Overview

Dataset statistics

Number of variables3
Number of observations240
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory25.6 B

Variable types

Text2
Numeric1

Dataset

Description온라인수출플랫폼(Gobizkorea)에서 보유하고 현재 국내외에서 회원가입, 인콰이어리 발송 등을 통해 활동 중인 국가별 해외 바이어 수 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15071457/fileData.do

Alerts

국가명(국문) has unique valuesUnique
국가명(영문) has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:21:17.506814
Analysis finished2023-12-12 03:21:17.934449
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

국가명(국문)
Text

UNIQUE 

Distinct240
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-12T12:21:18.117050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length4.3583333
Min length1

Characters and Unicode

Total characters1046
Distinct characters213
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

Unique240 ?
Unique (%)100.0%

Sample

1st row미국
2nd row중국
3rd row아프가니스탄
4th row인도
5th row홍콩
ValueCountFrequency (%)
제도 11
 
3.9%
섬 6
 
2.1%
공화국 6
 
2.1%
도미니카 2
 
0.7%
연방 2
 
0.7%
미국령 2
 
0.7%
콩고 2
 
0.7%
프랑스령 2
 
0.7%
기니 2
 
0.7%
버진아일랜드 2
 
0.7%
Other values (247) 247
87.0%
2023-12-12T12:21:18.566712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 63
 
6.0%
44
 
4.2%
스 41
 
3.9%
리 37
 
3.5%
르 28
 
2.7%
니 26
 
2.5%
이 24
 
2.3%
도 23
 
2.2%
라 23
 
2.2%
나 20
 
1.9%
Other values (203) 717
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1002
95.8%
Space Separator 44
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 63
 
6.3%
스 41
 
4.1%
리 37
 
3.7%
르 28
 
2.8%
니 26
 
2.6%
이 24
 
2.4%
도 23
 
2.3%
라 23
 
2.3%
나 20
 
2.0%
트 18
 
1.8%
Other values (202) 699
69.8%
Space Separator
ValueCountFrequency (%)
44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1002
95.8%
Common 44
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 63
 
6.3%
스 41
 
4.1%
리 37
 
3.7%
르 28
 
2.8%
니 26
 
2.6%
이 24
 
2.4%
도 23
 
2.3%
라 23
 
2.3%
나 20
 
2.0%
트 18
 
1.8%
Other values (202) 699
69.8%
Common
ValueCountFrequency (%)
44
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1002
95.8%
ASCII 44
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 63
 
6.3%
스 41
 
4.1%
리 37
 
3.7%
르 28
 
2.8%
니 26
 
2.6%
이 24
 
2.4%
도 23
 
2.3%
라 23
 
2.3%
나 20
 
2.0%
트 18
 
1.8%
Other values (202) 699
69.8%
ASCII
ValueCountFrequency (%)
44
100.0%

국가명(영문)
Text

UNIQUE 

Distinct240
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-12T12:21:19.120079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length41
Mean length11.216667
Min length4

Characters and Unicode

Total characters2692
Distinct characters58
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique240 ?
Unique (%)100.0%

Sample

1st rowUnited States of America
2nd rowChina
3rd rowAfghanistan
4th rowIndia
5th rowChina, Hong Kong Special Administrative Region
ValueCountFrequency (%)
islands 15
 
3.8%
of 14
 
3.6%
republic 12
 
3.1%
and 12
 
3.1%
united 6
 
1.5%
saint 5
 
1.3%
states 4
 
1.0%
the 3
 
0.8%
democratic 3
 
0.8%
island 3
 
0.8%
Other values (293) 315
80.4%
2023-12-12T12:21:19.812995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 363
 
13.5%
i 216
 
8.0%
n 214
 
7.9%
e 194
 
7.2%
152
 
5.6%
r 140
 
5.2%
o 136
 
5.1%
l 118
 
4.4%
t 110
 
4.1%
s 105
 
3.9%
Other values (48) 944
35.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2151
79.9%
Uppercase Letter 363
 
13.5%
Space Separator 152
 
5.6%
Other Punctuation 10
 
0.4%
Open Punctuation 7
 
0.3%
Close Punctuation 7
 
0.3%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 363
16.9%
i 216
10.0%
n 214
9.9%
e 194
9.0%
r 140
 
6.5%
o 136
 
6.3%
l 118
 
5.5%
t 110
 
5.1%
s 105
 
4.9%
u 98
 
4.6%
Other values (16) 457
21.2%
Uppercase Letter
ValueCountFrequency (%)
S 44
12.1%
M 31
 
8.5%
I 30
 
8.3%
C 26
 
7.2%
B 25
 
6.9%
A 23
 
6.3%
G 21
 
5.8%
R 20
 
5.5%
N 18
 
5.0%
T 17
 
4.7%
Other values (15) 108
29.8%
Other Punctuation
ValueCountFrequency (%)
? 4
40.0%
' 3
30.0%
, 3
30.0%
Space Separator
ValueCountFrequency (%)
152
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2514
93.4%
Common 178
 
6.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 363
14.4%
i 216
 
8.6%
n 214
 
8.5%
e 194
 
7.7%
r 140
 
5.6%
o 136
 
5.4%
l 118
 
4.7%
t 110
 
4.4%
s 105
 
4.2%
u 98
 
3.9%
Other values (41) 820
32.6%
Common
ValueCountFrequency (%)
152
85.4%
( 7
 
3.9%
) 7
 
3.9%
? 4
 
2.2%
' 3
 
1.7%
, 3
 
1.7%
- 2
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2692
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 363
 
13.5%
i 216
 
8.0%
n 214
 
7.9%
e 194
 
7.2%
152
 
5.6%
r 140
 
5.2%
o 136
 
5.1%
l 118
 
4.4%
t 110
 
4.1%
s 105
 
3.9%
Other values (48) 944
35.1%

해외바이어 수
Real number (ℝ)

Distinct172
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1399.65
Minimum2
Maximum64310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T12:21:20.033583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile68
Q183
median193.5
Q3475.75
95-th percentile5276.5
Maximum64310
Range64308
Interquartile range (IQR)392.75

Descriptive statistics

Standard deviation5649.666
Coefficient of variation (CV)4.0364849
Kurtosis75.413223
Mean1399.65
Median Absolute Deviation (MAD)117.5
Skewness8.0602259
Sum335916
Variance31918726
MonotonicityDecreasing
2023-12-12T12:21:20.242533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75 8
 
3.3%
80 6
 
2.5%
79 5
 
2.1%
87 5
 
2.1%
68 5
 
2.1%
93 4
 
1.7%
229 4
 
1.7%
84 4
 
1.7%
78 4
 
1.7%
76 4
 
1.7%
Other values (162) 191
79.6%
ValueCountFrequency (%)
2 1
 
0.4%
3 2
 
0.8%
51 1
 
0.4%
60 1
 
0.4%
63 1
 
0.4%
65 3
1.2%
66 1
 
0.4%
67 1
 
0.4%
68 5
2.1%
69 2
 
0.8%
ValueCountFrequency (%)
64310 1
0.4%
35803 1
0.4%
32414 1
0.4%
29227 1
0.4%
14707 1
0.4%
8090 1
0.4%
7968 1
0.4%
7195 1
0.4%
7103 1
0.4%
6137 1
0.4%

Interactions

2023-12-12T12:21:17.674019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T12:21:17.824536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:21:17.902590image/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

국가명(국문)국가명(영문)해외바이어 수
0미국United States of America64310
1중국China35803
2아프가니스탄Afghanistan32414
3인도India29227
4홍콩China, Hong Kong Special Administrative Region14707
5일본Japan8090
6싱가포르Singapore7968
7프랑스France7195
8대한민국Republic of Korea7103
9대만Taiwan6137
국가명(국문)국가명(영문)해외바이어 수
230카보베르데Cabo Verde66
231니우에Niue65
232쿡 제도Cook Islands65
233투발루Tuvalu65
234세인트빈센트 그레나딘Saint Vincent and the Grenadines63
235몬테네그로Montenegro60
236레소토Lesotho51
237미국령 군소 제도United States Minor Outlying Islands3
238크리스마스 섬Christmas Island3
239코코스 제도Cocos (Keeling) Islands2