Overview

Dataset statistics

Number of variables4
Number of observations487
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.3 KiB
Average record size in memory34.3 B

Variable types

Numeric1
Text1
Categorical2

Dataset

Description서울특별시에서 제공하는 도로 기능별 구분정보입니다.
Author서울특별시
URLhttp://data.seoul.go.kr/dataList/OA-15059/S/1/datasetView.do

Alerts

도로기능별 구분명 is highly overall correlated with 도로기능별 구분코드High correlation
도로기능별 구분코드 is highly overall correlated with 도로기능별 구분명High correlation
도로축코드 has unique valuesUnique
도로명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 06:57:57.724467
Analysis finished2023-12-11 06:57:58.270677
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도로축코드
Real number (ℝ)

UNIQUE 

Distinct487
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean258.92402
Minimum1
Maximum536
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2023-12-11T15:57:58.374225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25.3
Q1131.5
median257
Q3384.5
95-th percentile497.7
Maximum536
Range535
Interquartile range (IQR)253

Descriptive statistics

Standard deviation150.58231
Coefficient of variation (CV)0.58156949
Kurtosis-1.1496339
Mean258.92402
Median Absolute Deviation (MAD)127
Skewness0.050766566
Sum126096
Variance22675.033
MonotonicityNot monotonic
2023-12-11T15:57:58.860096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
536 1
 
0.2%
157 1
 
0.2%
154 1
 
0.2%
153 1
 
0.2%
523 1
 
0.2%
152 1
 
0.2%
148 1
 
0.2%
146 1
 
0.2%
144 1
 
0.2%
140 1
 
0.2%
Other values (477) 477
97.9%
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 (%)
536 1
0.2%
533 1
0.2%
532 1
0.2%
531 1
0.2%
527 1
0.2%
525 1
0.2%
524 1
0.2%
523 1
0.2%
522 1
0.2%
521 1
0.2%

도로명
Text

UNIQUE 

Distinct487
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-11T15:57:59.259551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length4.1991786
Min length2

Characters and Unicode

Total characters2045
Distinct characters264
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique487 ?
Unique (%)100.0%

Sample

1st row강남순환로
2nd row강변북로
3rd row경부고속도로
4th row경인고속도로
5th row내부순환로
ValueCountFrequency (%)
강남순환로 1
 
0.2%
상암로79길 1
 
0.2%
매봉산로 1
 
0.2%
망원로 1
 
0.2%
망우로36길 1
 
0.2%
망우로21길 1
 
0.2%
마천로 1
 
0.2%
마장로1길 1
 
0.2%
마방로 1
 
0.2%
디지털로9길 1
 
0.2%
Other values (477) 477
97.9%
2023-12-11T15:57:59.849671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 475
23.2%
길 116
 
5.7%
대 58
 
2.8%
1 40
 
2.0%
동 36
 
1.8%
산 32
 
1.6%
천 31
 
1.5%
2 30
 
1.5%
5 24
 
1.2%
양 22
 
1.1%
Other values (254) 1181
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1844
90.2%
Decimal Number 196
 
9.6%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 475
25.8%
길 116
 
6.3%
대 58
 
3.1%
동 36
 
2.0%
산 32
 
1.7%
천 31
 
1.7%
양 22
 
1.2%
서 19
 
1.0%
사 19
 
1.0%
문 19
 
1.0%
Other values (241) 1017
55.2%
Decimal Number
ValueCountFrequency (%)
1 40
20.4%
2 30
15.3%
5 24
12.2%
7 20
10.2%
6 17
8.7%
4 17
8.7%
9 13
 
6.6%
3 13
 
6.6%
8 12
 
6.1%
0 10
 
5.1%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1844
90.2%
Common 201
 
9.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 475
25.8%
길 116
 
6.3%
대 58
 
3.1%
동 36
 
2.0%
산 32
 
1.7%
천 31
 
1.7%
양 22
 
1.2%
서 19
 
1.0%
사 19
 
1.0%
문 19
 
1.0%
Other values (241) 1017
55.2%
Common
ValueCountFrequency (%)
1 40
19.9%
2 30
14.9%
5 24
11.9%
7 20
10.0%
6 17
8.5%
4 17
8.5%
9 13
 
6.5%
3 13
 
6.5%
8 12
 
6.0%
0 10
 
5.0%
Other values (3) 5
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1844
90.2%
ASCII 201
 
9.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 475
25.8%
길 116
 
6.3%
대 58
 
3.1%
동 36
 
2.0%
산 32
 
1.7%
천 31
 
1.7%
양 22
 
1.2%
서 19
 
1.0%
사 19
 
1.0%
문 19
 
1.0%
Other values (241) 1017
55.2%
ASCII
ValueCountFrequency (%)
1 40
19.9%
2 30
14.9%
5 24
11.9%
7 20
10.0%
6 17
8.5%
4 17
8.5%
9 13
 
6.5%
3 13
 
6.5%
8 12
 
6.0%
0 10
 
5.0%
Other values (3) 5
 
2.5%

도로기능별 구분코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
5
216 
4
183 
3
77 
2
 
11

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
5 216
44.4%
4 183
37.6%
3 77
 
15.8%
2 11
 
2.3%

Length

2023-12-11T15:58:00.003678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:58:00.161284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 216
44.4%
4 183
37.6%
3 77
 
15.8%
2 11
 
2.3%

도로기능별 구분명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
기타도로
216 
보조간선도로
183 
주간선도로
77 
도시고속도로
 
11

Length

Max length6
Median length5
Mean length4.9548255
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타도로 216
44.4%
보조간선도로 183
37.6%
주간선도로 77
 
15.8%
도시고속도로 11
 
2.3%

Length

2023-12-11T15:58:00.313397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:58:00.451861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타도로 216
44.4%
보조간선도로 183
37.6%
주간선도로 77
 
15.8%
도시고속도로 11
 
2.3%

Interactions

2023-12-11T15:57:57.968553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T15:58:00.531605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로축코드도로기능별 구분코드도로기능별 구분명
도로축코드1.0000.0000.000
도로기능별 구분코드0.0001.0001.000
도로기능별 구분명0.0001.0001.000
2023-12-11T15:58:00.633336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로기능별 구분명도로기능별 구분코드
도로기능별 구분명1.0001.000
도로기능별 구분코드1.0001.000
2023-12-11T15:58:00.731932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로축코드도로기능별 구분코드도로기능별 구분명
도로축코드1.0000.0000.000
도로기능별 구분코드0.0001.0001.000
도로기능별 구분명0.0001.0001.000

Missing values

2023-12-11T15:57:58.124233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T15:57:58.228821image/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

도로축코드도로명도로기능별 구분코드도로기능별 구분명
0536강남순환로2도시고속도로
114강변북로2도시고속도로
226경부고속도로2도시고속도로
327경인고속도로2도시고속도로
479내부순환로2도시고속도로
5124동부간선도로2도시고속도로
6200북부간선도로2도시고속도로
7204분당수서로2도시고속도로
8241서부간선도로2도시고속도로
9364올림픽대로2도시고속도로
도로축코드도로명도로기능별 구분코드도로기능별 구분명
477490허준로5기타도로
478493혜화로5기타도로
479495홍릉로5기타도로
480497홍제천로5기타도로
481498화계사길5기타도로
482501화랑로32길5기타도로
483503회기로5길5기타도로
484506효창원로5기타도로
485508휘경로5기타도로
486509희우정로5기타도로