Overview

Dataset statistics

Number of variables6
Number of observations37
Missing cells39
Missing cells (%)17.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory53.6 B

Variable types

Numeric1
Unsupported1
Categorical1
Text3

Dataset

Description해외 대리인 데이터로, 해외대리인명 및 홈페이지 정보가 포함됨. 전화번호 및 주소 등 세부정보가 필요한 경우 IP-NAVI 사이트에서 확인 가능
Author한국지식재산보호원
URLhttps://www.data.go.kr/data/15092954/fileData.do

Alerts

국가 has constant value ""Constant
대륙 has 37 (100.0%) missing valuesMissing
해외대리인명(원문) has 2 (5.4%) missing valuesMissing
순번 has unique valuesUnique
대륙 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 21:07:40.676212
Analysis finished2023-12-12 21:07:41.274687
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19
Minimum1
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:07:41.365931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.8
Q110
median19
Q328
95-th percentile35.2
Maximum37
Range36
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.824355
Coefficient of variation (CV)0.56970291
Kurtosis-1.2
Mean19
Median Absolute Deviation (MAD)9
Skewness0
Sum703
Variance117.16667
MonotonicityStrictly increasing
2023-12-13T06:07:41.531696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 1
 
2.7%
29 1
 
2.7%
22 1
 
2.7%
23 1
 
2.7%
24 1
 
2.7%
25 1
 
2.7%
26 1
 
2.7%
27 1
 
2.7%
28 1
 
2.7%
30 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
1 1
2.7%
2 1
2.7%
3 1
2.7%
4 1
2.7%
5 1
2.7%
6 1
2.7%
7 1
2.7%
8 1
2.7%
9 1
2.7%
10 1
2.7%
ValueCountFrequency (%)
37 1
2.7%
36 1
2.7%
35 1
2.7%
34 1
2.7%
33 1
2.7%
32 1
2.7%
31 1
2.7%
30 1
2.7%
29 1
2.7%
28 1
2.7%

대륙
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)100.0%
Memory size465.0 B

국가
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
US
37 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
US 37
100.0%

Length

2023-12-13T06:07:41.703926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:07:41.821323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
us 37
100.0%

해외대리인명(영어)
Text

Distinct36
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-13T06:07:42.044610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length34
Mean length24.432432
Min length9

Characters and Unicode

Total characters904
Distinct characters49
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)94.6%

Sample

1st rowGlaser Weil Fink Howard Avchen & Shapiro LLP
2nd rowYancy IP Law, PLLC
3rd rowBrinks Gilson & Lione
4th rowH.C. Park & Associates, PLC
5th rowSughrue Mion, PLLC
ValueCountFrequency (%)
21
 
13.7%
llp 13
 
8.5%
law 4
 
2.6%
pllc 4
 
2.6%
p.c 3
 
2.0%
knobbe 2
 
1.3%
plc 2
 
1.3%
birch 2
 
1.3%
martens 2
 
1.3%
group 2
 
1.3%
Other values (95) 98
64.1%
2023-12-13T06:07:42.440819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
117
 
12.9%
e 74
 
8.2%
n 61
 
6.7%
a 53
 
5.9%
r 51
 
5.6%
L 48
 
5.3%
o 43
 
4.8%
s 35
 
3.9%
i 34
 
3.8%
P 31
 
3.4%
Other values (39) 357
39.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 543
60.1%
Uppercase Letter 188
 
20.8%
Space Separator 117
 
12.9%
Other Punctuation 56
 
6.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 74
13.6%
n 61
11.2%
a 53
9.8%
r 51
9.4%
o 43
 
7.9%
s 35
 
6.4%
i 34
 
6.3%
l 26
 
4.8%
t 24
 
4.4%
c 22
 
4.1%
Other values (12) 120
22.1%
Uppercase Letter
ValueCountFrequency (%)
L 48
25.5%
P 31
16.5%
C 18
 
9.6%
K 10
 
5.3%
S 9
 
4.8%
M 9
 
4.8%
H 8
 
4.3%
B 7
 
3.7%
G 6
 
3.2%
W 6
 
3.2%
Other values (12) 36
19.1%
Other Punctuation
ValueCountFrequency (%)
, 25
44.6%
& 22
39.3%
. 8
 
14.3%
' 1
 
1.8%
Space Separator
ValueCountFrequency (%)
117
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 731
80.9%
Common 173
 
19.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 74
 
10.1%
n 61
 
8.3%
a 53
 
7.3%
r 51
 
7.0%
L 48
 
6.6%
o 43
 
5.9%
s 35
 
4.8%
i 34
 
4.7%
P 31
 
4.2%
l 26
 
3.6%
Other values (34) 275
37.6%
Common
ValueCountFrequency (%)
117
67.6%
, 25
 
14.5%
& 22
 
12.7%
. 8
 
4.6%
' 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 904
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117
 
12.9%
e 74
 
8.2%
n 61
 
6.7%
a 53
 
5.9%
r 51
 
5.6%
L 48
 
5.3%
o 43
 
4.8%
s 35
 
3.9%
i 34
 
3.8%
P 31
 
3.4%
Other values (39) 357
39.5%

해외대리인명(원문)
Text

MISSING 

Distinct34
Distinct (%)97.1%
Missing2
Missing (%)5.4%
Memory size428.0 B
2023-12-13T06:07:42.666419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length33
Mean length24.428571
Min length9

Characters and Unicode

Total characters855
Distinct characters49
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)94.3%

Sample

1st rowGlaser Weil Fink Howard Avchen & Shapiro LLP
2nd rowYancy IP Law, PLLC
3rd rowBrinks Gilson & Lione
4th rowH.C. Park & Associates, PLC
5th rowSughrue Mion, PLLC
ValueCountFrequency (%)
21
 
14.6%
llp 13
 
9.0%
pllc 3
 
2.1%
knobbe 2
 
1.4%
plc 2
 
1.4%
martens 2
 
1.4%
p.c 2
 
1.4%
lee 2
 
1.4%
and 2
 
1.4%
law 2
 
1.4%
Other values (92) 93
64.6%
2023-12-13T06:07:42.976488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
110
 
12.9%
e 73
 
8.5%
n 60
 
7.0%
r 50
 
5.8%
a 49
 
5.7%
L 44
 
5.1%
o 42
 
4.9%
s 34
 
4.0%
i 33
 
3.9%
P 28
 
3.3%
Other values (39) 332
38.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 523
61.2%
Uppercase Letter 170
 
19.9%
Space Separator 110
 
12.9%
Other Punctuation 52
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 73
14.0%
n 60
11.5%
r 50
9.6%
a 49
9.4%
o 42
 
8.0%
s 34
 
6.5%
i 33
 
6.3%
l 25
 
4.8%
t 24
 
4.6%
c 21
 
4.0%
Other values (12) 112
21.4%
Uppercase Letter
ValueCountFrequency (%)
L 44
25.9%
P 28
16.5%
C 14
 
8.2%
S 9
 
5.3%
K 8
 
4.7%
H 8
 
4.7%
M 8
 
4.7%
B 7
 
4.1%
D 6
 
3.5%
W 6
 
3.5%
Other values (12) 32
18.8%
Other Punctuation
ValueCountFrequency (%)
, 23
44.2%
& 22
42.3%
. 6
 
11.5%
' 1
 
1.9%
Space Separator
ValueCountFrequency (%)
110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 693
81.1%
Common 162
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 73
 
10.5%
n 60
 
8.7%
r 50
 
7.2%
a 49
 
7.1%
L 44
 
6.3%
o 42
 
6.1%
s 34
 
4.9%
i 33
 
4.8%
P 28
 
4.0%
l 25
 
3.6%
Other values (34) 255
36.8%
Common
ValueCountFrequency (%)
110
67.9%
, 23
 
14.2%
& 22
 
13.6%
. 6
 
3.7%
' 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 855
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
110
 
12.9%
e 73
 
8.5%
n 60
 
7.0%
r 50
 
5.8%
a 49
 
5.7%
L 44
 
5.1%
o 42
 
4.9%
s 34
 
4.0%
i 33
 
3.9%
P 28
 
3.3%
Other values (39) 332
38.8%

주소(url)
Text

Distinct36
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-13T06:07:43.158691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length15.081081
Min length9

Characters and Unicode

Total characters558
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)94.6%

Sample

1st rowwww.glaserweil.com
2nd rowwww.yancyip.com
3rd rowwww.brinksgilson.com
4th rowwww.park-law.com
5th rowwww.sughrue.com
ValueCountFrequency (%)
www.knobbe.com 2
 
5.4%
www.glaserweil.com 1
 
2.7%
www.venable.com 1
 
2.7%
www.oliff.com 1
 
2.7%
www.fr.com 1
 
2.7%
www.kilpatricktownsend.com 1
 
2.7%
www.foley.com 1
 
2.7%
www.finnegan.com 1
 
2.7%
www.mwe.com 1
 
2.7%
www.slwip.com 1
 
2.7%
Other values (26) 26
70.3%
2023-12-13T06:07:43.446859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 114
20.4%
. 71
12.7%
o 54
9.7%
c 46
 
8.2%
m 41
 
7.3%
a 26
 
4.7%
l 25
 
4.5%
e 23
 
4.1%
n 20
 
3.6%
r 19
 
3.4%
Other values (15) 119
21.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 486
87.1%
Other Punctuation 71
 
12.7%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 114
23.5%
o 54
11.1%
c 46
9.5%
m 41
 
8.4%
a 26
 
5.3%
l 25
 
5.1%
e 23
 
4.7%
n 20
 
4.1%
r 19
 
3.9%
s 16
 
3.3%
Other values (13) 102
21.0%
Other Punctuation
ValueCountFrequency (%)
. 71
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 486
87.1%
Common 72
 
12.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 114
23.5%
o 54
11.1%
c 46
9.5%
m 41
 
8.4%
a 26
 
5.3%
l 25
 
5.1%
e 23
 
4.7%
n 20
 
4.1%
r 19
 
3.9%
s 16
 
3.3%
Other values (13) 102
21.0%
Common
ValueCountFrequency (%)
. 71
98.6%
- 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 558
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 114
20.4%
. 71
12.7%
o 54
9.7%
c 46
 
8.2%
m 41
 
7.3%
a 26
 
4.7%
l 25
 
4.5%
e 23
 
4.1%
n 20
 
3.6%
r 19
 
3.4%
Other values (15) 119
21.3%

Interactions

2023-12-13T06:07:40.896617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:07:43.528633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번해외대리인명(영어)해외대리인명(원문)주소(url)
순번1.0000.9160.9250.916
해외대리인명(영어)0.9161.0001.0001.000
해외대리인명(원문)0.9251.0001.0001.000
주소(url)0.9161.0001.0001.000

Missing values

2023-12-13T06:07:41.057519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:07:41.211174image/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

순번대륙국가해외대리인명(영어)해외대리인명(원문)주소(url)
01<NA>USGlaser Weil Fink Howard Avchen & Shapiro LLPGlaser Weil Fink Howard Avchen & Shapiro LLPwww.glaserweil.com
12<NA>USYancy IP Law, PLLCYancy IP Law, PLLCwww.yancyip.com
23<NA>USBrinks Gilson & LioneBrinks Gilson & Lionewww.brinksgilson.com
34<NA>USH.C. Park & Associates, PLCH.C. Park & Associates, PLCwww.park-law.com
45<NA>USSughrue Mion, PLLCSughrue Mion, PLLCwww.sughrue.com
56<NA>USVorys, Sater, Seymour and Pease LLPVorys, Sater, Seymour and Pease LLPwww.vorys.com
67<NA>USNovick, Kim & Lee, PLLCNovick, Kim & Lee, PLLCwww.nkllaw.com
78<NA>USBaker HostetlerBaker Hostetlerwww.bakerlaw.com
89<NA>USLucas & Mercanti LLPLucas & Mercanti LLPwww.lmiplaw.com
910<NA>USBlakely Law GroupBlakely Law Groupwww.blakelylawgroup.com
순번대륙국가해외대리인명(영어)해외대리인명(원문)주소(url)
2728<NA>USVenable LLPVenable LLPwww.venable.com
2829<NA>USSchwehman Lundberg & Woessner PASchwehman Lundberg & Woessner PAwww.slwip.com
2930<NA>USWenderoth Lind & Ponack, LLPWenderoth Lind & Ponack, LLPwww.wenderoth.com
3031<NA>USStaas & HalseyStaas & Halseywww.staasandhalsey.com
3132<NA>USBuchanan Ingersoll & RooneyBuchanan Ingersoll & Rooneywww.bipc.com
3233<NA>USPerkins Coie LLPPerkins Coie LLPwww.perkinscoie.com
3334<NA>USVolpe and Koeing, P.C.Volpe and Koeing, P.C.vklaw.com
3435<NA>USRopes & Gray LLPRopes & Gray LLPwww.ropesgray.com
3536<NA>USAMPACC Law Group, PLLC<NA>www.ampacc.com
3637<NA>USKlaus Kang Law Office, P.C.<NA>klauskang.com