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-15281/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 07:19:42.480013
Analysis finished2023-12-11 07:19:43.494526
Duration1.01 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
2023-12-11T16:19:43.641337image/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%
2023-12-11T16:19:44.010540image/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
2023-12-11T16:19:44.277092image/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 row141,071
2nd row147,649
3rd row150,873
4th row150,294
5th row145,750
ValueCountFrequency (%)
141,071 1
8.3%
147,649 1
8.3%
150,873 1
8.3%
150,294 1
8.3%
145,750 1
8.3%
147,576 1
8.3%
144,429 1
8.3%
144,804 1
8.3%
147,065 1
8.3%
146,144 1
8.3%
Other values (2) 2
16.7%
2023-12-11T16:19:44.877934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 17
17.7%
1 16
16.7%
, 12
12.5%
12
12.5%
5 9
9.4%
7 8
8.3%
0 6
 
6.2%
9 5
 
5.2%
6 4
 
4.2%
8 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 (%)
4 17
23.6%
1 16
22.2%
5 9
12.5%
7 8
11.1%
0 6
 
8.3%
9 5
 
6.9%
6 4
 
5.6%
8 3
 
4.2%
2 3
 
4.2%
3 1
 
1.4%
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 (%)
4 17
17.7%
1 16
16.7%
, 12
12.5%
12
12.5%
5 9
9.4%
7 8
8.3%
0 6
 
6.2%
9 5
 
5.2%
6 4
 
4.2%
8 3
 
3.1%
Other values (2) 4
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 17
17.7%
1 16
16.7%
, 12
12.5%
12
12.5%
5 9
9.4%
7 8
8.3%
0 6
 
6.2%
9 5
 
5.2%
6 4
 
4.2%
8 3
 
3.1%
Other values (2) 4
 
4.2%

강변북로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T16:19:45.067075image/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 row215,619
2nd row230,826
3rd row236,613
4th row236,091
5th row233,557
ValueCountFrequency (%)
215,619 1
8.3%
230,826 1
8.3%
236,613 1
8.3%
236,091 1
8.3%
233,557 1
8.3%
238,598 1
8.3%
231,799 1
8.3%
231,821 1
8.3%
242,281 1
8.3%
226,624 1
8.3%
Other values (2) 2
16.7%
2023-12-11T16:19:45.435512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 19
19.8%
, 12
12.5%
12
12.5%
1 10
10.4%
3 9
9.4%
6 7
 
7.3%
5 6
 
6.2%
8 6
 
6.2%
9 5
 
5.2%
0 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 (%)
2 19
26.4%
1 10
13.9%
3 9
12.5%
6 7
 
9.7%
5 6
 
8.3%
8 6
 
8.3%
9 5
 
6.9%
0 4
 
5.6%
4 4
 
5.6%
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 (%)
2 19
19.8%
, 12
12.5%
12
12.5%
1 10
10.4%
3 9
9.4%
6 7
 
7.3%
5 6
 
6.2%
8 6
 
6.2%
9 5
 
5.2%
0 4
 
4.2%
Other values (2) 6
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 19
19.8%
, 12
12.5%
12
12.5%
1 10
10.4%
3 9
9.4%
6 7
 
7.3%
5 6
 
6.2%
8 6
 
6.2%
9 5
 
5.2%
0 4
 
4.2%
Other values (2) 6
 
6.2%

북부간선도로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T16:19:45.657526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.6666667
Min length7

Characters and Unicode

Total characters92
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 row93,370
2nd row97,925
3rd row101,909
4th row103,641
5th row102,135
ValueCountFrequency (%)
93,370 1
8.3%
97,925 1
8.3%
101,909 1
8.3%
103,641 1
8.3%
102,135 1
8.3%
103,100 1
8.3%
97,009 1
8.3%
100,006 1
8.3%
104,369 1
8.3%
103,488 1
8.3%
Other values (2) 2
16.7%
2023-12-11T16:19:46.043071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17
18.5%
1 13
14.1%
, 12
13.0%
12
13.0%
9 10
10.9%
3 8
8.7%
6 4
 
4.3%
4 4
 
4.3%
8 4
 
4.3%
7 3
 
3.3%
Other values (2) 5
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
73.9%
Other Punctuation 12
 
13.0%
Space Separator 12
 
13.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17
25.0%
1 13
19.1%
9 10
14.7%
3 8
11.8%
6 4
 
5.9%
4 4
 
5.9%
8 4
 
5.9%
7 3
 
4.4%
2 3
 
4.4%
5 2
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 92
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17
18.5%
1 13
14.1%
, 12
13.0%
12
13.0%
9 10
10.9%
3 8
8.7%
6 4
 
4.3%
4 4
 
4.3%
8 4
 
4.3%
7 3
 
3.3%
Other values (2) 5
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17
18.5%
1 13
14.1%
, 12
13.0%
12
13.0%
9 10
10.9%
3 8
8.7%
6 4
 
4.3%
4 4
 
4.3%
8 4
 
4.3%
7 3
 
3.3%
Other values (2) 5
 
5.4%

올림픽대로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T16:19:46.254092image/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 row213,361
2nd row224,859
3rd row232,186
4th row236,206
5th row237,772
ValueCountFrequency (%)
213,361 1
8.3%
224,859 1
8.3%
232,186 1
8.3%
236,206 1
8.3%
237,772 1
8.3%
236,045 1
8.3%
227,630 1
8.3%
228,392 1
8.3%
240,754 1
8.3%
228,152 1
8.3%
Other values (2) 2
16.7%
2023-12-11T16:19:46.685333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 21
21.9%
, 12
12.5%
12
12.5%
3 11
11.5%
6 7
 
7.3%
1 6
 
6.2%
5 6
 
6.2%
0 5
 
5.2%
7 5
 
5.2%
4 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 21
29.2%
3 11
15.3%
6 7
 
9.7%
1 6
 
8.3%
5 6
 
8.3%
0 5
 
6.9%
7 5
 
6.9%
4 4
 
5.6%
8 4
 
5.6%
9 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 21
21.9%
, 12
12.5%
12
12.5%
3 11
11.5%
6 7
 
7.3%
1 6
 
6.2%
5 6
 
6.2%
0 5
 
5.2%
7 5
 
5.2%
4 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 21
21.9%
, 12
12.5%
12
12.5%
3 11
11.5%
6 7
 
7.3%
1 6
 
6.2%
5 6
 
6.2%
0 5
 
5.2%
7 5
 
5.2%
4 4
 
4.2%
Other values (2) 7
 
7.3%

동부간선도로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T16:19:46.934279image/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 row133,618
2nd row137,571
3rd row141,249
4th row145,145
5th row143,866
ValueCountFrequency (%)
133,618 1
8.3%
137,571 1
8.3%
141,249 1
8.3%
145,145 1
8.3%
143,866 1
8.3%
144,989 1
8.3%
135,415 1
8.3%
137,259 1
8.3%
147,390 1
8.3%
137,569 1
8.3%
Other values (2) 2
16.7%
2023-12-11T16:19:47.348278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
17.7%
3 12
12.5%
, 12
12.5%
12
12.5%
4 10
10.4%
5 8
8.3%
9 7
7.3%
6 5
 
5.2%
7 5
 
5.2%
8 4
 
4.2%
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 (%)
1 17
23.6%
3 12
16.7%
4 10
13.9%
5 8
11.1%
9 7
9.7%
6 5
 
6.9%
7 5
 
6.9%
8 4
 
5.6%
2 3
 
4.2%
0 1
 
1.4%
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 17
17.7%
3 12
12.5%
, 12
12.5%
12
12.5%
4 10
10.4%
5 8
8.3%
9 7
7.3%
6 5
 
5.2%
7 5
 
5.2%
8 4
 
4.2%
Other values (2) 4
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
17.7%
3 12
12.5%
, 12
12.5%
12
12.5%
4 10
10.4%
5 8
8.3%
9 7
7.3%
6 5
 
5.2%
7 5
 
5.2%
8 4
 
4.2%
Other values (2) 4
 
4.2%

분당수서로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T16:19:47.588873image/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 row113,339
2nd row117,008
3rd row122,219
4th row124,501
5th row125,918
ValueCountFrequency (%)
113,339 1
8.3%
117,008 1
8.3%
122,219 1
8.3%
124,501 1
8.3%
125,918 1
8.3%
123,747 1
8.3%
118,340 1
8.3%
120,276 1
8.3%
128,173 1
8.3%
123,686 1
8.3%
Other values (2) 2
16.7%
2023-12-11T16:19:47.990310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
21.9%
, 12
12.5%
12
12.5%
2 11
11.5%
3 8
 
8.3%
7 6
 
6.2%
0 6
 
6.2%
9 5
 
5.2%
8 5
 
5.2%
5 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 (%)
1 21
29.2%
2 11
15.3%
3 8
 
11.1%
7 6
 
8.3%
0 6
 
8.3%
9 5
 
6.9%
8 5
 
6.9%
5 4
 
5.6%
4 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 (%)
1 21
21.9%
, 12
12.5%
12
12.5%
2 11
11.5%
3 8
 
8.3%
7 6
 
6.2%
0 6
 
6.2%
9 5
 
5.2%
8 5
 
5.2%
5 4
 
4.2%
Other values (2) 6
 
6.2%

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%
2 11
11.5%
3 8
 
8.3%
7 6
 
6.2%
0 6
 
6.2%
9 5
 
5.2%
8 5
 
5.2%
5 4
 
4.2%
Other values (2) 6
 
6.2%

경부고속도로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T16:19:48.192703image/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 row175,620
2nd row181,084
3rd row191,378
4th row193,862
5th row195,073
ValueCountFrequency (%)
175,620 1
8.3%
181,084 1
8.3%
191,378 1
8.3%
193,862 1
8.3%
195,073 1
8.3%
194,448 1
8.3%
183,254 1
8.3%
185,739 1
8.3%
201,513 1
8.3%
192,267 1
8.3%
Other values (2) 2
16.7%
2023-12-11T16:19:48.616055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
16.7%
, 12
12.5%
12
12.5%
8 9
9.4%
3 8
8.3%
2 7
7.3%
9 7
7.3%
7 6
 
6.2%
5 5
 
5.2%
6 5
 
5.2%
Other values (2) 9
9.4%

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 16
22.2%
8 9
12.5%
3 8
11.1%
2 7
9.7%
9 7
9.7%
7 6
 
8.3%
5 5
 
6.9%
6 5
 
6.9%
4 5
 
6.9%
0 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 16
16.7%
, 12
12.5%
12
12.5%
8 9
9.4%
3 8
8.3%
2 7
7.3%
9 7
7.3%
7 6
 
6.2%
5 5
 
5.2%
6 5
 
5.2%
Other values (2) 9
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
16.7%
, 12
12.5%
12
12.5%
8 9
9.4%
3 8
8.3%
2 7
7.3%
9 7
7.3%
7 6
 
6.2%
5 5
 
5.2%
6 5
 
5.2%
Other values (2) 9
9.4%

서부간선도로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T16:19:48.834682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.25
Min length1

Characters and Unicode

Total characters87
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 row99,662
2nd row99,878
3rd row-
4th row108,276
5th row115,385
ValueCountFrequency (%)
99,662 1
8.3%
99,878 1
8.3%
1
8.3%
108,276 1
8.3%
115,385 1
8.3%
117,215 1
8.3%
111,646 1
8.3%
110,476 1
8.3%
119,332 1
8.3%
112,190 1
8.3%
Other values (2) 2
16.7%
2023-12-11T16:19:49.240948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
23.0%
, 11
12.6%
11
12.6%
6 7
 
8.0%
9 6
 
6.9%
2 6
 
6.9%
7 5
 
5.7%
0 5
 
5.7%
8 4
 
4.6%
5 4
 
4.6%
Other values (3) 8
 
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
73.6%
Other Punctuation 11
 
12.6%
Space Separator 11
 
12.6%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
31.2%
6 7
 
10.9%
9 6
 
9.4%
2 6
 
9.4%
7 5
 
7.8%
0 5
 
7.8%
8 4
 
6.2%
5 4
 
6.2%
3 4
 
6.2%
4 3
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 87
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
23.0%
, 11
12.6%
11
12.6%
6 7
 
8.0%
9 6
 
6.9%
2 6
 
6.9%
7 5
 
5.7%
0 5
 
5.7%
8 4
 
4.6%
5 4
 
4.6%
Other values (3) 8
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 87
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
23.0%
, 11
12.6%
11
12.6%
6 7
 
8.0%
9 6
 
6.9%
2 6
 
6.9%
7 5
 
5.7%
0 5
 
5.7%
8 4
 
4.6%
5 4
 
4.6%
Other values (3) 8
 
9.2%

강남순환로
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-11T16:19:49.446660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7.0833333
Min length7

Characters and Unicode

Total characters85
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 row78,917
2nd row78,188
3rd row88,672
4th row91,552
5th row92,695
ValueCountFrequency (%)
78,917 1
8.3%
78,188 1
8.3%
88,672 1
8.3%
91,552 1
8.3%
92,695 1
8.3%
88,905 1
8.3%
84,727 1
8.3%
97,403 1
8.3%
99,695 1
8.3%
109,677 1
8.3%
Other values (2) 2
16.7%
2023-12-11T16:19:49.805933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 13
15.3%
, 12
14.1%
12
14.1%
7 11
12.9%
8 10
11.8%
1 5
 
5.9%
5 5
 
5.9%
6 4
 
4.7%
2 4
 
4.7%
0 4
 
4.7%
Other values (2) 5
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
71.8%
Other Punctuation 12
 
14.1%
Space Separator 12
 
14.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 13
21.3%
7 11
18.0%
8 10
16.4%
1 5
 
8.2%
5 5
 
8.2%
6 4
 
6.6%
2 4
 
6.6%
0 4
 
6.6%
4 4
 
6.6%
3 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 13
15.3%
, 12
14.1%
12
14.1%
7 11
12.9%
8 10
11.8%
1 5
 
5.9%
5 5
 
5.9%
6 4
 
4.7%
2 4
 
4.7%
0 4
 
4.7%
Other values (2) 5
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 13
15.3%
, 12
14.1%
12
14.1%
7 11
12.9%
8 10
11.8%
1 5
 
5.9%
5 5
 
5.9%
6 4
 
4.7%
2 4
 
4.7%
0 4
 
4.7%
Other values (2) 5
 
5.9%

Correlations

2023-12-11T16:19:49.923000image/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

2023-12-11T16:19:42.960721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T16:19:43.150518image/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.
2023-12-11T16:19:43.339802image/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
01월141,071215,61993,370213,361133,618113,339175,62099,66278,917
12월147,649230,82697,925224,859137,571117,008181,08499,87878,188
23월150,873236,613101,909232,186141,249122,219191,378-88,672
34월150,294236,091103,641236,206145,145124,501193,862108,27691,552
45월145,750233,557102,135237,772143,866125,918195,073115,38592,695
56월147,576238,598103,100236,045144,989123,747194,448117,21588,905
67월144,429231,79997,009227,630135,415118,340183,254111,64684,727
78월144,804231,821100,006228,392137,259120,276185,739110,47697,403
89월147,065242,281104,369240,754147,390128,173201,513119,33299,695
910월146,144226,624103,488228,152137,569123,686192,267112,190109,677
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