Overview

Dataset statistics

Number of variables18
Number of observations543
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory79.1 KiB
Average record size in memory149.2 B

Variable types

Categorical8
Text4
DateTime2
Numeric4

Dataset

Description광진구 도로명 현황 자료도로명 도로관할구역(광역구분) 도로명, 영문도로명, 부여사유, 부여권자, 부여일자, 고시일자, 시점및종점 , 도로폭, 도로고시길이, 기초간격 등
Author서울특별시 광진구
URLhttps://www.data.go.kr/data/15036739/fileData.do

Alerts

시군구 has constant value ""Constant
종속구분 has constant value ""Constant
부여방식 is highly overall correlated with 도로고시길이 and 5 other fieldsHigh correlation
부여사유 is highly overall correlated with 광역구분 and 1 other fieldsHigh correlation
위계 is highly overall correlated with 도로폭 and 6 other fieldsHigh correlation
기초간격 is highly overall correlated with 도로폭 and 6 other fieldsHigh correlation
부여사유설명 is highly overall correlated with 도로폭 and 7 other fieldsHigh correlation
도로폭 is highly overall correlated with 도로고시길이 and 5 other fieldsHigh correlation
도로고시길이 is highly overall correlated with 도로폭 and 6 other fieldsHigh correlation
도로물리길이 is highly overall correlated with 도로폭 and 6 other fieldsHigh correlation
광역구분 is highly overall correlated with 도로폭 and 7 other fieldsHigh correlation
위계 is highly imbalanced (84.4%)Imbalance
광역구분 is highly imbalanced (88.9%)Imbalance
기초간격 is highly imbalanced (74.7%)Imbalance
부여방식 is highly imbalanced (59.9%)Imbalance
도로명 has unique valuesUnique
영문도로명 has unique valuesUnique
도로물리길이 has unique valuesUnique
도로구간일련번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 17:48:47.622046
Analysis finished2024-03-14 17:48:54.835360
Duration7.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
광진구
543 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광진구 543
100.0%

Length

2024-03-15T02:48:55.061981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:48:55.408001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광진구 543
100.0%

위계
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
길
522 
로
 
20
대로
 
1

Length

Max length2
Median length1
Mean length1.0018416
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row대로
2nd row로
3rd row로
4th row로
5th row로

Common Values

ValueCountFrequency (%)
길 522
96.1%
로 20
 
3.7%
대로 1
 
0.2%

Length

2024-03-15T02:48:55.736845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:48:56.059936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
길 522
96.1%
로 20
 
3.7%
대로 1
 
0.2%

광역구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
시군구
531 
행안부
 
6
시도
 
6

Length

Max length3
Median length3
Mean length2.9889503
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row행안부
2nd row시도
3rd row시군구
4th row시도
5th row시군구

Common Values

ValueCountFrequency (%)
시군구 531
97.8%
행안부 6
 
1.1%
시도 6
 
1.1%

Length

2024-03-15T02:48:56.412730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:48:56.977266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시군구 531
97.8%
행안부 6
 
1.1%
시도 6
 
1.1%

종속구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
주도로
543 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주도로 543
100.0%

Length

2024-03-15T02:48:57.307012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:48:57.610263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주도로 543
100.0%

도로명
Text

UNIQUE 

Distinct543
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-03-15T02:48:58.638606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.4714549
Min length3

Characters and Unicode

Total characters3514
Distinct characters63
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique543 ?
Unique (%)100.0%

Sample

1st row천호대로
2nd row강변북로
3rd row강변역로
4th row광나루로
5th row광장로
ValueCountFrequency (%)
천호대로 1
 
0.2%
영화사로13길 1
 
0.2%
아차산로78가길 1
 
0.2%
아차산로76길 1
 
0.2%
아차산로76가길 1
 
0.2%
아차산로75길 1
 
0.2%
아차산로73길 1
 
0.2%
아차산로70길 1
 
0.2%
아차산로69길 1
 
0.2%
아차산로66길 1
 
0.2%
Other values (533) 533
98.2%
2024-03-15T02:49:00.187633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 540
 
15.4%
길 522
 
14.9%
1 171
 
4.9%
3 140
 
4.0%
2 139
 
4.0%
4 124
 
3.5%
동 110
 
3.1%
자 94
 
2.7%
5 93
 
2.6%
산 90
 
2.6%
Other values (53) 1491
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2541
72.3%
Decimal Number 973
 
27.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 540
21.3%
길 522
20.5%
동 110
 
4.3%
자 94
 
3.7%
산 90
 
3.5%
양 78
 
3.1%
나 61
 
2.4%
섬 57
 
2.2%
능 57
 
2.2%
뚝 57
 
2.2%
Other values (43) 875
34.4%
Decimal Number
ValueCountFrequency (%)
1 171
17.6%
3 140
14.4%
2 139
14.3%
4 124
12.7%
5 93
9.6%
6 85
8.7%
0 61
 
6.3%
8 60
 
6.2%
7 59
 
6.1%
9 41
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2541
72.3%
Common 973
 
27.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 540
21.3%
길 522
20.5%
동 110
 
4.3%
자 94
 
3.7%
산 90
 
3.5%
양 78
 
3.1%
나 61
 
2.4%
섬 57
 
2.2%
능 57
 
2.2%
뚝 57
 
2.2%
Other values (43) 875
34.4%
Common
ValueCountFrequency (%)
1 171
17.6%
3 140
14.4%
2 139
14.3%
4 124
12.7%
5 93
9.6%
6 85
8.7%
0 61
 
6.3%
8 60
 
6.2%
7 59
 
6.1%
9 41
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2541
72.3%
ASCII 973
 
27.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 540
21.3%
길 522
20.5%
동 110
 
4.3%
자 94
 
3.7%
산 90
 
3.5%
양 78
 
3.1%
나 61
 
2.4%
섬 57
 
2.2%
능 57
 
2.2%
뚝 57
 
2.2%
Other values (43) 875
34.4%
ASCII
ValueCountFrequency (%)
1 171
17.6%
3 140
14.4%
2 139
14.3%
4 124
12.7%
5 93
9.6%
6 85
8.7%
0 61
 
6.3%
8 60
 
6.2%
7 59
 
6.1%
9 41
 
4.2%

영문도로명
Text

UNIQUE 

Distinct543
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-03-15T02:49:01.410915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length18.191529
Min length7

Characters and Unicode

Total characters9878
Distinct characters44
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique543 ?
Unique (%)100.0%

Sample

1st rowCheonho-daero
2nd rowGangbyeonbuk-ro
3rd rowGangbyeonyeok-ro
4th rowGwangnaru-ro
5th rowGwangjang-ro
ValueCountFrequency (%)
jayang-ro 60
 
5.6%
neungdong-ro 57
 
5.4%
ttukseom-ro 57
 
5.4%
achasan-ro 52
 
4.9%
dongil-ro 51
 
4.8%
gingorang-ro 44
 
4.1%
cheonho-daero 40
 
3.8%
yongmasan-ro 38
 
3.6%
gwangnaru-ro 37
 
3.5%
jayangbeonyeong-ro 17
 
1.6%
Other values (207) 609
57.3%
2024-03-15T02:49:02.886184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1062
 
10.8%
g 1057
 
10.7%
o 970
 
9.8%
n 738
 
7.5%
a 678
 
6.9%
i 652
 
6.6%
r 626
 
6.3%
l 576
 
5.8%
519
 
5.3%
e 282
 
2.9%
Other values (34) 2718
27.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6781
68.6%
Dash Punctuation 1062
 
10.8%
Decimal Number 973
 
9.9%
Uppercase Letter 543
 
5.5%
Space Separator 519
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
g 1057
15.6%
o 970
14.3%
n 738
10.9%
a 678
10.0%
i 652
9.6%
r 626
9.2%
l 576
8.5%
e 282
 
4.2%
u 206
 
3.0%
s 173
 
2.6%
Other values (11) 823
12.1%
Uppercase Letter
ValueCountFrequency (%)
G 127
23.4%
J 79
14.5%
D 60
11.0%
T 57
10.5%
N 57
10.5%
Y 55
10.1%
A 52
9.6%
C 40
 
7.4%
M 14
 
2.6%
W 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 171
17.6%
3 140
14.4%
2 139
14.3%
4 124
12.7%
5 93
9.6%
6 85
8.7%
0 61
 
6.3%
8 60
 
6.2%
7 59
 
6.1%
9 41
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 1062
100.0%
Space Separator
ValueCountFrequency (%)
519
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7324
74.1%
Common 2554
 
25.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
g 1057
14.4%
o 970
13.2%
n 738
10.1%
a 678
9.3%
i 652
8.9%
r 626
8.5%
l 576
7.9%
e 282
 
3.9%
u 206
 
2.8%
s 173
 
2.4%
Other values (22) 1366
18.7%
Common
ValueCountFrequency (%)
- 1062
41.6%
519
20.3%
1 171
 
6.7%
3 140
 
5.5%
2 139
 
5.4%
4 124
 
4.9%
5 93
 
3.6%
6 85
 
3.3%
0 61
 
2.4%
8 60
 
2.3%
Other values (2) 100
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9878
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1062
 
10.8%
g 1057
 
10.7%
o 970
 
9.8%
n 738
 
7.5%
a 678
 
6.9%
i 652
 
6.6%
r 626
 
6.3%
l 576
 
5.8%
519
 
5.3%
e 282
 
2.9%
Other values (34) 2718
27.5%

고시일자
Date

Distinct10
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
Minimum2009-07-10 00:00:00
Maximum2023-01-19 00:00:00
2024-03-15T02:49:03.296705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:49:03.566907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

시점
Text

Distinct538
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-03-15T02:49:04.955247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length9.6169429
Min length7

Characters and Unicode

Total characters5222
Distinct characters82
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique533 ?
Unique (%)98.2%

Sample

1st row광진구 중곡동 680-20
2nd row마포구 상암동 496-106(가양대교)
3rd row구의동 245-8(광진우체국)
4th row성동구 성수동1가 671(성동교남단)
5th row광장동 401-17(양진중학교)
ValueCountFrequency (%)
중곡동 156
 
14.1%
자양동 146
 
13.2%
구의동 105
 
9.5%
군자동 51
 
4.6%
화양동 37
 
3.3%
광장동 26
 
2.3%
능동 15
 
1.4%
광진구 9
 
0.8%
성동구 4
 
0.4%
서울특별시 3
 
0.3%
Other values (539) 556
50.2%
2024-03-15T02:49:06.878241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
565
 
10.8%
동 548
 
10.5%
- 535
 
10.2%
1 402
 
7.7%
2 362
 
6.9%
3 239
 
4.6%
4 234
 
4.5%
5 234
 
4.5%
6 228
 
4.4%
자 200
 
3.8%
Other values (72) 1675
32.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2320
44.4%
Other Letter 1763
33.8%
Space Separator 565
 
10.8%
Dash Punctuation 535
 
10.2%
Open Punctuation 18
 
0.3%
Close Punctuation 18
 
0.3%
Uppercase Letter 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 548
31.1%
자 200
 
11.3%
양 188
 
10.7%
중 160
 
9.1%
곡 158
 
9.0%
구 122
 
6.9%
의 106
 
6.0%
군 51
 
2.9%
광 39
 
2.2%
화 37
 
2.1%
Other values (55) 154
 
8.7%
Decimal Number
ValueCountFrequency (%)
1 402
17.3%
2 362
15.6%
3 239
10.3%
4 234
10.1%
5 234
10.1%
6 228
9.8%
7 170
7.3%
9 155
 
6.7%
8 154
 
6.6%
0 142
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
565
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 535
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3457
66.2%
Hangul 1763
33.8%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 548
31.1%
자 200
 
11.3%
양 188
 
10.7%
중 160
 
9.1%
곡 158
 
9.0%
구 122
 
6.9%
의 106
 
6.0%
군 51
 
2.9%
광 39
 
2.2%
화 37
 
2.1%
Other values (55) 154
 
8.7%
Common
ValueCountFrequency (%)
565
16.3%
- 535
15.5%
1 402
11.6%
2 362
10.5%
3 239
6.9%
4 234
6.8%
5 234
6.8%
6 228
6.6%
7 170
 
4.9%
9 155
 
4.5%
Other values (5) 333
9.6%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3459
66.2%
Hangul 1763
33.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
565
16.3%
- 535
15.5%
1 402
11.6%
2 362
10.5%
3 239
6.9%
4 234
6.8%
5 234
6.8%
6 228
6.6%
7 170
 
4.9%
9 155
 
4.5%
Other values (7) 335
9.7%
Hangul
ValueCountFrequency (%)
동 548
31.1%
자 200
 
11.3%
양 188
 
10.7%
중 160
 
9.1%
곡 158
 
9.0%
구 122
 
6.9%
의 106
 
6.0%
군 51
 
2.9%
광 39
 
2.2%
화 37
 
2.1%
Other values (55) 154
 
8.7%

종점
Text

Distinct523
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-03-15T02:49:08.783023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length9.6298343
Min length6

Characters and Unicode

Total characters5229
Distinct characters90
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique504 ?
Unique (%)92.8%

Sample

1st row광진구 광장동 557-1
2nd row광진구 광장동 594(광장동 시계)
3rd row구의동 658(세양아파트 입구)
4th row광진구 광장동 575-3(올림픽대교남단)
5th row광장동 334-12(광장육교)
ValueCountFrequency (%)
중곡동 161
 
14.5%
자양동 141
 
12.7%
구의동 106
 
9.6%
군자동 50
 
4.5%
화양동 37
 
3.3%
광장동 30
 
2.7%
능동 15
 
1.4%
광진구 11
 
1.0%
서울특별시 3
 
0.3%
533-2 3
 
0.3%
Other values (528) 552
49.8%
2024-03-15T02:49:10.860907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
567
 
10.8%
동 547
 
10.5%
- 530
 
10.1%
1 419
 
8.0%
2 336
 
6.4%
5 251
 
4.8%
3 250
 
4.8%
4 234
 
4.5%
6 222
 
4.2%
자 193
 
3.7%
Other values (80) 1680
32.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2329
44.5%
Other Letter 1766
33.8%
Space Separator 567
 
10.8%
Dash Punctuation 530
 
10.1%
Open Punctuation 17
 
0.3%
Close Punctuation 17
 
0.3%
Uppercase Letter 2
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 547
31.0%
자 193
 
10.9%
양 181
 
10.2%
곡 162
 
9.2%
중 162
 
9.2%
구 123
 
7.0%
의 108
 
6.1%
군 51
 
2.9%
광 43
 
2.4%
화 37
 
2.1%
Other values (63) 159
 
9.0%
Decimal Number
ValueCountFrequency (%)
1 419
18.0%
2 336
14.4%
5 251
10.8%
3 250
10.7%
4 234
10.0%
6 222
9.5%
7 179
7.7%
9 155
 
6.7%
0 149
 
6.4%
8 134
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
567
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 530
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Other Symbol
ValueCountFrequency (%)
ⓐ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3461
66.2%
Hangul 1766
33.8%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 547
31.0%
자 193
 
10.9%
양 181
 
10.2%
곡 162
 
9.2%
중 162
 
9.2%
구 123
 
7.0%
의 108
 
6.1%
군 51
 
2.9%
광 43
 
2.4%
화 37
 
2.1%
Other values (63) 159
 
9.0%
Common
ValueCountFrequency (%)
567
16.4%
- 530
15.3%
1 419
12.1%
2 336
9.7%
5 251
7.3%
3 250
7.2%
4 234
6.8%
6 222
 
6.4%
7 179
 
5.2%
9 155
 
4.5%
Other values (5) 318
9.2%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3462
66.2%
Hangul 1766
33.8%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
567
16.4%
- 530
15.3%
1 419
12.1%
2 336
9.7%
5 251
7.3%
3 250
7.2%
4 234
6.8%
6 222
 
6.4%
7 179
 
5.2%
9 155
 
4.5%
Other values (6) 319
9.2%
Hangul
ValueCountFrequency (%)
동 547
31.0%
자 193
 
10.9%
양 181
 
10.2%
곡 162
 
9.2%
중 162
 
9.2%
구 123
 
7.0%
의 108
 
6.1%
군 51
 
2.9%
광 43
 
2.4%
화 37
 
2.1%
Other values (63) 159
 
9.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓐ 1
100.0%

도로폭
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4714549
Minimum2
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2024-03-15T02:49:11.280423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q16
median7
Q37.5
95-th percentile13
Maximum52
Range50
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation4.7694654
Coefficient of variation (CV)0.63835832
Kurtosis29.502008
Mean7.4714549
Median Absolute Deviation (MAD)1
Skewness4.8450336
Sum4057
Variance22.7478
MonotonicityNot monotonic
2024-03-15T02:49:11.686660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
7 162
29.8%
6 111
20.4%
5 81
14.9%
9 48
 
8.8%
4 47
 
8.7%
8 41
 
7.6%
10 7
 
1.3%
11 7
 
1.3%
3 5
 
0.9%
15 5
 
0.9%
Other values (20) 29
 
5.3%
ValueCountFrequency (%)
2 1
 
0.2%
3 5
 
0.9%
4 47
 
8.7%
5 81
14.9%
6 111
20.4%
7 162
29.8%
8 41
 
7.6%
9 48
 
8.8%
10 7
 
1.3%
11 7
 
1.3%
ValueCountFrequency (%)
52 1
0.2%
39 1
0.2%
38 1
0.2%
37 1
0.2%
35 1
0.2%
34 1
0.2%
32 1
0.2%
29 1
0.2%
28 1
0.2%
27 2
0.4%

도로고시길이
Real number (ℝ)

HIGH CORRELATION 

Distinct336
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean721.54144
Minimum31
Maximum50356
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2024-03-15T02:49:12.031092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile103
Q1171
median251
Q3395.5
95-th percentile802.6
Maximum50356
Range50325
Interquartile range (IQR)224.5

Descriptive statistics

Standard deviation3366.8808
Coefficient of variation (CV)4.6662335
Kurtosis120.32159
Mean721.54144
Median Absolute Deviation (MAD)101
Skewness10.283589
Sum391797
Variance11335886
MonotonicityNot monotonic
2024-03-15T02:49:12.459068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
245 9
 
1.7%
111 7
 
1.3%
243 7
 
1.3%
230 5
 
0.9%
171 5
 
0.9%
418 5
 
0.9%
213 4
 
0.7%
235 4
 
0.7%
132 4
 
0.7%
202 4
 
0.7%
Other values (326) 489
90.1%
ValueCountFrequency (%)
31 1
 
0.2%
52 1
 
0.2%
56 1
 
0.2%
76 1
 
0.2%
78 1
 
0.2%
79 3
0.6%
80 3
0.6%
81 1
 
0.2%
87 2
0.4%
90 2
0.4%
ValueCountFrequency (%)
50356 1
0.2%
31688 1
0.2%
28595 1
0.2%
27950 1
0.2%
23700 1
0.2%
15510 1
0.2%
12710 1
0.2%
7303 1
0.2%
7050 1
0.2%
6750 1
0.2%

도로물리길이
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct543
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean388.23293
Minimum51.694
Maximum6826.086
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2024-03-15T02:49:12.819789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51.694
5-th percentile103.3893
Q1171.791
median251.984
Q3395.596
95-th percentile771.1005
Maximum6826.086
Range6774.392
Interquartile range (IQR)223.805

Descriptive statistics

Standard deviation643.16113
Coefficient of variation (CV)1.6566372
Kurtosis54.683503
Mean388.23293
Median Absolute Deviation (MAD)100.587
Skewness6.8391758
Sum210810.48
Variance413656.24
MonotonicityNot monotonic
2024-03-15T02:49:13.221756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3820.001 1
 
0.2%
212.678 1
 
0.2%
139.636 1
 
0.2%
295.775 1
 
0.2%
103.25 1
 
0.2%
219.701 1
 
0.2%
489.871 1
 
0.2%
488.715 1
 
0.2%
536.026 1
 
0.2%
6818.984 1
 
0.2%
Other values (533) 533
98.2%
ValueCountFrequency (%)
51.694 1
0.2%
56.221 1
0.2%
75.513 1
0.2%
78.329 1
0.2%
78.955 1
0.2%
79.321 1
0.2%
79.622 1
0.2%
79.74 1
0.2%
80.193 1
0.2%
81.067 1
0.2%
ValueCountFrequency (%)
6826.086 1
0.2%
6818.984 1
0.2%
5761.108 1
0.2%
4642.292 1
0.2%
4509.589 1
0.2%
3820.001 1
0.2%
3491.494 1
0.2%
3282.968 1
0.2%
2896.502 1
0.2%
2818.163 1
0.2%

기초간격
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
10
520 
20
 
23

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20
2nd row20
3rd row20
4th row20
5th row20

Common Values

ValueCountFrequency (%)
10 520
95.8%
20 23
 
4.2%

Length

2024-03-15T02:49:13.527878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:49:13.699163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 520
95.8%
20 23
 
4.2%

부여사유
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
지명·자연마을이름
290 
행정구역 명칭
230 
종교
 
17
기타
 
4
역사적인물·기념
 
2

Length

Max length9
Median length9
Mean length7.878453
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row지명·자연마을이름
3rd row지명·자연마을이름
4th row지명·자연마을이름
5th row행정구역 명칭

Common Values

ValueCountFrequency (%)
지명·자연마을이름 290
53.4%
행정구역 명칭 230
42.4%
종교 17
 
3.1%
기타 4
 
0.7%
역사적인물·기념 2
 
0.4%

Length

2024-03-15T02:49:13.976122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:49:14.182544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지명·자연마을이름 290
37.5%
행정구역 230
29.8%
명칭 230
29.8%
종교 17
 
2.2%
기타 4
 
0.5%
역사적인물·기념 2
 
0.3%

부여방식
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
일련번호
427 
기타
93 
고유명사
 
20
복합명사
 
2
방위
 
1

Length

Max length4
Median length4
Mean length3.6537753
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
일련번호 427
78.6%
기타 93
 
17.1%
고유명사 20
 
3.7%
복합명사 2
 
0.4%
방위 1
 
0.2%

Length

2024-03-15T02:49:14.590683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:49:14.942565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일련번호 427
78.6%
기타 93
 
17.1%
고유명사 20
 
3.7%
복합명사 2
 
0.4%
방위 1
 
0.2%

부여일자
Date

Distinct10
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
Minimum2009-06-16 00:00:00
Maximum2021-02-26 00:00:00
2024-03-15T02:49:15.296344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:49:15.656187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

부여사유설명
Categorical

HIGH CORRELATION 

Distinct39
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
자양로에서 분기되는 도로
59 
뚝섬로에서 분기되는 도로
56 
능동로에서 분기되는 도로
56 
아차산로에서 분기되는 도로
51 
동일로에서 분기되는 도로
50 
Other values (34)
271 

Length

Max length61
Median length43
Mean length14.047882
Min length10

Unique

Unique20 ?
Unique (%)3.7%

Sample

1st row행정구역 명칭 사용
2nd row한강의 북쪽 도로를 뜻함
3rd row강변역이란 시설물이 있어 주민이 인지하기 쉬운 도로명임
4th row옛날 광나루가 있던 곳을 연결하는 도로
5th row광장동을 가로지르는 도로로서 “동”명칭을 생략하여 도로명 부여

Common Values

ValueCountFrequency (%)
자양로에서 분기되는 도로 59
10.9%
뚝섬로에서 분기되는 도로 56
10.3%
능동로에서 분기되는 도로 56
10.3%
아차산로에서 분기되는 도로 51
9.4%
동일로에서 분기되는 도로 50
9.2%
긴고랑로에서 분기되는 도로 43
7.9%
천호대로에서 분기되는 도로 39
 
7.2%
용마산로에서 분기되는 도로 37
 
6.8%
광나루로에서 분기되는 도로 36
 
6.6%
자양번영로에서 분기되는 도로 16
 
2.9%
Other values (29) 100
18.4%

Length

2024-03-15T02:49:16.085793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도로 522
30.7%
분기되는 519
30.5%
자양로에서 59
 
3.5%
뚝섬로에서 56
 
3.3%
능동로에서 56
 
3.3%
아차산로에서 51
 
3.0%
동일로에서 50
 
2.9%
긴고랑로에서 43
 
2.5%
천호대로에서 39
 
2.3%
용마산로에서 37
 
2.2%
Other values (112) 270
15.9%

도로구간일련번호
Real number (ℝ)

UNIQUE 

Distinct543
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean459.61878
Minimum3
Maximum3223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2024-03-15T02:49:16.563294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile31.1
Q1140.5
median281
Q3420.5
95-th percentile2710.8
Maximum3223
Range3220
Interquartile range (IQR)280

Descriptive statistics

Standard deviation679.14095
Coefficient of variation (CV)1.4776179
Kurtosis6.8432574
Mean459.61878
Median Absolute Deviation (MAD)140
Skewness2.8422168
Sum249573
Variance461232.42
MonotonicityNot monotonic
2024-03-15T02:49:16.923709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 1
 
0.2%
144 1
 
0.2%
384 1
 
0.2%
383 1
 
0.2%
387 1
 
0.2%
446 1
 
0.2%
372 1
 
0.2%
142 1
 
0.2%
2729 1
 
0.2%
2935 1
 
0.2%
Other values (533) 533
98.2%
ValueCountFrequency (%)
3 1
0.2%
4 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
11 1
0.2%
12 1
0.2%
13 1
0.2%
ValueCountFrequency (%)
3223 1
0.2%
3203 1
0.2%
3103 1
0.2%
2944 1
0.2%
2935 1
0.2%
2737 1
0.2%
2735 1
0.2%
2734 1
0.2%
2733 1
0.2%
2732 1
0.2%

Interactions

2024-03-15T02:48:51.988476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:49.044180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:50.085001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:51.055993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:52.354666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:49.300229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:50.337319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:51.241684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:52.669353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:49.556878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:50.580963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:51.417210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:53.129567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:49.823983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:50.886498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:51.604748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:49:17.145685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위계광역구분고시일자도로폭도로고시길이도로물리길이기초간격부여사유부여방식부여일자부여사유설명도로구간일련번호
위계1.0000.8360.9690.9920.8780.9600.7090.5320.6910.9690.9400.148
광역구분0.8361.0000.9240.8670.9460.8980.4620.6430.6270.9530.9960.545
고시일자0.9690.9241.0000.7990.9310.8190.9970.8320.9570.9960.9670.629
도로폭0.9920.8670.7991.0000.7760.9060.7260.6000.6420.8320.9410.300
도로고시길이0.8780.9460.9310.7761.0000.8620.8860.6600.7540.9590.9910.537
도로물리길이0.9600.8980.8190.9060.8621.0000.8600.5750.7860.8880.9840.454
기초간격0.7090.4620.9970.7260.8860.8601.0000.4090.8320.9971.0000.469
부여사유0.5320.6430.8320.6000.6600.5750.4091.0000.5300.8840.9960.316
부여방식0.6910.6270.9570.6420.7540.7860.8320.5301.0000.9590.9270.648
부여일자0.9690.9530.9960.8320.9590.8880.9970.8840.9591.0000.9910.630
부여사유설명0.9400.9960.9670.9410.9910.9841.0000.9960.9270.9911.0000.619
도로구간일련번호0.1480.5450.6290.3000.5370.4540.4690.3160.6480.6300.6191.000
2024-03-15T02:49:17.460837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부여방식부여사유위계광역구분기초간격부여사유설명
부여방식1.0000.2220.6690.5860.9520.711
부여사유0.2221.0000.4710.6070.4960.942
위계0.6690.4711.0000.5120.9530.734
광역구분0.5860.6070.5121.0000.7130.898
기초간격0.9520.4960.9530.7131.0000.965
부여사유설명0.7110.9420.7340.8980.9651.000
2024-03-15T02:49:17.760500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로폭도로고시길이도로물리길이도로구간일련번호위계광역구분기초간격부여사유부여방식부여사유설명
도로폭1.0000.5840.577-0.2520.8980.5940.7590.4150.4580.701
도로고시길이0.5841.0000.993-0.1860.8430.9520.7060.4830.5930.901
도로물리길이0.5770.9931.000-0.1860.7590.6310.8870.3770.6040.858
도로구간일련번호-0.252-0.186-0.1861.0000.0880.3870.3580.1360.3220.257
위계0.8980.8430.7590.0881.0000.5120.9530.4710.6690.734
광역구분0.5940.9520.6310.3870.5121.0000.7130.6070.5860.898
기초간격0.7590.7060.8870.3580.9530.7131.0000.4960.9520.965
부여사유0.4150.4830.3770.1360.4710.6070.4961.0000.2220.942
부여방식0.4580.5930.6040.3220.6690.5860.9520.2221.0000.711
부여사유설명0.7010.9010.8580.2570.7340.8980.9650.9420.7111.000

Missing values

2024-03-15T02:48:53.694443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:48:54.545482image/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

시군구위계광역구분종속구분도로명영문도로명고시일자시점종점도로폭도로고시길이도로물리길이기초간격부여사유부여방식부여일자부여사유설명도로구간일련번호
0광진구대로행안부주도로천호대로Cheonho-daero2010-03-15광진구 중곡동 680-20광진구 광장동 557-152155103820.00120기타고유명사2010-05-07행정구역 명칭 사용3
1광진구로시도주도로강변북로Gangbyeonbuk-ro2009-07-10마포구 상암동 496-106(가양대교)광진구 광장동 594(광장동 시계)20279506818.98420지명·자연마을이름고유명사2009-07-01한강의 북쪽 도로를 뜻함2935
2광진구로시군구주도로강변역로Gangbyeonyeok-ro2009-10-28구의동 245-8(광진우체국)구의동 658(세양아파트 입구)3911261126.33220지명·자연마을이름고유명사2009-10-28강변역이란 시설물이 있어 주민이 인지하기 쉬운 도로명임19
3광진구로시도주도로광나루로Gwangnaru-ro2009-07-10성동구 성수동1가 671(성동교남단)광진구 광장동 575-3(올림픽대교남단)3862543491.49420지명·자연마을이름고유명사2009-07-01옛날 광나루가 있던 곳을 연결하는 도로7
4광진구로시군구주도로광장로Gwangjang-ro2009-10-28광장동 401-17(양진중학교)광장동 334-12(광장육교)15907906.63720행정구역 명칭고유명사2009-10-28광장동을 가로지르는 도로로서 “동”명칭을 생략하여 도로명 부여15
5광진구로시군구주도로구의강변로Guuigangbyeon-ro2010-06-03자양동 813-0(구의 빗물펌프장)구의동 199-18(삼성쉐르빌ⓐ)2310901090.39420지명·자연마을이름고유명사2010-05-28구의동에 강변역과 한강변이 인접한 도로2703
6광진구로시군구주도로구의로Guui-ro2009-10-28구의동 244-50(KT광진지사)구의동 228-1(구의시장앞)15767767.22620행정구역 명칭고유명사2009-10-28구의동의 중심이 되는 도로이며 주민이 인지가 쉬운 도로명임16
7광진구로시도주도로구천면로Gucheonmyeon-ro2010-04-22광진구 광장동 303-111(광진교남단)강동구 상일동444-1(상일동길)237050466.4220역사적인물·기념고유명사2010-04-19옛 지명인 구천면의 역사성 반영388
8광진구로시군구주도로군자로Gunja-ro2009-10-28군자동 503(구, 민중병원 앞)군자동 478-1(군자역)1119171916.88120행정구역 명칭고유명사2009-10-28군자동을 가로지르는 도로로서 “동”명칭을 생략하여 도로명 부여17
9광진구로시군구주도로긴고랑로Gingorang-ro2009-10-28중곡동 238-5(중곡펌프장)중곡동 143-146(아차산긴고랑입구)2221492148.8220지명·자연마을이름고유명사2009-10-28중곡동을 가로지르는 하천을 복개하여 만든 도로이며 주민들이 긴고랑길이라 부르던 익숙한 도로명으로 인지하기 쉬움13
시군구위계광역구분종속구분도로명영문도로명고시일자시점종점도로폭도로고시길이도로물리길이기초간격부여사유부여방식부여일자부여사유설명도로구간일련번호
533광진구길시군구주도로천호대로134길Cheonho-daero 134-gil2010-06-03구의동 73-6구의동 70-207372372.17510행정구역 명칭일련번호2010-05-28천호대로에서 분기되는 도로2722
534광진구길시군구주도로천호대로135길Cheonho-daero 135-gil2010-06-03구의동 57-79구의동 57-455149148.57910행정구역 명칭일련번호2010-05-28천호대로에서 분기되는 도로119
535광진구길시군구주도로천호대로136길Cheonho-daero 136-gil2010-06-03구의동 73-9구의동 64-188378378.03610행정구역 명칭일련번호2010-05-28천호대로에서 분기되는 도로194
536광진구길시군구주도로천호대로137길Cheonho-daero 137-gil2010-06-03구의동 57-30구의동 48-17358358.21810행정구역 명칭일련번호2010-05-28천호대로에서 분기되는 도로120
537광진구길시군구주도로천호대로138길Cheonho-daero 138-gil2010-06-03구의동 59-14구의동 61-215341339.03910행정구역 명칭일련번호2010-05-28천호대로에서 분기되는 도로191
538광진구길시군구주도로천호대로140길Cheonho-daero 140-gil2010-06-03광장동 396-13광장동 414-810510510.29710행정구역 명칭일련번호2010-05-28천호대로에서 분기되는 도로523
539광진구길시군구주도로천호대로141길Cheonho-daero 141-gil2010-06-03광장동 394-28광장동 394-27119119.3810행정구역 명칭일련번호2010-05-28천호대로에서 분기되는 도로135
540광진구길시군구주도로천호대로143길Cheonho-daero 143-gil2010-06-03광장동 246-11광장동 257-39215215.26410행정구역 명칭일련번호2010-05-28천호대로에서 분기되는 도로137
541광진구길시군구주도로천호대로145길Cheonho-daero 145-gil2010-06-03광장동 244-28광장동 245-1269796.90110행정구역 명칭일련번호2010-05-28천호대로에서 분기되는 도로145
542광진구길행안부주도로한강북자전거길Hangangbukjajeongeo-gil2021-02-26서울특별시 광진구 자양동 158-17천(2712)서울특별시 광진구 광장동 564천(3396)2503566826.08620지명·자연마을이름복합명사2021-02-26하천명(한강)과 방위(한강의 북쪽에 위치)를 활용하여 명명3203