Overview

Dataset statistics

Number of variables5
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory43.8 B

Variable types

Categorical2
Text3

Dataset

Description강원특별자치도 마을세무사 배치현황 정보(세무사 성명, 세무사 연락처 등) 데이터를 제공합니다. * 마을세무사란? : 주민들의 세금고민 해결을 위해 무료 세무상담 서비스(재능기부)를 제공하기로 약속한 우리 이웃 세무사입니다.
URLhttps://www.data.go.kr/data/15033666/fileData.do

Alerts

광역 has constant value ""Constant

Reproduction

Analysis started2023-12-12 23:58:44.318869
Analysis finished2023-12-12 23:58:44.641011
Duration0.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

광역
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
강원특별자치도
35 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원특별자치도 35
100.0%

Length

2023-12-13T08:58:44.714374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:58:44.792208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원특별자치도 35
100.0%

기초
Text

Distinct18
Distinct (%)51.4%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T08:58:44.904337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters105
Distinct characters32
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

Unique13 ?
Unique (%)37.1%

Sample

1st row춘천시
2nd row춘천시
3rd row춘천시
4th row춘천시
5th row춘천시
ValueCountFrequency (%)
원주시 8
22.9%
춘천시 7
20.0%
동해시 3
 
8.6%
강릉시 2
 
5.7%
횡성군 2
 
5.7%
화천군 1
 
2.9%
정선군 1
 
2.9%
고성군 1
 
2.9%
인제군 1
 
2.9%
양구군 1
 
2.9%
Other values (8) 8
22.9%
2023-12-13T08:58:45.122857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 23
21.9%
군 12
11.4%
원 9
 
8.6%
천 9
 
8.6%
주 8
 
7.6%
춘 7
 
6.7%
양 3
 
2.9%
성 3
 
2.9%
해 3
 
2.9%
동 3
 
2.9%
Other values (22) 25
23.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 23
21.9%
군 12
11.4%
원 9
 
8.6%
천 9
 
8.6%
주 8
 
7.6%
춘 7
 
6.7%
양 3
 
2.9%
성 3
 
2.9%
해 3
 
2.9%
동 3
 
2.9%
Other values (22) 25
23.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 23
21.9%
군 12
11.4%
원 9
 
8.6%
천 9
 
8.6%
주 8
 
7.6%
춘 7
 
6.7%
양 3
 
2.9%
성 3
 
2.9%
해 3
 
2.9%
동 3
 
2.9%
Other values (22) 25
23.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 23
21.9%
군 12
11.4%
원 9
 
8.6%
천 9
 
8.6%
주 8
 
7.6%
춘 7
 
6.7%
양 3
 
2.9%
성 3
 
2.9%
해 3
 
2.9%
동 3
 
2.9%
Other values (22) 25
23.8%

성명
Text

Distinct33
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T08:58:45.286848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters105
Distinct characters57
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

Unique31 ?
Unique (%)88.6%

Sample

1st row양종천
2nd row남은희
3rd row김보경
4th row최민섭
5th row이창희
ValueCountFrequency (%)
박기석 2
 
5.7%
장종호 2
 
5.7%
양종천 1
 
2.9%
강용태 1
 
2.9%
박동운 1
 
2.9%
전우철 1
 
2.9%
정원배 1
 
2.9%
이석우 1
 
2.9%
김형식 1
 
2.9%
위재민 1
 
2.9%
Other values (23) 23
65.7%
2023-12-13T08:58:45.556571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
박 6
 
5.7%
김 6
 
5.7%
석 4
 
3.8%
종 4
 
3.8%
이 4
 
3.8%
창 3
 
2.9%
원 3
 
2.9%
용 3
 
2.9%
우 3
 
2.9%
정 3
 
2.9%
Other values (47) 66
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
박 6
 
5.7%
김 6
 
5.7%
석 4
 
3.8%
종 4
 
3.8%
이 4
 
3.8%
창 3
 
2.9%
원 3
 
2.9%
용 3
 
2.9%
우 3
 
2.9%
정 3
 
2.9%
Other values (47) 66
62.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
박 6
 
5.7%
김 6
 
5.7%
석 4
 
3.8%
종 4
 
3.8%
이 4
 
3.8%
창 3
 
2.9%
원 3
 
2.9%
용 3
 
2.9%
우 3
 
2.9%
정 3
 
2.9%
Other values (47) 66
62.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
박 6
 
5.7%
김 6
 
5.7%
석 4
 
3.8%
종 4
 
3.8%
이 4
 
3.8%
창 3
 
2.9%
원 3
 
2.9%
용 3
 
2.9%
우 3
 
2.9%
정 3
 
2.9%
Other values (47) 66
62.9%

담당구역
Categorical

Distinct12
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
관내일원
24 
흥업면, 일산동, 무실동
 
1
문막읍, 소초면, 호저면, 단구동
 
1
봉산동, 행구동, 반곡관설동
 
1
개운동, 우산동, 원인동
 
1
Other values (7)
7 

Length

Max length23
Median length4
Mean length7.5142857
Min length4

Unique

Unique11 ?
Unique (%)31.4%

Sample

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

Common Values

ValueCountFrequency (%)
관내일원 24
68.6%
흥업면, 일산동, 무실동 1
 
2.9%
문막읍, 소초면, 호저면, 단구동 1
 
2.9%
봉산동, 행구동, 반곡관설동 1
 
2.9%
개운동, 우산동, 원인동 1
 
2.9%
명륜1,2동, 학성동, 단계동 1
 
2.9%
판부면, 중앙동, 태장1동 1
 
2.9%
지정면, 부론면, 귀래면, 신림면 1
 
2.9%
문막읍, 반곡관설동, 태장2동 1
 
2.9%
부곡동, 동호동, 발한동, 묵호동, 망상동 1
 
2.9%
Other values (2) 2
 
5.7%

Length

2023-12-13T08:58:45.682649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
관내일원 24
40.0%
반곡관설동 2
 
3.3%
문막읍 2
 
3.3%
부론면 1
 
1.7%
귀래면 1
 
1.7%
신림면 1
 
1.7%
태장2동 1
 
1.7%
부곡동 1
 
1.7%
동호동 1
 
1.7%
발한동 1
 
1.7%
Other values (25) 25
41.7%

전화번호
Text

Distinct33
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T08:58:45.839941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.057143
Min length12

Characters and Unicode

Total characters422
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

Unique31 ?
Unique (%)88.6%

Sample

1st row033-264-2237
2nd row033-264-1354
3rd row033-256-3331
4th row033-264-4480
5th row033-911-3344
ValueCountFrequency (%)
033-638-6771 2
 
5.7%
033-553-3193 2
 
5.7%
033-264-2237 1
 
2.9%
033-535-6688 1
 
2.9%
033-244-9001 1
 
2.9%
033-482-8500 1
 
2.9%
033-244-8077 1
 
2.9%
033-452-9033 1
 
2.9%
033-642-1472 1
 
2.9%
033-373-4500 1
 
2.9%
Other values (23) 23
65.7%
2023-12-13T08:58:46.118803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 107
25.4%
- 70
16.6%
0 68
16.1%
4 31
 
7.3%
7 28
 
6.6%
5 27
 
6.4%
2 26
 
6.2%
1 20
 
4.7%
6 19
 
4.5%
8 17
 
4.0%
Other values (2) 9
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 351
83.2%
Dash Punctuation 70
 
16.6%
Math Symbol 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 107
30.5%
0 68
19.4%
4 31
 
8.8%
7 28
 
8.0%
5 27
 
7.7%
2 26
 
7.4%
1 20
 
5.7%
6 19
 
5.4%
8 17
 
4.8%
9 8
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 422
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 107
25.4%
- 70
16.6%
0 68
16.1%
4 31
 
7.3%
7 28
 
6.6%
5 27
 
6.4%
2 26
 
6.2%
1 20
 
4.7%
6 19
 
4.5%
8 17
 
4.0%
Other values (2) 9
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 107
25.4%
- 70
16.6%
0 68
16.1%
4 31
 
7.3%
7 28
 
6.6%
5 27
 
6.4%
2 26
 
6.2%
1 20
 
4.7%
6 19
 
4.5%
8 17
 
4.0%
Other values (2) 9
 
2.1%

Correlations

2023-12-13T08:58:46.195366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기초성명담당구역전화번호
기초1.0000.0000.0000.000
성명0.0001.0001.0001.000
담당구역0.0001.0001.0001.000
전화번호0.0001.0001.0001.000

Missing values

2023-12-13T08:58:44.513232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:58:44.600804image/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

광역기초성명담당구역전화번호
0강원특별자치도춘천시양종천관내일원033-264-2237
1강원특별자치도춘천시남은희관내일원033-264-1354
2강원특별자치도춘천시김보경관내일원033-256-3331
3강원특별자치도춘천시최민섭관내일원033-264-4480
4강원특별자치도춘천시이창희관내일원033-911-3344
5강원특별자치도춘천시박상희관내일원033-252-1100
6강원특별자치도춘천시안태환관내일원033-264-2238
7강원특별자치도원주시김창수흥업면, 일산동, 무실동033-747-5800
8강원특별자치도원주시성용석문막읍, 소초면, 호저면, 단구동033-742-3773
9강원특별자치도원주시김종대봉산동, 행구동, 반곡관설동033-735-1900
광역기초성명담당구역전화번호
25강원특별자치도횡성군이홍명관내일원033-344-6100
26강원특별자치도영월군위재민관내일원033-373-4500
27강원특별자치도평창군김형곤관내일원033-335-3500
28강원특별자치도정선군장종호관내일원033-553-3193
29강원특별자치도철원군이석우관내일원033-452-9033
30강원특별자치도화천군정원배관내일원033-244-8077
31강원특별자치도양구군전우철관내일원033-482-8500
32강원특별자치도인제군박동운관내일원033-244-9001
33강원특별자치도고성군유태원관내일원033-638-8100
34강원특별자치도양양군박기석관내일원033-638-6771