Overview

Dataset statistics

Number of variables6
Number of observations45
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory51.9 B

Variable types

Numeric1
Text3
Categorical2

Dataset

Description2022년 1월 기준 부산광역시 부산진구 소재 행정사 사무소 현황에 대한 데이터로 행정사사무소명, 행정사 성명, 소재지를 제공합니다. (휴업 또는 폐업한 사무소 제외)
Author부산광역시 부산진구
URLhttps://www.data.go.kr/data/15007219/fileData.do

Alerts

행정사종류 is highly overall correlated with 외국어구분High correlation
외국어구분 is highly overall correlated with 행정사종류High correlation
행정사종류 is highly imbalanced (73.8%)Imbalance
외국어구분 is highly imbalanced (73.8%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:59:38.514389
Analysis finished2023-12-12 18:59:39.385964
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23
Minimum1
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-13T03:59:39.501153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.2
Q112
median23
Q334
95-th percentile42.8
Maximum45
Range44
Interquartile range (IQR)22

Descriptive statistics

Standard deviation13.133926
Coefficient of variation (CV)0.57104024
Kurtosis-1.2
Mean23
Median Absolute Deviation (MAD)11
Skewness0
Sum1035
Variance172.5
MonotonicityStrictly increasing
2023-12-13T03:59:39.690337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 1
 
2.2%
35 1
 
2.2%
26 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%
36 1
2.2%

사무소명칭
Text

Distinct44
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-13T03:59:40.473752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length9.5555556
Min length5

Characters and Unicode

Total characters430
Distinct characters90
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)95.6%

Sample

1st row세종행정사사무소
2nd row김정수행정사사무소
3rd row삼지국제행정사사무소
4th rowYES VISA 행정사
5th row삼지국제행정사사무소
ValueCountFrequency (%)
행정사 17
20.5%
행정사사무소 13
 
15.7%
사무소 4
 
4.8%
삼지국제행정사사무소 2
 
2.4%
영남 1
 
1.2%
정혁모사무소 1
 
1.2%
신삼섭 1
 
1.2%
최현민 1
 
1.2%
dit 1
 
1.2%
박 1
 
1.2%
Other values (41) 41
49.4%
2023-12-13T03:59:41.037986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 84
19.5%
정 49
11.4%
행 45
 
10.5%
무 40
 
9.3%
소 39
 
9.1%
38
 
8.8%
김 9
 
2.1%
석 5
 
1.2%
박 4
 
0.9%
삼 3
 
0.7%
Other values (80) 114
26.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 376
87.4%
Space Separator 38
 
8.8%
Uppercase Letter 10
 
2.3%
Lowercase Letter 6
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 84
22.3%
정 49
13.0%
행 45
12.0%
무 40
10.6%
소 39
10.4%
김 9
 
2.4%
석 5
 
1.3%
박 4
 
1.1%
삼 3
 
0.8%
실 3
 
0.8%
Other values (68) 95
25.3%
Uppercase Letter
ValueCountFrequency (%)
S 2
20.0%
I 2
20.0%
T 1
10.0%
D 1
10.0%
Y 1
10.0%
E 1
10.0%
V 1
10.0%
A 1
10.0%
Lowercase Letter
ValueCountFrequency (%)
d 2
33.3%
n 2
33.3%
a 2
33.3%
Space Separator
ValueCountFrequency (%)
38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 376
87.4%
Common 38
 
8.8%
Latin 16
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 84
22.3%
정 49
13.0%
행 45
12.0%
무 40
10.6%
소 39
10.4%
김 9
 
2.4%
석 5
 
1.3%
박 4
 
1.1%
삼 3
 
0.8%
실 3
 
0.8%
Other values (68) 95
25.3%
Latin
ValueCountFrequency (%)
d 2
12.5%
n 2
12.5%
a 2
12.5%
S 2
12.5%
I 2
12.5%
T 1
6.2%
D 1
6.2%
Y 1
6.2%
E 1
6.2%
V 1
6.2%
Common
ValueCountFrequency (%)
38
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 376
87.4%
ASCII 54
 
12.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 84
22.3%
정 49
13.0%
행 45
12.0%
무 40
10.6%
소 39
10.4%
김 9
 
2.4%
석 5
 
1.3%
박 4
 
1.1%
삼 3
 
0.8%
실 3
 
0.8%
Other values (68) 95
25.3%
ASCII
ValueCountFrequency (%)
38
70.4%
d 2
 
3.7%
n 2
 
3.7%
a 2
 
3.7%
S 2
 
3.7%
I 2
 
3.7%
T 1
 
1.9%
D 1
 
1.9%
Y 1
 
1.9%
E 1
 
1.9%
Other values (2) 2
 
3.7%

행정사종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size492.0 B
일반행정사
42 
외국어번역행정사(일본어)
 
2
외국어번역행정사(영어)
 
1

Length

Max length13
Median length5
Mean length5.5111111
Min length5

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st row일반행정사
2nd row일반행정사
3rd row일반행정사
4th row일반행정사
5th row외국어번역행정사(영어)

Common Values

ValueCountFrequency (%)
일반행정사 42
93.3%
외국어번역행정사(일본어) 2
 
4.4%
외국어번역행정사(영어) 1
 
2.2%

Length

2023-12-13T03:59:41.287586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:59:41.495966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반행정사 42
93.3%
외국어번역행정사(일본어 2
 
4.4%
외국어번역행정사(영어 1
 
2.2%

행정사 성명
Text

Distinct44
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-13T03:59:41.801804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters135
Distinct characters72
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

Unique43 ?
Unique (%)95.6%

Sample

1st row문영규
2nd row김정수
3rd row김종식
4th row임서목
5th row김종식
ValueCountFrequency (%)
김종식 2
 
4.4%
문영규 1
 
2.2%
김영식 1
 
2.2%
정혁모 1
 
2.2%
신삼섭 1
 
2.2%
최현민 1
 
2.2%
윤대건 1
 
2.2%
박인구 1
 
2.2%
조용일 1
 
2.2%
박석만 1
 
2.2%
Other values (34) 34
75.6%
2023-12-13T03:59:42.314682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 17
 
12.6%
영 6
 
4.4%
석 5
 
3.7%
정 5
 
3.7%
식 4
 
3.0%
규 4
 
3.0%
종 3
 
2.2%
조 3
 
2.2%
박 3
 
2.2%
윤 3
 
2.2%
Other values (62) 82
60.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 135
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 17
 
12.6%
영 6
 
4.4%
석 5
 
3.7%
정 5
 
3.7%
식 4
 
3.0%
규 4
 
3.0%
종 3
 
2.2%
조 3
 
2.2%
박 3
 
2.2%
윤 3
 
2.2%
Other values (62) 82
60.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 135
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 17
 
12.6%
영 6
 
4.4%
석 5
 
3.7%
정 5
 
3.7%
식 4
 
3.0%
규 4
 
3.0%
종 3
 
2.2%
조 3
 
2.2%
박 3
 
2.2%
윤 3
 
2.2%
Other values (62) 82
60.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 135
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 17
 
12.6%
영 6
 
4.4%
석 5
 
3.7%
정 5
 
3.7%
식 4
 
3.0%
규 4
 
3.0%
종 3
 
2.2%
조 3
 
2.2%
박 3
 
2.2%
윤 3
 
2.2%
Other values (62) 82
60.7%

외국어구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size492.0 B
42 
일본어
 
2
영어
 
1

Length

Max length3
Median length1
Mean length1.1111111
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st row
2nd row
3rd row
4th row
5th row영어

Common Values

ValueCountFrequency (%)
42
93.3%
일본어 2
 
4.4%
영어 1
 
2.2%

Length

2023-12-13T03:59:42.555681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:59:42.786124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일본어 2
66.7%
영어 1
33.3%

사무소 주소
Text

Distinct38
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-13T03:59:43.172614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length40
Mean length29.844444
Min length22

Characters and Unicode

Total characters1343
Distinct characters97
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)75.6%

Sample

1st row부산광역시 부산진구 중앙대로 981， 105호(양정동)
2nd row부산광역시 부산진구 전포대로199번길 43， 3층 16호(전포동)
3rd row부산광역시 부산진구 엄광로509번길 9-5 (범천동)
4th row부산광역시 부산진구 전포대로275번길 20， 102동 101호 (전포동， 서면롯데캐슬스카이)
5th row부산광역시 부산진구 엄광로509번길 9-5 (범천동)
ValueCountFrequency (%)
부산광역시 45
17.7%
부산진구 45
17.7%
부전동 18
 
7.1%
부전로 8
 
3.1%
새싹로 7
 
2.8%
양정동 6
 
2.4%
109-1 5
 
2.0%
범천동 5
 
2.0%
가야대로 4
 
1.6%
부전동， 4
 
1.6%
Other values (95) 107
42.1%
2023-12-13T03:59:43.940175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
209
 
15.6%
부 121
 
9.0%
산 90
 
6.7%
동 55
 
4.1%
1 49
 
3.6%
광 48
 
3.6%
시 46
 
3.4%
진 46
 
3.4%
( 45
 
3.4%
역 45
 
3.4%
Other values (87) 589
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 811
60.4%
Space Separator 209
 
15.6%
Decimal Number 196
 
14.6%
Open Punctuation 45
 
3.4%
Close Punctuation 45
 
3.4%
Other Punctuation 23
 
1.7%
Dash Punctuation 13
 
1.0%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 121
14.9%
산 90
 
11.1%
동 55
 
6.8%
광 48
 
5.9%
시 46
 
5.7%
진 46
 
5.7%
역 45
 
5.5%
구 45
 
5.5%
로 45
 
5.5%
전 38
 
4.7%
Other values (70) 232
28.6%
Decimal Number
ValueCountFrequency (%)
1 49
25.0%
0 28
14.3%
2 21
10.7%
9 20
10.2%
7 17
 
8.7%
4 16
 
8.2%
5 15
 
7.7%
3 11
 
5.6%
8 10
 
5.1%
6 9
 
4.6%
Other Punctuation
ValueCountFrequency (%)
， 22
95.7%
, 1
 
4.3%
Space Separator
ValueCountFrequency (%)
209
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 811
60.4%
Common 531
39.5%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 121
14.9%
산 90
 
11.1%
동 55
 
6.8%
광 48
 
5.9%
시 46
 
5.7%
진 46
 
5.7%
역 45
 
5.5%
구 45
 
5.5%
로 45
 
5.5%
전 38
 
4.7%
Other values (70) 232
28.6%
Common
ValueCountFrequency (%)
209
39.4%
1 49
 
9.2%
( 45
 
8.5%
) 45
 
8.5%
0 28
 
5.3%
， 22
 
4.1%
2 21
 
4.0%
9 20
 
3.8%
7 17
 
3.2%
4 16
 
3.0%
Other values (6) 59
 
11.1%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 811
60.4%
ASCII 510
38.0%
None 22
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
209
41.0%
1 49
 
9.6%
( 45
 
8.8%
) 45
 
8.8%
0 28
 
5.5%
2 21
 
4.1%
9 20
 
3.9%
7 17
 
3.3%
4 16
 
3.1%
5 15
 
2.9%
Other values (6) 45
 
8.8%
Hangul
ValueCountFrequency (%)
부 121
14.9%
산 90
 
11.1%
동 55
 
6.8%
광 48
 
5.9%
시 46
 
5.7%
진 46
 
5.7%
역 45
 
5.5%
구 45
 
5.5%
로 45
 
5.5%
전 38
 
4.7%
Other values (70) 232
28.6%
None
ValueCountFrequency (%)
， 22
100.0%

Interactions

2023-12-13T03:59:38.982437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:59:44.125848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사무소명칭행정사종류행정사 성명외국어구분사무소 주소
연번1.0001.0000.0001.0000.0000.894
사무소명칭1.0001.0000.0001.0000.0001.000
행정사종류0.0000.0001.0000.0001.0000.000
행정사 성명1.0001.0000.0001.0000.0001.000
외국어구분0.0000.0001.0000.0001.0000.000
사무소 주소0.8941.0000.0001.0000.0001.000
2023-12-13T03:59:44.327341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정사종류외국어구분
행정사종류1.0001.000
외국어구분1.0001.000
2023-12-13T03:59:44.468453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정사종류외국어구분
연번1.0000.0000.000
행정사종류0.0001.0001.000
외국어구분0.0001.0001.000

Missing values

2023-12-13T03:59:39.137952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:59:39.307868image/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

연번사무소명칭행정사종류행정사 성명외국어구분사무소 주소
01세종행정사사무소일반행정사문영규부산광역시 부산진구 중앙대로 981， 105호(양정동)
12김정수행정사사무소일반행정사김정수부산광역시 부산진구 전포대로199번길 43， 3층 16호(전포동)
23삼지국제행정사사무소일반행정사김종식부산광역시 부산진구 엄광로509번길 9-5 (범천동)
34YES VISA 행정사일반행정사임서목부산광역시 부산진구 전포대로275번길 20， 102동 101호 (전포동， 서면롯데캐슬스카이)
45삼지국제행정사사무소외국어번역행정사(영어)김종식영어부산광역시 부산진구 엄광로509번길 9-5 (범천동)
56온나라 행정사 사무소일반행정사김철영부산광역시 부산진구 서전로 8， 6층 (부전동)
67배수태행정사사무소일반행정사배수태부산광역시 부산진구 양지로11번길 11， 3층 (양정동)
78푸른도시 행정사사무소일반행정사정태권부산광역시 부산진구 가야대로 635-20， 101동 2104호 (당감동， 당감동태화현대아파트)
89김춘석 행정사사무소일반행정사김춘석부산광역시 부산진구 부전로 109-1 (부전동)
910조정섭 행정사사무소일반행정사조정섭부산광역시 부산진구 새싹로 10 (부전동)
연번사무소명칭행정사종류행정사 성명외국어구분사무소 주소
3536영남 행정사사무소일반행정사김인규부산광역시 부산진구 신암로 147 (범천동)
3637유대상 행정사사무소일반행정사유대상부산광역시 부산진구 대학로 72-8 (가야동)
3738가은행정사일반행정사손영호부산광역시 부산진구 거제대로36번가길 8 (양정동)
3839행정사 최윤경사무소일반행정사최윤경부산광역시 부산진구 부전로 109-1 (부전동)
3940행정사 전규곤사무소일반행정사전규곤부산광역시 부산진구 시민공원로19번길 65， 326호 (부암동， 타워베르빌)
4041행정사 신석현사무소일반행정사신석현부산광역시 부산진구 부전로 109-1 (부전동)
4142송기정 행정사무실일반행정사송기정부산광역시 부산진구 서면문화로 27， 1602호 (부전동， 유원오피스텔)
4243행정사 김길남사무소일반행정사김길남부산광역시 부산진구 부전로 109-1 (부전동)
4344백남웅 행정사사무소일반행정사백남웅부산광역시 부산진구 새싹로 4 (부전동)
4445행정사 김종곤사무소일반행정사김종곤부산광역시 부산진구 새싹로 76 (범전동)