Overview

Dataset statistics

Number of variables10
Number of observations27
Missing cells150
Missing cells (%)55.6%
Duplicate rows1
Duplicate rows (%)3.7%
Total size in memory2.2 KiB
Average record size in memory84.9 B

Variable types

Text10

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15282/F/1/datasetView.do

Alerts

Dataset has 1 (3.7%) duplicate rowsDuplicates
구분 has 15 (55.6%) missing valuesMissing
내부순환로 has 15 (55.6%) missing valuesMissing
강변북로 has 15 (55.6%) missing valuesMissing
북부간선도로 has 15 (55.6%) missing valuesMissing
올림픽대로 has 15 (55.6%) missing valuesMissing
동부간선도로 has 15 (55.6%) missing valuesMissing
분당수서로 has 15 (55.6%) missing valuesMissing
경부고속도로 has 15 (55.6%) missing valuesMissing
서부간선도로 has 15 (55.6%) missing valuesMissing
강남순환로 has 15 (55.6%) missing valuesMissing

Reproduction

Analysis started2023-12-11 09:18:11.554567
Analysis finished2023-12-11 09:18:12.651355
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T18:18:12.761214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.25
Min length2

Characters and Unicode

Total characters27
Distinct characters11
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

Unique12 ?
Unique (%)100.0%

Sample

1st row1월
2nd row2월
3rd row3월
4th row4월
5th row5월
ValueCountFrequency (%)
1월 1
8.3%
2월 1
8.3%
3월 1
8.3%
4월 1
8.3%
5월 1
8.3%
6월 1
8.3%
7월 1
8.3%
8월 1
8.3%
9월 1
8.3%
10월 1
8.3%
Other values (2) 2
16.7%
2023-12-11T18:18:13.078713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
월 12
44.4%
1 5
18.5%
2 2
 
7.4%
3 1
 
3.7%
4 1
 
3.7%
5 1
 
3.7%
6 1
 
3.7%
7 1
 
3.7%
8 1
 
3.7%
9 1
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15
55.6%
Other Letter 12
44.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
33.3%
2 2
 
13.3%
3 1
 
6.7%
4 1
 
6.7%
5 1
 
6.7%
6 1
 
6.7%
7 1
 
6.7%
8 1
 
6.7%
9 1
 
6.7%
0 1
 
6.7%
Other Letter
ValueCountFrequency (%)
월 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15
55.6%
Hangul 12
44.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5
33.3%
2 2
 
13.3%
3 1
 
6.7%
4 1
 
6.7%
5 1
 
6.7%
6 1
 
6.7%
7 1
 
6.7%
8 1
 
6.7%
9 1
 
6.7%
0 1
 
6.7%
Hangul
ValueCountFrequency (%)
월 12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
55.6%
Hangul 12
44.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
월 12
100.0%
ASCII
ValueCountFrequency (%)
1 5
33.3%
2 2
 
13.3%
3 1
 
6.7%
4 1
 
6.7%
5 1
 
6.7%
6 1
 
6.7%
7 1
 
6.7%
8 1
 
6.7%
9 1
 
6.7%
0 1
 
6.7%

내부순환로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T18:18:13.253632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters96
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row159,109
2nd row162,086
3rd row162,696
4th row160,920
5th row158,427
ValueCountFrequency (%)
159,109 1
8.3%
162,086 1
8.3%
162,696 1
8.3%
160,920 1
8.3%
158,427 1
8.3%
159,680 1
8.3%
156,055 1
8.3%
157,344 1
8.3%
159,052 1
8.3%
159,993 1
8.3%
Other values (2) 2
16.7%
2023-12-11T18:18:13.534770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
13.5%
, 12
12.5%
12
12.5%
6 12
12.5%
5 10
10.4%
9 9
9.4%
0 9
9.4%
2 7
7.3%
3 4
 
4.2%
8 3
 
3.1%
Other values (2) 5
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
75.0%
Other Punctuation 12
 
12.5%
Space Separator 12
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
18.1%
6 12
16.7%
5 10
13.9%
9 9
12.5%
0 9
12.5%
2 7
9.7%
3 4
 
5.6%
8 3
 
4.2%
4 3
 
4.2%
7 2
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
13.5%
, 12
12.5%
12
12.5%
6 12
12.5%
5 10
10.4%
9 9
9.4%
0 9
9.4%
2 7
7.3%
3 4
 
4.2%
8 3
 
3.1%
Other values (2) 5
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
13.5%
, 12
12.5%
12
12.5%
6 12
12.5%
5 10
10.4%
9 9
9.4%
0 9
9.4%
2 7
7.3%
3 4
 
4.2%
8 3
 
3.1%
Other values (2) 5
 
5.2%

강변북로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T18:18:13.702657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters96
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row244,834
2nd row253,010
3rd row255,960
4th row251,254
5th row247,928
ValueCountFrequency (%)
244,834 1
8.3%
253,010 1
8.3%
255,960 1
8.3%
251,254 1
8.3%
247,928 1
8.3%
253,718 1
8.3%
257,595 1
8.3%
255,978 1
8.3%
252,625 1
8.3%
245,772 1
8.3%
Other values (2) 2
16.7%
2023-12-11T18:18:14.013137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 17
17.7%
5 16
16.7%
, 12
12.5%
12
12.5%
7 7
7.3%
4 6
 
6.2%
8 5
 
5.2%
0 5
 
5.2%
9 5
 
5.2%
3 4
 
4.2%
Other values (2) 7
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
75.0%
Other Punctuation 12
 
12.5%
Space Separator 12
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 17
23.6%
5 16
22.2%
7 7
9.7%
4 6
 
8.3%
8 5
 
6.9%
0 5
 
6.9%
9 5
 
6.9%
3 4
 
5.6%
1 4
 
5.6%
6 3
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 17
17.7%
5 16
16.7%
, 12
12.5%
12
12.5%
7 7
7.3%
4 6
 
6.2%
8 5
 
5.2%
0 5
 
5.2%
9 5
 
5.2%
3 4
 
4.2%
Other values (2) 7
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 17
17.7%
5 16
16.7%
, 12
12.5%
12
12.5%
7 7
7.3%
4 6
 
6.2%
8 5
 
5.2%
0 5
 
5.2%
9 5
 
5.2%
3 4
 
4.2%
Other values (2) 7
7.3%

북부간선도로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T18:18:14.188561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters96
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row105,303
2nd row103,662
3rd row108,813
4th row108,355
5th row109,250
ValueCountFrequency (%)
105,303 1
8.3%
103,662 1
8.3%
108,813 1
8.3%
108,355 1
8.3%
109,250 1
8.3%
109,933 1
8.3%
107,420 1
8.3%
110,422 1
8.3%
110,075 1
8.3%
111,609 1
8.3%
Other values (2) 2
16.7%
2023-12-11T18:18:14.558084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
19.8%
0 16
16.7%
, 12
12.5%
12
12.5%
3 7
 
7.3%
2 7
 
7.3%
5 5
 
5.2%
6 5
 
5.2%
9 4
 
4.2%
7 4
 
4.2%
Other values (2) 5
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
75.0%
Other Punctuation 12
 
12.5%
Space Separator 12
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
26.4%
0 16
22.2%
3 7
 
9.7%
2 7
 
9.7%
5 5
 
6.9%
6 5
 
6.9%
9 4
 
5.6%
7 4
 
5.6%
8 3
 
4.2%
4 2
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
19.8%
0 16
16.7%
, 12
12.5%
12
12.5%
3 7
 
7.3%
2 7
 
7.3%
5 5
 
5.2%
6 5
 
5.2%
9 4
 
4.2%
7 4
 
4.2%
Other values (2) 5
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
19.8%
0 16
16.7%
, 12
12.5%
12
12.5%
3 7
 
7.3%
2 7
 
7.3%
5 5
 
5.2%
6 5
 
5.2%
9 4
 
4.2%
7 4
 
4.2%
Other values (2) 5
 
5.2%

올림픽대로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T18:18:14.774673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters96
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row241,465
2nd row254,495
3rd row251,119
4th row255,930
5th row254,500
ValueCountFrequency (%)
241,465 1
8.3%
254,495 1
8.3%
251,119 1
8.3%
255,930 1
8.3%
254,500 1
8.3%
255,447 1
8.3%
255,723 1
8.3%
251,695 1
8.3%
254,598 1
8.3%
248,858 1
8.3%
Other values (2) 2
16.7%
2023-12-11T18:18:15.073425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 18
18.8%
2 13
13.5%
, 12
12.5%
12
12.5%
4 10
10.4%
9 10
10.4%
1 5
 
5.2%
0 4
 
4.2%
8 4
 
4.2%
6 3
 
3.1%
Other values (2) 5
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
75.0%
Other Punctuation 12
 
12.5%
Space Separator 12
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 18
25.0%
2 13
18.1%
4 10
13.9%
9 10
13.9%
1 5
 
6.9%
0 4
 
5.6%
8 4
 
5.6%
6 3
 
4.2%
7 3
 
4.2%
3 2
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 18
18.8%
2 13
13.5%
, 12
12.5%
12
12.5%
4 10
10.4%
9 10
10.4%
1 5
 
5.2%
0 4
 
4.2%
8 4
 
4.2%
6 3
 
3.1%
Other values (2) 5
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 18
18.8%
2 13
13.5%
, 12
12.5%
12
12.5%
4 10
10.4%
9 10
10.4%
1 5
 
5.2%
0 4
 
4.2%
8 4
 
4.2%
6 3
 
3.1%
Other values (2) 5
 
5.2%

동부간선도로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T18:18:15.265105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters96
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row150,937
2nd row154,492
3rd row153,325
4th row155,802
5th row153,007
ValueCountFrequency (%)
150,937 1
8.3%
154,492 1
8.3%
153,325 1
8.3%
155,802 1
8.3%
153,007 1
8.3%
156,973 1
8.3%
154,865 1
8.3%
156,452 1
8.3%
159,222 1
8.3%
143,425 1
8.3%
Other values (2) 2
16.7%
2023-12-11T18:18:15.552897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 17
17.7%
1 13
13.5%
, 12
12.5%
12
12.5%
3 8
8.3%
2 8
8.3%
4 7
7.3%
7 5
 
5.2%
0 4
 
4.2%
9 4
 
4.2%
Other values (2) 6
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
75.0%
Other Punctuation 12
 
12.5%
Space Separator 12
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 17
23.6%
1 13
18.1%
3 8
11.1%
2 8
11.1%
4 7
9.7%
7 5
 
6.9%
0 4
 
5.6%
9 4
 
5.6%
8 3
 
4.2%
6 3
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 17
17.7%
1 13
13.5%
, 12
12.5%
12
12.5%
3 8
8.3%
2 8
8.3%
4 7
7.3%
7 5
 
5.2%
0 4
 
4.2%
9 4
 
4.2%
Other values (2) 6
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 17
17.7%
1 13
13.5%
, 12
12.5%
12
12.5%
3 8
8.3%
2 8
8.3%
4 7
7.3%
7 5
 
5.2%
0 4
 
4.2%
9 4
 
4.2%
Other values (2) 6
 
6.2%

분당수서로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T18:18:15.714536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters96
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row127,666
2nd row133,899
3rd row136,390
4th row137,781
5th row136,274
ValueCountFrequency (%)
127,666 1
8.3%
133,899 1
8.3%
136,390 1
8.3%
137,781 1
8.3%
136,274 1
8.3%
137,133 1
8.3%
133,169 1
8.3%
137,245 1
8.3%
139,744 1
8.3%
133,599 1
8.3%
Other values (2) 2
16.7%
2023-12-11T18:18:16.036537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 19
19.8%
1 15
15.6%
, 12
12.5%
12
12.5%
9 9
9.4%
7 7
 
7.3%
6 6
 
6.2%
8 5
 
5.2%
4 4
 
4.2%
2 3
 
3.1%
Other values (2) 4
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
75.0%
Other Punctuation 12
 
12.5%
Space Separator 12
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 19
26.4%
1 15
20.8%
9 9
12.5%
7 7
 
9.7%
6 6
 
8.3%
8 5
 
6.9%
4 4
 
5.6%
2 3
 
4.2%
0 2
 
2.8%
5 2
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 19
19.8%
1 15
15.6%
, 12
12.5%
12
12.5%
9 9
9.4%
7 7
 
7.3%
6 6
 
6.2%
8 5
 
5.2%
4 4
 
4.2%
2 3
 
3.1%
Other values (2) 4
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 19
19.8%
1 15
15.6%
, 12
12.5%
12
12.5%
9 9
9.4%
7 7
 
7.3%
6 6
 
6.2%
8 5
 
5.2%
4 4
 
4.2%
2 3
 
3.1%
Other values (2) 4
 
4.2%

경부고속도로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T18:18:16.207871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters96
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row190,387
2nd row198,469
3rd row203,690
4th row208,025
5th row208,721
ValueCountFrequency (%)
190,387 1
8.3%
198,469 1
8.3%
203,690 1
8.3%
208,025 1
8.3%
208,721 1
8.3%
212,667 1
8.3%
203,012 1
8.3%
205,687 1
8.3%
204,980 1
8.3%
207,455 1
8.3%
Other values (2) 2
16.7%
2023-12-11T18:18:16.555504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
15.6%
2 14
14.6%
, 12
12.5%
12
12.5%
5 7
7.3%
1 6
 
6.2%
8 6
 
6.2%
7 6
 
6.2%
6 6
 
6.2%
9 5
 
5.2%
Other values (2) 7
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
75.0%
Other Punctuation 12
 
12.5%
Space Separator 12
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
20.8%
2 14
19.4%
5 7
9.7%
1 6
 
8.3%
8 6
 
8.3%
7 6
 
8.3%
6 6
 
8.3%
9 5
 
6.9%
4 4
 
5.6%
3 3
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
15.6%
2 14
14.6%
, 12
12.5%
12
12.5%
5 7
7.3%
1 6
 
6.2%
8 6
 
6.2%
7 6
 
6.2%
6 6
 
6.2%
9 5
 
5.2%
Other values (2) 7
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
15.6%
2 14
14.6%
, 12
12.5%
12
12.5%
5 7
7.3%
1 6
 
6.2%
8 6
 
6.2%
7 6
 
6.2%
6 6
 
6.2%
9 5
 
5.2%
Other values (2) 7
7.3%

서부간선도로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T18:18:16.759452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.4166667
Min length1

Characters and Unicode

Total characters89
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row115,972
2nd row111,281
3rd row-
4th row116,662
5th row118,797
ValueCountFrequency (%)
115,972 1
8.3%
111,281 1
8.3%
1
8.3%
116,662 1
8.3%
118,797 1
8.3%
117,436 1
8.3%
117,890 1
8.3%
119,085 1
8.3%
119,114 1
8.3%
114,419 1
8.3%
Other values (2) 2
16.7%
2023-12-11T18:18:17.080959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 30
33.7%
, 11
 
12.4%
11
 
12.4%
9 7
 
7.9%
6 6
 
6.7%
4 6
 
6.7%
7 5
 
5.6%
8 4
 
4.5%
2 3
 
3.4%
5 2
 
2.2%
Other values (3) 4
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
74.2%
Other Punctuation 11
 
12.4%
Space Separator 11
 
12.4%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 30
45.5%
9 7
 
10.6%
6 6
 
9.1%
4 6
 
9.1%
7 5
 
7.6%
8 4
 
6.1%
2 3
 
4.5%
5 2
 
3.0%
0 2
 
3.0%
3 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 89
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 30
33.7%
, 11
 
12.4%
11
 
12.4%
9 7
 
7.9%
6 6
 
6.7%
4 6
 
6.7%
7 5
 
5.6%
8 4
 
4.5%
2 3
 
3.4%
5 2
 
2.2%
Other values (3) 4
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 30
33.7%
, 11
 
12.4%
11
 
12.4%
9 7
 
7.9%
6 6
 
6.7%
4 6
 
6.7%
7 5
 
5.6%
8 4
 
4.5%
2 3
 
3.4%
5 2
 
2.2%
Other values (3) 4
 
4.5%

강남순환로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T18:18:17.261236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters96
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row104,440
2nd row112,129
3rd row113,885
4th row123,076
5th row116,899
ValueCountFrequency (%)
104,440 1
8.3%
112,129 1
8.3%
113,885 1
8.3%
123,076 1
8.3%
116,899 1
8.3%
124,855 1
8.3%
117,916 1
8.3%
121,348 1
8.3%
124,547 1
8.3%
108,165 1
8.3%
Other values (2) 2
16.7%
2023-12-11T18:18:17.607788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
21.9%
, 12
12.5%
12
12.5%
0 7
 
7.3%
4 7
 
7.3%
2 7
 
7.3%
5 7
 
7.3%
8 6
 
6.2%
9 5
 
5.2%
3 4
 
4.2%
Other values (2) 8
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
75.0%
Other Punctuation 12
 
12.5%
Space Separator 12
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
29.2%
0 7
 
9.7%
4 7
 
9.7%
2 7
 
9.7%
5 7
 
9.7%
8 6
 
8.3%
9 5
 
6.9%
3 4
 
5.6%
7 4
 
5.6%
6 4
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 21
21.9%
, 12
12.5%
12
12.5%
0 7
 
7.3%
4 7
 
7.3%
2 7
 
7.3%
5 7
 
7.3%
8 6
 
6.2%
9 5
 
5.2%
3 4
 
4.2%
Other values (2) 8
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21
21.9%
, 12
12.5%
12
12.5%
0 7
 
7.3%
4 7
 
7.3%
2 7
 
7.3%
5 7
 
7.3%
8 6
 
6.2%
9 5
 
5.2%
3 4
 
4.2%
Other values (2) 8
 
8.3%

Correlations

2023-12-11T18:18:17.723524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분내부순환로강변북로북부간선도로올림픽대로동부간선도로분당수서로경부고속도로서부간선도로강남순환로
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
내부순환로1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
강변북로1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
북부간선도로1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
올림픽대로1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
동부간선도로1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
분당수서로1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
경부고속도로1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
서부간선도로1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
강남순환로1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-11T18:18:11.943789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:18:12.359828image/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.
2023-12-11T18:18:12.536365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

구분내부순환로강변북로북부간선도로올림픽대로동부간선도로분당수서로경부고속도로서부간선도로강남순환로
01월159,109244,834105,303241,465150,937127,666190,387115,972104,440
12월162,086253,010103,662254,495154,492133,899198,469111,281112,129
23월162,696255,960108,813251,119153,325136,390203,690-113,885
34월160,920251,254108,355255,930155,802137,781208,025116,662123,076
45월158,427247,928109,250254,500153,007136,274208,721118,797116,899
56월159,680253,718109,933255,447156,973137,133212,667117,436124,855
67월156,055257,595107,420255,723154,865133,169203,012117,890117,916
78월157,344255,978110,422251,695156,452137,245205,687119,085121,348
89월159,052252,625110,075254,598159,222139,744204,980119,114124,547
910월159,993245,772111,609248,858143,425133,599207,455114,419108,165
구분내부순환로강변북로북부간선도로올림픽대로동부간선도로분당수서로경부고속도로서부간선도로강남순환로
17<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
18<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
25<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

구분내부순환로강변북로북부간선도로올림픽대로동부간선도로분당수서로경부고속도로서부간선도로강남순환로# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>15