Overview

Dataset statistics

Number of variables7
Number of observations83
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory59.6 B

Variable types

Text2
Categorical3
Numeric2

Dataset

Description대전광역시 유성구에 있는 제설함설치현황에 대한 데이터로 장소, 사용목적, 법정동, 행정동, 지번주소, 위도, 경도 항목을 제공합니다.
Author대전광역시 유성구
URLhttps://www.data.go.kr/data/15089342/fileData.do

Alerts

사용목적 has constant value ""Constant
위도 is highly overall correlated with 경도 and 2 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
법정동 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
행정동 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
장소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:19:08.484742
Analysis finished2023-12-12 20:19:09.644451
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

장소
Text

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-13T05:19:09.901356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length8.3012048
Min length3

Characters and Unicode

Total characters689
Distinct characters197
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)100.0%

Sample

1st row남세종IC
2nd row외삼네거리
3rd row반석역
4th row하기1교
5th row유성여고
ValueCountFrequency (%)
앞 7
 
5.0%
7
 
5.0%
삼거리 5
 
3.6%
네거리 4
 
2.9%
정문 3
 
2.2%
전민동 2
 
1.4%
유성ic 2
 
1.4%
유성2교 2
 
1.4%
장대삼거리 2
 
1.4%
월드컵네거리 2
 
1.4%
Other values (102) 103
74.1%
2023-12-13T05:19:10.429938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56
 
8.1%
리 36
 
5.2%
거 32
 
4.6%
네 19
 
2.8%
교 17
 
2.5%
지 17
 
2.5%
~ 14
 
2.0%
삼 13
 
1.9%
성 13
 
1.9%
동 12
 
1.7%
Other values (187) 460
66.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 566
82.1%
Space Separator 56
 
8.1%
Decimal Number 29
 
4.2%
Math Symbol 14
 
2.0%
Uppercase Letter 12
 
1.7%
Close Punctuation 3
 
0.4%
Open Punctuation 3
 
0.4%
Dash Punctuation 3
 
0.4%
Other Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 36
 
6.4%
거 32
 
5.7%
네 19
 
3.4%
교 17
 
3.0%
지 17
 
3.0%
삼 13
 
2.3%
성 13
 
2.3%
동 12
 
2.1%
대 12
 
2.1%
유 12
 
2.1%
Other values (164) 383
67.7%
Decimal Number
ValueCountFrequency (%)
2 7
24.1%
3 5
17.2%
1 5
17.2%
5 4
13.8%
4 3
10.3%
8 2
 
6.9%
9 1
 
3.4%
7 1
 
3.4%
6 1
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
C 4
33.3%
I 3
25.0%
K 1
 
8.3%
M 1
 
8.3%
T 1
 
8.3%
G 1
 
8.3%
B 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
＆ 1
33.3%
Space Separator
ValueCountFrequency (%)
56
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 566
82.1%
Common 111
 
16.1%
Latin 12
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 36
 
6.4%
거 32
 
5.7%
네 19
 
3.4%
교 17
 
3.0%
지 17
 
3.0%
삼 13
 
2.3%
성 13
 
2.3%
동 12
 
2.1%
대 12
 
2.1%
유 12
 
2.1%
Other values (164) 383
67.7%
Common
ValueCountFrequency (%)
56
50.5%
~ 14
 
12.6%
2 7
 
6.3%
3 5
 
4.5%
1 5
 
4.5%
5 4
 
3.6%
) 3
 
2.7%
( 3
 
2.7%
4 3
 
2.7%
- 3
 
2.7%
Other values (6) 8
 
7.2%
Latin
ValueCountFrequency (%)
C 4
33.3%
I 3
25.0%
K 1
 
8.3%
M 1
 
8.3%
T 1
 
8.3%
G 1
 
8.3%
B 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 566
82.1%
ASCII 122
 
17.7%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
56
45.9%
~ 14
 
11.5%
2 7
 
5.7%
3 5
 
4.1%
1 5
 
4.1%
5 4
 
3.3%
C 4
 
3.3%
) 3
 
2.5%
( 3
 
2.5%
4 3
 
2.5%
Other values (12) 18
 
14.8%
Hangul
ValueCountFrequency (%)
리 36
 
6.4%
거 32
 
5.7%
네 19
 
3.4%
교 17
 
3.0%
지 17
 
3.0%
삼 13
 
2.3%
성 13
 
2.3%
동 12
 
2.1%
대 12
 
2.1%
유 12
 
2.1%
Other values (164) 383
67.7%
None
ValueCountFrequency (%)
＆ 1
100.0%

사용목적
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
제설자재보관
83 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제설자재보관 83
100.0%

Length

2023-12-13T05:19:10.620349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:19:10.735969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제설자재보관 83
100.0%

법정동
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)34.9%
Missing0
Missing (%)0.0%
Memory size796.0 B
관평동
7 
지족동
7 
하기동
6 
노은동
 
5
봉명동
 
5
Other values (24)
53 

Length

Max length4
Median length3
Mean length2.9638554
Min length2

Unique

Unique8 ?
Unique (%)9.6%

Sample

1st row안산동
2nd row반석동
3rd row반석동
4th row하기동
5th row죽동

Common Values

ValueCountFrequency (%)
관평동 7
 
8.4%
지족동 7
 
8.4%
하기동 6
 
7.2%
노은동 5
 
6.0%
봉명동 5
 
6.0%
구암동 4
 
4.8%
신성동 4
 
4.8%
송강동 4
 
4.8%
도룡동 4
 
4.8%
상대동 4
 
4.8%
Other values (19) 33
39.8%

Length

2023-12-13T05:19:10.889606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
관평동 7
 
8.4%
지족동 7
 
8.4%
하기동 6
 
7.2%
노은동 5
 
6.0%
봉명동 5
 
6.0%
송강동 4
 
4.8%
상대동 4
 
4.8%
도룡동 4
 
4.8%
신성동 4
 
4.8%
구암동 4
 
4.8%
Other values (19) 33
39.8%

행정동
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size796.0 B
노은2동
12 
신성동
11 
관평동
11 
온천1동
10 
구즉동
7 
Other values (6)
32 

Length

Max length4
Median length4
Mean length3.5301205
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row노은2동
2nd row노은2동
3rd row노은2동
4th row노은2동
5th row노은2동

Common Values

ValueCountFrequency (%)
노은2동 12
14.5%
신성동 11
13.3%
관평동 11
13.3%
온천1동 10
12.0%
구즉동 7
8.4%
노은1동 6
7.2%
전민동 6
7.2%
원신흥동 6
7.2%
온천2동 5
6.0%
노은3동 5
6.0%

Length

2023-12-13T05:19:11.059163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노은2동 12
14.5%
신성동 11
13.3%
관평동 11
13.3%
온천1동 10
12.0%
구즉동 7
8.4%
노은1동 6
7.2%
전민동 6
7.2%
원신흥동 6
7.2%
온천2동 5
6.0%
노은3동 5
6.0%

지번주소
Text

Distinct82
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-13T05:19:11.400981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length17.927711
Min length15

Characters and Unicode

Total characters1488
Distinct characters62
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

Unique81 ?
Unique (%)97.6%

Sample

1st row대전광역시 유성구 안산동 365-1
2nd row대전광역시 유성구 반석동 679
3rd row대전광역시 유성구 반석동 61-2
4th row대전광역시 유성구 하기동 518
5th row대전광역시 유성구 죽동 292
ValueCountFrequency (%)
대전광역시 83
25.0%
유성구 83
25.0%
지족동 7
 
2.1%
관평동 7
 
2.1%
하기동 6
 
1.8%
봉명동 5
 
1.5%
노은동 5
 
1.5%
송강동 4
 
1.2%
도룡동 4
 
1.2%
신성동 4
 
1.2%
Other values (103) 124
37.3%
2023-12-13T05:19:11.887413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
249
16.7%
대 89
 
6.0%
성 87
 
5.8%
구 87
 
5.8%
전 86
 
5.8%
시 83
 
5.6%
역 83
 
5.6%
유 83
 
5.6%
광 83
 
5.6%
동 83
 
5.6%
Other values (52) 475
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 910
61.2%
Decimal Number 290
 
19.5%
Space Separator 249
 
16.7%
Dash Punctuation 39
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 89
9.8%
성 87
9.6%
구 87
9.6%
전 86
9.5%
시 83
9.1%
역 83
9.1%
유 83
9.1%
광 83
9.1%
동 83
9.1%
지 8
 
0.9%
Other values (40) 138
15.2%
Decimal Number
ValueCountFrequency (%)
1 53
18.3%
5 36
12.4%
6 35
12.1%
2 33
11.4%
4 27
9.3%
9 27
9.3%
3 27
9.3%
0 22
7.6%
8 16
 
5.5%
7 14
 
4.8%
Space Separator
ValueCountFrequency (%)
249
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 910
61.2%
Common 578
38.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 89
9.8%
성 87
9.6%
구 87
9.6%
전 86
9.5%
시 83
9.1%
역 83
9.1%
유 83
9.1%
광 83
9.1%
동 83
9.1%
지 8
 
0.9%
Other values (40) 138
15.2%
Common
ValueCountFrequency (%)
249
43.1%
1 53
 
9.2%
- 39
 
6.7%
5 36
 
6.2%
6 35
 
6.1%
2 33
 
5.7%
4 27
 
4.7%
9 27
 
4.7%
3 27
 
4.7%
0 22
 
3.8%
Other values (2) 30
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 910
61.2%
ASCII 578
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
249
43.1%
1 53
 
9.2%
- 39
 
6.7%
5 36
 
6.2%
6 35
 
6.1%
2 33
 
5.7%
4 27
 
4.7%
9 27
 
4.7%
3 27
 
4.7%
0 22
 
3.8%
Other values (2) 30
 
5.2%
Hangul
ValueCountFrequency (%)
대 89
9.8%
성 87
9.6%
구 87
9.6%
전 86
9.5%
시 83
9.1%
역 83
9.1%
유 83
9.1%
광 83
9.1%
동 83
9.1%
지 8
 
0.9%
Other values (40) 138
15.2%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct78
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.382723
Minimum36.273573
Maximum36.493373
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2023-12-13T05:19:12.080609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.273573
5-th percentile36.340077
Q136.363417
median36.383466
Q336.398483
95-th percentile36.431222
Maximum36.493373
Range0.2198
Interquartile range (IQR)0.0350655

Descriptive statistics

Standard deviation0.03644228
Coefficient of variation (CV)0.001001637
Kurtosis1.6763226
Mean36.382723
Median Absolute Deviation (MAD)0.01891
Skewness-0.082168169
Sum3019.766
Variance0.0013280397
MonotonicityNot monotonic
2023-12-13T05:19:12.269077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.341035 3
 
3.6%
36.374047 2
 
2.4%
36.359294 2
 
2.4%
36.382332 2
 
2.4%
36.418994 1
 
1.2%
36.397604 1
 
1.2%
36.399361 1
 
1.2%
36.399641 1
 
1.2%
36.410921 1
 
1.2%
36.417698 1
 
1.2%
Other values (68) 68
81.9%
ValueCountFrequency (%)
36.273573 1
 
1.2%
36.282099 1
 
1.2%
36.301025 1
 
1.2%
36.302712 1
 
1.2%
36.33997 1
 
1.2%
36.341035 3
3.6%
36.344578 1
 
1.2%
36.347072 1
 
1.2%
36.354918 1
 
1.2%
36.356164 1
 
1.2%
ValueCountFrequency (%)
36.493373 1
1.2%
36.472066 1
1.2%
36.454424 1
1.2%
36.434624 1
1.2%
36.431266 1
1.2%
36.430831 1
1.2%
36.429564 1
1.2%
36.428956 1
1.2%
36.425999 1
1.2%
36.425483 1
1.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct78
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.34663
Minimum127.27238
Maximum127.40464
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2023-12-13T05:19:12.452452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.27238
5-th percentile127.30532
Q1127.31811
median127.34038
Q3127.38326
95-th percentile127.40104
Maximum127.40464
Range0.132258
Interquartile range (IQR)0.0651595

Descriptive statistics

Standard deviation0.035041909
Coefficient of variation (CV)0.00027516949
Kurtosis-1.1856221
Mean127.34663
Median Absolute Deviation (MAD)0.027338
Skewness0.14907407
Sum10569.771
Variance0.0012279354
MonotonicityNot monotonic
2023-12-13T05:19:12.613985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.32565 3
 
3.6%
127.317413 2
 
2.4%
127.340384 2
 
2.4%
127.309341 2
 
2.4%
127.379735 1
 
1.2%
127.402391 1
 
1.2%
127.40267 1
 
1.2%
127.395882 1
 
1.2%
127.39245 1
 
1.2%
127.387681 1
 
1.2%
Other values (68) 68
81.9%
ValueCountFrequency (%)
127.27238 1
1.2%
127.272675 1
1.2%
127.293918 1
1.2%
127.303889 1
1.2%
127.305309 1
1.2%
127.305452 1
1.2%
127.305621 1
1.2%
127.308684 1
1.2%
127.309341 2
2.4%
127.309967 1
1.2%
ValueCountFrequency (%)
127.404638 1
1.2%
127.402811 1
1.2%
127.40267 1
1.2%
127.402391 1
1.2%
127.4015 1
1.2%
127.396885 1
1.2%
127.396225 1
1.2%
127.395882 1
1.2%
127.394006 1
1.2%
127.39245 1
1.2%

Interactions

2023-12-13T05:19:09.149627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:19:08.880858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:19:09.264544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:19:09.009048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:19:12.723092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
장소법정동행정동지번주소위도경도
장소1.0001.0001.0001.0001.0001.000
법정동1.0001.0000.9921.0000.9790.959
행정동1.0000.9921.0001.0000.8750.782
지번주소1.0001.0001.0001.0001.0001.000
위도1.0000.9790.8751.0001.0000.609
경도1.0000.9590.7821.0000.6091.000
2023-12-13T05:19:12.846255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동행정동
법정동1.0000.812
행정동0.8121.000
2023-12-13T05:19:12.937868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도법정동행정동
위도1.0000.5540.7480.646
경도0.5541.0000.6630.475
법정동0.7480.6631.0000.812
행정동0.6460.4750.8121.000

Missing values

2023-12-13T05:19:09.417990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:19:09.573714image/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

장소사용목적법정동행정동지번주소위도경도
0남세종IC제설자재보관안산동노은2동대전광역시 유성구 안산동 365-136.421608127.293918
1외삼네거리제설자재보관반석동노은2동대전광역시 유성구 반석동 67936.396123127.309967
2반석역제설자재보관반석동노은2동대전광역시 유성구 반석동 61-236.392287127.313046
3하기1교제설자재보관하기동노은2동대전광역시 유성구 하기동 51836.384887127.318915
4유성여고제설자재보관죽동노은2동대전광역시 유성구 죽동 29236.383061127.325601
5월드컵네거리제설자재보관노은동노은1동대전광역시 유성구 노은동 41-636.366409127.32612
6월드컵네거리 ~ 장대삼거리제설자재보관노은동노은1동대전광역시 유성구 노은동 27036.365709127.32666
7장대삼거리 ~ 유성IC제설자재보관장대동온천2동대전광역시 유성구 장대동 120-1636.364556127.327074
8유성IC ~ 충대방향제설자재보관장대동온천2동대전광역시 유성구 장대동 306-836.365034127.335502
9지족3교제설자재보관반석동노은3동대전광역시 유성구 반석동 580-9736.38996127.305309
장소사용목적법정동행정동지번주소위도경도
73도안트리풀시티9블럭정문제설자재보관상대동원신흥동대전광역시 유성구 상대동 484-436.341035127.32565
74원신흥교제설자재보관원신흥동원신흥동대전광역시 유성구 원신흥동 488-236.354918127.314514
75고려교제설자재보관상대동원신흥동대전광역시 유성구 상대동 49936.341035127.32565
76상대교제설자재보관원신흥동원신흥동대전광역시 유성구 원신흥동 588-136.344578127.33045
77진잠 치안센터제설자재보관원내동진잠동대전광역시 유성구 원내동 9536.302712127.318585
78진잠우체국제설자재보관원내동진잠동대전광역시 유성구 원내동 92-1436.301025127.317897
79방동저수지제설자재보관방동진잠동대전광역시 유성구 방동 4136.282099127.305621
80방동~세정길(소)제설자재보관방동진잠동대전광역시 유성구 방동 741-736.273573127.272675
81시외버스~구암역제설자재보관구암동온천1동대전광역시 유성구 구암동 96-336.356593127.328517
82유성2교제설자재보관봉명동온천1동대전광역시 유성구 봉명동 60136.359294127.340384