Overview

Dataset statistics

Number of variables15
Number of observations354
Missing cells3
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.8 KiB
Average record size in memory132.4 B

Variable types

Categorical12
Text1
Numeric2

Dataset

Description관리기관,도로종별,도로명,도로표지-입력,도로표지-보유,도로표지-비율,관광지표지-입력,관광지표지-보유,관광지표지-비율,사설표지-입력,사설표지-보유,사설표지-비율,전체표지-입력,전체표지-보유,전체표지-비율
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15015/S/1/datasetView.do

Alerts

관리기관 has constant value ""Constant
도로표지-보유 has constant value ""Constant
도로표지-비율 has constant value ""Constant
관광지표지-보유 has constant value ""Constant
관광지표지-비율 has constant value ""Constant
사설표지-보유 has constant value ""Constant
사설표지-비율 has constant value ""Constant
전체표지-보유 has constant value ""Constant
전체표지-비율 has constant value ""Constant
도로표지-입력 is highly overall correlated with 전체표지-입력 and 1 other fieldsHigh correlation
전체표지-입력 is highly overall correlated with 도로표지-입력 and 1 other fieldsHigh correlation
도로종별 is highly overall correlated with 관광지표지-입력High correlation
관광지표지-입력 is highly overall correlated with 도로표지-입력 and 2 other fieldsHigh correlation
관광지표지-입력 is highly imbalanced (96.5%)Imbalance
사설표지-입력 is highly imbalanced (95.8%)Imbalance

Reproduction

Analysis started2023-12-11 04:20:45.478581
Analysis finished2023-12-11 04:20:46.653859
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
서울특별시
354 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 354
100.0%

Length

2023-12-11T13:20:46.712120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:20:46.827769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 354
100.0%

도로종별
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
구도
186 
시도
53 
시도61
 
18
일반국도1
 
17
시도88
 
15
Other values (25)
65 

Length

Max length6
Median length2
Mean length2.7768362
Min length2

Unique

Unique15 ?
Unique (%)4.2%

Sample

1st row고속국도15
2nd row고속국도15
3rd row군도
4th row일반국도1
5th row일반국도1

Common Values

ValueCountFrequency (%)
구도 186
52.5%
시도 53
 
15.0%
시도61 18
 
5.1%
일반국도1 17
 
4.8%
시도88 15
 
4.2%
시도70 15
 
4.2%
시도30 14
 
4.0%
시도20 5
 
1.4%
시도47 3
 
0.8%
일반국도47 3
 
0.8%
Other values (20) 25
 
7.1%

Length

2023-12-11T13:20:46.951592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
구도 186
52.5%
시도 53
 
15.0%
시도61 18
 
5.1%
일반국도1 17
 
4.8%
시도88 15
 
4.2%
시도70 15
 
4.2%
시도30 14
 
4.0%
시도20 5
 
1.4%
시도47 3
 
0.8%
일반국도47 3
 
0.8%
Other values (20) 25
 
7.1%

도로명
Text

Distinct272
Distinct (%)77.5%
Missing3
Missing (%)0.8%
Memory size2.9 KiB
2023-12-11T13:20:47.358747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.4216524
Min length3

Characters and Unicode

Total characters1552
Distinct characters209
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

Unique220 ?
Unique (%)62.7%

Sample

1st row서부샛길
2nd row서해안고속도로
3rd row서오릉로
4th row가좌로
5th row경부고속도로
ValueCountFrequency (%)
천호대로 5
 
1.4%
강변북로 5
 
1.4%
양재대로 4
 
1.1%
화곡로 4
 
1.1%
화랑로 4
 
1.1%
동부간선도로 4
 
1.1%
동일로 3
 
0.9%
통일로 3
 
0.9%
성산로 3
 
0.9%
개화동로 3
 
0.9%
Other values (262) 313
89.2%
2023-12-11T13:20:48.011865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 331
 
21.3%
길 100
 
6.4%
대 55
 
3.5%
천 32
 
2.1%
동 31
 
2.0%
1 30
 
1.9%
양 28
 
1.8%
2 25
 
1.6%
강 23
 
1.5%
3 23
 
1.5%
Other values (199) 874
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1369
88.2%
Decimal Number 168
 
10.8%
Uppercase Letter 12
 
0.8%
Connector Punctuation 2
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 331
24.2%
길 100
 
7.3%
대 55
 
4.0%
천 32
 
2.3%
동 31
 
2.3%
양 28
 
2.0%
강 23
 
1.7%
서 23
 
1.7%
산 20
 
1.5%
일 16
 
1.2%
Other values (182) 710
51.9%
Decimal Number
ValueCountFrequency (%)
1 30
17.9%
2 25
14.9%
3 23
13.7%
5 20
11.9%
6 15
8.9%
4 15
8.9%
0 12
 
7.1%
8 10
 
6.0%
7 9
 
5.4%
9 9
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
N 4
33.3%
O 2
16.7%
A 2
16.7%
M 2
16.7%
E 2
16.7%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1369
88.2%
Common 171
 
11.0%
Latin 12
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 331
24.2%
길 100
 
7.3%
대 55
 
4.0%
천 32
 
2.3%
동 31
 
2.3%
양 28
 
2.0%
강 23
 
1.7%
서 23
 
1.7%
산 20
 
1.5%
일 16
 
1.2%
Other values (182) 710
51.9%
Common
ValueCountFrequency (%)
1 30
17.5%
2 25
14.6%
3 23
13.5%
5 20
11.7%
6 15
8.8%
4 15
8.8%
0 12
 
7.0%
8 10
 
5.8%
7 9
 
5.3%
9 9
 
5.3%
Other values (2) 3
 
1.8%
Latin
ValueCountFrequency (%)
N 4
33.3%
O 2
16.7%
A 2
16.7%
M 2
16.7%
E 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1369
88.2%
ASCII 183
 
11.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 331
24.2%
길 100
 
7.3%
대 55
 
4.0%
천 32
 
2.3%
동 31
 
2.3%
양 28
 
2.0%
강 23
 
1.7%
서 23
 
1.7%
산 20
 
1.5%
일 16
 
1.2%
Other values (182) 710
51.9%
ASCII
ValueCountFrequency (%)
1 30
16.4%
2 25
13.7%
3 23
12.6%
5 20
10.9%
6 15
8.2%
4 15
8.2%
0 12
 
6.6%
8 10
 
5.5%
7 9
 
4.9%
9 9
 
4.9%
Other values (7) 15
8.2%

도로표지-입력
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.460452
Minimum0
Maximum223
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-11T13:20:48.220590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile12
Maximum223
Range223
Interquartile range (IQR)2

Descriptive statistics

Standard deviation16.033777
Coefficient of variation (CV)3.594653
Kurtosis137.34153
Mean4.460452
Median Absolute Deviation (MAD)1
Skewness11.179172
Sum1579
Variance257.082
MonotonicityNot monotonic
2023-12-11T13:20:48.398673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 168
47.5%
2 64
 
18.1%
3 38
 
10.7%
4 18
 
5.1%
6 11
 
3.1%
5 10
 
2.8%
7 9
 
2.5%
8 7
 
2.0%
9 4
 
1.1%
12 4
 
1.1%
Other values (15) 21
 
5.9%
ValueCountFrequency (%)
0 1
 
0.3%
1 168
47.5%
2 64
 
18.1%
3 38
 
10.7%
4 18
 
5.1%
5 10
 
2.8%
6 11
 
3.1%
7 9
 
2.5%
8 7
 
2.0%
9 4
 
1.1%
ValueCountFrequency (%)
223 1
0.3%
178 1
0.3%
74 1
0.3%
57 1
0.3%
28 1
0.3%
21 1
0.3%
20 1
0.3%
19 2
0.6%
17 1
0.3%
16 1
0.3%

도로표지-보유
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
354 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 354
100.0%

Length

2023-12-11T13:20:48.544605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:20:48.670260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 354
100.0%

도로표지-비율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
354 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 354
100.0%

Length

2023-12-11T13:20:48.833376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:20:48.942523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 354
100.0%

관광지표지-입력
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
352 
2
 
1
10
 
1

Length

Max length2
Median length1
Mean length1.0028249
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 352
99.4%
2 1
 
0.3%
10 1
 
0.3%

Length

2023-12-11T13:20:49.084439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:20:49.254348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 352
99.4%
2 1
 
0.3%
10 1
 
0.3%

관광지표지-보유
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
354 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 354
100.0%

Length

2023-12-11T13:20:49.381955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:20:49.504390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 354
100.0%

관광지표지-비율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
354 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 354
100.0%

Length

2023-12-11T13:20:49.622015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:20:49.747183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 354
100.0%

사설표지-입력
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
351 
1
 
1
3
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)0.8%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 351
99.2%
1 1
 
0.3%
3 1
 
0.3%
2 1
 
0.3%

Length

2023-12-11T13:20:49.862618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:20:49.989093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 351
99.2%
1 1
 
0.3%
3 1
 
0.3%
2 1
 
0.3%

사설표지-보유
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
354 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 354
100.0%

Length

2023-12-11T13:20:50.132360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:20:50.245120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 354
100.0%

사설표지-비율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
354 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 354
100.0%

Length

2023-12-11T13:20:50.382112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:20:50.499132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 354
100.0%

전체표지-입력
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5112994
Minimum1
Maximum223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-11T13:20:50.596601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile12
Maximum223
Range222
Interquartile range (IQR)2

Descriptive statistics

Standard deviation16.141413
Coefficient of variation (CV)3.5779963
Kurtosis133.82102
Mean4.5112994
Median Absolute Deviation (MAD)1
Skewness11.015881
Sum1597
Variance260.5452
MonotonicityNot monotonic
2023-12-11T13:20:50.718969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 169
47.7%
2 64
 
18.1%
3 37
 
10.5%
4 18
 
5.1%
6 12
 
3.4%
5 10
 
2.8%
7 9
 
2.5%
8 7
 
2.0%
9 4
 
1.1%
13 4
 
1.1%
Other values (14) 20
 
5.6%
ValueCountFrequency (%)
1 169
47.7%
2 64
 
18.1%
3 37
 
10.5%
4 18
 
5.1%
5 10
 
2.8%
6 12
 
3.4%
7 9
 
2.5%
8 7
 
2.0%
9 4
 
1.1%
10 3
 
0.8%
ValueCountFrequency (%)
223 1
0.3%
178 1
0.3%
74 1
0.3%
67 1
0.3%
28 1
0.3%
21 1
0.3%
20 1
0.3%
19 2
0.6%
18 1
0.3%
17 1
0.3%

전체표지-보유
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
354 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 354
100.0%

Length

2023-12-11T13:20:50.913344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:20:51.094927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 354
100.0%

전체표지-비율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
354 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 354
100.0%

Length

2023-12-11T13:20:51.224328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:20:51.354627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 354
100.0%

Interactions

2023-12-11T13:20:46.091072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:20:45.900336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:20:46.173381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:20:45.984764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T13:20:51.433781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로종별도로표지-입력관광지표지-입력사설표지-입력전체표지-입력
도로종별1.0000.5670.8950.0000.567
도로표지-입력0.5671.0000.9390.0001.000
관광지표지-입력0.8950.9391.0000.0000.939
사설표지-입력0.0000.0000.0001.0000.000
전체표지-입력0.5671.0000.9390.0001.000
2023-12-11T13:20:51.871043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광지표지-입력도로종별사설표지-입력
관광지표지-입력1.0000.6480.000
도로종별0.6481.0000.000
사설표지-입력0.0000.0001.000
2023-12-11T13:20:51.992600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로표지-입력전체표지-입력도로종별관광지표지-입력사설표지-입력
도로표지-입력1.0000.9980.2560.6990.000
전체표지-입력0.9981.0000.2560.6990.000
도로종별0.2560.2561.0000.6480.000
관광지표지-입력0.6990.6990.6481.0000.000
사설표지-입력0.0000.0000.0000.0001.000

Missing values

2023-12-11T13:20:46.339833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T13:20:46.583099image/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

관리기관도로종별도로명도로표지-입력도로표지-보유도로표지-비율관광지표지-입력관광지표지-보유관광지표지-비율사설표지-입력사설표지-보유사설표지-비율전체표지-입력전체표지-보유전체표지-비율
0서울특별시고속국도15서부샛길200000000200
1서울특별시고속국도15서해안고속도로200000000200
2서울특별시군도서오릉로100000000100
3서울특별시일반국도1<NA>400000000400
4서울특별시일반국도1가좌로100000000100
5서울특별시일반국도1경부고속도로100000000100
6서울특별시일반국도1국회대로100000000100
7서울특별시일반국도1마포나루길100000000100
8서울특별시일반국도1서부간선도로13000000001300
9서울특별시일반국도1서부샛길20000000002000
관리기관도로종별도로명도로표지-입력도로표지-보유도로표지-비율관광지표지-입력관광지표지-보유관광지표지-비율사설표지-입력사설표지-보유사설표지-비율전체표지-입력전체표지-보유전체표지-비율
344서울특별시구도현충로100000000100
345서울특별시구도호암로100000000100
346서울특별시구도홍제천로100000000100
347서울특별시구도화곡로300000000300
348서울특별시구도화곡로27길100000000100
349서울특별시구도화랑로100000000100
350서울특별시구도회기로100000000100
351서울특별시구도효령로200000000200
352서울특별시구도70양녕로100000000100
353서울특별시구도111증가로6길100000000100