Overview

Dataset statistics

Number of variables5
Number of observations54
Missing cells10
Missing cells (%)3.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory43.4 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description서울특별시 중랑구의 행정사 현황을 나타냅니다. 연번, 업체명, 주소, 전화번호, 데이터기준일자를 제공합니다. 참고해주시기 바랍니다. 감사합니다.
URLhttps://www.data.go.kr/data/15028837/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 10 (18.5%) missing valuesMissing
연번 has unique valuesUnique
업체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:28:17.010147
Analysis finished2023-12-12 14:28:17.541415
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.5
Minimum1
Maximum54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T23:28:17.608816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.65
Q114.25
median27.5
Q340.75
95-th percentile51.35
Maximum54
Range53
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation15.732133
Coefficient of variation (CV)0.57207755
Kurtosis-1.2
Mean27.5
Median Absolute Deviation (MAD)13.5
Skewness0
Sum1485
Variance247.5
MonotonicityStrictly increasing
2023-12-12T23:28:17.763846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
42 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
38 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
54 1
1.9%
53 1
1.9%
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%

업체명
Text

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-12T23:28:17.971520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.7962963
Min length2

Characters and Unicode

Total characters367
Distinct characters92
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)100.0%

Sample

1st row행정사 이정희(삼오사)
2nd row행정사 노흥산사무소
3rd row행정사 사무소 래인
4th row무지개 행정사 사무소
5th row행정사 장지홍 사무소
ValueCountFrequency (%)
행정사 8
 
11.6%
사무소 6
 
8.7%
형성은 1
 
1.4%
에이치비행정사사무소 1
 
1.4%
희망행정사사무소 1
 
1.4%
서울공인중개사사무소 1
 
1.4%
경성행정사사무소 1
 
1.4%
범진 1
 
1.4%
유치윤 1
 
1.4%
김중택 1
 
1.4%
Other values (47) 47
68.1%
2023-12-12T23:28:18.327109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 66
18.0%
정 39
 
10.6%
행 36
 
9.8%
무 29
 
7.9%
소 28
 
7.6%
15
 
4.1%
이 9
 
2.5%
김 6
 
1.6%
성 4
 
1.1%
용 4
 
1.1%
Other values (82) 131
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 350
95.4%
Space Separator 15
 
4.1%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 66
18.9%
정 39
 
11.1%
행 36
 
10.3%
무 29
 
8.3%
소 28
 
8.0%
이 9
 
2.6%
김 6
 
1.7%
성 4
 
1.1%
용 4
 
1.1%
기 4
 
1.1%
Other values (79) 125
35.7%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 350
95.4%
Common 17
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 66
18.9%
정 39
 
11.1%
행 36
 
10.3%
무 29
 
8.3%
소 28
 
8.0%
이 9
 
2.6%
김 6
 
1.7%
성 4
 
1.1%
용 4
 
1.1%
기 4
 
1.1%
Other values (79) 125
35.7%
Common
ValueCountFrequency (%)
15
88.2%
) 1
 
5.9%
( 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 350
95.4%
ASCII 17
 
4.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 66
18.9%
정 39
 
11.1%
행 36
 
10.3%
무 29
 
8.3%
소 28
 
8.0%
이 9
 
2.6%
김 6
 
1.7%
성 4
 
1.1%
용 4
 
1.1%
기 4
 
1.1%
Other values (79) 125
35.7%
ASCII
ValueCountFrequency (%)
15
88.2%
) 1
 
5.9%
( 1
 
5.9%

주소
Text

Distinct50
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-12T23:28:18.688303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length40
Mean length26.87037
Min length21

Characters and Unicode

Total characters1451
Distinct characters83
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

Unique47 ?
Unique (%)87.0%

Sample

1st row서울특별시 중랑구 면목로 218, 도일약국 (면목동)
2nd row서울특별시 중랑구 봉우재로 72 (면목동)
3rd row서울특별시 중랑구 용마산로 345, 101호 (면목동)
4th row서울특별시 중랑구 중랑역로13길 17, 1층 (중화동)
5th row서울특별시 중랑구 동일로 825-1, 601호 (중화동, 강오아파트)
ValueCountFrequency (%)
서울특별시 54
18.5%
중랑구 54
18.5%
면목동 16
 
5.5%
묵동 15
 
5.1%
중랑역로 8
 
2.7%
상봉동 7
 
2.4%
망우로 6
 
2.1%
신내동 4
 
1.4%
망우동 4
 
1.4%
138 3
 
1.0%
Other values (103) 121
41.4%
2023-12-12T23:28:19.192860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
239
 
16.5%
중 67
 
4.6%
랑 63
 
4.3%
동 62
 
4.3%
서 54
 
3.7%
특 54
 
3.7%
별 54
 
3.7%
시 54
 
3.7%
구 54
 
3.7%
울 54
 
3.7%
Other values (73) 696
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 850
58.6%
Space Separator 239
 
16.5%
Decimal Number 218
 
15.0%
Open Punctuation 53
 
3.7%
Close Punctuation 53
 
3.7%
Other Punctuation 23
 
1.6%
Dash Punctuation 9
 
0.6%
Uppercase Letter 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 67
 
7.9%
랑 63
 
7.4%
동 62
 
7.3%
서 54
 
6.4%
특 54
 
6.4%
별 54
 
6.4%
시 54
 
6.4%
구 54
 
6.4%
울 54
 
6.4%
로 53
 
6.2%
Other values (52) 281
33.1%
Decimal Number
ValueCountFrequency (%)
1 53
24.3%
4 24
11.0%
2 23
10.6%
6 21
 
9.6%
0 20
 
9.2%
3 20
 
9.2%
8 17
 
7.8%
5 15
 
6.9%
9 13
 
6.0%
7 12
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
A 2
33.3%
N 1
16.7%
U 1
16.7%
G 1
16.7%
D 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 20
87.0%
， 3
 
13.0%
Space Separator
ValueCountFrequency (%)
239
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 850
58.6%
Common 595
41.0%
Latin 6
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 67
 
7.9%
랑 63
 
7.4%
동 62
 
7.3%
서 54
 
6.4%
특 54
 
6.4%
별 54
 
6.4%
시 54
 
6.4%
구 54
 
6.4%
울 54
 
6.4%
로 53
 
6.2%
Other values (52) 281
33.1%
Common
ValueCountFrequency (%)
239
40.2%
( 53
 
8.9%
) 53
 
8.9%
1 53
 
8.9%
4 24
 
4.0%
2 23
 
3.9%
6 21
 
3.5%
0 20
 
3.4%
, 20
 
3.4%
3 20
 
3.4%
Other values (6) 69
 
11.6%
Latin
ValueCountFrequency (%)
A 2
33.3%
N 1
16.7%
U 1
16.7%
G 1
16.7%
D 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 850
58.6%
ASCII 598
41.2%
None 3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
239
40.0%
( 53
 
8.9%
) 53
 
8.9%
1 53
 
8.9%
4 24
 
4.0%
2 23
 
3.8%
6 21
 
3.5%
0 20
 
3.3%
, 20
 
3.3%
3 20
 
3.3%
Other values (10) 72
 
12.0%
Hangul
ValueCountFrequency (%)
중 67
 
7.9%
랑 63
 
7.4%
동 62
 
7.3%
서 54
 
6.4%
특 54
 
6.4%
별 54
 
6.4%
시 54
 
6.4%
구 54
 
6.4%
울 54
 
6.4%
로 53
 
6.2%
Other values (52) 281
33.1%
None
ValueCountFrequency (%)
， 3
100.0%

전화번호
Text

MISSING 

Distinct43
Distinct (%)97.7%
Missing10
Missing (%)18.5%
Memory size564.0 B
2023-12-12T23:28:19.460994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.931818
Min length1

Characters and Unicode

Total characters481
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

Unique42 ?
Unique (%)95.5%

Sample

1st row02-2209-0354
2nd row02-914-4825
3rd row02-433-3898
4th row02-335-3797
5th row02-433-8536
ValueCountFrequency (%)
02-0000-0000 2
 
4.7%
02-491-5841 1
 
2.3%
02-434-1935 1
 
2.3%
02-2209-0354 1
 
2.3%
02-436-3747 1
 
2.3%
02-976-9600 1
 
2.3%
02-436-0640 1
 
2.3%
02-432-7065 1
 
2.3%
02-437-4984 1
 
2.3%
02-436-1474 1
 
2.3%
Other values (32) 32
74.4%
2023-12-12T23:28:19.789226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 86
17.9%
0 82
17.0%
2 66
13.7%
4 54
11.2%
9 42
8.7%
3 36
7.5%
7 29
 
6.0%
1 24
 
5.0%
5 23
 
4.8%
6 20
 
4.2%
Other values (2) 19
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 394
81.9%
Dash Punctuation 86
 
17.9%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 82
20.8%
2 66
16.8%
4 54
13.7%
9 42
10.7%
3 36
9.1%
7 29
 
7.4%
1 24
 
6.1%
5 23
 
5.8%
6 20
 
5.1%
8 18
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 86
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 481
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 86
17.9%
0 82
17.0%
2 66
13.7%
4 54
11.2%
9 42
8.7%
3 36
7.5%
7 29
 
6.0%
1 24
 
5.0%
5 23
 
4.8%
6 20
 
4.2%
Other values (2) 19
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 481
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 86
17.9%
0 82
17.0%
2 66
13.7%
4 54
11.2%
9 42
8.7%
3 36
7.5%
7 29
 
6.0%
1 24
 
5.0%
5 23
 
4.8%
6 20
 
4.2%
Other values (2) 19
 
4.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-04-27
54 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-04-27
2nd row2023-04-27
3rd row2023-04-27
4th row2023-04-27
5th row2023-04-27

Common Values

ValueCountFrequency (%)
2023-04-27 54
100.0%

Length

2023-12-12T23:28:19.934693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:28:20.036482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-04-27 54
100.0%

Interactions

2023-12-12T23:28:17.291811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:28:20.116855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업체명주소전화번호
연번1.0001.0000.6751.000
업체명1.0001.0001.0001.000
주소0.6751.0001.0000.986
전화번호1.0001.0000.9861.000

Missing values

2023-12-12T23:28:17.417161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:28:17.509074image/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

연번업체명주소전화번호데이터기준일자
01행정사 이정희(삼오사)서울특별시 중랑구 면목로 218, 도일약국 (면목동)02-2209-03542023-04-27
12행정사 노흥산사무소서울특별시 중랑구 봉우재로 72 (면목동)02-914-48252023-04-27
23행정사 사무소 래인서울특별시 중랑구 용마산로 345, 101호 (면목동)02-433-38982023-04-27
34무지개 행정사 사무소서울특별시 중랑구 중랑역로13길 17, 1층 (중화동)<NA>2023-04-27
45행정사 장지홍 사무소서울특별시 중랑구 동일로 825-1, 601호 (중화동, 강오아파트)02-335-37972023-04-27
56탑행정사사무소서울특별시 중랑구 용마산로 616 (신내동, 새한아파트)<NA>2023-04-27
67행정사사무소 김광진서울특별시 중랑구 봉우재로 164 (면목동)02-433-85362023-04-27
78박호일서울특별시 중랑구 신내역로3길 40-11 (신내동)02-975-39972023-04-27
89이영근 행정사 사무소서울특별시 중랑구 면목천로19길 18-4 (면목동)<NA>2023-04-27
910이양재행정사 사무소서울특별시 중랑구 망우로 414, 1층 (망우동)02-434-14492023-04-27
연번업체명주소전화번호데이터기준일자
4445박성종서울특별시 중랑구 면목동 120번지 2호02-432-17182023-04-27
4546이갑덕서울특별시 중랑구 중랑역로 138 (묵동)02-974-47742023-04-27
4647윤관용서울특별시 중랑구 중랑역로 140 (묵동)02-481-47152023-04-27
4748한승우 행정사서울특별시 중랑구 용마산로 474(망우동)<NA>2023-04-27
4849이영진행정사사무소서울특별시 중랑구 망우로 280, 1층 (상봉동)02-494-95402023-04-27
4950라온행정사사무소서울특별시 중랑구 공릉로4길 4-5, 202호 (묵동, GU AND 빌리지)<NA>2023-04-27
5051뉴월드행정사사무소서울특별시 중랑구 동일로 937， 1층(묵동)02-978-50002023-04-27
5152즐거운 행정사 사무소서울특별시 중랑구 면목로37길 24， 1층(면목동)02-0000-00002023-04-27
5253희망행정사사무소서울특별시 중랑구 겸재로18길 13(면목동)02-0000-00002023-04-27
5354면목행정사사무소서울특별시 중랑구 겸재로50길 36， 1층(면목동)2023-04-27