Overview

Dataset statistics

Number of variables6
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory54.9 B

Variable types

Numeric2
Text4

Dataset

Description1. 개요출원지원사업, 브랜드 및 디자인 개발지원 사업, 출원비용 등을 지원하는 전국 지역지식재산센터 현황 정보를 제공합니다.2. 세부 정보 내용전국적으로 분포되어 있는 27개 지역지식재산센터 위치, 연락처 정보3. 데이터 출처지역지식재산센터 홈페이지http://ripc.org
Author특허청
URLhttps://www.data.go.kr/data/3071576/fileData.do

Alerts

NO is highly overall correlated with 우편번호High correlation
우편번호 is highly overall correlated with NOHigh correlation
NO has unique valuesUnique
센터명 has unique valuesUnique
운영기관 has unique valuesUnique
전화 has unique valuesUnique
우편번호 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:51:08.796637
Analysis finished2023-12-12 11:51:09.686932
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

NO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T20:51:09.756753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.3
Q17.5
median14
Q320.5
95-th percentile25.7
Maximum27
Range26
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.9372539
Coefficient of variation (CV)0.56694671
Kurtosis-1.2
Mean14
Median Absolute Deviation (MAD)7
Skewness0
Sum378
Variance63
MonotonicityStrictly increasing
2023-12-12T20:51:09.938134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 1
 
3.7%
2 1
 
3.7%
27 1
 
3.7%
26 1
 
3.7%
25 1
 
3.7%
24 1
 
3.7%
23 1
 
3.7%
22 1
 
3.7%
21 1
 
3.7%
20 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1 1
3.7%
2 1
3.7%
3 1
3.7%
4 1
3.7%
5 1
3.7%
6 1
3.7%
7 1
3.7%
8 1
3.7%
9 1
3.7%
10 1
3.7%
ValueCountFrequency (%)
27 1
3.7%
26 1
3.7%
25 1
3.7%
24 1
3.7%
23 1
3.7%
22 1
3.7%
21 1
3.7%
20 1
3.7%
19 1
3.7%
18 1
3.7%

센터명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T20:51:10.173470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.5925926
Min length8

Characters and Unicode

Total characters232
Distinct characters27
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

Unique27 ?
Unique (%)100.0%

Sample

1st row서울지식재산센터
2nd row인천지식재산센터
3rd row경기지식재산센터
4th row경기남부지식재산센터
5th row부천지식재산센터
ValueCountFrequency (%)
서울지식재산센터 1
 
3.7%
대전지식재산센터 1
 
3.7%
광주지식재산센터 1
 
3.7%
전남지식재산센터 1
 
3.7%
전북지식재산센터 1
 
3.7%
울산지식재산센터 1
 
3.7%
부산지식재산센터 1
 
3.7%
대구지식재산센터 1
 
3.7%
경남서부지식재산센터 1
 
3.7%
경남지식재산센터 1
 
3.7%
Other values (17) 17
63.0%
2023-12-12T20:51:10.554485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 29
12.5%
지 27
11.6%
식 27
11.6%
재 27
11.6%
센 27
11.6%
터 27
11.6%
부 10
 
4.3%
북 8
 
3.4%
경 7
 
3.0%
남 7
 
3.0%
Other values (17) 36
15.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 232
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 29
12.5%
지 27
11.6%
식 27
11.6%
재 27
11.6%
센 27
11.6%
터 27
11.6%
부 10
 
4.3%
북 8
 
3.4%
경 7
 
3.0%
남 7
 
3.0%
Other values (17) 36
15.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 232
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 29
12.5%
지 27
11.6%
식 27
11.6%
재 27
11.6%
센 27
11.6%
터 27
11.6%
부 10
 
4.3%
북 8
 
3.4%
경 7
 
3.0%
남 7
 
3.0%
Other values (17) 36
15.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 232
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 29
12.5%
지 27
11.6%
식 27
11.6%
재 27
11.6%
센 27
11.6%
터 27
11.6%
부 10
 
4.3%
북 8
 
3.4%
경 7
 
3.0%
남 7
 
3.0%
Other values (17) 36
15.5%

운영기관
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T20:51:10.824142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length7
Mean length7.962963
Min length7

Characters and Unicode

Total characters215
Distinct characters54
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

Unique27 ?
Unique (%)100.0%

Sample

1st row서울산업진흥원
2nd row인천상공회의소
3rd row경기테크노파크
4th row수원상공회의소
5th row부천산업진흥재단
ValueCountFrequency (%)
한국발명진흥회 2
 
6.9%
서울산업진흥원 1
 
3.4%
대전테크노파크 1
 
3.4%
한국발명진흥회광주지회 1
 
3.4%
목포상공회의소 1
 
3.4%
한국발명진흥회전북지부 1
 
3.4%
울산상공회의소 1
 
3.4%
한국발명진흥회부산지회 1
 
3.4%
대구상공회의소 1
 
3.4%
진주상공회의소 1
 
3.4%
Other values (18) 18
62.1%
2023-12-12T20:51:11.275297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 25
 
11.6%
소 17
 
7.9%
상 17
 
7.9%
공 17
 
7.9%
의 17
 
7.9%
진 9
 
4.2%
흥 8
 
3.7%
원 6
 
2.8%
주 5
 
2.3%
발 5
 
2.3%
Other values (44) 89
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 213
99.1%
Space Separator 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 25
 
11.7%
소 17
 
8.0%
상 17
 
8.0%
공 17
 
8.0%
의 17
 
8.0%
진 9
 
4.2%
흥 8
 
3.8%
원 6
 
2.8%
주 5
 
2.3%
발 5
 
2.3%
Other values (43) 87
40.8%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 213
99.1%
Common 2
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 25
 
11.7%
소 17
 
8.0%
상 17
 
8.0%
공 17
 
8.0%
의 17
 
8.0%
진 9
 
4.2%
흥 8
 
3.8%
원 6
 
2.8%
주 5
 
2.3%
발 5
 
2.3%
Other values (43) 87
40.8%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 213
99.1%
ASCII 2
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 25
 
11.7%
소 17
 
8.0%
상 17
 
8.0%
공 17
 
8.0%
의 17
 
8.0%
진 9
 
4.2%
흥 8
 
3.8%
원 6
 
2.8%
주 5
 
2.3%
발 5
 
2.3%
Other values (43) 87
40.8%
ASCII
ValueCountFrequency (%)
2
100.0%

전화
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T20:51:11.534651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length13.037037
Min length13

Characters and Unicode

Total characters352
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row02) 2222-3860
2nd row032) 810-2882
3rd row031) 500-3043
4th row031) 244-8321
5th row070) 7094-5483
ValueCountFrequency (%)
033 4
 
7.4%
054 3
 
5.6%
043 2
 
3.7%
031 2
 
3.7%
055 2
 
3.7%
041 2
 
3.7%
454-6613 1
 
1.9%
859-3093 1
 
1.9%
210-3085 1
 
1.9%
762-9411 1
 
1.9%
Other values (35) 35
64.8%
2023-12-12T20:51:12.029069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 48
13.6%
3 37
10.5%
4 35
9.9%
2 34
9.7%
5 33
9.4%
) 27
7.7%
27
7.7%
- 27
7.7%
8 19
 
5.4%
1 18
 
5.1%
Other values (3) 47
13.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 271
77.0%
Close Punctuation 27
 
7.7%
Space Separator 27
 
7.7%
Dash Punctuation 27
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 48
17.7%
3 37
13.7%
4 35
12.9%
2 34
12.5%
5 33
12.2%
8 19
 
7.0%
1 18
 
6.6%
6 17
 
6.3%
7 15
 
5.5%
9 15
 
5.5%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 352
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 48
13.6%
3 37
10.5%
4 35
9.9%
2 34
9.7%
5 33
9.4%
) 27
7.7%
27
7.7%
- 27
7.7%
8 19
 
5.4%
1 18
 
5.1%
Other values (3) 47
13.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 352
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 48
13.6%
3 37
10.5%
4 35
9.9%
2 34
9.7%
5 33
9.4%
) 27
7.7%
27
7.7%
- 27
7.7%
8 19
 
5.4%
1 18
 
5.1%
Other values (3) 47
13.4%

우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35057.667
Minimum3925
Maximum63208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T20:51:12.212531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3925
5-th percentile14827.8
Q125743
median31984
Q345836.5
95-th percentile60271.3
Maximum63208
Range59283
Interquartile range (IQR)20093.5

Descriptive statistics

Standard deviation15333.971
Coefficient of variation (CV)0.43739281
Kurtosis-0.5754624
Mean35057.667
Median Absolute Deviation (MAD)9276
Skewness0.15781382
Sum946557
Variance2.3513068 × 108
MonotonicityNot monotonic
2023-12-12T20:51:12.382856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
3925 1
 
3.7%
21632 1
 
3.7%
63208 1
 
3.7%
61003 1
 
3.7%
58564 1
 
3.7%
54853 1
 
3.7%
52782 1
 
3.7%
51444 1
 
3.7%
36709 1
 
3.7%
39277 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
3925 1
3.7%
14502 1
3.7%
15588 1
3.7%
16313 1
3.7%
21632 1
3.7%
24341 1
3.7%
25475 1
3.7%
26011 1
3.7%
26336 1
3.7%
27339 1
3.7%
ValueCountFrequency (%)
63208 1
3.7%
61003 1
3.7%
58564 1
3.7%
54853 1
3.7%
52782 1
3.7%
51444 1
3.7%
46984 1
3.7%
44689 1
3.7%
41260 1
3.7%
39277 1
3.7%

주소
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T20:51:12.758126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length32
Mean length29.62963
Min length20

Characters and Unicode

Total characters800
Distinct characters148
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

Unique27 ?
Unique (%)100.0%

Sample

1st row서울특별시 마포구월드컵북로400 서울산업진흥원13층
2nd row인천광역시 남동구 은봉로60번길 46 인천상공회의소 6층
3rd row경기도 안산시 상록구 해안로 705 경기테크노파크 지원편의동 1층
4th row경기도 수원시 장안구 수성로 311
5th row경기도 부천시 원미구 평천로655 부천테크노파크 401동 1503호
ValueCountFrequency (%)
1층 5
 
3.0%
3층 3
 
1.8%
경기도 3
 
1.8%
강원도 3
 
1.8%
경상북도 3
 
1.8%
충청북도 2
 
1.2%
경상남도 2
 
1.2%
2층 2
 
1.2%
남구 2
 
1.2%
중앙로 2
 
1.2%
Other values (137) 139
83.7%
2023-12-12T20:51:13.317615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
144
 
18.0%
시 26
 
3.2%
1 24
 
3.0%
로 23
 
2.9%
상 22
 
2.8%
구 20
 
2.5%
원 18
 
2.2%
층 18
 
2.2%
도 17
 
2.1%
3 15
 
1.9%
Other values (138) 473
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 517
64.6%
Space Separator 144
 
18.0%
Decimal Number 117
 
14.6%
Lowercase Letter 8
 
1.0%
Uppercase Letter 6
 
0.8%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Other Punctuation 2
 
0.2%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 26
 
5.0%
로 23
 
4.4%
상 22
 
4.3%
구 20
 
3.9%
원 18
 
3.5%
층 18
 
3.5%
도 17
 
3.3%
의 15
 
2.9%
소 14
 
2.7%
회 13
 
2.5%
Other values (113) 331
64.0%
Decimal Number
ValueCountFrequency (%)
1 24
20.5%
3 15
12.8%
0 14
12.0%
2 12
10.3%
5 12
10.3%
4 11
9.4%
6 9
 
7.7%
7 8
 
6.8%
9 6
 
5.1%
8 6
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
o 3
37.5%
t 2
25.0%
i 1
 
12.5%
a 1
 
12.5%
n 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
S 2
33.3%
T 1
16.7%
P 1
16.7%
B 1
16.7%
D 1
16.7%
Space Separator
ValueCountFrequency (%)
144
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 517
64.6%
Common 269
33.6%
Latin 14
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 26
 
5.0%
로 23
 
4.4%
상 22
 
4.3%
구 20
 
3.9%
원 18
 
3.5%
층 18
 
3.5%
도 17
 
3.3%
의 15
 
2.9%
소 14
 
2.7%
회 13
 
2.5%
Other values (113) 331
64.0%
Common
ValueCountFrequency (%)
144
53.5%
1 24
 
8.9%
3 15
 
5.6%
0 14
 
5.2%
2 12
 
4.5%
5 12
 
4.5%
4 11
 
4.1%
6 9
 
3.3%
7 8
 
3.0%
9 6
 
2.2%
Other values (5) 14
 
5.2%
Latin
ValueCountFrequency (%)
o 3
21.4%
S 2
14.3%
t 2
14.3%
T 1
 
7.1%
P 1
 
7.1%
i 1
 
7.1%
B 1
 
7.1%
D 1
 
7.1%
a 1
 
7.1%
n 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 517
64.6%
ASCII 283
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
144
50.9%
1 24
 
8.5%
3 15
 
5.3%
0 14
 
4.9%
2 12
 
4.2%
5 12
 
4.2%
4 11
 
3.9%
6 9
 
3.2%
7 8
 
2.8%
9 6
 
2.1%
Other values (15) 28
 
9.9%
Hangul
ValueCountFrequency (%)
시 26
 
5.0%
로 23
 
4.4%
상 22
 
4.3%
구 20
 
3.9%
원 18
 
3.5%
층 18
 
3.5%
도 17
 
3.3%
의 15
 
2.9%
소 14
 
2.7%
회 13
 
2.5%
Other values (113) 331
64.0%

Interactions

2023-12-12T20:51:09.295318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:09.111812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:09.394111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:09.195005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:51:13.461851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
NO센터명운영기관전화우편번호주소
NO1.0001.0001.0001.0000.8691.000
센터명1.0001.0001.0001.0001.0001.000
운영기관1.0001.0001.0001.0001.0001.000
전화1.0001.0001.0001.0001.0001.000
우편번호0.8691.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.000
2023-12-12T20:51:13.589850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
NO우편번호
NO1.0000.968
우편번호0.9681.000

Missing values

2023-12-12T20:51:09.502075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:51:09.608177image/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

NO센터명운영기관전화우편번호주소
01서울지식재산센터서울산업진흥원02) 2222-38603925서울특별시 마포구월드컵북로400 서울산업진흥원13층
12인천지식재산센터인천상공회의소032) 810-288221632인천광역시 남동구 은봉로60번길 46 인천상공회의소 6층
23경기지식재산센터경기테크노파크031) 500-304315588경기도 안산시 상록구 해안로 705 경기테크노파크 지원편의동 1층
34경기남부지식재산센터수원상공회의소031) 244-832116313경기도 수원시 장안구 수성로 311
45부천지식재산센터부천산업진흥재단070) 7094-548314502경기도 부천시 원미구 평천로655 부천테크노파크 401동 1503호
56강원지식재산센터강원도경제진흥원033) 749-332626336강원도 원주시 호저로 47 강원도산업경제진흥원 1층
67강원서부지식재산센터한국발명진흥회 강원지회033) 264-658024341강원 춘천시 강원대학길 1, 강원대학교 보듬관 403호
78강원남부지식재산센터태백상공회의소033) 552-477925475강원도 태백시 황지로 188-1 태백상공회의소
89강릉지식재산센터강릉상공회의소033) 643-441326011강원도 강릉시 종합운동장길 88 강릉상공회의소 5층
910충북지식재산센터청주상공회의소043) 229-273228514충청북도 청주시 상당구 상당로 106 청주상공회의소 1층
NO센터명운영기관전화우편번호주소
1718경북북부지식재산센터안동상공회의소054) 859-309341260경상북도 안동시 축제장길 240안동상공회의소
1819경남지식재산센터창원상공회의소055) 210-308537783경상남도 창원시 의창구 중앙대로 166 창원상공회의소 1층
1920경남서부지식재산센터진주상공회의소055) 762-941139277경상남도 진주시 동진로 255 진주상공회의소 3층
2021대구지식재산센터대구상공회의소053) 242-807936709대구광역시 동구 동대구로 457 대구상공회의소
2122부산지식재산센터한국발명진흥회부산지회051) 645-968351444부산 광역시 사상구 학감대로257 보생빌딩 3층
2223울산지식재산센터울산상공회의소052) 228-308752782울산광역시 남구 돋질로 97 울산상공회의소 2층
2324전북지식재산센터한국발명진흥회전북지부063) 252-930154853전주시 덕진구 반룡로 109 전북 TP 벤처지원동 105호
2425전남지식재산센터목포상공회의소061) 242-858758564전라남도 무안군 삼향읍 오룡3길 2 전남중소기업종합지원센터 4층
2526광주지식재산센터한국발명진흥회광주지회062) 954-384161003광주광역시 북구 추암로 249 이노비즈센터 7층(월출동 987)
2627제주지식재산센터제주상공회의소064) 755-255463208제주특별자치도 제주시 중앙로 217 벤처마루 6층 603호