Overview

Dataset statistics

Number of variables11
Number of observations61
Missing cells6
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory92.1 B

Variable types

Categorical4
Text5
Numeric2

Dataset

Description경기도 파주시 건축관련 업체 현황 정보로 업체명, 업종, 업체 연락처, 소재지 도로명주소, 소재지 지번주소, 위도, 경도 관련한 데이터를 제공합니다.
Author경기도 파주시
URLhttps://www.data.go.kr/data/15126657/fileData.do

Alerts

관리기관명 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
업체명 has 1 (1.6%) missing valuesMissing
전화번호 has 4 (6.6%) missing valuesMissing
소재지도로명주소 has 1 (1.6%) missing valuesMissing

Reproduction

Analysis started2024-03-14 20:06:02.709163
Analysis finished2024-03-14 20:06:05.015001
Duration2.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

항목명
Categorical

Distinct4
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size616.0 B
건설업
32 
공사업
22 
금속가공업
금속임가공업
 
1

Length

Max length6
Median length3
Mean length3.2459016
Min length3

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
건설업 32
52.5%
공사업 22
36.1%
금속가공업 6
 
9.8%
금속임가공업 1
 
1.6%

Length

2024-03-15T05:06:05.139296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:06:05.404510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건설업 32
52.5%
공사업 22
36.1%
금속가공업 6
 
9.8%
금속임가공업 1
 
1.6%

업체명
Text

MISSING 

Distinct60
Distinct (%)100.0%
Missing1
Missing (%)1.6%
Memory size616.0 B
2024-03-15T05:06:06.486879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.7833333
Min length4

Characters and Unicode

Total characters467
Distinct characters134
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row(주)제이일산
2nd row호천종합건설(주)
3rd row한류종합건설(주)
4th row(주)파주건설
5th row태윤건설(주)
ValueCountFrequency (%)
주식회사 2
 
3.2%
주)제이일산 1
 
1.6%
주)드림시스텍 1
 
1.6%
청해env주식회사 1
 
1.6%
주)청원산업 1
 
1.6%
진영공조(주 1
 
1.6%
정동전력(주 1
 
1.6%
재성전설(주 1
 
1.6%
주)자유로중장비학원 1
 
1.6%
주)에스엠디자인 1
 
1.6%
Other values (52) 52
82.5%
2024-03-15T05:06:07.714024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
 
11.1%
( 47
 
10.1%
) 47
 
10.1%
26
 
5.6%
26
 
5.6%
13
 
2.8%
13
 
2.8%
13
 
2.8%
8
 
1.7%
7
 
1.5%
Other values (124) 215
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 362
77.5%
Open Punctuation 47
 
10.1%
Close Punctuation 47
 
10.1%
Uppercase Letter 8
 
1.7%
Space Separator 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
52
 
14.4%
26
 
7.2%
26
 
7.2%
13
 
3.6%
13
 
3.6%
13
 
3.6%
8
 
2.2%
7
 
1.9%
7
 
1.9%
6
 
1.7%
Other values (113) 191
52.8%
Uppercase Letter
ValueCountFrequency (%)
L 1
12.5%
S 1
12.5%
D 1
12.5%
V 1
12.5%
N 1
12.5%
E 1
12.5%
Z 1
12.5%
M 1
12.5%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 362
77.5%
Common 97
 
20.8%
Latin 8
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
52
 
14.4%
26
 
7.2%
26
 
7.2%
13
 
3.6%
13
 
3.6%
13
 
3.6%
8
 
2.2%
7
 
1.9%
7
 
1.9%
6
 
1.7%
Other values (113) 191
52.8%
Latin
ValueCountFrequency (%)
L 1
12.5%
S 1
12.5%
D 1
12.5%
V 1
12.5%
N 1
12.5%
E 1
12.5%
Z 1
12.5%
M 1
12.5%
Common
ValueCountFrequency (%)
( 47
48.5%
) 47
48.5%
3
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 362
77.5%
ASCII 105
 
22.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
52
 
14.4%
26
 
7.2%
26
 
7.2%
13
 
3.6%
13
 
3.6%
13
 
3.6%
8
 
2.2%
7
 
1.9%
7
 
1.9%
6
 
1.7%
Other values (113) 191
52.8%
ASCII
ValueCountFrequency (%)
( 47
44.8%
) 47
44.8%
3
 
2.9%
L 1
 
1.0%
S 1
 
1.0%
D 1
 
1.0%
V 1
 
1.0%
N 1
 
1.0%
E 1
 
1.0%
Z 1
 
1.0%

업종
Text

Distinct33
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Memory size616.0 B
2024-03-15T05:06:08.484116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length11.639344
Min length3

Characters and Unicode

Total characters710
Distinct characters84
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)34.4%

Sample

1st row건설업
2nd row기타 토목시설물 건설업
3rd row기타 비주거용 건물 건설업
4th row기타 토목시설물 건설업
5th row단독 및 연립주택 건설업
ValueCountFrequency (%)
건설업 32
 
15.4%
20
 
9.6%
기타 18
 
8.7%
공사업 15
 
7.2%
건물 14
 
6.7%
사무 6
 
2.9%
상업용 6
 
2.9%
비주거용 6
 
2.9%
금속가공업 6
 
2.9%
5
 
2.4%
Other values (50) 80
38.5%
2024-03-15T05:06:09.500032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
147
20.7%
70
 
9.9%
49
 
6.9%
46
 
6.5%
30
 
4.2%
29
 
4.1%
24
 
3.4%
23
 
3.2%
20
 
2.8%
19
 
2.7%
Other values (74) 253
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 557
78.5%
Space Separator 147
 
20.7%
Other Punctuation 5
 
0.7%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
70
 
12.6%
49
 
8.8%
46
 
8.3%
30
 
5.4%
29
 
5.2%
24
 
4.3%
23
 
4.1%
20
 
3.6%
19
 
3.4%
14
 
2.5%
Other values (70) 233
41.8%
Other Punctuation
ValueCountFrequency (%)
, 3
60.0%
· 2
40.0%
Space Separator
ValueCountFrequency (%)
147
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 557
78.5%
Common 153
 
21.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
70
 
12.6%
49
 
8.8%
46
 
8.3%
30
 
5.4%
29
 
5.2%
24
 
4.3%
23
 
4.1%
20
 
3.6%
19
 
3.4%
14
 
2.5%
Other values (70) 233
41.8%
Common
ValueCountFrequency (%)
147
96.1%
, 3
 
2.0%
· 2
 
1.3%
2 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 557
78.5%
ASCII 151
 
21.3%
None 2
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
147
97.4%
, 3
 
2.0%
2 1
 
0.7%
Hangul
ValueCountFrequency (%)
70
 
12.6%
49
 
8.8%
46
 
8.3%
30
 
5.4%
29
 
5.2%
24
 
4.3%
23
 
4.1%
20
 
3.6%
19
 
3.4%
14
 
2.5%
Other values (70) 233
41.8%
None
ValueCountFrequency (%)
· 2
100.0%

전화번호
Text

MISSING 

Distinct56
Distinct (%)98.2%
Missing4
Missing (%)6.6%
Memory size616.0 B
2024-03-15T05:06:10.365441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.070175
Min length12

Characters and Unicode

Total characters688
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

Unique55 ?
Unique (%)96.5%

Sample

1st row031-944-4418
2nd row031-949-0479
3rd row031-949-3775
4th row031-957-7755
5th row031-943-2642
ValueCountFrequency (%)
031-945-1610 2
 
3.5%
031-941-2263 1
 
1.8%
02-3443-4830 1
 
1.8%
031-945-2375 1
 
1.8%
031-948-1171 1
 
1.8%
031-946-6600 1
 
1.8%
031-944-5656 1
 
1.8%
031-947-9944 1
 
1.8%
031-966-4736 1
 
1.8%
070-7525-0191 1
 
1.8%
Other values (46) 46
80.7%
2024-03-15T05:06:11.496940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 114
16.6%
1 93
13.5%
3 89
12.9%
0 76
11.0%
9 75
10.9%
4 75
10.9%
5 41
 
6.0%
2 35
 
5.1%
7 31
 
4.5%
6 28
 
4.1%
Other values (2) 31
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 571
83.0%
Dash Punctuation 114
 
16.6%
Space Separator 3
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 93
16.3%
3 89
15.6%
0 76
13.3%
9 75
13.1%
4 75
13.1%
5 41
7.2%
2 35
 
6.1%
7 31
 
5.4%
6 28
 
4.9%
8 28
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 688
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 114
16.6%
1 93
13.5%
3 89
12.9%
0 76
11.0%
9 75
10.9%
4 75
10.9%
5 41
 
6.0%
2 35
 
5.1%
7 31
 
4.5%
6 28
 
4.1%
Other values (2) 31
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 688
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 114
16.6%
1 93
13.5%
3 89
12.9%
0 76
11.0%
9 75
10.9%
4 75
10.9%
5 41
 
6.0%
2 35
 
5.1%
7 31
 
4.5%
6 28
 
4.1%
Other values (2) 31
 
4.5%
Distinct58
Distinct (%)96.7%
Missing1
Missing (%)1.6%
Memory size616.0 B
2024-03-15T05:06:12.635853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length18.866667
Min length13

Characters and Unicode

Total characters1132
Distinct characters114
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

Unique56 ?
Unique (%)93.3%

Sample

1st row경기도 파주시 광탄면 만장산로 310
2nd row경기도 파주시 운정역길 136
3rd row경기도 파주시 번영로 20
4th row경기도 파주시 책향기로 836
5th row경기도 파주시 황골로 9
ValueCountFrequency (%)
경기도 60
22.3%
파주시 60
22.3%
탄현면 7
 
2.6%
조리읍 6
 
2.2%
광탄면 5
 
1.9%
문산읍 3
 
1.1%
월롱면 3
 
1.1%
번영로 2
 
0.7%
적성면 2
 
0.7%
사임당로 2
 
0.7%
Other values (109) 119
44.2%
2024-03-15T05:06:14.167677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
217
19.2%
63
 
5.6%
62
 
5.5%
62
 
5.5%
62
 
5.5%
60
 
5.3%
60
 
5.3%
42
 
3.7%
1 38
 
3.4%
29
 
2.6%
Other values (104) 437
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 686
60.6%
Space Separator 217
 
19.2%
Decimal Number 211
 
18.6%
Dash Punctuation 18
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
63
 
9.2%
62
 
9.0%
62
 
9.0%
62
 
9.0%
60
 
8.7%
60
 
8.7%
42
 
6.1%
29
 
4.2%
17
 
2.5%
13
 
1.9%
Other values (92) 216
31.5%
Decimal Number
ValueCountFrequency (%)
1 38
18.0%
4 26
12.3%
2 24
11.4%
0 22
10.4%
5 21
10.0%
3 21
10.0%
6 19
9.0%
9 16
7.6%
8 12
 
5.7%
7 12
 
5.7%
Space Separator
ValueCountFrequency (%)
217
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 686
60.6%
Common 446
39.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
63
 
9.2%
62
 
9.0%
62
 
9.0%
62
 
9.0%
60
 
8.7%
60
 
8.7%
42
 
6.1%
29
 
4.2%
17
 
2.5%
13
 
1.9%
Other values (92) 216
31.5%
Common
ValueCountFrequency (%)
217
48.7%
1 38
 
8.5%
4 26
 
5.8%
2 24
 
5.4%
0 22
 
4.9%
5 21
 
4.7%
3 21
 
4.7%
6 19
 
4.3%
- 18
 
4.0%
9 16
 
3.6%
Other values (2) 24
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 686
60.6%
ASCII 446
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
217
48.7%
1 38
 
8.5%
4 26
 
5.8%
2 24
 
5.4%
0 22
 
4.9%
5 21
 
4.7%
3 21
 
4.7%
6 19
 
4.3%
- 18
 
4.0%
9 16
 
3.6%
Other values (2) 24
 
5.4%
Hangul
ValueCountFrequency (%)
63
 
9.2%
62
 
9.0%
62
 
9.0%
62
 
9.0%
60
 
8.7%
60
 
8.7%
42
 
6.1%
29
 
4.2%
17
 
2.5%
13
 
1.9%
Other values (92) 216
31.5%
Distinct58
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size616.0 B
2024-03-15T05:06:15.342725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length18.770492
Min length14

Characters and Unicode

Total characters1145
Distinct characters77
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

Unique55 ?
Unique (%)90.2%

Sample

1st row경기도 파주시 창만리 250-3
2nd row경기도 파주시 상지석동 673-10
3rd row경기도 파주시 금촌동 944-31
4th row경기도 파주시 와동동 1458-1
5th row경기도 파주시 금촌동 246-29
ValueCountFrequency (%)
경기도 61
22.4%
파주시 61
22.4%
금촌동 9
 
3.3%
탄현면 6
 
2.2%
조리읍 6
 
2.2%
봉일천리 4
 
1.5%
광탄면 4
 
1.5%
신산리 3
 
1.1%
문산읍 3
 
1.1%
야동동 3
 
1.1%
Other values (94) 112
41.2%
2024-03-15T05:06:17.642733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
211
18.4%
63
 
5.5%
63
 
5.5%
62
 
5.4%
61
 
5.3%
61
 
5.3%
61
 
5.3%
- 51
 
4.5%
45
 
3.9%
1 38
 
3.3%
Other values (67) 429
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 638
55.7%
Decimal Number 245
 
21.4%
Space Separator 211
 
18.4%
Dash Punctuation 51
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
63
 
9.9%
63
 
9.9%
62
 
9.7%
61
 
9.6%
61
 
9.6%
61
 
9.6%
45
 
7.1%
35
 
5.5%
15
 
2.4%
12
 
1.9%
Other values (55) 160
25.1%
Decimal Number
ValueCountFrequency (%)
1 38
15.5%
3 30
12.2%
4 29
11.8%
5 27
11.0%
2 26
10.6%
7 26
10.6%
6 25
10.2%
8 18
7.3%
0 14
 
5.7%
9 12
 
4.9%
Space Separator
ValueCountFrequency (%)
211
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 638
55.7%
Common 507
44.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
63
 
9.9%
63
 
9.9%
62
 
9.7%
61
 
9.6%
61
 
9.6%
61
 
9.6%
45
 
7.1%
35
 
5.5%
15
 
2.4%
12
 
1.9%
Other values (55) 160
25.1%
Common
ValueCountFrequency (%)
211
41.6%
- 51
 
10.1%
1 38
 
7.5%
3 30
 
5.9%
4 29
 
5.7%
5 27
 
5.3%
2 26
 
5.1%
7 26
 
5.1%
6 25
 
4.9%
8 18
 
3.6%
Other values (2) 26
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 638
55.7%
ASCII 507
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
211
41.6%
- 51
 
10.1%
1 38
 
7.5%
3 30
 
5.9%
4 29
 
5.7%
5 27
 
5.3%
2 26
 
5.1%
7 26
 
5.1%
6 25
 
4.9%
8 18
 
3.6%
Other values (2) 26
 
5.1%
Hangul
ValueCountFrequency (%)
63
 
9.9%
63
 
9.9%
62
 
9.7%
61
 
9.6%
61
 
9.6%
61
 
9.6%
45
 
7.1%
35
 
5.5%
15
 
2.4%
12
 
1.9%
Other values (55) 160
25.1%

위도
Real number (ℝ)

Distinct58
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.775333
Minimum37.702211
Maximum37.969561
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size677.0 B
2024-03-15T05:06:18.092527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.702211
5-th percentile37.718924
Q137.73783
median37.764652
Q337.787275
95-th percentile37.866997
Maximum37.969561
Range0.26734999
Interquartile range (IQR)0.04944567

Descriptive statistics

Standard deviation0.053041408
Coefficient of variation (CV)0.0014041282
Kurtosis3.3903676
Mean37.775333
Median Absolute Deviation (MAD)0.02682266
Skewness1.6106121
Sum2304.2953
Variance0.002813391
MonotonicityNot monotonic
2024-03-15T05:06:18.550978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.74675839 2
 
3.3%
37.75804153 2
 
3.3%
37.76693419 2
 
3.3%
37.73269428 1
 
1.6%
37.82456565 1
 
1.6%
37.72643877 1
 
1.6%
37.75835088 1
 
1.6%
37.74515269 1
 
1.6%
37.70309238 1
 
1.6%
37.83216259 1
 
1.6%
Other values (48) 48
78.7%
ValueCountFrequency (%)
37.7022112 1
1.6%
37.70309238 1
1.6%
37.71800557 1
1.6%
37.71892368 1
1.6%
37.72114294 1
1.6%
37.72460127 1
1.6%
37.72643877 1
1.6%
37.72700058 1
1.6%
37.72927091 1
1.6%
37.73011029 1
1.6%
ValueCountFrequency (%)
37.96956119 1
1.6%
37.95127728 1
1.6%
37.87911214 1
1.6%
37.8669968 1
1.6%
37.85329732 1
1.6%
37.84353827 1
1.6%
37.83319689 1
1.6%
37.83216259 1
1.6%
37.82793759 1
1.6%
37.82676069 1
1.6%

경도
Real number (ℝ)

Distinct58
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.77675
Minimum126.68377
Maximum126.90917
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size677.0 B
2024-03-15T05:06:19.003467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.68377
5-th percentile126.71081
Q1126.74136
median126.77495
Q3126.8014
95-th percentile126.86883
Maximum126.90917
Range0.2254031
Interquartile range (IQR)0.0600448

Descriptive statistics

Standard deviation0.049245646
Coefficient of variation (CV)0.00038844382
Kurtosis0.2071873
Mean126.77675
Median Absolute Deviation (MAD)0.0286762
Skewness0.56998743
Sum7733.3819
Variance0.0024251336
MonotonicityNot monotonic
2024-03-15T05:06:19.547689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8117806 2
 
3.3%
126.7710912 2
 
3.3%
126.7788571 2
 
3.3%
126.7667257 1
 
1.6%
126.7276677 1
 
1.6%
126.6950214 1
 
1.6%
126.7769894 1
 
1.6%
126.737108 1
 
1.6%
126.6837675 1
 
1.6%
126.731599 1
 
1.6%
Other values (48) 48
78.7%
ValueCountFrequency (%)
126.6837675 1
1.6%
126.6950214 1
1.6%
126.7060686 1
1.6%
126.7108148 1
1.6%
126.7108152 1
1.6%
126.7124101 1
1.6%
126.7191163 1
1.6%
126.7197131 1
1.6%
126.7207566 1
1.6%
126.7246132 1
1.6%
ValueCountFrequency (%)
126.9091706 1
1.6%
126.8955277 1
1.6%
126.8729976 1
1.6%
126.8688343 1
1.6%
126.8562461 1
1.6%
126.8487388 1
1.6%
126.846514 1
1.6%
126.8464858 1
1.6%
126.8372778 1
1.6%
126.8272622 1
1.6%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size616.0 B
경기도 파주시청
61 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 파주시청 61
100.0%

Length

2024-03-15T05:06:19.933773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:06:20.097740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 61
50.0%
파주시청 61
50.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size616.0 B
031-940-4532
61 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row031-940-4532
2nd row031-940-4532
3rd row031-940-4532
4th row031-940-4532
5th row031-940-4532

Common Values

ValueCountFrequency (%)
031-940-4532 61
100.0%

Length

2024-03-15T05:06:20.272689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:06:20.470989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-940-4532 61
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size616.0 B
2024-02-06
61 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-06
2nd row2024-02-06
3rd row2024-02-06
4th row2024-02-06
5th row2024-02-06

Common Values

ValueCountFrequency (%)
2024-02-06 61
100.0%

Length

2024-03-15T05:06:21.005927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:06:21.176913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-06 61
100.0%

Interactions

2024-03-15T05:06:03.849592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:06:03.515290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:06:04.091185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:06:03.708380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:06:21.343319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
항목명업체명업종전화번호소재지도로명주소소재지지번주소위도경도
항목명1.0001.0001.0000.9590.9010.9450.7130.459
업체명1.0001.0001.0001.0001.0001.0001.0001.000
업종1.0001.0001.0000.9690.0000.0000.5690.000
전화번호0.9591.0000.9691.0001.0001.0001.0001.000
소재지도로명주소0.9011.0000.0001.0001.0001.0001.0001.000
소재지지번주소0.9451.0000.0001.0001.0001.0001.0001.000
위도0.7131.0000.5691.0001.0001.0001.0000.679
경도0.4591.0000.0001.0001.0001.0000.6791.000
2024-03-15T05:06:21.694148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도항목명
위도1.0000.4000.370
경도0.4001.0000.271
항목명0.3700.2711.000

Missing values

2024-03-15T05:06:04.312567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:06:04.723408image/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.
2024-03-15T05:06:04.921371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

항목명업체명업종전화번호소재지도로명주소소재지지번주소위도경도관리기관명관리기관전화번호데이터기준일자
0건설업(주)제이일산건설업031-944-4418경기도 파주시 광탄면 만장산로 310경기도 파주시 창만리 250-337.796955126.868834경기도 파주시청031-940-45322024-02-06
1건설업호천종합건설(주)기타 토목시설물 건설업031-949-0479경기도 파주시 운정역길 136경기도 파주시 상지석동 673-1037.733205126.77495경기도 파주시청031-940-45322024-02-06
2건설업한류종합건설(주)기타 비주거용 건물 건설업031-949-3775경기도 파주시 번영로 20경기도 파주시 금촌동 944-3137.758042126.771091경기도 파주시청031-940-45322024-02-06
3건설업(주)파주건설기타 토목시설물 건설업031-957-7755경기도 파주시 책향기로 836경기도 파주시 와동동 1458-137.729271126.763761경기도 파주시청031-940-45322024-02-06
4건설업태윤건설(주)단독 및 연립주택 건설업031-943-2642경기도 파주시 황골로 9경기도 파주시 금촌동 246-2937.755442126.769732경기도 파주시청031-940-45322024-02-06
5건설업태성종합건설(주)사무 및 상업용 건물 건설업031-941-3917경기도 파주시 조리읍 송비말길 79-9경기도 파주시 조리읍 봉일천리 176-1037.743843126.803626경기도 파주시청031-940-45322024-02-06
6건설업(주)코리아종합건설사무 및 상업용 건물 건설업031-944-5040경기도 파주시 탄현면 평화로 538경기도 파주시 갈현리 1784-437.771805126.724613경기도 파주시청031-940-45322024-02-06
7건설업(주)청신종합건설기타 비주거용 건물 건설업031-959-3200경기도 파주시 적성면 적성산단1로 10경기도 파주시 적성면 가월리 1855-337.969561126.909171경기도 파주시청031-940-45322024-02-06
8건설업(주)지플러스사무 및 상업용 건물 건설업031-943-5483경기도 파주시 와석순환로515번길 61경기도 파주시 와동동 1450-137.727001126.763191경기도 파주시청031-940-45322024-02-06
9건설업지오종합건설(주)비주거용 건물 건설업031-942-2329경기도 파주시 책향기숲길 21경기도 파주시 문발동 610-737.718924126.710815경기도 파주시청031-940-45322024-02-06
항목명업체명업종전화번호소재지도로명주소소재지지번주소위도경도관리기관명관리기관전화번호데이터기준일자
51공사업네모코리아(주)기타 건물설비 설치 공사업031-8071-2114경기도 파주시 탄현면 오금로50번길 122경기도 파주시 탄현면 오금리 151-737.818725126.719116경기도 파주시청031-940-45322024-02-06
52공사업남양이앤지(주)일반전기 공사업031-957-0419경기도 파주시 가재울로 87경기도 파주시 목동동 743-237.730997126.746593경기도 파주시청031-940-45322024-02-06
53공사업(주)거산이엔지일반전기 공사업031-942-2465경기도 파주시 하우4길 26-1경기도 파주시 상지석동 554-4637.718006126.775866경기도 파주시청031-940-45322024-02-06
54금속가공업(주)차세대산업그외 기타 금속가공업031-957-1465경기도 파주시 광탄면 수레길 417경기도 파주시 광탄면 신산리 113-537.770261126.848739경기도 파주시청031-940-45322024-02-06
55금속가공업은한테크그 외 기타 금속가공업031-946-6681경기도 파주시 월롱산로 89-16경기도 파주시 야동동 257-1537.782973126.760902경기도 파주시청031-940-45322024-02-06
56금속가공업스튜디오성신그 외 기타 금속가공업 외 2 종031-949-6196경기도 파주시 광탄면 만장산로94번길 46경기도 파주시 광탄면 신산리 15-137.784054126.856246경기도 파주시청031-940-45322024-02-06
57금속가공업(주)서울내장기업그 외 기타 금속가공업031-979-5535경기도 파주시 광탄면 우랑길 100-10경기도 파주시 광탄면 마장리 362-837.783498126.872998경기도 파주시청031-940-45322024-02-06
58금속가공업(주)더블에이치그 외 기타 금속가공업031-941-6271경기도 파주시 산업단지길 152경기도 파주시 신촌동 70737.73011126.710815경기도 파주시청031-940-45322024-02-06
59금속가공업(주)골드락그외 기타 금속가공업031-941-6648경기도 파주시 조리읍 능안로266번길 19경기도 파주시 조리읍 능안리 388-2737.73783126.784096경기도 파주시청031-940-45322024-02-06
60금속임가공업우경산업금속임가공업031-959-8181경기도 파주시 법원읍 사임당로 572-64경기도 파주시 법원읍 동문리 577-537.853297126.846486경기도 파주시청031-940-45322024-02-06