Overview

Dataset statistics

Number of variables5
Number of observations122
Missing cells9
Missing cells (%)1.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory42.1 B

Variable types

Numeric1
Text4

Dataset

Description불법감청설비탐지업을 중앙전파관리소에 등록한 업체 현황(연번, 법인명칭, 대표자, 소재지, 전화번호 등)에 대한정보를 제공하고 있습니다. 해당 데이터가 보유한 내용은 아래와 같습니다.정보내역 : 연번, 법인병칭, 대표자, 소재지, 전화번호
Author과학기술정보통신부 중앙전파관리소
URLhttps://www.data.go.kr/data/15125572/fileData.do

Alerts

전화번호 has 9 (7.4%) missing valuesMissing
연번 has unique valuesUnique
법인명칭 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-23 07:49:06.273140
Analysis finished2023-12-23 07:49:09.675180
Duration3.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.5
Minimum1
Maximum122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-23T07:49:10.060881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.05
Q131.25
median61.5
Q391.75
95-th percentile115.95
Maximum122
Range121
Interquartile range (IQR)60.5

Descriptive statistics

Standard deviation35.362409
Coefficient of variation (CV)0.57499853
Kurtosis-1.2
Mean61.5
Median Absolute Deviation (MAD)30.5
Skewness0
Sum7503
Variance1250.5
MonotonicityStrictly increasing
2023-12-23T07:49:11.226423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
93 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
Other values (112) 112
91.8%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
122 1
0.8%
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%

법인명칭
Text

UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-23T07:49:12.708683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.9098361
Min length3

Characters and Unicode

Total characters843
Distinct characters199
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)100.0%

Sample

1st row㈜에스원
2nd row금성시큐리티㈜
3rd row㈜한국스파이존
4th row㈜글로벌티에쓰시엠그룹
5th row에이치디에스㈜
ValueCountFrequency (%)
㈜에스원 1
 
0.8%
주)시티캅 1
 
0.8%
㈜아라세이브 1
 
0.8%
㈜조은스탭스 1
 
0.8%
㈜이터널파트너스 1
 
0.8%
㈜탐정법인오앤 1
 
0.8%
가평하우징㈜ 1
 
0.8%
㈜보안정보통신 1
 
0.8%
㈜지에스시큐리티 1
 
0.8%
㈜명진이엔지 1
 
0.8%
Other values (115) 115
92.0%
2023-12-23T07:49:14.689021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 98
 
11.6%
스 49
 
5.8%
이 40
 
4.7%
에 25
 
3.0%
( 24
 
2.8%
) 24
 
2.8%
시 20
 
2.4%
리 18
 
2.1%
주 18
 
2.1%
티 18
 
2.1%
Other values (189) 509
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 691
82.0%
Other Symbol 98
 
11.6%
Open Punctuation 24
 
2.8%
Close Punctuation 24
 
2.8%
Space Separator 3
 
0.4%
Uppercase Letter 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 49
 
7.1%
이 40
 
5.8%
에 25
 
3.6%
시 20
 
2.9%
리 18
 
2.6%
주 18
 
2.6%
티 18
 
2.6%
보 16
 
2.3%
큐 15
 
2.2%
아 15
 
2.2%
Other values (182) 457
66.1%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
B 1
33.3%
W 1
33.3%
Other Symbol
ValueCountFrequency (%)
㈜ 98
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 789
93.6%
Common 51
 
6.0%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 98
 
12.4%
스 49
 
6.2%
이 40
 
5.1%
에 25
 
3.2%
시 20
 
2.5%
리 18
 
2.3%
주 18
 
2.3%
티 18
 
2.3%
보 16
 
2.0%
큐 15
 
1.9%
Other values (183) 472
59.8%
Common
ValueCountFrequency (%)
( 24
47.1%
) 24
47.1%
3
 
5.9%
Latin
ValueCountFrequency (%)
C 1
33.3%
B 1
33.3%
W 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 691
82.0%
None 98
 
11.6%
ASCII 54
 
6.4%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 98
100.0%
Hangul
ValueCountFrequency (%)
스 49
 
7.1%
이 40
 
5.8%
에 25
 
3.6%
시 20
 
2.9%
리 18
 
2.6%
주 18
 
2.6%
티 18
 
2.6%
보 16
 
2.3%
큐 15
 
2.2%
아 15
 
2.2%
Other values (182) 457
66.1%
ASCII
ValueCountFrequency (%)
( 24
44.4%
) 24
44.4%
3
 
5.6%
C 1
 
1.9%
B 1
 
1.9%
W 1
 
1.9%

대표자
Text

Distinct121
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-23T07:49:15.961587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.2459016
Min length2

Characters and Unicode

Total characters396
Distinct characters118
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

Unique120 ?
Unique (%)98.4%

Sample

1st row남궁범
2nd row남형종
3rd row박현자
4th row안교승
5th row조한봉
ValueCountFrequency (%)
백봉현 2
 
1.5%
이영진 1
 
0.8%
박헌환 1
 
0.8%
이두훈 1
 
0.8%
김용준 1
 
0.8%
이현민 1
 
0.8%
최환욱 1
 
0.8%
장동혁 1
 
0.8%
유채은 1
 
0.8%
남성곤 1
 
0.8%
Other values (119) 119
91.5%
2023-12-23T07:49:19.182735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 23
 
5.8%
이 16
 
4.0%
영 13
 
3.3%
박 12
 
3.0%
성 11
 
2.8%
현 10
 
2.5%
남 8
 
2.0%
철 8
 
2.0%
형 8
 
2.0%
은 8
 
2.0%
Other values (108) 279
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 388
98.0%
Space Separator 8
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 23
 
5.9%
이 16
 
4.1%
영 13
 
3.4%
박 12
 
3.1%
성 11
 
2.8%
현 10
 
2.6%
남 8
 
2.1%
철 8
 
2.1%
형 8
 
2.1%
은 8
 
2.1%
Other values (107) 271
69.8%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 388
98.0%
Common 8
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 23
 
5.9%
이 16
 
4.1%
영 13
 
3.4%
박 12
 
3.1%
성 11
 
2.8%
현 10
 
2.6%
남 8
 
2.1%
철 8
 
2.1%
형 8
 
2.1%
은 8
 
2.1%
Other values (107) 271
69.8%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 388
98.0%
ASCII 8
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 23
 
5.9%
이 16
 
4.1%
영 13
 
3.4%
박 12
 
3.1%
성 11
 
2.8%
현 10
 
2.6%
남 8
 
2.1%
철 8
 
2.1%
형 8
 
2.1%
은 8
 
2.1%
Other values (107) 271
69.8%
ASCII
ValueCountFrequency (%)
8
100.0%

소재지
Text

UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-23T07:49:21.264025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length44
Mean length30.647541
Min length15

Characters and Unicode

Total characters3739
Distinct characters273
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)100.0%

Sample

1st row서울시 중구 세종대로7길 25 삼성생명에스원빌딩
2nd row서울시 마포구 동교로 179
3rd row서울시 강남구 테헤란로25길, 20 (역삼현대벤쳐텔 20층 2003호)
4th row경기도 안산시 단원구 산단로 278, 에이동 413호(원시동)
5th row서울시 서초구 양재대로11길 36 (서울오토갤러리 금관 4층)
ValueCountFrequency (%)
서울시 49
 
6.5%
경기도 24
 
3.2%
2층 9
 
1.2%
송파구 9
 
1.2%
강남구 7
 
0.9%
성남시 6
 
0.8%
마포구 6
 
0.8%
북구 6
 
0.8%
남구 6
 
0.8%
1층 6
 
0.8%
Other values (504) 626
83.0%
2023-12-23T07:49:23.299582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
633
 
16.9%
1 144
 
3.9%
, 129
 
3.5%
시 121
 
3.2%
로 119
 
3.2%
구 109
 
2.9%
2 106
 
2.8%
동 91
 
2.4%
0 88
 
2.4%
3 84
 
2.2%
Other values (263) 2115
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2080
55.6%
Decimal Number 702
 
18.8%
Space Separator 633
 
16.9%
Other Punctuation 129
 
3.5%
Close Punctuation 74
 
2.0%
Open Punctuation 73
 
2.0%
Dash Punctuation 27
 
0.7%
Uppercase Letter 20
 
0.5%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 121
 
5.8%
로 119
 
5.7%
구 109
 
5.2%
동 91
 
4.4%
서 75
 
3.6%
호 67
 
3.2%
울 55
 
2.6%
길 45
 
2.2%
남 45
 
2.2%
층 44
 
2.1%
Other values (238) 1309
62.9%
Decimal Number
ValueCountFrequency (%)
1 144
20.5%
2 106
15.1%
0 88
12.5%
3 84
12.0%
4 69
9.8%
6 57
 
8.1%
5 46
 
6.6%
7 39
 
5.6%
8 35
 
5.0%
9 34
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
C 4
20.0%
B 4
20.0%
A 3
15.0%
E 2
10.0%
T 2
10.0%
I 2
10.0%
O 1
 
5.0%
S 1
 
5.0%
R 1
 
5.0%
Space Separator
ValueCountFrequency (%)
633
100.0%
Other Punctuation
ValueCountFrequency (%)
, 129
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2080
55.6%
Common 1638
43.8%
Latin 21
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 121
 
5.8%
로 119
 
5.7%
구 109
 
5.2%
동 91
 
4.4%
서 75
 
3.6%
호 67
 
3.2%
울 55
 
2.6%
길 45
 
2.2%
남 45
 
2.2%
층 44
 
2.1%
Other values (238) 1309
62.9%
Common
ValueCountFrequency (%)
633
38.6%
1 144
 
8.8%
, 129
 
7.9%
2 106
 
6.5%
0 88
 
5.4%
3 84
 
5.1%
) 74
 
4.5%
( 73
 
4.5%
4 69
 
4.2%
6 57
 
3.5%
Other values (5) 181
 
11.1%
Latin
ValueCountFrequency (%)
C 4
19.0%
B 4
19.0%
A 3
14.3%
E 2
9.5%
T 2
9.5%
I 2
9.5%
O 1
 
4.8%
S 1
 
4.8%
e 1
 
4.8%
R 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2080
55.6%
ASCII 1659
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
633
38.2%
1 144
 
8.7%
, 129
 
7.8%
2 106
 
6.4%
0 88
 
5.3%
3 84
 
5.1%
) 74
 
4.5%
( 73
 
4.4%
4 69
 
4.2%
6 57
 
3.4%
Other values (15) 202
 
12.2%
Hangul
ValueCountFrequency (%)
시 121
 
5.8%
로 119
 
5.7%
구 109
 
5.2%
동 91
 
4.4%
서 75
 
3.6%
호 67
 
3.2%
울 55
 
2.6%
길 45
 
2.2%
남 45
 
2.2%
층 44
 
2.1%
Other values (238) 1309
62.9%

전화번호
Text

MISSING 

Distinct113
Distinct (%)100.0%
Missing9
Missing (%)7.4%
Memory size1.1 KiB
2023-12-23T07:49:24.681254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.637168
Min length9

Characters and Unicode

Total characters1315
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

Unique113 ?
Unique (%)100.0%

Sample

1st row02-6403-3111
2nd row02-333-4000
3rd row02-544-5119
4th row02-3776-5000
5th row02-2055-8282
ValueCountFrequency (%)
02-852-3560 1
 
0.9%
031-8035-9112 1
 
0.9%
02-6952-7706 1
 
0.9%
02-2039-2321 1
 
0.9%
031-5176-9888 1
 
0.9%
070-4383-2112 1
 
0.9%
02-557-4818 1
 
0.9%
031-8015-1526 1
 
0.9%
031-731-0020 1
 
0.9%
1544-3835 1
 
0.9%
Other values (103) 103
91.2%
2023-12-23T07:49:26.945036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 215
16.3%
0 207
15.7%
2 155
11.8%
1 133
10.1%
3 123
9.4%
5 103
7.8%
6 93
7.1%
4 83
 
6.3%
7 81
 
6.2%
8 73
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
83.7%
Dash Punctuation 215
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 207
18.8%
2 155
14.1%
1 133
12.1%
3 123
11.2%
5 103
9.4%
6 93
8.5%
4 83
7.5%
7 81
 
7.4%
8 73
 
6.6%
9 49
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 215
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1315
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 215
16.3%
0 207
15.7%
2 155
11.8%
1 133
10.1%
3 123
9.4%
5 103
7.8%
6 93
7.1%
4 83
 
6.3%
7 81
 
6.2%
8 73
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1315
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 215
16.3%
0 207
15.7%
2 155
11.8%
1 133
10.1%
3 123
9.4%
5 103
7.8%
6 93
7.1%
4 83
 
6.3%
7 81
 
6.2%
8 73
 
5.6%

Interactions

2023-12-23T07:49:07.813321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-23T07:49:08.628338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-23T07:49:09.406480image/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

연번법인명칭대표자소재지전화번호
01㈜에스원남궁범서울시 중구 세종대로7길 25 삼성생명에스원빌딩02-6403-3111
12금성시큐리티㈜남형종서울시 마포구 동교로 17902-333-4000
23㈜한국스파이존박현자서울시 강남구 테헤란로25길, 20 (역삼현대벤쳐텔 20층 2003호)02-544-5119
34㈜글로벌티에쓰시엠그룹안교승경기도 안산시 단원구 산단로 278, 에이동 413호(원시동)02-3776-5000
45에이치디에스㈜조한봉서울시 서초구 양재대로11길 36 (서울오토갤러리 금관 4층)02-2055-8282
56코세스코리아㈜백봉현서울시 송파구 송파대로 474, 501호 (송파동,성정빌딩)02-424-0112
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