Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells9154
Missing cells (%)5.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory139.0 B

Variable types

Text7
Categorical4
Numeric2
Boolean1
DateTime2

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실)
Author행정안전부
URLhttps://www.data.go.kr/data/15107743/standard.do

Alerts

데이터기준일자 has constant value ""Constant
제공기관코드 has constant value ""Constant
제공기관명 has constant value ""Constant
행정사종류 is highly imbalanced (91.7%)Imbalance
대표행정사여부 is highly imbalanced (79.3%)Imbalance
운영상태 is highly imbalanced (68.2%)Imbalance
소재지도로명주소 has 782 (7.8%) missing valuesMissing
소재지지번주소 has 3796 (38.0%) missing valuesMissing
행정사사무소전화번호 has 4576 (45.8%) missing valuesMissing

Reproduction

Analysis started2024-03-15 00:05:02.129036
Analysis finished2024-03-15 00:05:08.276289
Duration6.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사무소명
Text

Distinct8780
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T09:05:09.333019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length9.469
Min length2

Characters and Unicode

Total characters94690
Distinct characters742
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8113 ?
Unique (%)81.1%

Sample

1st row유대상 행정사사무소
2nd row뉴 스마트 행정사 사무소
3rd row대경행정사
4th row최진규행정사
5th row한국가정행복연구원
ValueCountFrequency (%)
행정사 2675
 
14.8%
사무소 2141
 
11.9%
행정사사무소 1559
 
8.6%
행정사법인 150
 
0.8%
합동사무소 112
 
0.6%
행정사무소 100
 
0.6%
행정사합동사무소 99
 
0.5%
일반행정사 92
 
0.5%
더나은 29
 
0.2%
법무사 28
 
0.2%
Other values (8691) 11071
61.3%
2024-03-15T09:05:11.194213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 17556
18.5%
정 10366
 
10.9%
행 9843
 
10.4%
무 8157
 
8.6%
소 8070
 
8.5%
8062
 
8.5%
이 1009
 
1.1%
김 914
 
1.0%
동 651
 
0.7%
인 603
 
0.6%
Other values (732) 29459
31.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84677
89.4%
Space Separator 8062
 
8.5%
Uppercase Letter 1268
 
1.3%
Lowercase Letter 401
 
0.4%
Decimal Number 231
 
0.2%
Other Punctuation 20
 
< 0.1%
Open Punctuation 10
 
< 0.1%
Close Punctuation 9
 
< 0.1%
Connector Punctuation 5
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 17556
20.7%
정 10366
 
12.2%
행 9843
 
11.6%
무 8157
 
9.6%
소 8070
 
9.5%
이 1009
 
1.2%
김 914
 
1.1%
동 651
 
0.8%
인 603
 
0.7%
한 497
 
0.6%
Other values (663) 27011
31.9%
Uppercase Letter
ValueCountFrequency (%)
K 142
 
11.2%
S 137
 
10.8%
A 103
 
8.1%
J 76
 
6.0%
O 69
 
5.4%
C 66
 
5.2%
I 65
 
5.1%
M 57
 
4.5%
H 56
 
4.4%
E 52
 
4.1%
Other values (15) 445
35.1%
Lowercase Letter
ValueCountFrequency (%)
n 51
12.7%
o 44
11.0%
e 41
10.2%
a 39
9.7%
i 30
 
7.5%
t 27
 
6.7%
l 27
 
6.7%
r 23
 
5.7%
s 21
 
5.2%
h 15
 
3.7%
Other values (13) 83
20.7%
Decimal Number
ValueCountFrequency (%)
1 77
33.3%
2 54
23.4%
4 35
15.2%
9 15
 
6.5%
5 14
 
6.1%
8 13
 
5.6%
3 11
 
4.8%
0 5
 
2.2%
6 5
 
2.2%
7 2
 
0.9%
Other Punctuation
ValueCountFrequency (%)
/ 10
50.0%
· 5
25.0%
& 3
 
15.0%
， 2
 
10.0%
Math Symbol
ValueCountFrequency (%)
+ 4
80.0%
→ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
8062
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84582
89.3%
Common 8344
 
8.8%
Latin 1669
 
1.8%
Han 95
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 17556
20.8%
정 10366
 
12.3%
행 9843
 
11.6%
무 8157
 
9.6%
소 8070
 
9.5%
이 1009
 
1.2%
김 914
 
1.1%
동 651
 
0.8%
인 603
 
0.7%
한 497
 
0.6%
Other values (594) 26916
31.8%
Han
ValueCountFrequency (%)
正 7
 
7.4%
人 5
 
5.3%
明 3
 
3.2%
道 3
 
3.2%
政 3
 
3.2%
大 3
 
3.2%
友 2
 
2.1%
悠 2
 
2.1%
好 2
 
2.1%
多 2
 
2.1%
Other values (59) 63
66.3%
Latin
ValueCountFrequency (%)
K 142
 
8.5%
S 137
 
8.2%
A 103
 
6.2%
J 76
 
4.6%
O 69
 
4.1%
C 66
 
4.0%
I 65
 
3.9%
M 57
 
3.4%
H 56
 
3.4%
E 52
 
3.1%
Other values (38) 846
50.7%
Common
ValueCountFrequency (%)
8062
96.6%
1 77
 
0.9%
2 54
 
0.6%
4 35
 
0.4%
9 15
 
0.2%
5 14
 
0.2%
8 13
 
0.2%
3 11
 
0.1%
( 10
 
0.1%
/ 10
 
0.1%
Other values (11) 43
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84579
89.3%
ASCII 10005
 
10.6%
CJK 93
 
0.1%
None 7
 
< 0.1%
Compat Jamo 3
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 17556
20.8%
정 10366
 
12.3%
행 9843
 
11.6%
무 8157
 
9.6%
소 8070
 
9.5%
이 1009
 
1.2%
김 914
 
1.1%
동 651
 
0.8%
인 603
 
0.7%
한 497
 
0.6%
Other values (593) 26913
31.8%
ASCII
ValueCountFrequency (%)
8062
80.6%
K 142
 
1.4%
S 137
 
1.4%
A 103
 
1.0%
1 77
 
0.8%
J 76
 
0.8%
O 69
 
0.7%
C 66
 
0.7%
I 65
 
0.6%
M 57
 
0.6%
Other values (56) 1151
 
11.5%
CJK
ValueCountFrequency (%)
正 7
 
7.5%
人 5
 
5.4%
明 3
 
3.2%
道 3
 
3.2%
政 3
 
3.2%
大 3
 
3.2%
友 2
 
2.2%
悠 2
 
2.2%
好 2
 
2.2%
多 2
 
2.2%
Other values (57) 61
65.6%
None
ValueCountFrequency (%)
· 5
71.4%
， 2
 
28.6%
Compat Jamo
ValueCountFrequency (%)
ㅇ 3
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
律 1
50.0%
利 1
50.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

행정사종류
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반행정사
9675 
외국어번역행정사(영어)
 
208
해사행정사
 
51
외국어번역행정사(중국어)
 
28
외국어번역행정사(일본어)
 
23
Other values (4)
 
15

Length

Max length14
Median length5
Mean length5.1995
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반행정사 9675
96.8%
외국어번역행정사(영어) 208
 
2.1%
해사행정사 51
 
0.5%
외국어번역행정사(중국어) 28
 
0.3%
외국어번역행정사(일본어) 23
 
0.2%
외국어번역행정사(프랑스어) 5
 
0.1%
외국어번역행정사(독일어) 4
 
< 0.1%
외국어번역행정사(러시아어) 4
 
< 0.1%
외국어번역행정사(스페인어) 2
 
< 0.1%

Length

2024-03-15T09:05:11.604999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:05:11.944921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반행정사 9675
96.8%
외국어번역행정사(영어 208
 
2.1%
해사행정사 51
 
0.5%
외국어번역행정사(중국어 28
 
0.3%
외국어번역행정사(일본어 23
 
0.2%
외국어번역행정사(프랑스어 5
 
< 0.1%
외국어번역행정사(독일어 4
 
< 0.1%
외국어번역행정사(러시아어 4
 
< 0.1%
외국어번역행정사(스페인어 2
 
< 0.1%

행정사자격증번호
Text

Distinct9982
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T09:05:12.774915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length11
Mean length12.5944
Min length11

Characters and Unicode

Total characters125944
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9965 ?
Unique (%)99.7%

Sample

1st rowT329000012100000050
2nd row17101025227
3rd row15101015673
4th rowT318000012100000196
5th rowT468000012100000066
ValueCountFrequency (%)
13100000204 3
 
< 0.1%
14101020723 2
 
< 0.1%
21101014552 2
 
< 0.1%
15101043681 2
 
< 0.1%
16101059112 2
 
< 0.1%
14101055053 2
 
< 0.1%
14101012209 2
 
< 0.1%
17102044751 2
 
< 0.1%
20102017038 2
 
< 0.1%
22110009075 2
 
< 0.1%
Other values (9972) 9979
99.8%
2024-03-15T09:05:14.030015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 47634
37.8%
1 29329
23.3%
3 9315
 
7.4%
2 8543
 
6.8%
4 6591
 
5.2%
5 5274
 
4.2%
6 4889
 
3.9%
7 4479
 
3.6%
8 4269
 
3.4%
9 3628
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 123951
98.4%
Uppercase Letter 1993
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 47634
38.4%
1 29329
23.7%
3 9315
 
7.5%
2 8543
 
6.9%
4 6591
 
5.3%
5 5274
 
4.3%
6 4889
 
3.9%
7 4479
 
3.6%
8 4269
 
3.4%
9 3628
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
T 1993
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 123951
98.4%
Latin 1993
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 47634
38.4%
1 29329
23.7%
3 9315
 
7.5%
2 8543
 
6.9%
4 6591
 
5.3%
5 5274
 
4.3%
6 4889
 
3.9%
7 4479
 
3.6%
8 4269
 
3.4%
9 3628
 
2.9%
Latin
ValueCountFrequency (%)
T 1993
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 125944
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 47634
37.8%
1 29329
23.3%
3 9315
 
7.4%
2 8543
 
6.8%
4 6591
 
5.2%
5 5274
 
4.2%
6 4889
 
3.9%
7 4479
 
3.6%
8 4269
 
3.4%
9 3628
 
2.9%

소재지도로명주소
Text

MISSING 

Distinct8429
Distinct (%)91.4%
Missing782
Missing (%)7.8%
Memory size156.2 KiB
2024-03-15T09:05:15.469292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length54
Mean length32.189412
Min length17

Characters and Unicode

Total characters296722
Distinct characters715
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7935 ?
Unique (%)86.1%

Sample

1st row부산광역시 부산진구 대학로 72-8 (가야동)
2nd row경기도 시흥시 시청로72번길 6 (장현동)
3rd row대구광역시 달성군 논공읍 논공로7길 30-17
4th row서울특별시 영등포구 당산로 217 (당산동5가)
5th row전북특별자치도 익산시 선화로 210 (남중동)
ValueCountFrequency (%)
서울특별시 2810
 
4.8%
경기도 2356
 
4.0%
부산광역시 478
 
0.8%
경상남도 413
 
0.7%
2층 408
 
0.7%
서초구 407
 
0.7%
중구 393
 
0.7%
인천광역시 384
 
0.7%
1층 376
 
0.6%
대구광역시 343
 
0.6%
Other values (14406) 49878
85.6%
2024-03-15T09:05:18.201832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49028
 
16.5%
1 11848
 
4.0%
동 11108
 
3.7%
시 9078
 
3.1%
로 8943
 
3.0%
( 8233
 
2.8%
) 8233
 
2.8%
2 7763
 
2.6%
, 7528
 
2.5%
구 7194
 
2.4%
Other values (705) 167766
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 169115
57.0%
Decimal Number 51398
 
17.3%
Space Separator 49028
 
16.5%
Open Punctuation 8234
 
2.8%
Close Punctuation 8234
 
2.8%
Other Punctuation 7985
 
2.7%
Dash Punctuation 1865
 
0.6%
Uppercase Letter 760
 
0.3%
Lowercase Letter 77
 
< 0.1%
Letter Number 16
 
< 0.1%
Other values (2) 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 11108
 
6.6%
시 9078
 
5.4%
로 8943
 
5.3%
구 7194
 
4.3%
도 5095
 
3.0%
서 5043
 
3.0%
호 4869
 
2.9%
길 3700
 
2.2%
별 3583
 
2.1%
특 3551
 
2.1%
Other values (632) 106951
63.2%
Uppercase Letter
ValueCountFrequency (%)
B 185
24.3%
A 117
15.4%
C 66
 
8.7%
S 53
 
7.0%
E 34
 
4.5%
I 33
 
4.3%
K 33
 
4.3%
D 29
 
3.8%
T 27
 
3.6%
W 23
 
3.0%
Other values (16) 160
21.1%
Lowercase Letter
ValueCountFrequency (%)
e 20
26.0%
t 8
 
10.4%
i 7
 
9.1%
r 4
 
5.2%
s 4
 
5.2%
a 4
 
5.2%
b 4
 
5.2%
y 3
 
3.9%
k 3
 
3.9%
o 3
 
3.9%
Other values (10) 17
22.1%
Decimal Number
ValueCountFrequency (%)
1 11848
23.1%
2 7763
15.1%
0 6903
13.4%
3 5744
11.2%
4 4250
 
8.3%
5 3894
 
7.6%
6 3170
 
6.2%
7 2862
 
5.6%
8 2602
 
5.1%
9 2362
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 7528
94.3%
， 434
 
5.4%
. 15
 
0.2%
· 7
 
0.1%
@ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 8
50.0%
Ⅰ 7
43.8%
Ⅲ 1
 
6.2%
Open Punctuation
ValueCountFrequency (%)
( 8233
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 8233
> 99.9%
] 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 8
88.9%
+ 1
 
11.1%
Space Separator
ValueCountFrequency (%)
49028
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1865
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 169116
57.0%
Common 126753
42.7%
Latin 853
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 11108
 
6.6%
시 9078
 
5.4%
로 8943
 
5.3%
구 7194
 
4.3%
도 5095
 
3.0%
서 5043
 
3.0%
호 4869
 
2.9%
길 3700
 
2.2%
별 3583
 
2.1%
특 3551
 
2.1%
Other values (633) 106952
63.2%
Latin
ValueCountFrequency (%)
B 185
21.7%
A 117
13.7%
C 66
 
7.7%
S 53
 
6.2%
E 34
 
4.0%
I 33
 
3.9%
K 33
 
3.9%
D 29
 
3.4%
T 27
 
3.2%
W 23
 
2.7%
Other values (39) 253
29.7%
Common
ValueCountFrequency (%)
49028
38.7%
1 11848
 
9.3%
( 8233
 
6.5%
) 8233
 
6.5%
2 7763
 
6.1%
, 7528
 
5.9%
0 6903
 
5.4%
3 5744
 
4.5%
4 4250
 
3.4%
5 3894
 
3.1%
Other values (13) 13329
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 169114
57.0%
ASCII 127149
42.9%
None 442
 
0.1%
Number Forms 16
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49028
38.6%
1 11848
 
9.3%
( 8233
 
6.5%
) 8233
 
6.5%
2 7763
 
6.1%
, 7528
 
5.9%
0 6903
 
5.4%
3 5744
 
4.5%
4 4250
 
3.3%
5 3894
 
3.1%
Other values (57) 13725
 
10.8%
Hangul
ValueCountFrequency (%)
동 11108
 
6.6%
시 9078
 
5.4%
로 8943
 
5.3%
구 7194
 
4.3%
도 5095
 
3.0%
서 5043
 
3.0%
호 4869
 
2.9%
길 3700
 
2.2%
별 3583
 
2.1%
특 3551
 
2.1%
Other values (631) 106950
63.2%
None
ValueCountFrequency (%)
， 434
98.2%
· 7
 
1.6%
㈜ 1
 
0.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 8
50.0%
Ⅰ 7
43.8%
Ⅲ 1
 
6.2%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

소재지지번주소
Text

MISSING 

Distinct5697
Distinct (%)91.8%
Missing3796
Missing (%)38.0%
Memory size156.2 KiB
2024-03-15T09:05:19.775739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length45
Mean length26.405222
Min length11

Characters and Unicode

Total characters163818
Distinct characters613
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5372 ?
Unique (%)86.6%

Sample

1st row부산광역시 부산진구 가야동 454번지 69호
2nd row경기도 시흥시 장현동 539번지 2호
3rd row서울특별시 영등포구 당산동5가 14번지 3호 3층
4th row전북특별자치도 익산시 남중동 238번지 6호
5th row경기도 오산시 부산동 778번지 1호 운암주공1단지아파트 109동 1804호
ValueCountFrequency (%)
서울특별시 2001
 
5.6%
경기도 1429
 
4.0%
1호 642
 
1.8%
2호 379
 
1.1%
서초구 352
 
1.0%
3호 348
 
1.0%
부산광역시 346
 
1.0%
전북특별자치도 329
 
0.9%
서초동 290
 
0.8%
경상남도 286
 
0.8%
Other values (7273) 29183
82.0%
2024-03-15T09:05:21.504191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29381
 
17.9%
1 6846
 
4.2%
동 6446
 
3.9%
시 5973
 
3.6%
호 5565
 
3.4%
지 5525
 
3.4%
번 5147
 
3.1%
구 4871
 
3.0%
2 3936
 
2.4%
3 3334
 
2.0%
Other values (603) 86794
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 101946
62.2%
Decimal Number 31322
 
19.1%
Space Separator 29381
 
17.9%
Dash Punctuation 764
 
0.5%
Uppercase Letter 276
 
0.2%
Close Punctuation 36
 
< 0.1%
Open Punctuation 36
 
< 0.1%
Other Punctuation 24
 
< 0.1%
Lowercase Letter 18
 
< 0.1%
Letter Number 13
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6446
 
6.3%
시 5973
 
5.9%
호 5565
 
5.5%
지 5525
 
5.4%
번 5147
 
5.0%
구 4871
 
4.8%
도 3294
 
3.2%
서 3221
 
3.2%
별 2625
 
2.6%
특 2615
 
2.6%
Other values (547) 56664
55.6%
Uppercase Letter
ValueCountFrequency (%)
B 45
16.3%
A 36
13.0%
S 30
10.9%
E 20
 
7.2%
K 20
 
7.2%
T 13
 
4.7%
M 13
 
4.7%
D 13
 
4.7%
C 12
 
4.3%
R 9
 
3.3%
Other values (16) 65
23.6%
Decimal Number
ValueCountFrequency (%)
1 6846
21.9%
2 3936
12.6%
3 3334
10.6%
0 3246
10.4%
4 2903
9.3%
5 2564
 
8.2%
6 2345
 
7.5%
7 2267
 
7.2%
8 1951
 
6.2%
9 1930
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 7
38.9%
a 2
 
11.1%
k 2
 
11.1%
b 2
 
11.1%
s 1
 
5.6%
t 1
 
5.6%
r 1
 
5.6%
w 1
 
5.6%
o 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 17
70.8%
@ 4
 
16.7%
. 3
 
12.5%
Letter Number
ValueCountFrequency (%)
Ⅰ 8
61.5%
Ⅱ 5
38.5%
Space Separator
ValueCountFrequency (%)
29381
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 764
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 101947
62.2%
Common 61564
37.6%
Latin 307
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6446
 
6.3%
시 5973
 
5.9%
호 5565
 
5.5%
지 5525
 
5.4%
번 5147
 
5.0%
구 4871
 
4.8%
도 3294
 
3.2%
서 3221
 
3.2%
별 2625
 
2.6%
특 2615
 
2.6%
Other values (548) 56665
55.6%
Latin
ValueCountFrequency (%)
B 45
14.7%
A 36
 
11.7%
S 30
 
9.8%
E 20
 
6.5%
K 20
 
6.5%
T 13
 
4.2%
M 13
 
4.2%
D 13
 
4.2%
C 12
 
3.9%
R 9
 
2.9%
Other values (27) 96
31.3%
Common
ValueCountFrequency (%)
29381
47.7%
1 6846
 
11.1%
2 3936
 
6.4%
3 3334
 
5.4%
0 3246
 
5.3%
4 2903
 
4.7%
5 2564
 
4.2%
6 2345
 
3.8%
7 2267
 
3.7%
8 1951
 
3.2%
Other values (8) 2791
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 101946
62.2%
ASCII 61858
37.8%
Number Forms 13
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29381
47.5%
1 6846
 
11.1%
2 3936
 
6.4%
3 3334
 
5.4%
0 3246
 
5.2%
4 2903
 
4.7%
5 2564
 
4.1%
6 2345
 
3.8%
7 2267
 
3.7%
8 1951
 
3.2%
Other values (43) 3085
 
5.0%
Hangul
ValueCountFrequency (%)
동 6446
 
6.3%
시 5973
 
5.9%
호 5565
 
5.5%
지 5525
 
5.4%
번 5147
 
5.0%
구 4871
 
4.8%
도 3294
 
3.2%
서 3221
 
3.2%
별 2625
 
2.6%
특 2615
 
2.6%
Other values (547) 56664
55.6%
Number Forms
ValueCountFrequency (%)
Ⅰ 8
61.5%
Ⅱ 5
38.5%
None
ValueCountFrequency (%)
㈜ 1
100.0%

위도
Real number (ℝ)

Distinct8285
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.797484
Minimum33.221067
Maximum38.379953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T09:05:21.928501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.221067
5-th percentile35.098589
Q135.92834
median37.368176
Q337.521517
95-th percentile37.696008
Maximum38.379953
Range5.1588869
Interquartile range (IQR)1.5931765

Descriptive statistics

Standard deviation1.0109021
Coefficient of variation (CV)0.027472043
Kurtosis0.16563844
Mean36.797484
Median Absolute Deviation (MAD)0.23114209
Skewness-1.0839985
Sum367974.84
Variance1.021923
MonotonicityNot monotonic
2024-03-15T09:05:22.395522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.56251274 27
 
0.3%
36.60175776 25
 
0.2%
37.56399274 23
 
0.2%
37.52242249 13
 
0.1%
37.52267788 12
 
0.1%
37.49187304 12
 
0.1%
37.4931402 11
 
0.1%
37.49316973 11
 
0.1%
37.45199637 11
 
0.1%
37.56156803 11
 
0.1%
Other values (8275) 9844
98.4%
ValueCountFrequency (%)
33.22106658 1
< 0.1%
33.22599337 1
< 0.1%
33.24802151 1
< 0.1%
33.251944 1
< 0.1%
33.25218803 1
< 0.1%
33.25219658 1
< 0.1%
33.25416592 1
< 0.1%
33.26253524 1
< 0.1%
33.27479848 1
< 0.1%
33.28014123 1
< 0.1%
ValueCountFrequency (%)
38.37995347 1
< 0.1%
38.37952925 1
< 0.1%
38.37808519 1
< 0.1%
38.37782924 1
< 0.1%
38.35280572 1
< 0.1%
38.31755859 1
< 0.1%
38.25295863 1
< 0.1%
38.22729626 1
< 0.1%
38.21093187 1
< 0.1%
38.20753341 1
< 0.1%

경도
Real number (ℝ)

Distinct8283
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.3455
Minimum124.71514
Maximum130.90479
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T09:05:22.832204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124.71514
5-th percentile126.67001
Q1126.90543
median127.04716
Q3127.38986
95-th percentile129.07424
Maximum130.90479
Range6.1896559
Interquartile range (IQR)0.48443107

Descriptive statistics

Standard deviation0.74986901
Coefficient of variation (CV)0.005888461
Kurtosis0.79383844
Mean127.3455
Median Absolute Deviation (MAD)0.16543365
Skewness1.4205278
Sum1273455
Variance0.56230354
MonotonicityNot monotonic
2024-03-15T09:05:23.269896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9978271 27
 
0.3%
127.2946576 25
 
0.2%
127.0077117 17
 
0.2%
126.8939302 13
 
0.1%
127.0088236 12
 
0.1%
127.1188619 11
 
0.1%
127.159592 11
 
0.1%
126.9884678 11
 
0.1%
126.8231457 11
 
0.1%
127.0130358 11
 
0.1%
Other values (8273) 9851
98.5%
ValueCountFrequency (%)
124.7151385 1
< 0.1%
124.7187809 1
< 0.1%
125.4257819 1
< 0.1%
126.097206 1
< 0.1%
126.1106418 1
< 0.1%
126.1108094 1
< 0.1%
126.205461 1
< 0.1%
126.2059282 1
< 0.1%
126.2069888 1
< 0.1%
126.2108571 1
< 0.1%
ValueCountFrequency (%)
130.9047944 1
< 0.1%
129.4734834 1
< 0.1%
129.4519933 1
< 0.1%
129.4501853 1
< 0.1%
129.4501358 1
< 0.1%
129.4442464 1
< 0.1%
129.429612 1
< 0.1%
129.4284337 1
< 0.1%
129.4278303 1
< 0.1%
129.4241325 1
< 0.1%

행정사명
Text

Distinct8518
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T09:05:24.731407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length2.9947
Min length2

Characters and Unicode

Total characters29947
Distinct characters319
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

Unique7468 ?
Unique (%)74.7%

Sample

1st row유대상
2nd row유상호
3rd row김주석
4th row최진규
5th row신유식
ValueCountFrequency (%)
김정수 9
 
0.1%
김종호 9
 
0.1%
김영근 8
 
0.1%
김영일 8
 
0.1%
김광수 7
 
0.1%
이상호 7
 
0.1%
김영철 7
 
0.1%
김용환 6
 
0.1%
김동호 6
 
0.1%
김정훈 6
 
0.1%
Other values (8513) 9932
99.3%
2024-03-15T09:05:26.346924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 2061
 
6.9%
이 1575
 
5.3%
정 918
 
3.1%
박 854
 
2.9%
영 844
 
2.8%
성 633
 
2.1%
수 600
 
2.0%
호 517
 
1.7%
종 508
 
1.7%
재 489
 
1.6%
Other values (309) 20948
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29868
99.7%
Uppercase Letter 47
 
0.2%
Lowercase Letter 27
 
0.1%
Space Separator 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 2061
 
6.9%
이 1575
 
5.3%
정 918
 
3.1%
박 854
 
2.9%
영 844
 
2.8%
성 633
 
2.1%
수 600
 
2.0%
호 517
 
1.7%
종 508
 
1.7%
재 489
 
1.6%
Other values (281) 20869
69.9%
Uppercase Letter
ValueCountFrequency (%)
N 8
17.0%
I 7
14.9%
J 4
8.5%
S 3
 
6.4%
G 3
 
6.4%
U 3
 
6.4%
E 3
 
6.4%
L 3
 
6.4%
K 2
 
4.3%
M 2
 
4.3%
Other values (6) 9
19.1%
Lowercase Letter
ValueCountFrequency (%)
a 5
18.5%
i 4
14.8%
x 3
11.1%
n 3
11.1%
g 3
11.1%
u 3
11.1%
h 2
 
7.4%
f 1
 
3.7%
e 1
 
3.7%
b 1
 
3.7%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29868
99.7%
Latin 74
 
0.2%
Common 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 2061
 
6.9%
이 1575
 
5.3%
정 918
 
3.1%
박 854
 
2.9%
영 844
 
2.8%
성 633
 
2.1%
수 600
 
2.0%
호 517
 
1.7%
종 508
 
1.7%
재 489
 
1.6%
Other values (281) 20869
69.9%
Latin
ValueCountFrequency (%)
N 8
 
10.8%
I 7
 
9.5%
a 5
 
6.8%
i 4
 
5.4%
J 4
 
5.4%
S 3
 
4.1%
x 3
 
4.1%
n 3
 
4.1%
g 3
 
4.1%
G 3
 
4.1%
Other values (17) 31
41.9%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29868
99.7%
ASCII 79
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 2061
 
6.9%
이 1575
 
5.3%
정 918
 
3.1%
박 854
 
2.9%
영 844
 
2.8%
성 633
 
2.1%
수 600
 
2.0%
호 517
 
1.7%
종 508
 
1.7%
재 489
 
1.6%
Other values (281) 20869
69.9%
ASCII
ValueCountFrequency (%)
N 8
 
10.1%
I 7
 
8.9%
a 5
 
6.3%
5
 
6.3%
i 4
 
5.1%
J 4
 
5.1%
S 3
 
3.8%
x 3
 
3.8%
n 3
 
3.8%
g 3
 
3.8%
Other values (18) 34
43.0%

대표행정사여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
True
9674 
False
 
326
ValueCountFrequency (%)
True 9674
96.7%
False 326
 
3.3%
2024-03-15T09:05:26.666064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

행정사사무소전화번호
Text

MISSING 

Distinct5017
Distinct (%)92.5%
Missing4576
Missing (%)45.8%
Memory size156.2 KiB
2024-03-15T09:05:27.575247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.786504
Min length9

Characters and Unicode

Total characters63930
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

Unique4779 ?
Unique (%)88.1%

Sample

1st row053-611-8825
2nd row063-855-4383
3rd row031-374-1328
4th row043-534-8979
5th row041-852-1254
ValueCountFrequency (%)
02-3789-9001 27
 
0.5%
044-862-6621 25
 
0.5%
02-784-8029 10
 
0.2%
02-2068-5102 9
 
0.2%
031-224-2001 7
 
0.1%
02-6292-7580 7
 
0.1%
042-822-1990 7
 
0.1%
02-6925-2653 6
 
0.1%
062-371-1117 5
 
0.1%
061-544-9969 5
 
0.1%
Other values (5007) 5316
98.0%
2024-03-15T09:05:28.677751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 10847
17.0%
0 9110
14.2%
2 6976
10.9%
3 6401
10.0%
5 5773
9.0%
1 5130
8.0%
4 4360
6.8%
6 4337
 
6.8%
8 3952
 
6.2%
7 3906
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53083
83.0%
Dash Punctuation 10847
 
17.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9110
17.2%
2 6976
13.1%
3 6401
12.1%
5 5773
10.9%
1 5130
9.7%
4 4360
8.2%
6 4337
8.2%
8 3952
7.4%
7 3906
7.4%
9 3138
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 10847
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63930
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 10847
17.0%
0 9110
14.2%
2 6976
10.9%
3 6401
10.0%
5 5773
9.0%
1 5130
8.0%
4 4360
6.8%
6 4337
 
6.8%
8 3952
 
6.2%
7 3906
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63930
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 10847
17.0%
0 9110
14.2%
2 6976
10.9%
3 6401
10.0%
5 5773
9.0%
1 5130
8.0%
4 4360
6.8%
6 4337
 
6.8%
8 3952
 
6.2%
7 3906
 
6.1%

운영상태
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업중
9423 
휴업
 
577

Length

Max length3
Median length3
Mean length2.9423
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 9423
94.2%
휴업 577
 
5.8%

Length

2024-03-15T09:05:29.110762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:05:29.423757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 9423
94.2%
휴업 577
 
5.8%

신고일자
Date

Distinct3669
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1966-03-01 00:00:00
Maximum2024-01-19 00:00:00
2024-03-15T09:05:29.768330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:05:30.209771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리기관명
Text

Distinct227
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T09:05:31.429122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.4496
Min length8

Characters and Unicode

Total characters94496
Distinct characters141
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

Unique5 ?
Unique (%)< 0.1%

Sample

1st row부산광역시 부산진구청
2nd row경기도 시흥시청
3rd row대구광역시 달성군청
4th row서울특별시 영등포구청
5th row전북특별자치도 익산시청
ValueCountFrequency (%)
서울특별시 3033
 
15.2%
경기도 2556
 
12.8%
부산광역시 490
 
2.5%
서초구청 463
 
2.3%
경상남도 458
 
2.3%
전북특별자치도 430
 
2.2%
인천광역시 419
 
2.1%
중구청 399
 
2.0%
대구광역시 351
 
1.8%
충청남도 343
 
1.7%
Other values (211) 10977
55.1%
2024-03-15T09:05:33.053771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
청 10644
 
11.3%
9919
 
10.5%
시 9455
 
10.0%
구 5418
 
5.7%
도 5019
 
5.3%
서 4035
 
4.3%
특 3926
 
4.2%
별 3926
 
4.2%
경 3399
 
3.6%
울 3188
 
3.4%
Other values (131) 35567
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84577
89.5%
Space Separator 9919
 
10.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 10644
 
12.6%
시 9455
 
11.2%
구 5418
 
6.4%
도 5019
 
5.9%
서 4035
 
4.8%
특 3926
 
4.6%
별 3926
 
4.6%
경 3399
 
4.0%
울 3188
 
3.8%
기 2574
 
3.0%
Other values (130) 32993
39.0%
Space Separator
ValueCountFrequency (%)
9919
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84577
89.5%
Common 9919
 
10.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 10644
 
12.6%
시 9455
 
11.2%
구 5418
 
6.4%
도 5019
 
5.9%
서 4035
 
4.8%
특 3926
 
4.6%
별 3926
 
4.6%
경 3399
 
4.0%
울 3188
 
3.8%
기 2574
 
3.0%
Other values (130) 32993
39.0%
Common
ValueCountFrequency (%)
9919
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84577
89.5%
ASCII 9919
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
청 10644
 
12.6%
시 9455
 
11.2%
구 5418
 
6.4%
도 5019
 
5.9%
서 4035
 
4.8%
특 3926
 
4.6%
별 3926
 
4.6%
경 3399
 
4.0%
울 3188
 
3.8%
기 2574
 
3.0%
Other values (130) 32993
39.0%
ASCII
ValueCountFrequency (%)
9919
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-01-19 00:00:00
Maximum2024-01-19 00:00:00
2024-03-15T09:05:33.404372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:05:33.711050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

제공기관코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1741000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1741000
2nd row1741000
3rd row1741000
4th row1741000
5th row1741000

Common Values

ValueCountFrequency (%)
1741000 10000
100.0%

Length

2024-03-15T09:05:34.072956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:05:34.367726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1741000 10000
100.0%

제공기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
행정안전부
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
행정안전부 10000
100.0%

Length

2024-03-15T09:05:34.684901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:05:34.976995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행정안전부 10000
100.0%

Interactions

2024-03-15T09:05:06.321891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:05:05.905718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:05:06.598478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:05:06.070692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:05:35.159930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정사종류위도경도대표행정사여부운영상태
행정사종류1.0000.1000.1240.0210.000
위도0.1001.0000.8090.0730.077
경도0.1240.8091.0000.0460.081
대표행정사여부0.0210.0730.0461.0000.060
운영상태0.0000.0770.0810.0601.000
2024-03-15T09:05:35.426884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대표행정사여부행정사종류운영상태
대표행정사여부1.0000.0210.038
행정사종류0.0211.0000.000
운영상태0.0380.0001.000
2024-03-15T09:05:35.689311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도행정사종류대표행정사여부운영상태
위도1.000-0.3450.0320.0730.077
경도-0.3451.0000.0400.0460.080
행정사종류0.0320.0401.0000.0210.000
대표행정사여부0.0730.0460.0211.0000.038
운영상태0.0770.0800.0000.0381.000

Missing values

2024-03-15T09:05:06.901868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:05:07.558746image/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.
2024-03-15T09:05:08.034512image/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

사무소명행정사종류행정사자격증번호소재지도로명주소소재지지번주소위도경도행정사명대표행정사여부행정사사무소전화번호운영상태신고일자관리기관명데이터기준일자제공기관코드제공기관명
10180유대상 행정사사무소일반행정사T329000012100000050부산광역시 부산진구 대학로 72-8 (가야동)부산광역시 부산진구 가야동 454번지 69호35.151349129.035512유대상Y<NA>영업중2012-07-09부산광역시 부산진구청2024-01-191741000행정안전부
7907뉴 스마트 행정사 사무소일반행정사17101025227경기도 시흥시 시청로72번길 6 (장현동)경기도 시흥시 장현동 539번지 2호37.380833126.800172유상호Y<NA>영업중2018-06-01경기도 시흥시청2024-01-191741000행정안전부
8836대경행정사일반행정사15101015673대구광역시 달성군 논공읍 논공로7길 30-17<NA>35.729894128.439095김주석Y053-611-8825영업중2016-06-17대구광역시 달성군청2024-01-191741000행정안전부
9947최진규행정사일반행정사T318000012100000196서울특별시 영등포구 당산로 217 (당산동5가)서울특별시 영등포구 당산동5가 14번지 3호 3층37.533307126.901195최진규Y<NA>영업중2012-11-20서울특별시 영등포구청2024-01-191741000행정안전부
4066한국가정행복연구원일반행정사T468000012100000066전북특별자치도 익산시 선화로 210 (남중동)전북특별자치도 익산시 남중동 238번지 6호35.945662126.953284신유식Y063-855-4383영업중2000-03-30전북특별자치도 익산시청2024-01-191741000행정안전부
33이철우 행정사 사무소일반행정사13100003071경기도 오산시 운암로 122, 109동 1804호 (부산동, 운암주공1단지아파트 )경기도 오산시 부산동 778번지 1호 운암주공1단지아파트 109동 1804호37.156898127.079406이철우Y031-374-1328영업중2012-11-15경기도 오산시청2024-01-191741000행정안전부
9799행정사 이정수 사무소일반행정사13100001455충청북도 진천군 진천읍 남산3길 3충청북도 진천군 진천읍 교성리 236번지 2호36.853718127.440131이정수Y043-534-8979영업중2012-12-17충청북도 진천군청2024-01-191741000행정안전부
6341모란행정사일반행정사18101025336충청남도 공주시 정안면 모란길 113<NA>36.536317127.121436노수광Y041-852-1254영업중2023-02-23충청남도 공주시청2024-01-191741000행정안전부
5223바른길 행정사사무소일반행정사14101024287강원특별자치도 원주시 로아노크로 15, 101동 204호(단계동, 코오롱아파트)<NA>37.343457127.927774김정환Y<NA>영업중2022-04-01강원특별자치도 원주시청2024-01-191741000행정안전부
1673강경환 행정사사무소일반행정사21102002344경상남도 창원시 성산구 용지로 161， 301호 (용호동)<NA>35.229553128.681613강경환Y055-282-2823영업중2023-11-20경상남도 창원시청2024-01-191741000행정안전부
사무소명행정사종류행정사자격증번호소재지도로명주소소재지지번주소위도경도행정사명대표행정사여부행정사사무소전화번호운영상태신고일자관리기관명데이터기준일자제공기관코드제공기관명
8335한국행정사사무소일반행정사13101038156경기도 화성시 남양읍 역골중앙로 118, B동 101호 (동광뷰엘)경기도 화성시 남양읍 남양리 2235번지 동광뷰엘37.20918126.827238백동우Y031-357-7615영업중2016-11-07경기도 화성시청2024-01-191741000행정안전부
7769삼칠 행정사 사무소일반행정사18101024799경상남도 함안군 칠원읍 운무로 6, 우리들의원경상남도 함안군 칠원읍 구성리 665번지 3호 우리들의원35.308899128.519529안병호Y055-586-3345영업중2019-05-23경상남도 함안군청2024-01-191741000행정안전부
6845행정사법인 세종일반행정사22110006295충청남도 천안시 서북구 불당23로 73-27, 503호 (불당동)<NA>36.820418127.109686조석인N041-418-9475영업중2023-08-16충청남도 천안시청2024-01-191741000행정안전부
3506김봉기행정사사무소일반행정사13100003793부산광역시 연제구 법원로8번길 4 (거제동)부산광역시 연제구 거제동 1166번지 30호35.189901129.072698김봉기Y051-506-1383영업중2004-07-15부산광역시 연제구청2024-01-191741000행정안전부
9069안제동행정사사무소일반행정사14101035860부산광역시 부산진구 양지로17번길 74 (양정동)부산광역시 부산진구 양정동 342-2535.17148129.072378안제동Y<NA>영업중2015-04-01부산광역시 부산진구청2024-01-191741000행정안전부
3950류수석행정사사무소일반행정사T331000013100000002부산광역시 남구 황령대로319번나길 46 (대연동)부산광역시 남구 대연동 245번지 75호35.151723129.090337류수석Y<NA>영업중1999-10-14부산광역시 남구청2024-01-191741000행정안전부
6559행정사사무소 활로일반행정사22110009169경기도 고양시 덕양구 원흥3로 16, 4층 403호(원흥동)<NA>37.649247126.874833임종석Y<NA>영업중2023-03-27경기도 고양시청2024-01-191741000행정안전부
8148오병필행정사사무소일반행정사14101078117제주특별자치도 제주시 중앙로 248, 4층 (이도이동, 아산빌딩)<NA>33.497728126.530853오병필Y064-721-3115영업중2017-10-13제주특별자치도 제주시청2024-01-191741000행정안전부
6057대한 행정사일반행정사16101005136경기도 의정부시 녹양로 25-2, 1층(가능동)<NA>37.753673127.03206이수천Y031-874-5454영업중2022-12-07경기도 의정부시청2024-01-191741000행정안전부
8758산재전문행정사사무소일반행정사13101049303울산광역시 남구 문수로388번길 17 (옥동)<NA>35.532629129.295263김희동Y<NA>영업중2016-05-12울산광역시 남구청2024-01-191741000행정안전부