Overview

Dataset statistics

Number of variables4
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 KiB
Average record size in memory36.6 B

Variable types

Text3
Categorical1

Dataset

Description서울특별시 중랑구에서 운영하는 마을변호사 현황을 제공합니다. 운영 동 명칭, 운영위치, 연락처, 담당자 연락처를 제공합니다.
Author서울특별시 중랑구
URLhttps://www.data.go.kr/data/15032228/fileData.do

Reproduction

Analysis started2024-05-04 07:06:13.481538
Analysis finished2024-05-04 07:06:14.593477
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct16
Distinct (%)55.2%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-05-04T07:06:14.906410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.0344828
Min length3

Characters and Unicode

Total characters117
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)13.8%

Sample

1st row면목본동
2nd row면목본동
3rd row면목2동
4th row면목2동
5th row면목3.8동
ValueCountFrequency (%)
면목7동 3
 
10.3%
면목본동 2
 
6.9%
면목2동 2
 
6.9%
면목3.8동 2
 
6.9%
면목4동 2
 
6.9%
면목5동 2
 
6.9%
상봉2동 2
 
6.9%
중화1동 2
 
6.9%
중화2동 2
 
6.9%
묵1동 2
 
6.9%
Other values (6) 8
27.6%
2024-05-04T07:06:16.070395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
24.8%
13
11.1%
13
11.1%
2 9
 
7.7%
1 7
 
6.0%
4
 
3.4%
4
 
3.4%
4
 
3.4%
4
 
3.4%
3
 
2.6%
Other values (11) 27
23.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87
74.4%
Decimal Number 28
 
23.9%
Other Punctuation 2
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
29
33.3%
13
14.9%
13
14.9%
4
 
4.6%
4
 
4.6%
4
 
4.6%
4
 
4.6%
3
 
3.4%
3
 
3.4%
3
 
3.4%
Other values (3) 7
 
8.0%
Decimal Number
ValueCountFrequency (%)
2 9
32.1%
1 7
25.0%
7 3
 
10.7%
3 3
 
10.7%
5 2
 
7.1%
4 2
 
7.1%
8 2
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87
74.4%
Common 30
 
25.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
29
33.3%
13
14.9%
13
14.9%
4
 
4.6%
4
 
4.6%
4
 
4.6%
4
 
4.6%
3
 
3.4%
3
 
3.4%
3
 
3.4%
Other values (3) 7
 
8.0%
Common
ValueCountFrequency (%)
2 9
30.0%
1 7
23.3%
7 3
 
10.0%
3 3
 
10.0%
5 2
 
6.7%
4 2
 
6.7%
8 2
 
6.7%
. 2
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87
74.4%
ASCII 30
 
25.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
29
33.3%
13
14.9%
13
14.9%
4
 
4.6%
4
 
4.6%
4
 
4.6%
4
 
4.6%
3
 
3.4%
3
 
3.4%
3
 
3.4%
Other values (3) 7
 
8.0%
ASCII
ValueCountFrequency (%)
2 9
30.0%
1 7
23.3%
7 3
 
10.0%
3 3
 
10.0%
5 2
 
6.7%
4 2
 
6.7%
8 2
 
6.7%
. 2
 
6.7%

상담장소
Categorical

Distinct13
Distinct (%)44.8%
Missing0
Missing (%)0.0%
Memory size364.0 B
1층 상담실
2층 프로그램실
2층 강의실
2층 교양강좌실
2층 한울실
Other values (8)
14 

Length

Max length15
Median length11
Mean length8
Min length6

Unique

Unique2 ?
Unique (%)6.9%

Sample

1st row2층 교양강좌실
2nd row2층 교양강좌실
3rd row2층 한울실
4th row2층 한울실
5th row용마문화복지센터 3층

Common Values

ValueCountFrequency (%)
1층 상담실 5
17.2%
2층 프로그램실 3
10.3%
2층 강의실 3
10.3%
2층 교양강좌실 2
 
6.9%
2층 한울실 2
 
6.9%
용마문화복지센터 3층 2
 
6.9%
2층 주민자치회실 2
 
6.9%
1층 사회복지상담실 2
 
6.9%
중화문화복지센터 4층 강의실 2
 
6.9%
2층 다목적실 2
 
6.9%
Other values (3) 4
13.8%

Length

2024-05-04T07:06:16.605132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2층 15
25.0%
상담실 8
13.3%
1층 7
11.7%
강의실 5
 
8.3%
3층 4
 
6.7%
프로그램실 3
 
5.0%
교양강좌실 2
 
3.3%
한울실 2
 
3.3%
용마문화복지센터 2
 
3.3%
주민자치회실 2
 
3.3%
Other values (6) 10
16.7%
Distinct26
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-05-04T07:06:17.148803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length19.793103
Min length19

Characters and Unicode

Total characters574
Distinct characters29
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)82.8%

Sample

1st row세번째 수요일 14:00~16:00
2nd row첫번째 수요일 14:00~16:00
3rd row두번째 월요일 10:00~12:00
4th row짝)네번째 월요일 10:00~12:00
5th row세번째 월요일 10:00~12:00
ValueCountFrequency (%)
10:00~12:00 17
18.9%
월요일 13
14.4%
세번째 10
11.1%
14:00~16:00 8
8.9%
수요일 6
 
6.7%
첫번째 6
 
6.7%
두번째 5
 
5.6%
화요일 5
 
5.6%
금요일 5
 
5.6%
네번째 3
 
3.3%
Other values (10) 12
13.3%
2024-05-04T07:06:18.743636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 134
23.3%
62
10.8%
: 59
10.3%
1 58
10.1%
29
 
5.1%
29
 
5.1%
29
 
5.1%
29
 
5.1%
~ 29
 
5.1%
2 17
 
3.0%
Other values (19) 99
17.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 232
40.4%
Other Letter 183
31.9%
Space Separator 62
 
10.8%
Other Punctuation 59
 
10.3%
Math Symbol 29
 
5.1%
Close Punctuation 8
 
1.4%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
29
15.8%
29
15.8%
29
15.8%
29
15.8%
13
7.1%
10
 
5.5%
9
 
4.9%
6
 
3.3%
5
 
2.7%
5
 
2.7%
Other values (6) 19
10.4%
Decimal Number
ValueCountFrequency (%)
0 134
57.8%
1 58
25.0%
2 17
 
7.3%
4 10
 
4.3%
6 9
 
3.9%
7 2
 
0.9%
8 1
 
0.4%
9 1
 
0.4%
Space Separator
ValueCountFrequency (%)
62
100.0%
Other Punctuation
ValueCountFrequency (%)
: 59
100.0%
Math Symbol
ValueCountFrequency (%)
~ 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 391
68.1%
Hangul 183
31.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
29
15.8%
29
15.8%
29
15.8%
29
15.8%
13
7.1%
10
 
5.5%
9
 
4.9%
6
 
3.3%
5
 
2.7%
5
 
2.7%
Other values (6) 19
10.4%
Common
ValueCountFrequency (%)
0 134
34.3%
62
15.9%
: 59
15.1%
1 58
14.8%
~ 29
 
7.4%
2 17
 
4.3%
4 10
 
2.6%
6 9
 
2.3%
) 8
 
2.0%
7 2
 
0.5%
Other values (3) 3
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 391
68.1%
Hangul 183
31.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 134
34.3%
62
15.9%
: 59
15.1%
1 58
14.8%
~ 29
 
7.4%
2 17
 
4.3%
4 10
 
2.6%
6 9
 
2.3%
) 8
 
2.0%
7 2
 
0.5%
Other values (3) 3
 
0.8%
Hangul
ValueCountFrequency (%)
29
15.8%
29
15.8%
29
15.8%
29
15.8%
13
7.1%
10
 
5.5%
9
 
4.9%
6
 
3.3%
5
 
2.7%
5
 
2.7%
Other values (6) 19
10.4%
Distinct16
Distinct (%)55.2%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-05-04T07:06:19.233819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters348
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)13.8%

Sample

1st row02-2094-6012
2nd row02-2094-6012
3rd row02-2094-6056
4th row02-2094-6056
5th row02-2094-6111
ValueCountFrequency (%)
02-2094-6225 3
 
10.3%
02-2094-6012 2
 
6.9%
02-2094-6056 2
 
6.9%
02-2094-6111 2
 
6.9%
02-2094-6147 2
 
6.9%
02-2094-6179 2
 
6.9%
02-2094-6293 2
 
6.9%
02-2094-6335 2
 
6.9%
02-2094-6373 2
 
6.9%
02-2094-6415 2
 
6.9%
Other values (6) 8
27.6%
2024-05-04T07:06:20.661429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 71
20.4%
0 62
17.8%
- 58
16.7%
4 38
10.9%
6 35
10.1%
9 33
9.5%
5 16
 
4.6%
1 15
 
4.3%
3 12
 
3.4%
7 8
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 290
83.3%
Dash Punctuation 58
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 71
24.5%
0 62
21.4%
4 38
13.1%
6 35
12.1%
9 33
11.4%
5 16
 
5.5%
1 15
 
5.2%
3 12
 
4.1%
7 8
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 71
20.4%
0 62
17.8%
- 58
16.7%
4 38
10.9%
6 35
10.1%
9 33
9.5%
5 16
 
4.6%
1 15
 
4.3%
3 12
 
3.4%
7 8
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 71
20.4%
0 62
17.8%
- 58
16.7%
4 38
10.9%
6 35
10.1%
9 33
9.5%
5 16
 
4.6%
1 15
 
4.3%
3 12
 
3.4%
7 8
 
2.3%

Correlations

2024-05-04T07:06:21.268637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영동명칭상담장소정기상담일담당자전화번호
운영동명칭1.0001.0000.8971.000
상담장소1.0001.0000.7521.000
정기상담일0.8970.7521.0000.897
담당자전화번호1.0001.0000.8971.000

Missing values

2024-05-04T07:06:14.020940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T07:06:14.405589image/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

운영동명칭상담장소정기상담일담당자전화번호
0면목본동2층 교양강좌실세번째 수요일 14:00~16:0002-2094-6012
1면목본동2층 교양강좌실첫번째 수요일 14:00~16:0002-2094-6012
2면목2동2층 한울실두번째 월요일 10:00~12:0002-2094-6056
3면목2동2층 한울실짝)네번째 월요일 10:00~12:0002-2094-6056
4면목3.8동용마문화복지센터 3층세번째 월요일 10:00~12:0002-2094-6111
5면목3.8동용마문화복지센터 3층짝)첫번째 월요일 10:00~12:0002-2094-6111
6면목4동2층 주민자치회실첫번째 화요일 10:00~12:0002-2094-6147
7면목4동2층 주민자치회실세번째 금요일 10:00~12:0002-2094-6147
8면목5동1층 사회복지상담실두번째 월요일 10:00~12:0002-2094-6179
9면목5동1층 사회복지상담실홀)네번째 월요일 10:00~12:0002-2094-6179
운영동명칭상담장소정기상담일담당자전화번호
19중화2동중화문화복지센터 4층 강의실세번째 수요일 10:00~12:0002-2094-6373
20묵1동2층 다목적실두번째 월요일 10:00~12:0002-2094-6415
21묵1동2층 다목적실네번째 월요일 10:00~12:0002-2094-6415
22묵2동2층 상담실네번째 금요일 10:00~12:0002-2094-6454
23망우본동지하1층 생활체육실첫번째 월요일 10:00~12:0002-2094-6513
24망우3동1층 상담실공석 (세번째 월요일 10:00~12:00)02-2094-6535
25신내1동1층 상담실짝) 두번째 월요일 14::00~17:0002-2094-6574
26신내1동1층 상담실짝) 세번째 월요일 14:00~17:0002-2094-6574
27신내2동3층 상담실첫번째 수요일 09:00~11:0002-2094-6626
28신내2동3층 상담실세번째 수요일 10:00~12:0002-2094-6626