Overview

Dataset statistics

Number of variables8
Number of observations185
Missing cells103
Missing cells (%)7.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.7 KiB
Average record size in memory64.7 B

Variable types

DateTime1
Text5
Categorical1
Boolean1

Dataset

Description관내 행정사사무소 현황으로 사무소 명칭, 행정사 성명, 업무 신고연월, 소재지, 전화번호 등의 정보를 제공합니다.
Author서울특별시 송파구
URLhttps://www.data.go.kr/data/15028825/fileData.do

Alerts

행정사종류 is highly imbalanced (76.8%)Imbalance
대표여부 is highly imbalanced (63.3%)Imbalance
사무소 전화번호 has 103 (55.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 05:34:05.668917
Analysis finished2023-12-12 05:34:06.395431
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

신고일자
Date

Distinct152
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum1995-12-11 00:00:00
Maximum2022-07-21 00:00:00
2023-12-12T14:34:06.471004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:34:06.627513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사무소명칭
Text

Distinct171
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T14:34:07.266818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length9.5351351
Min length5

Characters and Unicode

Total characters1764
Distinct characters230
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)88.6%

Sample

1st row메이트 행정사 사무소
2nd row선한 행정사 사무소
3rd row범진 행정사법인
4th row손해사정 행정사사무소
5th row아인 행정사사무소
ValueCountFrequency (%)
행정사 51
 
14.5%
사무소 41
 
11.6%
행정사사무소 37
 
10.5%
행정사법인 16
 
4.5%
제이엔티 4
 
1.1%
청효 4
 
1.1%
티움 3
 
0.9%
케이디엠(kdm 3
 
0.9%
청록 3
 
0.9%
행정사합동사무소 3
 
0.9%
Other values (181) 187
53.1%
2023-12-12T14:34:07.797586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 312
17.7%
정 196
 
11.1%
행 184
 
10.4%
167
 
9.5%
무 134
 
7.6%
소 131
 
7.4%
인 26
 
1.5%
이 23
 
1.3%
법 17
 
1.0%
서 9
 
0.5%
Other values (220) 565
32.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1543
87.5%
Space Separator 167
 
9.5%
Uppercase Letter 30
 
1.7%
Lowercase Letter 10
 
0.6%
Close Punctuation 5
 
0.3%
Open Punctuation 5
 
0.3%
Other Punctuation 3
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 312
20.2%
정 196
 
12.7%
행 184
 
11.9%
무 134
 
8.7%
소 131
 
8.5%
인 26
 
1.7%
이 23
 
1.5%
법 17
 
1.1%
서 9
 
0.6%
일 9
 
0.6%
Other values (191) 502
32.5%
Uppercase Letter
ValueCountFrequency (%)
K 6
20.0%
H 4
13.3%
D 4
13.3%
M 3
10.0%
S 2
 
6.7%
B 2
 
6.7%
O 1
 
3.3%
P 1
 
3.3%
I 1
 
3.3%
V 1
 
3.3%
Other values (5) 5
16.7%
Lowercase Letter
ValueCountFrequency (%)
e 2
20.0%
i 2
20.0%
r 1
10.0%
a 1
10.0%
n 1
10.0%
w 1
10.0%
h 1
10.0%
t 1
10.0%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
· 1
33.3%
Space Separator
ValueCountFrequency (%)
167
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1541
87.4%
Common 181
 
10.3%
Latin 40
 
2.3%
Han 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 312
20.2%
정 196
 
12.7%
행 184
 
11.9%
무 134
 
8.7%
소 131
 
8.5%
인 26
 
1.7%
이 23
 
1.5%
법 17
 
1.1%
서 9
 
0.6%
일 9
 
0.6%
Other values (190) 500
32.4%
Latin
ValueCountFrequency (%)
K 6
15.0%
H 4
 
10.0%
D 4
 
10.0%
M 3
 
7.5%
S 2
 
5.0%
e 2
 
5.0%
B 2
 
5.0%
i 2
 
5.0%
O 1
 
2.5%
P 1
 
2.5%
Other values (13) 13
32.5%
Common
ValueCountFrequency (%)
167
92.3%
) 5
 
2.8%
( 5
 
2.8%
& 2
 
1.1%
· 1
 
0.6%
- 1
 
0.6%
Han
ValueCountFrequency (%)
多 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1541
87.4%
ASCII 220
 
12.5%
CJK 2
 
0.1%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 312
20.2%
정 196
 
12.7%
행 184
 
11.9%
무 134
 
8.7%
소 131
 
8.5%
인 26
 
1.7%
이 23
 
1.5%
법 17
 
1.1%
서 9
 
0.6%
일 9
 
0.6%
Other values (190) 500
32.4%
ASCII
ValueCountFrequency (%)
167
75.9%
K 6
 
2.7%
) 5
 
2.3%
( 5
 
2.3%
H 4
 
1.8%
D 4
 
1.8%
M 3
 
1.4%
S 2
 
0.9%
e 2
 
0.9%
B 2
 
0.9%
Other values (18) 20
 
9.1%
CJK
ValueCountFrequency (%)
多 2
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

행정사종류
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
일반행정사
178 
외국어번역행정사(영어)
 
7

Length

Max length12
Median length5
Mean length5.2648649
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반행정사 178
96.2%
외국어번역행정사(영어) 7
 
3.8%

Length

2023-12-12T14:34:07.960933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:34:08.073237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반행정사 178
96.2%
외국어번역행정사(영어 7
 
3.8%

행정사 성명
Text

Distinct182
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T14:34:08.403093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9891892
Min length2

Characters and Unicode

Total characters553
Distinct characters130
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

Unique179 ?
Unique (%)96.8%

Sample

1st row윤지현
2nd row이한구
3rd row정은상
4th row허창원
5th row황범노
ValueCountFrequency (%)
이충식 2
 
1.1%
이규권 2
 
1.1%
유종호 2
 
1.1%
박승용 1
 
0.5%
박중규 1
 
0.5%
전용우 1
 
0.5%
김영진 1
 
0.5%
서정영 1
 
0.5%
윤지현 1
 
0.5%
이영석 1
 
0.5%
Other values (172) 172
93.0%
2023-12-12T14:34:09.043585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 31
 
5.6%
이 30
 
5.4%
박 23
 
4.2%
정 15
 
2.7%
수 12
 
2.2%
용 12
 
2.2%
영 12
 
2.2%
종 11
 
2.0%
기 11
 
2.0%
식 10
 
1.8%
Other values (120) 386
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 553
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 31
 
5.6%
이 30
 
5.4%
박 23
 
4.2%
정 15
 
2.7%
수 12
 
2.2%
용 12
 
2.2%
영 12
 
2.2%
종 11
 
2.0%
기 11
 
2.0%
식 10
 
1.8%
Other values (120) 386
69.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 553
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 31
 
5.6%
이 30
 
5.4%
박 23
 
4.2%
정 15
 
2.7%
수 12
 
2.2%
용 12
 
2.2%
영 12
 
2.2%
종 11
 
2.0%
기 11
 
2.0%
식 10
 
1.8%
Other values (120) 386
69.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 553
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 31
 
5.6%
이 30
 
5.4%
박 23
 
4.2%
정 15
 
2.7%
수 12
 
2.2%
용 12
 
2.2%
영 12
 
2.2%
종 11
 
2.0%
기 11
 
2.0%
식 10
 
1.8%
Other values (120) 386
69.8%

대표여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size317.0 B
True
172 
False
 
13
ValueCountFrequency (%)
True 172
93.0%
False 13
 
7.0%
2023-12-12T14:34:09.211651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

사무소 도로명전체주소
Text

Distinct136
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T14:34:09.512019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length46
Mean length31.167568
Min length1

Characters and Unicode

Total characters5766
Distinct characters179
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)64.9%

Sample

1st row서울특별시 송파구 충민로 66， 가든파이브 라이프 패션관 9층 9066호(문정동)
2nd row서울특별시 송파구 동남로8길 30-9， 101동 101호(문정동， 엠카운티)
3rd row서울특별시 송파구 정의로7길 13， 힐스테이트에코송파 오피스 905호(문정동)
4th row서울특별시 송파구 성내천로39길 23-3， 2층(마천동)
5th row서울특별시 송파구 충민로 66， 가든파이브 라이프 에프동 9층 9024호(문정동)
ValueCountFrequency (%)
서울특별시 161
 
15.1%
송파구 161
 
15.1%
20
 
1.9%
송파대로 14
 
1.3%
문정동 12
 
1.1%
방이동 12
 
1.1%
충민로 12
 
1.1%
가락로 11
 
1.0%
석촌동 10
 
0.9%
잠실동 9
 
0.8%
Other values (384) 647
60.5%
2023-12-12T14:34:09.961781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
936
 
16.2%
1 241
 
4.2%
파 227
 
3.9%
동 213
 
3.7%
송 200
 
3.5%
0 169
 
2.9%
시 166
 
2.9%
로 163
 
2.8%
별 161
 
2.8%
특 161
 
2.8%
Other values (169) 3129
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3244
56.3%
Decimal Number 1023
 
17.7%
Space Separator 936
 
16.2%
Other Punctuation 182
 
3.2%
Open Punctuation 160
 
2.8%
Close Punctuation 160
 
2.8%
Dash Punctuation 35
 
0.6%
Uppercase Letter 26
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 227
 
7.0%
동 213
 
6.6%
송 200
 
6.2%
시 166
 
5.1%
로 163
 
5.0%
별 161
 
5.0%
특 161
 
5.0%
구 161
 
5.0%
서 161
 
5.0%
울 161
 
5.0%
Other values (146) 1470
45.3%
Decimal Number
ValueCountFrequency (%)
1 241
23.6%
0 169
16.5%
3 141
13.8%
2 126
12.3%
4 73
 
7.1%
5 71
 
6.9%
6 66
 
6.5%
8 51
 
5.0%
7 44
 
4.3%
9 41
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 10
38.5%
C 6
23.1%
S 3
 
11.5%
A 3
 
11.5%
G 2
 
7.7%
T 1
 
3.8%
P 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
， 155
85.2%
, 27
 
14.8%
Space Separator
ValueCountFrequency (%)
936
100.0%
Open Punctuation
ValueCountFrequency (%)
( 160
100.0%
Close Punctuation
ValueCountFrequency (%)
) 160
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3244
56.3%
Common 2496
43.3%
Latin 26
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 227
 
7.0%
동 213
 
6.6%
송 200
 
6.2%
시 166
 
5.1%
로 163
 
5.0%
별 161
 
5.0%
특 161
 
5.0%
구 161
 
5.0%
서 161
 
5.0%
울 161
 
5.0%
Other values (146) 1470
45.3%
Common
ValueCountFrequency (%)
936
37.5%
1 241
 
9.7%
0 169
 
6.8%
( 160
 
6.4%
) 160
 
6.4%
， 155
 
6.2%
3 141
 
5.6%
2 126
 
5.0%
4 73
 
2.9%
5 71
 
2.8%
Other values (6) 264
 
10.6%
Latin
ValueCountFrequency (%)
B 10
38.5%
C 6
23.1%
S 3
 
11.5%
A 3
 
11.5%
G 2
 
7.7%
T 1
 
3.8%
P 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3243
56.2%
ASCII 2367
41.1%
None 155
 
2.7%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
936
39.5%
1 241
 
10.2%
0 169
 
7.1%
( 160
 
6.8%
) 160
 
6.8%
3 141
 
6.0%
2 126
 
5.3%
4 73
 
3.1%
5 71
 
3.0%
6 66
 
2.8%
Other values (12) 224
 
9.5%
Hangul
ValueCountFrequency (%)
파 227
 
7.0%
동 213
 
6.6%
송 200
 
6.2%
시 166
 
5.1%
로 163
 
5.0%
별 161
 
5.0%
특 161
 
5.0%
구 161
 
5.0%
서 161
 
5.0%
울 161
 
5.0%
Other values (145) 1469
45.3%
None
ValueCountFrequency (%)
， 155
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

사무소 주소
Text

Distinct124
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T14:34:10.344662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length20.378378
Min length1

Characters and Unicode

Total characters3770
Distinct characters168
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

Unique118 ?
Unique (%)63.8%

Sample

1st row
2nd row
3rd row
4th row서울특별시 은평구 응암동 74-3
5th row
ValueCountFrequency (%)
서울특별시 133
 
16.9%
송파구 129
 
16.3%
가락동 23
 
2.9%
문정동 20
 
2.5%
방이동 19
 
2.4%
2호 16
 
2.0%
잠실동 13
 
1.6%
석촌동 13
 
1.6%
3호 11
 
1.4%
1호 9
 
1.1%
Other values (273) 403
51.1%
2023-12-12T14:34:10.899497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
714
18.9%
파 162
 
4.3%
1 158
 
4.2%
동 150
 
4.0%
송 143
 
3.8%
호 141
 
3.7%
시 139
 
3.7%
서 134
 
3.6%
별 133
 
3.5%
특 133
 
3.5%
Other values (158) 1763
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2332
61.9%
Space Separator 714
 
18.9%
Decimal Number 685
 
18.2%
Dash Punctuation 20
 
0.5%
Uppercase Letter 12
 
0.3%
Other Punctuation 3
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 162
 
6.9%
동 150
 
6.4%
송 143
 
6.1%
호 141
 
6.0%
시 139
 
6.0%
서 134
 
5.7%
별 133
 
5.7%
특 133
 
5.7%
구 133
 
5.7%
울 133
 
5.7%
Other values (135) 931
39.9%
Decimal Number
ValueCountFrequency (%)
1 158
23.1%
2 101
14.7%
0 74
10.8%
3 63
 
9.2%
4 55
 
8.0%
9 55
 
8.0%
5 52
 
7.6%
7 48
 
7.0%
6 43
 
6.3%
8 36
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
B 5
41.7%
A 2
 
16.7%
T 1
 
8.3%
D 1
 
8.3%
M 1
 
8.3%
G 1
 
8.3%
Y 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
， 2
66.7%
/ 1
33.3%
Space Separator
ValueCountFrequency (%)
714
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2332
61.9%
Common 1426
37.8%
Latin 12
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 162
 
6.9%
동 150
 
6.4%
송 143
 
6.1%
호 141
 
6.0%
시 139
 
6.0%
서 134
 
5.7%
별 133
 
5.7%
특 133
 
5.7%
구 133
 
5.7%
울 133
 
5.7%
Other values (135) 931
39.9%
Common
ValueCountFrequency (%)
714
50.1%
1 158
 
11.1%
2 101
 
7.1%
0 74
 
5.2%
3 63
 
4.4%
4 55
 
3.9%
9 55
 
3.9%
5 52
 
3.6%
7 48
 
3.4%
6 43
 
3.0%
Other values (6) 63
 
4.4%
Latin
ValueCountFrequency (%)
B 5
41.7%
A 2
 
16.7%
T 1
 
8.3%
D 1
 
8.3%
M 1
 
8.3%
G 1
 
8.3%
Y 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2332
61.9%
ASCII 1436
38.1%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
714
49.7%
1 158
 
11.0%
2 101
 
7.0%
0 74
 
5.2%
3 63
 
4.4%
4 55
 
3.8%
9 55
 
3.8%
5 52
 
3.6%
7 48
 
3.3%
6 43
 
3.0%
Other values (12) 73
 
5.1%
Hangul
ValueCountFrequency (%)
파 162
 
6.9%
동 150
 
6.4%
송 143
 
6.1%
호 141
 
6.0%
시 139
 
6.0%
서 134
 
5.7%
별 133
 
5.7%
특 133
 
5.7%
구 133
 
5.7%
울 133
 
5.7%
Other values (135) 931
39.9%
None
ValueCountFrequency (%)
， 2
100.0%

사무소 전화번호
Text

MISSING 

Distinct75
Distinct (%)91.5%
Missing103
Missing (%)55.7%
Memory size1.6 KiB
2023-12-12T14:34:11.209247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10.987805
Min length1

Characters and Unicode

Total characters901
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

Unique71 ?
Unique (%)86.6%

Sample

1st row
2nd row02-449-5217
3rd row02-422-8332
4th row02-419-1213
5th row02-419-1213
ValueCountFrequency (%)
02-419-1213 4
 
4.9%
02-416-9981 3
 
3.7%
02-443-4585 2
 
2.5%
02-409-2988 2
 
2.5%
02-415-5000 1
 
1.2%
02-472-6432 1
 
1.2%
02-796-0307 1
 
1.2%
02-448-0238 1
 
1.2%
02-446-4111 1
 
1.2%
02-2415-7711 1
 
1.2%
Other values (64) 64
79.0%
2023-12-12T14:34:11.740837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 157
17.4%
0 152
16.9%
2 141
15.6%
4 105
11.7%
1 81
9.0%
8 51
 
5.7%
5 47
 
5.2%
3 44
 
4.9%
7 44
 
4.9%
6 40
 
4.4%
Other values (2) 39
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 743
82.5%
Dash Punctuation 157
 
17.4%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 152
20.5%
2 141
19.0%
4 105
14.1%
1 81
10.9%
8 51
 
6.9%
5 47
 
6.3%
3 44
 
5.9%
7 44
 
5.9%
6 40
 
5.4%
9 38
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 157
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 901
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 157
17.4%
0 152
16.9%
2 141
15.6%
4 105
11.7%
1 81
9.0%
8 51
 
5.7%
5 47
 
5.2%
3 44
 
4.9%
7 44
 
4.9%
6 40
 
4.4%
Other values (2) 39
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 901
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 157
17.4%
0 152
16.9%
2 141
15.6%
4 105
11.7%
1 81
9.0%
8 51
 
5.7%
5 47
 
5.2%
3 44
 
4.9%
7 44
 
4.9%
6 40
 
4.4%
Other values (2) 39
 
4.3%

Correlations

2023-12-12T14:34:11.890749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정사종류대표여부사무소 전화번호
행정사종류1.0000.0000.000
대표여부0.0001.0000.000
사무소 전화번호0.0000.0001.000
2023-12-12T14:34:12.025796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대표여부행정사종류
대표여부1.0000.000
행정사종류0.0001.000
2023-12-12T14:34:12.141066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정사종류대표여부
행정사종류1.0000.000
대표여부0.0001.000

Missing values

2023-12-12T14:34:06.215245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:34:06.347790image/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

신고일자사무소명칭행정사종류행정사 성명대표여부사무소 도로명전체주소사무소 주소사무소 전화번호
02022-07-21메이트 행정사 사무소일반행정사윤지현Y서울특별시 송파구 충민로 66， 가든파이브 라이프 패션관 9층 9066호(문정동)
12022-06-21선한 행정사 사무소일반행정사이한구Y서울특별시 송파구 동남로8길 30-9， 101동 101호(문정동， 엠카운티)02-449-5217
22022-05-12범진 행정사법인일반행정사정은상N서울특별시 송파구 정의로7길 13， 힐스테이트에코송파 오피스 905호(문정동)<NA>
32022-04-27손해사정 행정사사무소일반행정사허창원Y서울특별시 송파구 성내천로39길 23-3， 2층(마천동)서울특별시 은평구 응암동 74-3<NA>
42022-04-11아인 행정사사무소일반행정사황범노Y서울특별시 송파구 충민로 66， 가든파이브 라이프 에프동 9층 9024호(문정동)<NA>
52010-01-18위 더 피플 행정사일반행정사이경수Y서울특별시 송파구 백제고분로 432 2층(송파동, 송온빌딩)서울특별시 송파구 송파동 135번지 2호 송온빌딩 2층02-422-8332
62022-06-15인정 행정사사무소일반행정사정혜인Y서울특별시 송파구 토성로 38-6， 상가동 104호(풍납동， 한강극동아파트)<NA>
72022-03-02행정사법인 청효일반행정사박성모N서울특별시 송파구 위례성대로 6， 12층 1205호(방이동)02-419-1213
82022-03-02행정사법인 청효일반행정사류정욱N서울특별시 송파구 위례성대로 6， 12층 1205호(방이동)02-419-1213
92022-03-02행정사법인 청효일반행정사차재필N서울특별시 송파구 위례성대로 6， 12층 1205호(방이동)02-419-1213
신고일자사무소명칭행정사종류행정사 성명대표여부사무소 도로명전체주소사무소 주소사무소 전화번호
1752004-06-30송흥철행정사일반행정사송흥철Y서울특별시 송파구 오금동 119번지 12호 401호02-408-1516
1762005-04-19서일용행정사일반행정사서일웅Y서울특별시 송파구 가락동 98번지 4호 동원빌딩 9층<NA>
1772005-10-12염희성 행정사 사무소일반행정사염희성Y서울특별시 송파구 방이동 159번지 21호02-420-7578
1782006-01-05문윤원 행정사사무소일반행정사문윤원Y서울특별시 송파구 가락동 159번지 23호 20102-408-5770
1792006-02-02이규환 행정사사무소일반행정사이규환Y서울특별시 송파구 가락동 112번지 2호 화영B/D 1층 GM 대우지판(주)02-402-0440
1802006-03-09김창곤 법무 행정사일반행정사김창곤Y서울특별시 송파구 마천동 307번지 14호02-402-4489
1812007-02-02행정사 박승용 사무소일반행정사박승용Y서울특별시 송파구 가락동 99번지 3호 제일오피스텔 722호<NA>
1822008-06-13행정사 양기철 사무소일반행정사양기철Y서울특별시 송파구 문정동 16번지02-402-7707
1832009-05-11행정사 하영규 사무소일반행정사김정식Y서울특별시 송파구 방이동 49번지 15호 굿오피스텔 1001호<NA>
1842010-01-11장은석행정사일반행정사장은석Y서울특별시 송파구 잠실동 85번지 1호 102호02-417-5040