Overview

Dataset statistics

Number of variables11
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory95.8 B

Variable types

Numeric5
DateTime3
Text2
Categorical1

Dataset

Description대구공공시설관리공단(구.대구시설공단) 도로시설물관리시스템 인수시설물현황입니다.일련번호, 생성자번호, 인수일시, 사업명, 위치 등으로 구성되어있습니다.
Author대구공공시설관리공단
URLhttps://www.data.go.kr/data/15120471/fileData.do

Alerts

일련번호 is highly overall correlated with 생성자번호High correlation
생성자번호 is highly overall correlated with 일련번호High correlation
도로폭 is highly overall correlated with 도로면적High correlation
도로연장 is highly overall correlated with 도로면적High correlation
도로면적 is highly overall correlated with 도로폭 and 1 other fieldsHigh correlation
일련번호 has unique valuesUnique
생성자번호 has unique valuesUnique
사업명 has unique valuesUnique
도로면적 has unique valuesUnique
도로폭 has 1 (2.1%) zerosZeros

Reproduction

Analysis started2024-04-17 17:39:20.218636
Analysis finished2024-04-17 17:39:22.434836
Duration2.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.5
Minimum1
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-04-18T02:39:22.488070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.35
Q112.75
median24.5
Q336.25
95-th percentile45.65
Maximum48
Range47
Interquartile range (IQR)23.5

Descriptive statistics

Standard deviation14
Coefficient of variation (CV)0.57142857
Kurtosis-1.2
Mean24.5
Median Absolute Deviation (MAD)12
Skewness0
Sum1176
Variance196
MonotonicityStrictly increasing
2024-04-18T02:39:22.590858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
1 1
 
2.1%
26 1
 
2.1%
28 1
 
2.1%
29 1
 
2.1%
30 1
 
2.1%
31 1
 
2.1%
32 1
 
2.1%
33 1
 
2.1%
34 1
 
2.1%
35 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
1 1
2.1%
2 1
2.1%
3 1
2.1%
4 1
2.1%
5 1
2.1%
6 1
2.1%
7 1
2.1%
8 1
2.1%
9 1
2.1%
10 1
2.1%
ValueCountFrequency (%)
48 1
2.1%
47 1
2.1%
46 1
2.1%
45 1
2.1%
44 1
2.1%
43 1
2.1%
42 1
2.1%
41 1
2.1%
40 1
2.1%
39 1
2.1%

생성자번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0111768 × 108
Minimum2.01001 × 108
Maximum2.0130101 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-04-18T02:39:22.692399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.01001 × 108
5-th percentile2.01001 × 108
Q12.0100102 × 108
median2.0110101 × 108
Q32.0120101 × 108
95-th percentile2.01301 × 108
Maximum2.0130101 × 108
Range300006
Interquartile range (IQR)199991.75

Descriptive statistics

Standard deviation99643.439
Coefficient of variation (CV)0.00049544844
Kurtosis-0.784737
Mean2.0111768 × 108
Median Absolute Deviation (MAD)99996
Skewness0.45873605
Sum9.6536484 × 109
Variance9.9288149 × 109
MonotonicityStrictly increasing
2024-04-18T02:39:22.798437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
201001001 1
 
2.1%
201101013 1
 
2.1%
201101015 1
 
2.1%
201101016 1
 
2.1%
201101018 1
 
2.1%
201101019 1
 
2.1%
201101020 1
 
2.1%
201201001 1
 
2.1%
201201002 1
 
2.1%
201201006 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
201001001 1
2.1%
201001002 1
2.1%
201001003 1
2.1%
201001005 1
2.1%
201001007 1
2.1%
201001008 1
2.1%
201001009 1
2.1%
201001010 1
2.1%
201001011 1
2.1%
201001012 1
2.1%
ValueCountFrequency (%)
201301007 1
2.1%
201301006 1
2.1%
201301005 1
2.1%
201301004 1
2.1%
201301003 1
2.1%
201301002 1
2.1%
201201014 1
2.1%
201201013 1
2.1%
201201012 1
2.1%
201201011 1
2.1%

인수일시
Date

Distinct34
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size516.0 B
Minimum2010-01-05 00:00:00
Maximum2013-12-30 00:00:00
2024-04-18T02:39:22.905539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:23.000343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

사업명
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-04-18T02:39:23.174154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length26.5
Mean length19.645833
Min length8

Characters and Unicode

Total characters943
Distinct characters187
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

Unique48 ?
Unique (%)100.0%

Sample

1st row율하(2) 택지개발사업 조성공사(율하지하차도)
2nd row평리2동 주택재건축 정비사업 아파트 신축
3rd row두산위브더제니스 신축
4th row(주)호텔 인터불고 엑스코 신축
5th row구안국도-칠곡2지구간 도로건설공사
ValueCountFrequency (%)
도로건설공사 7
 
5.0%
신축 5
 
3.5%
건설공사 4
 
2.8%
성서5차 3
 
2.1%
확장공사 3
 
2.1%
신축공사 3
 
2.1%
도로확장 2
 
1.4%
2
 
1.4%
팔공로-공항교간 2
 
1.4%
첨단산업단지 2
 
1.4%
Other values (106) 108
76.6%
2024-04-18T02:39:23.462622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
93
 
9.9%
사 49
 
5.2%
공 48
 
5.1%
로 38
 
4.0%
도 30
 
3.2%
구 28
 
3.0%
( 22
 
2.3%
설 22
 
2.3%
) 22
 
2.3%
건 21
 
2.2%
Other values (177) 570
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 746
79.1%
Space Separator 93
 
9.9%
Decimal Number 29
 
3.1%
Open Punctuation 22
 
2.3%
Close Punctuation 22
 
2.3%
Math Symbol 12
 
1.3%
Dash Punctuation 11
 
1.2%
Uppercase Letter 7
 
0.7%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 49
 
6.6%
공 48
 
6.4%
로 38
 
5.1%
도 30
 
4.0%
구 28
 
3.8%
설 22
 
2.9%
건 21
 
2.8%
대 21
 
2.8%
지 20
 
2.7%
간 17
 
2.3%
Other values (157) 452
60.6%
Decimal Number
ValueCountFrequency (%)
2 10
34.5%
1 7
24.1%
5 3
 
10.3%
4 2
 
6.9%
3 2
 
6.9%
6 2
 
6.9%
7 2
 
6.9%
0 1
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
K 2
28.6%
S 1
14.3%
M 1
14.3%
C 1
14.3%
T 1
14.3%
I 1
14.3%
Space Separator
ValueCountFrequency (%)
93
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 746
79.1%
Common 190
 
20.1%
Latin 7
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 49
 
6.6%
공 48
 
6.4%
로 38
 
5.1%
도 30
 
4.0%
구 28
 
3.8%
설 22
 
2.9%
건 21
 
2.8%
대 21
 
2.8%
지 20
 
2.7%
간 17
 
2.3%
Other values (157) 452
60.6%
Common
ValueCountFrequency (%)
93
48.9%
( 22
 
11.6%
) 22
 
11.6%
~ 12
 
6.3%
- 11
 
5.8%
2 10
 
5.3%
1 7
 
3.7%
5 3
 
1.6%
4 2
 
1.1%
3 2
 
1.1%
Other values (4) 6
 
3.2%
Latin
ValueCountFrequency (%)
K 2
28.6%
S 1
14.3%
M 1
14.3%
C 1
14.3%
T 1
14.3%
I 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 746
79.1%
ASCII 197
 
20.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
93
47.2%
( 22
 
11.2%
) 22
 
11.2%
~ 12
 
6.1%
- 11
 
5.6%
2 10
 
5.1%
1 7
 
3.6%
5 3
 
1.5%
4 2
 
1.0%
3 2
 
1.0%
Other values (10) 13
 
6.6%
Hangul
ValueCountFrequency (%)
사 49
 
6.6%
공 48
 
6.4%
로 38
 
5.1%
도 30
 
4.0%
구 28
 
3.8%
설 22
 
2.9%
건 21
 
2.8%
대 21
 
2.8%
지 20
 
2.7%
간 17
 
2.3%
Other values (157) 452
60.6%

위치
Text

Distinct31
Distinct (%)64.6%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-04-18T02:39:23.623922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length7.2291667
Min length2

Characters and Unicode

Total characters347
Distinct characters105
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

Unique25 ?
Unique (%)52.1%

Sample

1st row동구
2nd row서구
3rd row수성구
4th row북구
5th row북구
ValueCountFrequency (%)
동구 8
 
12.1%
달서구 6
 
9.1%
북구 4
 
6.1%
성서5차 3
 
4.5%
수성구 2
 
3.0%
달성군 2
 
3.0%
서구 2
 
3.0%
첨단산업단지 2
 
3.0%
범안로 2
 
3.0%
대구출판산업단지 1
 
1.5%
Other values (34) 34
51.5%
2024-04-18T02:39:23.887739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 29
 
8.4%
20
 
5.8%
로 18
 
5.2%
서 13
 
3.7%
대 11
 
3.2%
동 9
 
2.6%
지 9
 
2.6%
~ 8
 
2.3%
달 8
 
2.3%
성 8
 
2.3%
Other values (95) 214
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 279
80.4%
Decimal Number 24
 
6.9%
Space Separator 20
 
5.8%
Math Symbol 8
 
2.3%
Open Punctuation 5
 
1.4%
Close Punctuation 5
 
1.4%
Dash Punctuation 2
 
0.6%
Other Punctuation 2
 
0.6%
Uppercase Letter 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 29
 
10.4%
로 18
 
6.5%
서 13
 
4.7%
대 11
 
3.9%
동 9
 
3.2%
지 9
 
3.2%
달 8
 
2.9%
성 8
 
2.9%
도 7
 
2.5%
단 7
 
2.5%
Other values (79) 160
57.3%
Decimal Number
ValueCountFrequency (%)
1 5
20.8%
3 5
20.8%
5 4
16.7%
2 4
16.7%
6 2
 
8.3%
0 2
 
8.3%
7 1
 
4.2%
4 1
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 279
80.4%
Common 66
 
19.0%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 29
 
10.4%
로 18
 
6.5%
서 13
 
4.7%
대 11
 
3.9%
동 9
 
3.2%
지 9
 
3.2%
달 8
 
2.9%
성 8
 
2.9%
도 7
 
2.5%
단 7
 
2.5%
Other values (79) 160
57.3%
Common
ValueCountFrequency (%)
20
30.3%
~ 8
 
12.1%
( 5
 
7.6%
1 5
 
7.6%
3 5
 
7.6%
) 5
 
7.6%
5 4
 
6.1%
2 4
 
6.1%
- 2
 
3.0%
6 2
 
3.0%
Other values (4) 6
 
9.1%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 279
80.4%
ASCII 68
 
19.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 29
 
10.4%
로 18
 
6.5%
서 13
 
4.7%
대 11
 
3.9%
동 9
 
3.2%
지 9
 
3.2%
달 8
 
2.9%
성 8
 
2.9%
도 7
 
2.5%
단 7
 
2.5%
Other values (79) 160
57.3%
ASCII
ValueCountFrequency (%)
20
29.4%
~ 8
 
11.8%
( 5
 
7.4%
1 5
 
7.4%
3 5
 
7.4%
) 5
 
7.4%
5 4
 
5.9%
2 4
 
5.9%
- 2
 
2.9%
6 2
 
2.9%
Other values (6) 8
 
11.8%

하자담보시작일
Date

Distinct43
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Memory size516.0 B
Minimum2009-05-25 00:00:00
Maximum2013-11-29 00:00:00
2024-04-18T02:39:23.983305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:24.079690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)

하자담보종료일
Date

Distinct43
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Memory size516.0 B
Minimum2011-05-24 00:00:00
Maximum2015-11-28 00:00:00
2024-04-18T02:39:24.175459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:24.273984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)

도로폭
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)47.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.388333
Minimum0
Maximum51.6
Zeros1
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-04-18T02:39:24.365035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q14.625
median24
Q335
95-th percentile48.25
Maximum51.6
Range51.6
Interquartile range (IQR)30.375

Descriptive statistics

Standard deviation15.518595
Coefficient of variation (CV)0.69315544
Kurtosis-1.1801705
Mean22.388333
Median Absolute Deviation (MAD)12
Skewness0.062209413
Sum1074.64
Variance240.82679
MonotonicityNot monotonic
2024-04-18T02:39:24.451205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3.0 10
20.8%
35.0 5
 
10.4%
30.0 4
 
8.3%
20.0 4
 
8.3%
28.0 3
 
6.2%
36.0 3
 
6.2%
25.0 2
 
4.2%
50.0 2
 
4.2%
18.0 1
 
2.1%
5.0 1
 
2.1%
Other values (13) 13
27.1%
ValueCountFrequency (%)
0.0 1
 
2.1%
3.0 10
20.8%
3.5 1
 
2.1%
5.0 1
 
2.1%
6.0 1
 
2.1%
7.0 1
 
2.1%
7.3 1
 
2.1%
18.0 1
 
2.1%
19.0 1
 
2.1%
20.0 4
 
8.3%
ValueCountFrequency (%)
51.6 1
 
2.1%
50.0 2
 
4.2%
45.0 1
 
2.1%
44.5 1
 
2.1%
40.0 1
 
2.1%
37.5 1
 
2.1%
36.0 3
6.2%
35.0 5
10.4%
30.0 4
8.3%
28.0 3
6.2%

도로연장
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean884.375
Minimum51
Maximum6749
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-04-18T02:39:24.541989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51
5-th percentile78.2
Q1222.25
median540.5
Q31101.25
95-th percentile2375.45
Maximum6749
Range6698
Interquartile range (IQR)879

Descriptive statistics

Standard deviation1134.6333
Coefficient of variation (CV)1.2829776
Kurtosis15.35617
Mean884.375
Median Absolute Deviation (MAD)358
Skewness3.4676298
Sum42450
Variance1287392.8
MonotonicityNot monotonic
2024-04-18T02:39:24.865260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
140 2
 
4.2%
126 1
 
2.1%
314 1
 
2.1%
255 1
 
2.1%
840 1
 
2.1%
1951 1
 
2.1%
51 1
 
2.1%
1207 1
 
2.1%
1246 1
 
2.1%
480 1
 
2.1%
Other values (37) 37
77.1%
ValueCountFrequency (%)
51 1
2.1%
55 1
2.1%
60 1
2.1%
112 1
2.1%
126 1
2.1%
134 1
2.1%
140 2
4.2%
177 1
2.1%
201 1
2.1%
210 1
2.1%
ValueCountFrequency (%)
6749 1
2.1%
3800 1
2.1%
2604 1
2.1%
1951 1
2.1%
1844 1
2.1%
1800 1
2.1%
1660 1
2.1%
1340 1
2.1%
1260 1
2.1%
1255 1
2.1%

도로면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17113.327
Minimum18.5
Maximum113320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-04-18T02:39:24.978828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18.5
5-th percentile332.1
Q11438.25
median7867
Q323509.205
95-th percentile56173
Maximum113320
Range113301.5
Interquartile range (IQR)22070.955

Descriptive statistics

Standard deviation24498.14
Coefficient of variation (CV)1.4315241
Kurtosis7.8522292
Mean17113.327
Median Absolute Deviation (MAD)7300
Skewness2.6273637
Sum821439.72
Variance6.0015887 × 108
MonotonicityNot monotonic
2024-04-18T02:39:25.080215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
2268.0 1
 
2.1%
113320.0 1
 
2.1%
18.5 1
 
2.1%
4594.0 1
 
2.1%
23459.0 1
 
2.1%
64286.0 1
 
2.1%
1412.0 1
 
2.1%
27828.0 1
 
2.1%
23659.82 1
 
2.1%
11110.0 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
18.5 1
2.1%
226.0 1
2.1%
330.0 1
2.1%
336.0 1
2.1%
490.0 1
2.1%
531.0 1
2.1%
603.0 1
2.1%
660.0 1
2.1%
669.0 1
2.1%
790.0 1
2.1%
ValueCountFrequency (%)
113320.0 1
2.1%
109162.0 1
2.1%
64286.0 1
2.1%
41106.0 1
2.1%
38225.0 1
2.1%
37809.0 1
2.1%
34770.0 1
2.1%
33143.0 1
2.1%
32209.0 1
2.1%
30136.0 1
2.1%

차로종류
Categorical

Distinct3
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
개설
26 
확장
13 
완화
9 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개설
2nd row완화
3rd row완화
4th row완화
5th row개설

Common Values

ValueCountFrequency (%)
개설 26
54.2%
확장 13
27.1%
완화 9
 
18.8%

Length

2024-04-18T02:39:25.181424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:39:25.251704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개설 26
54.2%
확장 13
27.1%
완화 9
 
18.8%

Interactions

2024-04-18T02:39:21.920646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:20.600158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:20.911544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.237956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.540034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.979048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:20.656462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:20.974893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.294613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.616678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:22.053023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:20.720173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.043705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.359655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.703898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:22.121036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:20.784150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.107309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.415524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.780820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:22.191603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:20.853008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.173584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.477181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:39:21.860650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T02:39:25.308285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호생성자번호인수일시사업명위치하자담보시작일하자담보종료일도로폭도로연장도로면적차로종류
일련번호1.0000.9660.9931.0000.7620.9510.9510.3020.0000.3240.532
생성자번호0.9661.0001.0001.0000.9650.9670.9670.4670.0000.0000.206
인수일시0.9931.0001.0001.0000.9560.9260.9260.0000.0000.6080.666
사업명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위치0.7620.9650.9561.0001.0000.7800.7800.6600.0000.7480.000
하자담보시작일0.9510.9670.9261.0000.7801.0001.0000.9290.8270.0000.902
하자담보종료일0.9510.9670.9261.0000.7801.0001.0000.9290.8270.0000.902
도로폭0.3020.4670.0001.0000.6600.9290.9291.0000.6860.7790.591
도로연장0.0000.0000.0001.0000.0000.8270.8270.6861.0000.9160.566
도로면적0.3240.0000.6081.0000.7480.0000.0000.7790.9161.0000.395
차로종류0.5320.2060.6661.0000.0000.9020.9020.5910.5660.3951.000
2024-04-18T02:39:25.408054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호생성자번호도로폭도로연장도로면적차로종류
일련번호1.0001.0000.2920.2760.2240.340
생성자번호1.0001.0000.2920.2760.2240.144
도로폭0.2920.2921.0000.4600.7010.291
도로연장0.2760.2760.4601.0000.8710.267
도로면적0.2240.2240.7010.8711.0000.165
차로종류0.3400.1440.2910.2670.1651.000

Missing values

2024-04-18T02:39:22.277012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T02:39:22.390676image/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

일련번호생성자번호인수일시사업명위치하자담보시작일하자담보종료일도로폭도로연장도로면적차로종류
012010010012010-01-05율하(2) 택지개발사업 조성공사(율하지하차도)동구2009-05-312011-05-3018.01262268.0개설
122010010022010-01-05평리2동 주택재건축 정비사업 아파트 신축서구2009-12-242011-12-233.0220660.0완화
232010010032010-01-05두산위브더제니스 신축수성구2009-12-242011-12-233.5140490.0완화
342010010052010-02-08(주)호텔 인터불고 엑스코 신축북구2009-05-252011-05-243.0112336.0완화
452010010072010-03-24구안국도-칠곡2지구간 도로건설공사북구2010-02-092012-02-0925.074518721.0개설
562010010082010-04-07강창교 확장공사달성군2010-01-292012-01-2950.01406398.0확장
672010010092010-04-07송현주공아파트 재건축 사업(상인 화성 파크드림)달서구2010-03-142012-03-146.05142570.0확장
782010010102010-05-06화원유원지입구-월배차량기지간 도로건설공사달성군2010-01-272012-01-2630.0184438225.0개설
892010010112010-05-06백조1차 상인아파트 주택 재건축(상인푸르지오)달서구2010-04-232012-04-223.0201603.0확장
9102010010122010-06-25매천로-지천간 도로확장 공사북구2010-05-122012-05-1137.53800109162.0확장
일련번호생성자번호인수일시사업명위치하자담보시작일하자담보종료일도로폭도로연장도로면적차로종류
38392012010112012-05-03대구광역시 중로1-277호선 외 1개도로 시설공사동구 율하동2012-02-172014-02-1620.0106615680.0개설
39402012010122012-05-07세천지구 토지구획정리사업세천지구2011-12-012013-11-3036.089318038.6개설
40412012010132012-05-31(신설)팔조령터널팔조령터널2012-01-062014-01-057.37165226.8개설
41422012010142012-02-22신천좌안도로(용계교~헤성빌라)건설공사신천좌안도로(용계교~헤성빌라)2012-01-172014-01-1630.04108534.0개설
42432013010022013-02-14대구출판산업단지 조성공사대구출판산업단지2012-11-132014-11-1223.09239590.0개설
43442013010032013-03-08다사읍사무소~다사정거장간 도로건설공사매곡로2길 중로1-341호선2013-02-062015-02-0620.051710764.0개설
44452013010042013-03-27혁신도시진입도로(율하교~혁신도시간) 건설공사(2공구)범안로(율하교~혁시도시) 범안로 대로1류 70호선2013-01-282015-01-2720.24125534770.0개설
45462013010052013-06-26감삼동 우방드림시티 북편 도로건설공사와룡로 31길 대로 3-53호선2013-06-142015-06-1325.03927200.0개설
46472013010062013-10-10대구4차순환도로(상인~범물간) 민자투자시설사업상화로, 범안로2013-05-152015-05-1435.0166013991.0확장
47482013010072013-12-30대구연구개발특구 진입도로 건설공사(각산역~반야월로)신서로(각산역~반야월로)2013-11-292015-11-2835.02104829.0개설