Overview

Dataset statistics

Number of variables7
Number of observations496
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.2 KiB
Average record size in memory58.3 B

Variable types

Numeric2
Categorical2
DateTime2
Text1

Dataset

Description대구공공시설관리공단(구.대구시설공단) 도로시설물 경찰청심의자료입니다.일련번호, 문서번호1, 문서번호2, 발송일자, 접수일자, 심의내용, 시행여부로 구성되어있습니다.
Author대구공공시설관리공단
URLhttps://www.data.go.kr/data/15120458/fileData.do

Alerts

문서번호2 is highly overall correlated with 문서번호1High correlation
문서번호1 is highly overall correlated with 문서번호2High correlation
문서번호1 is highly imbalanced (91.9%)Imbalance
일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:59:52.661282
Analysis finished2023-12-12 21:59:53.962455
Duration1.3 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

UNIQUE 

Distinct496
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean248.5
Minimum1
Maximum496
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T06:59:54.059558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25.75
Q1124.75
median248.5
Q3372.25
95-th percentile471.25
Maximum496
Range495
Interquartile range (IQR)247.5

Descriptive statistics

Standard deviation143.32713
Coefficient of variation (CV)0.57676914
Kurtosis-1.2
Mean248.5
Median Absolute Deviation (MAD)124
Skewness0
Sum123256
Variance20542.667
MonotonicityStrictly increasing
2023-12-13T06:59:54.227645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
328 1
 
0.2%
341 1
 
0.2%
340 1
 
0.2%
339 1
 
0.2%
338 1
 
0.2%
337 1
 
0.2%
336 1
 
0.2%
335 1
 
0.2%
334 1
 
0.2%
Other values (486) 486
98.0%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
496 1
0.2%
495 1
0.2%
494 1
0.2%
493 1
0.2%
492 1
0.2%
491 1
0.2%
490 1
0.2%
489 1
0.2%
488 1
0.2%
487 1
0.2%

문서번호1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
경비교통과
488 
교통과
 
7
도로보수팀
 
1

Length

Max length5
Median length5
Mean length4.9717742
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
경비교통과 488
98.4%
교통과 7
 
1.4%
도로보수팀 1
 
0.2%

Length

2023-12-13T06:59:54.420187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:59:54.519315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경비교통과 488
98.4%
교통과 7
 
1.4%
도로보수팀 1
 
0.2%

문서번호2
Real number (ℝ)

HIGH CORRELATION 

Distinct428
Distinct (%)86.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16060.633
Minimum139
Maximum82300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T06:59:54.662584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum139
5-th percentile2731.5
Q19034
median14523
Q321722
95-th percentile33427.25
Maximum82300
Range82161
Interquartile range (IQR)12688

Descriptive statistics

Standard deviation9779.8205
Coefficient of variation (CV)0.6089312
Kurtosis6.450895
Mean16060.633
Median Absolute Deviation (MAD)6328
Skewness1.5169662
Sum7966074
Variance95644890
MonotonicityNot monotonic
2023-12-13T06:59:54.810485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21130 7
 
1.4%
19243 5
 
1.0%
19105 4
 
0.8%
18932 4
 
0.8%
17934 4
 
0.8%
5038 3
 
0.6%
8208 3
 
0.6%
24588 3
 
0.6%
13515 3
 
0.6%
10705 3
 
0.6%
Other values (418) 457
92.1%
ValueCountFrequency (%)
139 1
0.2%
571 1
0.2%
698 1
0.2%
840 1
0.2%
994 1
0.2%
1052 1
0.2%
1127 1
0.2%
1178 1
0.2%
1185 1
0.2%
1191 1
0.2%
ValueCountFrequency (%)
82300 1
0.2%
71769 1
0.2%
64844 1
0.2%
50188 1
0.2%
36380 1
0.2%
36309 1
0.2%
36246 1
0.2%
35722 1
0.2%
35719 1
0.2%
35575 1
0.2%

발송일자
Date

Distinct277
Distinct (%)55.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2012-03-27 00:00:00
Maximum2016-03-08 00:00:00
2023-12-13T06:59:54.931471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:55.072999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

접수일자
Date

Distinct275
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2012-03-27 00:00:00
Maximum2016-03-08 00:00:00
2023-12-13T06:59:55.197967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:55.347924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

심의내용
Text

Distinct493
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T06:59:55.618639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length98
Median length61
Mean length26.020161
Min length8

Characters and Unicode

Total characters12906
Distinct characters429
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique490 ?
Unique (%)98.8%

Sample

1st row황색복선- 두류네거리~두류공원네거리
2nd row황색복선 - 들안길네거리~황금고가교네거리
3rd row황색복선- 경대제2체육관~복현오거리
4th row황색복선 - 영대병원네거리~신천대로서편
5th row황색복선 - 상인네거리~송현청구제네스101동
ValueCountFrequency (%)
횡단보도 81
 
3.6%
신설 67
 
3.0%
63
 
2.8%
앞 59
 
2.6%
설치 53
 
2.3%
북구 40
 
1.8%
달서구 39
 
1.7%
황색복선 32
 
1.4%
노면표시 30
 
1.3%
및 28
 
1.2%
Other values (1091) 1772
78.3%
2023-12-13T06:59:56.066956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1779
 
13.8%
리 320
 
2.5%
동 302
 
2.3%
) 302
 
2.3%
( 298
 
2.3%
구 284
 
2.2%
거 282
 
2.2%
도 268
 
2.1%
선 235
 
1.8%
로 224
 
1.7%
Other values (419) 8612
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9533
73.9%
Space Separator 1779
 
13.8%
Decimal Number 423
 
3.3%
Close Punctuation 304
 
2.4%
Open Punctuation 300
 
2.3%
Other Punctuation 179
 
1.4%
Dash Punctuation 148
 
1.1%
Math Symbol 139
 
1.1%
Uppercase Letter 59
 
0.5%
Lowercase Letter 42
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 320
 
3.4%
동 302
 
3.2%
구 284
 
3.0%
거 282
 
3.0%
도 268
 
2.8%
선 235
 
2.5%
로 224
 
2.3%
설 222
 
2.3%
서 197
 
2.1%
보 191
 
2.0%
Other values (363) 7008
73.5%
Uppercase Letter
ValueCountFrequency (%)
C 12
20.3%
I 9
15.3%
L 6
10.2%
M 4
 
6.8%
S 4
 
6.8%
G 4
 
6.8%
H 3
 
5.1%
P 3
 
5.1%
R 3
 
5.1%
A 2
 
3.4%
Other values (8) 9
15.3%
Lowercase Letter
ValueCountFrequency (%)
m 22
52.4%
k 8
 
19.0%
t 2
 
4.8%
p 2
 
4.8%
l 1
 
2.4%
d 1
 
2.4%
n 1
 
2.4%
j 1
 
2.4%
s 1
 
2.4%
h 1
 
2.4%
Other values (2) 2
 
4.8%
Decimal Number
ValueCountFrequency (%)
0 97
22.9%
1 67
15.8%
3 46
10.9%
2 43
10.2%
5 42
9.9%
4 38
 
9.0%
6 34
 
8.0%
7 24
 
5.7%
9 17
 
4.0%
8 15
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 153
85.5%
. 13
 
7.3%
" 8
 
4.5%
: 4
 
2.2%
/ 1
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 61
43.9%
→ 39
28.1%
> 33
23.7%
↔ 4
 
2.9%
= 2
 
1.4%
Close Punctuation
ValueCountFrequency (%)
) 302
99.3%
] 2
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 298
99.3%
[ 2
 
0.7%
Space Separator
ValueCountFrequency (%)
1779
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 148
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9533
73.9%
Common 3272
 
25.4%
Latin 101
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 320
 
3.4%
동 302
 
3.2%
구 284
 
3.0%
거 282
 
3.0%
도 268
 
2.8%
선 235
 
2.5%
로 224
 
2.3%
설 222
 
2.3%
서 197
 
2.1%
보 191
 
2.0%
Other values (363) 7008
73.5%
Latin
ValueCountFrequency (%)
m 22
21.8%
C 12
11.9%
I 9
 
8.9%
k 8
 
7.9%
L 6
 
5.9%
M 4
 
4.0%
S 4
 
4.0%
G 4
 
4.0%
H 3
 
3.0%
P 3
 
3.0%
Other values (20) 26
25.7%
Common
ValueCountFrequency (%)
1779
54.4%
) 302
 
9.2%
( 298
 
9.1%
, 153
 
4.7%
- 148
 
4.5%
0 97
 
3.0%
1 67
 
2.0%
~ 61
 
1.9%
3 46
 
1.4%
2 43
 
1.3%
Other values (16) 278
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9533
73.9%
ASCII 3330
 
25.8%
Arrows 43
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1779
53.4%
) 302
 
9.1%
( 298
 
8.9%
, 153
 
4.6%
- 148
 
4.4%
0 97
 
2.9%
1 67
 
2.0%
~ 61
 
1.8%
3 46
 
1.4%
2 43
 
1.3%
Other values (44) 336
 
10.1%
Hangul
ValueCountFrequency (%)
리 320
 
3.4%
동 302
 
3.2%
구 284
 
3.0%
거 282
 
3.0%
도 268
 
2.8%
선 235
 
2.5%
로 224
 
2.3%
설 222
 
2.3%
서 197
 
2.1%
보 191
 
2.0%
Other values (363) 7008
73.5%
Arrows
ValueCountFrequency (%)
→ 39
90.7%
↔ 4
 
9.3%

시행여부
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
시행
251 
미시행
237 
기시행
 
8

Length

Max length3
Median length2
Mean length2.4939516
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시행 251
50.6%
미시행 237
47.8%
기시행 8
 
1.6%

Length

2023-12-13T06:59:56.197003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:59:56.281056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시행 251
50.6%
미시행 237
47.8%
기시행 8
 
1.6%

Interactions

2023-12-13T06:59:53.547914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:53.348790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:53.634866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:53.456136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:59:56.336332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호문서번호1문서번호2시행여부
일련번호1.0000.2340.6970.490
문서번호10.2341.0000.8540.591
문서번호20.6970.8541.0000.476
시행여부0.4900.5910.4761.000
2023-12-13T06:59:56.410015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
문서번호1시행여부
문서번호11.0000.265
시행여부0.2651.000
2023-12-13T06:59:56.483095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호문서번호2문서번호1시행여부
일련번호1.0000.0830.1430.335
문서번호20.0831.0000.5240.238
문서번호10.1430.5241.0000.265
시행여부0.3350.2380.2651.000

Missing values

2023-12-13T06:59:53.762878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:59:53.896991image/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

일련번호문서번호1문서번호2발송일자접수일자심의내용시행여부
01경비교통과363802012-12-282012-12-28황색복선- 두류네거리~두류공원네거리미시행
12경비교통과362462012-12-262012-12-27황색복선 - 들안길네거리~황금고가교네거리미시행
23경비교통과363092012-12-242012-12-24황색복선- 경대제2체육관~복현오거리미시행
34경비교통과355652012-12-182012-12-18황색복선 - 영대병원네거리~신천대로서편미시행
45경비교통과355752012-12-192012-12-18황색복선 - 상인네거리~송현청구제네스101동미시행
56경비교통과357192012-12-202012-12-20황색복선 - 두류네거리~평리네거리미시행
67경비교통과357222012-12-202012-12-20황색복선 - 평리네거리~만평네거리미시행
78경비교통과348932012-12-102012-12-11황색복선 - 대구법원앞, 서부지방법원~동서우방타운미시행
89경비교통과348892012-12-102012-12-11황색복선 - 수성네거리남편~수성파크드림2차미시행
910경비교통과345882012-12-062012-12-06황색복선 - 입석네거리~동촌초등삼거리시행
일련번호문서번호1문서번호2발송일자접수일자심의내용시행여부
486487경비교통과289902015-12-072015-12-07용산로(대구학생문화센터 북편삼거리) 노면표시 변경미시행
487488경비교통과294962015-12-112015-12-14테크노폴리스 내(하나리움퀸즈아파트 서편) 차선조정미시행
488489경비교통과303012015-12-232015-12-23명덕로(범어동 라온제나 호텔 네거리) 횡단보도 신설미시행
489490경비교통과303312015-12-232015-12-23성서공단로(산업은행) 횡단보도 신설미시행
490491경비교통과303312015-12-232015-12-23서재로(다사농협 서재지점) 횡단보도 이설미시행
491492경비교통과259422015-11-022015-11-02조암로6길(월성푸르지오) 횡단보도 신설시행
492493경비교통과141922016-03-082016-03-08도시철도 3호선 만평역 1번 출구(횡단보도 신설)미시행
493494경비교통과148342015-06-162015-06-18서구 다이텍 연구소 앞("비보호겸용" 신설)미시행
494495경비교통과148342015-06-162015-06-18이현지구대 앞 ("비보호겸용" 신설)미시행
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