01-21영업/정상063-245-9248전북특별자치도 전주시 덕진구 동부대로 877전북특별자치도 전주시 덕진구 호성동1가 836-435.864344127.1485992024-01-18
56유한회사두승산업2008-07-28영업/정상063-225-2939전북특별자치도 전주시 완산구 거마평로 189-11전북특별자치도 전주시 완산구 효자동1가 43135.808559127.1146772024-01-18
57일신방제2009-09-28영업/정상<NA>전북특별자치도 전주시 덕진구 여산로 130-14전북특별자치도 전주시 덕진구 여의동 551-335.863457127.0789412024-01-18
58주식회사에코유2014-11-19영업/정상063-277-7479전북특별자치도 전주시 완산구 산월1길 36전북특별자치도 전주시 완산구 중화산동2가 452-935.813081127.1193542024-01-18
59주식회사에코유2014-11-19영업/정상063-277-7479전북특별자치도 전주시 완산구 중산6길 9전북특별자치도 전주시 완산구 중화산동2가 601-635.817025127.1212462024-01-18
60천일용역1997-08-11영업/정상063-253-5755전북특별자치도 전주시 덕진구 신복1길 13전북특별자치도 전주시 덕진구 팔복동2가 12-135.852152127.1101192024-01-18
61클린허브2021-07-27영업/정상<NA>전북특별자치도 전주시 완산구 고덕산2길 19전북특별자치도 전주시 완산구 대성동 4035.7975127.178762024-01-18
62한국환경방역공사2009-08-12영업/정상063-252-6020전북특별자치도 전주시 덕진구 용산1길 12전북특별자치도 전주시 덕진구 금암동 765-135.834952127.1305252024-01-18
63현대환경방역공사1997-03-22영업/정상063-227-1188전북특별자치도 전주시 완산구 성지산로 61-4전북특별자치도 전주시 완산구 효자동1가 565-335.802543127.1241622024-01-18
64환경개발(주)2021-04-09영업/정상063-231-1600전북특별자치도 전주시 완산구 현무2길 13-7전북특별자치도 전주시 완산구 경원동3가 86-935.819895127.1492752024-01-18

Duplicate rows

Most frequently occurring

사업장명인허가일자영업상태명소재지전화도로명주소지번주소위도경도데이터기준일자# duplicates
0(유)세영환경2022-04-11영업/정상<NA>전북특별자치도 전주시 완산구 백제대로 165-10전북특별자치도 전주시 완산구 효자동1가 311-935.808039127.1219282024-01-182