Overview

Dataset statistics

Number of variables6
Number of observations298
Missing cells137
Missing cells (%)7.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.4 KiB
Average record size in memory49.4 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description서울특별시 영등포구 행정사사무소 현황 데이터를 제공합니다. (제공내용: 일련번호, 신고일자, 사무소명칭, 운영상태, 행정사종류, 행정사 성명, 사무소 주소)
Author서울특별시 영등포구
URLhttps://www.data.go.kr/data/15028829/fileData.do

Alerts

영업상태 has constant value ""Constant
행정사 종류 is highly imbalanced (92.8%)Imbalance
전화번호 has 137 (46.0%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:39:01.589481
Analysis finished2023-12-12 07:39:02.168951
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct298
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean149.5
Minimum1
Maximum298
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-12T16:39:02.263057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.85
Q175.25
median149.5
Q3223.75
95-th percentile283.15
Maximum298
Range297
Interquartile range (IQR)148.5

Descriptive statistics

Standard deviation86.169407
Coefficient of variation (CV)0.57638399
Kurtosis-1.2
Mean149.5
Median Absolute Deviation (MAD)74.5
Skewness0
Sum44551
Variance7425.1667
MonotonicityStrictly increasing
2023-12-12T16:39:02.489279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
206 1
 
0.3%
204 1
 
0.3%
203 1
 
0.3%
202 1
 
0.3%
201 1
 
0.3%
200 1
 
0.3%
199 1
 
0.3%
198 1
 
0.3%
197 1
 
0.3%
Other values (288) 288
96.6%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
298 1
0.3%
297 1
0.3%
296 1
0.3%
295 1
0.3%
294 1
0.3%
293 1
0.3%
292 1
0.3%
291 1
0.3%
290 1
0.3%
289 1
0.3%

행정사 종류
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
일반행정사
294 
외국어번역행정사(영어)
 
3
외국어번역행정사(중국어)
 
1

Length

Max length13
Median length5
Mean length5.0973154
Min length5

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
일반행정사 294
98.7%
외국어번역행정사(영어) 3
 
1.0%
외국어번역행정사(중국어) 1
 
0.3%

Length

2023-12-12T16:39:02.702879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:39:02.832114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반행정사 294
98.7%
외국어번역행정사(영어 3
 
1.0%
외국어번역행정사(중국어 1
 
0.3%

명 칭
Text

Distinct256
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T16:39:03.079649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length9.0503356
Min length2

Characters and Unicode

Total characters2697
Distinct characters258
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique239 ?
Unique (%)80.2%

Sample

1st row행정사사무소
2nd rowAP행정사 합동사무소
3rd rowAP행정사 합동사무소
4th rowAP행정사 합동사무소
5th rowAP행정사 합동사무소
ValueCountFrequency (%)
행정사사무소 65
 
14.4%
행정사 32
 
7.1%
사무소 31
 
6.9%
합동사무소 16
 
3.5%
ap행정사 8
 
1.8%
대한행정사사무소 6
 
1.3%
대한행정사합동사무소 5
 
1.1%
여의도행정사합동사무소 5
 
1.1%
휴민행정사합동사무소 5
 
1.1%
국제 4
 
0.9%
Other values (255) 275
60.8%
2023-12-12T16:39:03.516042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 507
18.8%
정 297
 
11.0%
행 292
 
10.8%
소 232
 
8.6%
무 231
 
8.6%
154
 
5.7%
동 53
 
2.0%
합 40
 
1.5%
한 37
 
1.4%
국 28
 
1.0%
Other values (248) 826
30.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2487
92.2%
Space Separator 154
 
5.7%
Uppercase Letter 31
 
1.1%
Decimal Number 8
 
0.3%
Other Punctuation 6
 
0.2%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Lowercase Letter 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 507
20.4%
정 297
 
11.9%
행 292
 
11.7%
소 232
 
9.3%
무 231
 
9.3%
동 53
 
2.1%
합 40
 
1.6%
한 37
 
1.5%
국 28
 
1.1%
대 22
 
0.9%
Other values (223) 748
30.1%
Uppercase Letter
ValueCountFrequency (%)
A 8
25.8%
P 8
25.8%
D 4
12.9%
H 3
 
9.7%
W 2
 
6.5%
C 1
 
3.2%
Y 1
 
3.2%
S 1
 
3.2%
G 1
 
3.2%
K 1
 
3.2%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
0 2
25.0%
1 1
 
12.5%
4 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
. 2
33.3%
" 2
33.3%
& 1
16.7%
· 1
16.7%
Lowercase Letter
ValueCountFrequency (%)
u 1
50.0%
o 1
50.0%
Space Separator
ValueCountFrequency (%)
154
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2487
92.2%
Common 177
 
6.6%
Latin 33
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 507
20.4%
정 297
 
11.9%
행 292
 
11.7%
소 232
 
9.3%
무 231
 
9.3%
동 53
 
2.1%
합 40
 
1.6%
한 37
 
1.5%
국 28
 
1.1%
대 22
 
0.9%
Other values (223) 748
30.1%
Latin
ValueCountFrequency (%)
A 8
24.2%
P 8
24.2%
D 4
12.1%
H 3
 
9.1%
W 2
 
6.1%
C 1
 
3.0%
u 1
 
3.0%
o 1
 
3.0%
Y 1
 
3.0%
S 1
 
3.0%
Other values (3) 3
 
9.1%
Common
ValueCountFrequency (%)
154
87.0%
( 4
 
2.3%
) 4
 
2.3%
2 4
 
2.3%
0 2
 
1.1%
. 2
 
1.1%
" 2
 
1.1%
1 1
 
0.6%
& 1
 
0.6%
4 1
 
0.6%
Other values (2) 2
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2487
92.2%
ASCII 209
 
7.7%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 507
20.4%
정 297
 
11.9%
행 292
 
11.7%
소 232
 
9.3%
무 231
 
9.3%
동 53
 
2.1%
합 40
 
1.6%
한 37
 
1.5%
국 28
 
1.1%
대 22
 
0.9%
Other values (223) 748
30.1%
ASCII
ValueCountFrequency (%)
154
73.7%
A 8
 
3.8%
P 8
 
3.8%
D 4
 
1.9%
( 4
 
1.9%
) 4
 
1.9%
2 4
 
1.9%
H 3
 
1.4%
W 2
 
1.0%
0 2
 
1.0%
Other values (14) 16
 
7.7%
None
ValueCountFrequency (%)
· 1
100.0%

소재지
Text

Distinct233
Distinct (%)78.2%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T16:39:03.807870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length46.5
Mean length31.463087
Min length23

Characters and Unicode

Total characters9376
Distinct characters169
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)67.1%

Sample

1st row서울특별시 영등포구 영신로 37, 3층 (영등포동)
2nd row서울특별시 영등포구 은행로 37, 기계산업진흥회 본관동 7층 (여의도동)
3rd row서울특별시 영등포구 은행로 37, 기계산업진흥회 본관동 7층 (여의도동)
4th row서울특별시 영등포구 은행로 37, 기계산업진흥회 본관동 7층 (여의도동)
5th row서울특별시 영등포구 은행로 37, 기계산업진흥회 본관동 7층 (여의도동)
ValueCountFrequency (%)
서울특별시 298
 
17.0%
영등포구 298
 
17.0%
대림동 99
 
5.6%
여의도동 61
 
3.5%
영등포로 26
 
1.5%
당산동2가 25
 
1.4%
신길동 23
 
1.3%
당산동3가 22
 
1.3%
도림로 22
 
1.3%
109 21
 
1.2%
Other values (376) 860
49.0%
2023-12-12T16:39:04.247836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1457
 
15.5%
영 386
 
4.1%
포 359
 
3.8%
등 359
 
3.8%
동 329
 
3.5%
서 303
 
3.2%
시 302
 
3.2%
로 299
 
3.2%
울 299
 
3.2%
구 298
 
3.2%
Other values (159) 4985
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5667
60.4%
Space Separator 1457
 
15.5%
Decimal Number 1423
 
15.2%
Open Punctuation 298
 
3.2%
Close Punctuation 298
 
3.2%
Other Punctuation 167
 
1.8%
Dash Punctuation 48
 
0.5%
Uppercase Letter 18
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 386
 
6.8%
포 359
 
6.3%
등 359
 
6.3%
동 329
 
5.8%
서 303
 
5.3%
시 302
 
5.3%
로 299
 
5.3%
울 299
 
5.3%
구 298
 
5.3%
별 298
 
5.3%
Other values (133) 2435
43.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
16.7%
A 3
16.7%
C 3
16.7%
I 2
11.1%
W 1
 
5.6%
E 1
 
5.6%
V 1
 
5.6%
K 1
 
5.6%
T 1
 
5.6%
S 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 296
20.8%
2 239
16.8%
3 192
13.5%
0 148
10.4%
7 106
 
7.4%
5 101
 
7.1%
4 98
 
6.9%
9 90
 
6.3%
6 82
 
5.8%
8 71
 
5.0%
Space Separator
ValueCountFrequency (%)
1457
100.0%
Open Punctuation
ValueCountFrequency (%)
( 298
100.0%
Close Punctuation
ValueCountFrequency (%)
) 298
100.0%
Other Punctuation
ValueCountFrequency (%)
, 167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5667
60.4%
Common 3691
39.4%
Latin 18
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 386
 
6.8%
포 359
 
6.3%
등 359
 
6.3%
동 329
 
5.8%
서 303
 
5.3%
시 302
 
5.3%
로 299
 
5.3%
울 299
 
5.3%
구 298
 
5.3%
별 298
 
5.3%
Other values (133) 2435
43.0%
Common
ValueCountFrequency (%)
1457
39.5%
( 298
 
8.1%
) 298
 
8.1%
1 296
 
8.0%
2 239
 
6.5%
3 192
 
5.2%
, 167
 
4.5%
0 148
 
4.0%
7 106
 
2.9%
5 101
 
2.7%
Other values (5) 389
 
10.5%
Latin
ValueCountFrequency (%)
B 3
16.7%
A 3
16.7%
C 3
16.7%
I 2
11.1%
W 1
 
5.6%
E 1
 
5.6%
V 1
 
5.6%
K 1
 
5.6%
T 1
 
5.6%
S 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5667
60.4%
ASCII 3709
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1457
39.3%
( 298
 
8.0%
) 298
 
8.0%
1 296
 
8.0%
2 239
 
6.4%
3 192
 
5.2%
, 167
 
4.5%
0 148
 
4.0%
7 106
 
2.9%
5 101
 
2.7%
Other values (16) 407
 
11.0%
Hangul
ValueCountFrequency (%)
영 386
 
6.8%
포 359
 
6.3%
등 359
 
6.3%
동 329
 
5.8%
서 303
 
5.3%
시 302
 
5.3%
로 299
 
5.3%
울 299
 
5.3%
구 298
 
5.3%
별 298
 
5.3%
Other values (133) 2435
43.0%

전화번호
Text

MISSING 

Distinct133
Distinct (%)82.6%
Missing137
Missing (%)46.0%
Memory size2.5 KiB
2023-12-12T16:39:04.535834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.024845
Min length8

Characters and Unicode

Total characters1775
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

Unique123 ?
Unique (%)76.4%

Sample

1st row02-862-9995
2nd row02-832-7772
3rd row02-706-5100
4th row2324-1389
5th row02-834-8996
ValueCountFrequency (%)
02-2068-5102 13
 
8.1%
02-6925-2653 5
 
3.1%
02-844-7348 4
 
2.5%
02-2634-6777 3
 
1.9%
02-2672-1133 3
 
1.9%
070-8816-6211 2
 
1.2%
02-3775-3801 2
 
1.2%
02-832-8952 2
 
1.2%
02-834-8996 2
 
1.2%
02-846-0361 2
 
1.2%
Other values (123) 123
76.4%
2023-12-12T16:39:04.984040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 294
16.6%
- 283
15.9%
0 231
13.0%
8 167
9.4%
6 156
8.8%
3 134
7.5%
7 130
7.3%
1 114
 
6.4%
5 106
 
6.0%
4 95
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1492
84.1%
Dash Punctuation 283
 
15.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 294
19.7%
0 231
15.5%
8 167
11.2%
6 156
10.5%
3 134
9.0%
7 130
8.7%
1 114
 
7.6%
5 106
 
7.1%
4 95
 
6.4%
9 65
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 283
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1775
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 294
16.6%
- 283
15.9%
0 231
13.0%
8 167
9.4%
6 156
8.8%
3 134
7.5%
7 130
7.3%
1 114
 
6.4%
5 106
 
6.0%
4 95
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1775
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 294
16.6%
- 283
15.9%
0 231
13.0%
8 167
9.4%
6 156
8.8%
3 134
7.5%
7 130
7.3%
1 114
 
6.4%
5 106
 
6.0%
4 95
 
5.4%

영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
영업중
298 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 298
100.0%

Length

2023-12-12T16:39:05.130199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:39:05.221494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 298
100.0%

Interactions

2023-12-12T16:39:01.891202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:39:05.280249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정사 종류
연번1.0000.000
행정사 종류0.0001.000
2023-12-12T16:39:05.365141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정사 종류
연번1.0000.000
행정사 종류0.0001.000

Missing values

2023-12-12T16:39:02.001364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:39:02.116176image/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

연번행정사 종류명 칭소재지전화번호영업상태
01일반행정사행정사사무소서울특별시 영등포구 영신로 37, 3층 (영등포동)02-862-9995영업중
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