Overview

Dataset statistics

Number of variables4
Number of observations58
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory34.3 B

Variable types

Categorical1
Text3

Dataset

Description인천광역시 무료세무상담 "마을세무사"현황 데이터를 제공합니다.(담당기관, 담당지역, 세무사명,전화번호)
Author인천광역시
URLhttps://www.data.go.kr/data/15029613/fileData.do

Alerts

세무사명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:14:40.720188
Analysis finished2023-12-12 08:14:41.262415
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관
Categorical

Distinct11
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size596.0 B
남동구
9 
부평구
9 
연수구
8 
서구
8 
계양구
7 
Other values (6)
17 

Length

Max length4
Median length3
Mean length2.8448276
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시청
2nd row시청
3rd row중구
4th row중구
5th row동구

Common Values

ValueCountFrequency (%)
남동구 9
15.5%
부평구 9
15.5%
연수구 8
13.8%
서구 8
13.8%
계양구 7
12.1%
미추홀구 6
10.3%
동구 3
 
5.2%
시청 2
 
3.4%
중구 2
 
3.4%
강화군 2
 
3.4%

Length

2023-12-12T17:14:41.374184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남동구 9
15.5%
부평구 9
15.5%
연수구 8
13.8%
서구 8
13.8%
계양구 7
12.1%
미추홀구 6
10.3%
동구 3
 
5.2%
시청 2
 
3.4%
중구 2
 
3.4%
강화군 2
 
3.4%

세무사명
Text

UNIQUE 

Distinct58
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size596.0 B
2023-12-12T17:14:41.666448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters174
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)100.0%

Sample

1st row손영철
2nd row정용은
3rd row이경원
4th row조은혜
5th row서두범
ValueCountFrequency (%)
손영철 1
 
1.7%
김현재 1
 
1.7%
신원덕 1
 
1.7%
박종렬 1
 
1.7%
정진영 1
 
1.7%
이재관 1
 
1.7%
이중수 1
 
1.7%
박상록 1
 
1.7%
이후종 1
 
1.7%
고상용 1
 
1.7%
Other values (48) 48
82.8%
2023-12-12T17:14:42.138579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 15
 
8.6%
김 10
 
5.7%
수 8
 
4.6%
재 7
 
4.0%
정 6
 
3.4%
현 6
 
3.4%
상 4
 
2.3%
호 4
 
2.3%
영 4
 
2.3%
용 3
 
1.7%
Other values (71) 107
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 174
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 15
 
8.6%
김 10
 
5.7%
수 8
 
4.6%
재 7
 
4.0%
정 6
 
3.4%
현 6
 
3.4%
상 4
 
2.3%
호 4
 
2.3%
영 4
 
2.3%
용 3
 
1.7%
Other values (71) 107
61.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 174
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 15
 
8.6%
김 10
 
5.7%
수 8
 
4.6%
재 7
 
4.0%
정 6
 
3.4%
현 6
 
3.4%
상 4
 
2.3%
호 4
 
2.3%
영 4
 
2.3%
용 3
 
1.7%
Other values (71) 107
61.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 174
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 15
 
8.6%
김 10
 
5.7%
수 8
 
4.6%
재 7
 
4.0%
정 6
 
3.4%
현 6
 
3.4%
상 4
 
2.3%
호 4
 
2.3%
영 4
 
2.3%
용 3
 
1.7%
Other values (71) 107
61.5%

소속마을
Text

Distinct43
Distinct (%)74.1%
Missing0
Missing (%)0.0%
Memory size596.0 B
2023-12-12T17:14:42.577158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length29
Mean length22.034483
Min length3

Characters and Unicode

Total characters1278
Distinct characters112
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)53.4%

Sample

1st row시본청
2nd row시본청
3rd row신포동, 연안동, 신흥동, 북성동, 송월동
4th row도원동, 율목동, 동인천동, 영종동, 영종1동, 운서동, 용유동
5th row만석동, 화수1·화평동, 송림4동, 송림6동
ValueCountFrequency (%)
송도1동 4
 
1.7%
송도4동 4
 
1.7%
송도5동 4
 
1.7%
송도2동 4
 
1.7%
송도3동 4
 
1.7%
부평1동 3
 
1.3%
부평2동 3
 
1.3%
부평3동 3
 
1.3%
논현1동 3
 
1.3%
부평5동 3
 
1.3%
Other values (147) 202
85.2%
2023-12-12T17:14:43.229481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 212
16.6%
181
 
14.2%
, 179
 
14.0%
1 50
 
3.9%
2 50
 
3.9%
3 33
 
2.6%
송 31
 
2.4%
도 29
 
2.3%
면 26
 
2.0%
4 23
 
1.8%
Other values (102) 464
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 736
57.6%
Other Punctuation 185
 
14.5%
Space Separator 181
 
14.2%
Decimal Number 176
 
13.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 212
28.8%
송 31
 
4.2%
도 29
 
3.9%
면 26
 
3.5%
산 23
 
3.1%
부 21
 
2.9%
평 21
 
2.9%
수 20
 
2.7%
현 15
 
2.0%
계 14
 
1.9%
Other values (91) 324
44.0%
Decimal Number
ValueCountFrequency (%)
1 50
28.4%
2 50
28.4%
3 33
18.8%
4 23
13.1%
5 11
 
6.2%
6 7
 
4.0%
8 1
 
0.6%
7 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
, 179
96.8%
· 6
 
3.2%
Space Separator
ValueCountFrequency (%)
181
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 736
57.6%
Common 542
42.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 212
28.8%
송 31
 
4.2%
도 29
 
3.9%
면 26
 
3.5%
산 23
 
3.1%
부 21
 
2.9%
평 21
 
2.9%
수 20
 
2.7%
현 15
 
2.0%
계 14
 
1.9%
Other values (91) 324
44.0%
Common
ValueCountFrequency (%)
181
33.4%
, 179
33.0%
1 50
 
9.2%
2 50
 
9.2%
3 33
 
6.1%
4 23
 
4.2%
5 11
 
2.0%
6 7
 
1.3%
· 6
 
1.1%
8 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 736
57.6%
ASCII 536
41.9%
None 6
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 212
28.8%
송 31
 
4.2%
도 29
 
3.9%
면 26
 
3.5%
산 23
 
3.1%
부 21
 
2.9%
평 21
 
2.9%
수 20
 
2.7%
현 15
 
2.0%
계 14
 
1.9%
Other values (91) 324
44.0%
ASCII
ValueCountFrequency (%)
181
33.8%
, 179
33.4%
1 50
 
9.3%
2 50
 
9.3%
3 33
 
6.2%
4 23
 
4.3%
5 11
 
2.1%
6 7
 
1.3%
8 1
 
0.2%
7 1
 
0.2%
None
ValueCountFrequency (%)
· 6
100.0%

전화번호
Text

UNIQUE 

Distinct58
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size596.0 B
2023-12-12T17:14:43.568515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.017241
Min length11

Characters and Unicode

Total characters697
Distinct characters11
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

Unique58 ?
Unique (%)100.0%

Sample

1st row032-858-0606
2nd row032-463-0008
3rd row032-719-9077
4th row032-465-4207
5th row032-710-2133
ValueCountFrequency (%)
032-858-0606 1
 
1.7%
032-567-5575 1
 
1.7%
032-471-3533 1
 
1.7%
032-552-4955 1
 
1.7%
032-710-1101 1
 
1.7%
032-202-7728 1
 
1.7%
032-710-3791 1
 
1.7%
032-623-6363 1
 
1.7%
02-402-2353 1
 
1.7%
032-546-3300 1
 
1.7%
Other values (48) 48
82.8%
2023-12-12T17:14:44.106618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 116
16.6%
0 111
15.9%
3 108
15.5%
2 97
13.9%
7 53
7.6%
5 49
7.0%
1 48
6.9%
4 34
 
4.9%
6 31
 
4.4%
9 29
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 581
83.4%
Dash Punctuation 116
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 111
19.1%
3 108
18.6%
2 97
16.7%
7 53
9.1%
5 49
8.4%
1 48
8.3%
4 34
 
5.9%
6 31
 
5.3%
9 29
 
5.0%
8 21
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 697
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 116
16.6%
0 111
15.9%
3 108
15.5%
2 97
13.9%
7 53
7.6%
5 49
7.0%
1 48
6.9%
4 34
 
4.9%
6 31
 
4.4%
9 29
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 697
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 116
16.6%
0 111
15.9%
3 108
15.5%
2 97
13.9%
7 53
7.6%
5 49
7.0%
1 48
6.9%
4 34
 
4.9%
6 31
 
4.4%
9 29
 
4.2%

Correlations

2023-12-12T17:14:44.241635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관세무사명소속마을전화번호
기관1.0001.0001.0001.000
세무사명1.0001.0001.0001.000
소속마을1.0001.0001.0001.000
전화번호1.0001.0001.0001.000

Missing values

2023-12-12T17:14:41.074621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:14:41.214417image/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

기관세무사명소속마을전화번호
0시청손영철시본청032-858-0606
1시청정용은시본청032-463-0008
2중구이경원신포동, 연안동, 신흥동, 북성동, 송월동032-719-9077
3중구조은혜도원동, 율목동, 동인천동, 영종동, 영종1동, 운서동, 용유동032-465-4207
4동구서두범만석동, 화수1·화평동, 송림4동, 송림6동032-710-2133
5동구배호식화수2동, 송현1·2동, 송림4동, 송림6동032-716-6290
6동구김창수송현3동, 송림1동, 송림2동, 송림3·5동, 금창동032-832-3060
7미추홀구고재성숭의1·3동, 숭의2동, 숭의4동, 용현5동032-777-2777
8미추홀구유광수학익1동, 학익2동, 도화1동032-223-7870
9미추홀구민상원용현2동, 용현3동, 용현1·4동032-463-3120
기관세무사명소속마을전화번호
48서구이흥현가좌1동, 가좌2동, 가좌3동, 가좌4동, 연희동032-569-0200
49서구강명길청라1동, 청라2동, 청라3동032-563-7692
50서구가순태가정1동, 가정2동, 가정3동032-715-5678
51서구김한수신현원창동, 석남1동, 석남2동, 석남3동032-566-9338
52서구임병호불로대곡동, 원당동, 마전동, 아라동032-565-3343
53서구이대주검단동, 오류왕길동070-4047-7177
54강화군이재봉강화읍, 내가면, 하점면, 양사면, 송해면, 교동면, 삼산면, 서도면032-933-3205
55강화군이기흥강화읍, 선원면, 불은면, 길상면, 화도면, 양도면032-933-3941
56옹진군신원덕북도면, 연평면, 백령면, 대청면, 덕적면, 자월면, 영흥면032-471-3533
57옹진군배승호북도면, 연평면, 백령면, 대청면, 덕적면, 자월면, 영흥면032-710-5019