Overview

Dataset statistics

Number of variables16
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory131.7 B

Variable types

Text15
Categorical1

Dataset

Description샘플 데이터
Author세종대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=7b0092b0-31dd-11ea-b948-6903051715f4

Alerts

GDP 설명(억 $) has unique valuesUnique
국가 코드 has unique valuesUnique
국가 한글 명 has unique valuesUnique
국가 영문 명 has unique valuesUnique
면적(㎢ ) has unique valuesUnique
수도 설명 has unique valuesUnique
인구 설명(명) has unique valuesUnique
언어 설명 has unique valuesUnique
종교 설명 has unique valuesUnique
인당 GDP 설명($) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:19:34.389673
Analysis finished2023-12-10 10:19:36.712077
Duration2.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

GDP 설명(억 $)
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:36.893605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10.5
Mean length7.4444444
Min length4

Characters and Unicode

Total characters268
Distinct characters20
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row102억$
2nd row109억$
3rd row12,358억 $
4th row123,617억$
5th row149억$
ValueCountFrequency (%)
15
26.3%
102억 1
 
1.8%
4조 1
 
1.8%
482억 1
 
1.8%
32억 1
 
1.8%
3억 1
 
1.8%
3,600만 1
 
1.8%
3,381억 1
 
1.8%
3,906억 1
 
1.8%
4,594 1
 
1.8%
Other values (33) 33
57.9%
2023-12-10T19:19:37.453480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
$ 35
13.1%
억 34
12.7%
2 25
9.3%
25
9.3%
0 22
8.2%
, 20
 
7.5%
1 17
 
6.3%
8 15
 
5.6%
3 13
 
4.9%
6 12
 
4.5%
Other values (10) 50
18.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 141
52.6%
Other Letter 43
 
16.0%
Currency Symbol 35
 
13.1%
Space Separator 25
 
9.3%
Other Punctuation 22
 
8.2%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 25
17.7%
0 22
15.6%
1 17
12.1%
8 15
10.6%
3 13
9.2%
6 12
8.5%
4 12
8.5%
5 10
 
7.1%
9 10
 
7.1%
7 5
 
3.5%
Other Letter
ValueCountFrequency (%)
억 34
79.1%
만 4
 
9.3%
조 3
 
7.0%
백 2
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 20
90.9%
. 2
 
9.1%
Currency Symbol
ValueCountFrequency (%)
$ 35
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 225
84.0%
Hangul 43
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
$ 35
15.6%
2 25
11.1%
25
11.1%
0 22
9.8%
, 20
8.9%
1 17
7.6%
8 15
6.7%
3 13
 
5.8%
6 12
 
5.3%
4 12
 
5.3%
Other values (6) 29
12.9%
Hangul
ValueCountFrequency (%)
억 34
79.1%
만 4
 
9.3%
조 3
 
7.0%
백 2
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 225
84.0%
Hangul 43
 
16.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
$ 35
15.6%
2 25
11.1%
25
11.1%
0 22
9.8%
, 20
8.9%
1 17
7.6%
8 15
6.7%
3 13
 
5.8%
6 12
 
5.3%
4 12
 
5.3%
Other values (6) 29
12.9%
Hangul
ValueCountFrequency (%)
억 34
79.1%
만 4
 
9.3%
조 3
 
7.0%
백 2
 
4.7%

국가 코드
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:37.806852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters72
Distinct characters25
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

Unique36 ?
Unique (%)100.0%

Sample

1st rowMG
2nd rowMK
3rd rowRS
4th rowCH
5th rowLA
ValueCountFrequency (%)
mg 1
 
2.8%
mk 1
 
2.8%
tx 1
 
2.8%
gq 1
 
2.8%
fm 1
 
2.8%
my 1
 
2.8%
th 1
 
2.8%
ir 1
 
2.8%
jp 1
 
2.8%
kn 1
 
2.8%
Other values (26) 26
72.2%
2023-12-10T19:19:38.328261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 7
 
9.7%
K 7
 
9.7%
P 7
 
9.7%
T 5
 
6.9%
G 4
 
5.6%
I 4
 
5.6%
N 4
 
5.6%
B 4
 
5.6%
S 4
 
5.6%
H 3
 
4.2%
Other values (15) 23
31.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 72
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 7
 
9.7%
K 7
 
9.7%
P 7
 
9.7%
T 5
 
6.9%
G 4
 
5.6%
I 4
 
5.6%
N 4
 
5.6%
B 4
 
5.6%
S 4
 
5.6%
H 3
 
4.2%
Other values (15) 23
31.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 72
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 7
 
9.7%
K 7
 
9.7%
P 7
 
9.7%
T 5
 
6.9%
G 4
 
5.6%
I 4
 
5.6%
N 4
 
5.6%
B 4
 
5.6%
S 4
 
5.6%
H 3
 
4.2%
Other values (15) 23
31.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 7
 
9.7%
K 7
 
9.7%
P 7
 
9.7%
T 5
 
6.9%
G 4
 
5.6%
I 4
 
5.6%
N 4
 
5.6%
B 4
 
5.6%
S 4
 
5.6%
H 3
 
4.2%
Other values (15) 23
31.9%

국가 한글 명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:38.692458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length112
Median length34.5
Mean length30.555556
Min length4

Characters and Unicode

Total characters1100
Distinct characters150
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row몽골(Mongolia)
2nd row구유고슬라비아 마케도니아 공화국(Former Yugoslav Republic of Macedonia)
3rd row러시아(Russia)
4th row중화인민공화국(中華人民共和國, The People’s Republic of China: P.R.C.)
5th rowLao PDR)
ValueCountFrequency (%)
of 25
 
17.0%
republic 13
 
8.8%
the 7
 
4.8%
공화국(republic 4
 
2.7%
사회주의 2
 
1.4%
socialist 2
 
1.4%
공화국(the 2
 
1.4%
china 2
 
1.4%
islamic 2
 
1.4%
people’s 2
 
1.4%
Other values (86) 86
58.5%
2023-12-10T19:19:39.263278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
111
 
10.1%
a 62
 
5.6%
i 61
 
5.5%
e 58
 
5.3%
o 50
 
4.5%
n 42
 
3.8%
l 34
 
3.1%
) 30
 
2.7%
( 28
 
2.5%
c 27
 
2.5%
Other values (140) 597
54.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 583
53.0%
Other Letter 234
21.3%
Space Separator 111
 
10.1%
Uppercase Letter 101
 
9.2%
Close Punctuation 30
 
2.7%
Open Punctuation 28
 
2.5%
Other Punctuation 11
 
1.0%
Final Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 23
 
9.8%
화 19
 
8.1%
공 17
 
7.3%
스 9
 
3.8%
탄 8
 
3.4%
아 8
 
3.4%
민 6
 
2.6%
이 5
 
2.1%
시 5
 
2.1%
인 5
 
2.1%
Other values (86) 129
55.1%
Lowercase Letter
ValueCountFrequency (%)
a 62
 
10.6%
i 61
 
10.5%
e 58
 
9.9%
o 50
 
8.6%
n 42
 
7.2%
l 34
 
5.8%
c 27
 
4.6%
u 27
 
4.6%
f 26
 
4.5%
t 26
 
4.5%
Other values (14) 170
29.2%
Uppercase Letter
ValueCountFrequency (%)
R 22
21.8%
T 12
11.9%
P 11
10.9%
K 8
 
7.9%
S 7
 
6.9%
I 6
 
5.9%
M 5
 
5.0%
C 4
 
4.0%
A 4
 
4.0%
D 3
 
3.0%
Other values (11) 19
18.8%
Other Punctuation
ValueCountFrequency (%)
, 5
45.5%
. 3
27.3%
/ 1
 
9.1%
: 1
 
9.1%
' 1
 
9.1%
Space Separator
ValueCountFrequency (%)
111
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 684
62.2%
Hangul 223
 
20.3%
Common 182
 
16.5%
Han 11
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 23
 
10.3%
화 19
 
8.5%
공 17
 
7.6%
스 9
 
4.0%
탄 8
 
3.6%
아 8
 
3.6%
민 6
 
2.7%
이 5
 
2.2%
시 5
 
2.2%
인 5
 
2.2%
Other values (75) 118
52.9%
Latin
ValueCountFrequency (%)
a 62
 
9.1%
i 61
 
8.9%
e 58
 
8.5%
o 50
 
7.3%
n 42
 
6.1%
l 34
 
5.0%
c 27
 
3.9%
u 27
 
3.9%
f 26
 
3.8%
t 26
 
3.8%
Other values (35) 271
39.6%
Han
ValueCountFrequency (%)
本 1
9.1%
臺 1
9.1%
日 1
9.1%
灣 1
9.1%
國 1
9.1%
和 1
9.1%
共 1
9.1%
民 1
9.1%
人 1
9.1%
華 1
9.1%
Common
ValueCountFrequency (%)
111
61.0%
) 30
 
16.5%
( 28
 
15.4%
, 5
 
2.7%
. 3
 
1.6%
’ 2
 
1.1%
/ 1
 
0.5%
: 1
 
0.5%
' 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 864
78.5%
Hangul 223
 
20.3%
CJK 11
 
1.0%
Punctuation 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111
 
12.8%
a 62
 
7.2%
i 61
 
7.1%
e 58
 
6.7%
o 50
 
5.8%
n 42
 
4.9%
l 34
 
3.9%
) 30
 
3.5%
( 28
 
3.2%
c 27
 
3.1%
Other values (43) 361
41.8%
Hangul
ValueCountFrequency (%)
국 23
 
10.3%
화 19
 
8.5%
공 17
 
7.6%
스 9
 
4.0%
탄 8
 
3.6%
아 8
 
3.6%
민 6
 
2.7%
이 5
 
2.2%
시 5
 
2.2%
인 5
 
2.2%
Other values (75) 118
52.9%
Punctuation
ValueCountFrequency (%)
’ 2
100.0%
CJK
ValueCountFrequency (%)
本 1
9.1%
臺 1
9.1%
日 1
9.1%
灣 1
9.1%
國 1
9.1%
和 1
9.1%
共 1
9.1%
民 1
9.1%
人 1
9.1%
華 1
9.1%

국가 영문 명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:39.595604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length12
Mean length8.6666667
Min length4

Characters and Unicode

Total characters312
Distinct characters46
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

Unique36 ?
Unique (%)100.0%

Sample

1st rowMongolia
2nd rowMakedonia
3rd rowRussian
4th rowChina
5th rowLaos
ValueCountFrequency (%)
korea 2
 
4.3%
mongolia 1
 
2.2%
people's 1
 
2.2%
kong 1
 
2.2%
turkmenistan 1
 
2.2%
guam 1
 
2.2%
micronesia 1
 
2.2%
malaysia 1
 
2.2%
thailand 1
 
2.2%
iran 1
 
2.2%
Other values (35) 35
76.1%
2023-12-10T19:19:40.227815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 52
16.7%
n 32
 
10.3%
i 26
 
8.3%
e 19
 
6.1%
s 16
 
5.1%
o 14
 
4.5%
10
 
3.2%
l 9
 
2.9%
r 9
 
2.9%
p 9
 
2.9%
Other values (36) 116
37.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 253
81.1%
Uppercase Letter 44
 
14.1%
Space Separator 10
 
3.2%
Other Punctuation 5
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 52
20.6%
n 32
12.6%
i 26
10.3%
e 19
 
7.5%
s 16
 
6.3%
o 14
 
5.5%
l 9
 
3.6%
r 9
 
3.6%
p 9
 
3.6%
t 9
 
3.6%
Other values (13) 58
22.9%
Uppercase Letter
ValueCountFrequency (%)
M 5
11.4%
K 5
11.4%
P 5
11.4%
T 4
 
9.1%
R 3
 
6.8%
I 3
 
6.8%
B 2
 
4.5%
S 2
 
4.5%
G 2
 
4.5%
N 2
 
4.5%
Other values (9) 11
25.0%
Other Punctuation
ValueCountFrequency (%)
. 2
40.0%
, 2
40.0%
' 1
20.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 297
95.2%
Common 15
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 52
17.5%
n 32
 
10.8%
i 26
 
8.8%
e 19
 
6.4%
s 16
 
5.4%
o 14
 
4.7%
l 9
 
3.0%
r 9
 
3.0%
p 9
 
3.0%
t 9
 
3.0%
Other values (32) 102
34.3%
Common
ValueCountFrequency (%)
10
66.7%
. 2
 
13.3%
, 2
 
13.3%
' 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 52
16.7%
n 32
 
10.3%
i 26
 
8.3%
e 19
 
6.1%
s 16
 
5.1%
o 14
 
4.5%
10
 
3.2%
l 9
 
2.9%
r 9
 
2.9%
p 9
 
2.9%
Other values (36) 116
37.2%

면적(㎢ )
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:40.620491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length26
Mean length15.138889
Min length4

Characters and Unicode

Total characters545
Distinct characters56
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row156만 4,116㎢
2nd row25,713㎦(한반도의 약 1/8)
3rd row1,712만 5,407㎢
4th row약 960만㎢(면적: 세계 제4위, 한반도의 약 44배)
5th row236,800㎢(한반도의 약 1.1배), 국토의 70%가 산악지대
ValueCountFrequency (%)
약 7
 
7.9%
cia 2
 
2.2%
면적의 2
 
2.2%
세계 2
 
2.2%
한반도의 2
 
2.2%
33배 1
 
1.1%
179km² 1
 
1.1%
328,550㎢ 1
 
1.1%
705㎢ 1
 
1.1%
544㎢ 1
 
1.1%
Other values (69) 69
77.5%
2023-12-10T19:19:41.244828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64
 
11.7%
, 37
 
6.8%
1 36
 
6.6%
0 35
 
6.4%
㎢ 33
 
6.1%
2 27
 
5.0%
3 25
 
4.6%
5 24
 
4.4%
7 21
 
3.9%
9 20
 
3.7%
Other values (46) 223
40.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240
44.0%
Other Letter 118
21.7%
Space Separator 64
 
11.7%
Other Punctuation 49
 
9.0%
Other Symbol 34
 
6.2%
Open Punctuation 14
 
2.6%
Close Punctuation 13
 
2.4%
Lowercase Letter 6
 
1.1%
Uppercase Letter 6
 
1.1%
Other Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 14
11.9%
한 12
 
10.2%
반 10
 
8.5%
도 10
 
8.5%
만 10
 
8.5%
배 10
 
8.5%
약 7
 
5.9%
세 5
 
4.2%
위 5
 
4.2%
계 5
 
4.2%
Other values (19) 30
25.4%
Decimal Number
ValueCountFrequency (%)
1 36
15.0%
0 35
14.6%
2 27
11.2%
3 25
10.4%
5 24
10.0%
7 21
8.8%
9 20
8.3%
4 20
8.3%
6 18
7.5%
8 14
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 37
75.5%
. 7
 
14.3%
/ 2
 
4.1%
? 1
 
2.0%
% 1
 
2.0%
: 1
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
33.3%
I 2
33.3%
C 2
33.3%
Other Symbol
ValueCountFrequency (%)
㎢ 33
97.1%
㎦ 1
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
k 3
50.0%
m 3
50.0%
Space Separator
ValueCountFrequency (%)
64
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 415
76.1%
Hangul 118
 
21.7%
Latin 12
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 14
11.9%
한 12
 
10.2%
반 10
 
8.5%
도 10
 
8.5%
만 10
 
8.5%
배 10
 
8.5%
약 7
 
5.9%
세 5
 
4.2%
위 5
 
4.2%
계 5
 
4.2%
Other values (19) 30
25.4%
Common
ValueCountFrequency (%)
64
15.4%
, 37
 
8.9%
1 36
 
8.7%
0 35
 
8.4%
㎢ 33
 
8.0%
2 27
 
6.5%
3 25
 
6.0%
5 24
 
5.8%
7 21
 
5.1%
9 20
 
4.8%
Other values (12) 93
22.4%
Latin
ValueCountFrequency (%)
k 3
25.0%
m 3
25.0%
A 2
16.7%
I 2
16.7%
C 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 392
71.9%
Hangul 118
 
21.7%
CJK Compat 34
 
6.2%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64
16.3%
, 37
9.4%
1 36
9.2%
0 35
8.9%
2 27
 
6.9%
3 25
 
6.4%
5 24
 
6.1%
7 21
 
5.4%
9 20
 
5.1%
4 20
 
5.1%
Other values (14) 83
21.2%
CJK Compat
ValueCountFrequency (%)
㎢ 33
97.1%
㎦ 1
 
2.9%
Hangul
ValueCountFrequency (%)
의 14
11.9%
한 12
 
10.2%
반 10
 
8.5%
도 10
 
8.5%
만 10
 
8.5%
배 10
 
8.5%
약 7
 
5.9%
세 5
 
4.2%
위 5
 
4.2%
계 5
 
4.2%
Other values (19) 30
25.4%
None
ValueCountFrequency (%)
² 1
100.0%

수도 설명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:41.650025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length18
Mean length12.833333
Min length2

Characters and Unicode

Total characters462
Distinct characters131
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row울란바토르(Ulaanbaatar)
2nd row스코피예(Skopje)
3rd row모스크바
4th row베이징
5th row비엔티안(Vientiane)
ValueCountFrequency (%)
울란바토르(ulaanbaatar 1
 
1.9%
자카르타 1
 
1.9%
없음 1
 
1.9%
아쉬하바드 1
 
1.9%
ashgabat 1
 
1.9%
하갓냐(hagatna 1
 
1.9%
팔리키르(palikir 1
 
1.9%
쿠알라룸푸르(kuala 1
 
1.9%
lumpur 1
 
1.9%
방콕(bangkok 1
 
1.9%
Other values (44) 44
81.5%
2023-12-10T19:19:42.305657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 39
 
8.4%
( 28
 
6.1%
) 28
 
6.1%
18
 
3.9%
e 18
 
3.9%
n 15
 
3.2%
i 13
 
2.8%
t 12
 
2.6%
h 11
 
2.4%
k 10
 
2.2%
Other values (121) 270
58.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 196
42.4%
Other Letter 147
31.8%
Uppercase Letter 43
 
9.3%
Open Punctuation 28
 
6.1%
Close Punctuation 28
 
6.1%
Space Separator 18
 
3.9%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
르 6
 
4.1%
이 5
 
3.4%
트 5
 
3.4%
도 5
 
3.4%
바 4
 
2.7%
스 4
 
2.7%
가 4
 
2.7%
타 4
 
2.7%
카 4
 
2.7%
하 3
 
2.0%
Other values (78) 103
70.1%
Lowercase Letter
ValueCountFrequency (%)
a 39
19.9%
e 18
 
9.2%
n 15
 
7.7%
i 13
 
6.6%
t 12
 
6.1%
h 11
 
5.6%
k 10
 
5.1%
u 9
 
4.6%
r 9
 
4.6%
o 9
 
4.6%
Other values (11) 51
26.0%
Uppercase Letter
ValueCountFrequency (%)
P 6
14.0%
T 5
11.6%
M 5
11.6%
K 5
11.6%
N 3
 
7.0%
D 3
 
7.0%
B 2
 
4.7%
H 2
 
4.7%
A 2
 
4.7%
S 2
 
4.7%
Other values (7) 8
18.6%
Other Punctuation
ValueCountFrequency (%)
/ 1
50.0%
? 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 239
51.7%
Hangul 145
31.4%
Common 76
 
16.5%
Han 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
르 6
 
4.1%
이 5
 
3.4%
트 5
 
3.4%
도 5
 
3.4%
바 4
 
2.8%
스 4
 
2.8%
가 4
 
2.8%
타 4
 
2.8%
카 4
 
2.8%
하 3
 
2.1%
Other values (76) 101
69.7%
Latin
ValueCountFrequency (%)
a 39
16.3%
e 18
 
7.5%
n 15
 
6.3%
i 13
 
5.4%
t 12
 
5.0%
h 11
 
4.6%
k 10
 
4.2%
u 9
 
3.8%
r 9
 
3.8%
o 9
 
3.8%
Other values (28) 94
39.3%
Common
ValueCountFrequency (%)
( 28
36.8%
) 28
36.8%
18
23.7%
/ 1
 
1.3%
? 1
 
1.3%
Han
ValueCountFrequency (%)
東 1
50.0%
京 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 315
68.2%
Hangul 145
31.4%
CJK 2
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 39
 
12.4%
( 28
 
8.9%
) 28
 
8.9%
18
 
5.7%
e 18
 
5.7%
n 15
 
4.8%
i 13
 
4.1%
t 12
 
3.8%
h 11
 
3.5%
k 10
 
3.2%
Other values (33) 123
39.0%
Hangul
ValueCountFrequency (%)
르 6
 
4.1%
이 5
 
3.4%
트 5
 
3.4%
도 5
 
3.4%
바 4
 
2.8%
스 4
 
2.8%
가 4
 
2.8%
타 4
 
2.8%
카 4
 
2.8%
하 3
 
2.1%
Other values (76) 101
69.7%
CJK
ValueCountFrequency (%)
東 1
50.0%
京 1
50.0%

인구 설명(명)
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:42.673132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length21
Mean length12.222222
Min length2

Characters and Unicode

Total characters440
Distinct characters47
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

Unique36 ?
Unique (%)100.0%

Sample

1st row312만 902명
2nd row209만명
3rd row1억 4,650만 명
4th row13억 7,462만 명
5th row649만 2,400명
ValueCountFrequency (%)
명 11
 
14.1%
1억 5
 
6.4%
약 4
 
5.1%
2016 2
 
2.6%
13억 2
 
2.6%
312만 1
 
1.3%
2,515만 1
 
1.3%
2,687만 1
 
1.3%
81,800,000명 1
 
1.3%
6,898만 1
 
1.3%
Other values (49) 49
62.8%
2023-12-10T19:19:43.276392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 48
 
10.9%
, 45
 
10.2%
44
 
10.0%
명 33
 
7.5%
1 30
 
6.8%
2 27
 
6.1%
5 24
 
5.5%
3 23
 
5.2%
만 22
 
5.0%
9 20
 
4.5%
Other values (37) 124
28.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 234
53.2%
Other Letter 82
 
18.6%
Other Punctuation 49
 
11.1%
Space Separator 44
 
10.0%
Uppercase Letter 10
 
2.3%
Lowercase Letter 8
 
1.8%
Open Punctuation 6
 
1.4%
Close Punctuation 6
 
1.4%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
명 33
40.2%
만 22
26.8%
억 8
 
9.8%
약 4
 
4.9%
년 2
 
2.4%
세 2
 
2.4%
계 2
 
2.4%
위 2
 
2.4%
준 1
 
1.2%
기 1
 
1.2%
Other values (5) 5
 
6.1%
Decimal Number
ValueCountFrequency (%)
0 48
20.5%
1 30
12.8%
2 27
11.5%
5 24
10.3%
3 23
9.8%
9 20
8.5%
7 20
8.5%
6 19
 
8.1%
8 14
 
6.0%
4 9
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
I 2
20.0%
O 1
10.0%
E 1
10.0%
C 1
10.0%
A 1
10.0%
W 1
10.0%
F 1
10.0%
M 1
10.0%
N 1
10.0%
Lowercase Letter
ValueCountFrequency (%)
l 2
25.0%
i 2
25.0%
n 1
12.5%
m 1
12.5%
o 1
12.5%
s 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 45
91.8%
. 3
 
6.1%
\ 1
 
2.0%
Space Separator
ValueCountFrequency (%)
44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 340
77.3%
Hangul 82
 
18.6%
Latin 18
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 48
14.1%
, 45
13.2%
44
12.9%
1 30
8.8%
2 27
7.9%
5 24
7.1%
3 23
6.8%
9 20
5.9%
7 20
5.9%
6 19
 
5.6%
Other values (7) 40
11.8%
Hangul
ValueCountFrequency (%)
명 33
40.2%
만 22
26.8%
억 8
 
9.8%
약 4
 
4.9%
년 2
 
2.4%
세 2
 
2.4%
계 2
 
2.4%
위 2
 
2.4%
준 1
 
1.2%
기 1
 
1.2%
Other values (5) 5
 
6.1%
Latin
ValueCountFrequency (%)
I 2
 
11.1%
l 2
 
11.1%
i 2
 
11.1%
O 1
 
5.6%
E 1
 
5.6%
C 1
 
5.6%
n 1
 
5.6%
A 1
 
5.6%
m 1
 
5.6%
o 1
 
5.6%
Other values (5) 5
27.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 358
81.4%
Hangul 82
 
18.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 48
13.4%
, 45
12.6%
44
12.3%
1 30
8.4%
2 27
7.5%
5 24
6.7%
3 23
 
6.4%
9 20
 
5.6%
7 20
 
5.6%
6 19
 
5.3%
Other values (22) 58
16.2%
Hangul
ValueCountFrequency (%)
명 33
40.2%
만 22
26.8%
억 8
 
9.8%
약 4
 
4.9%
년 2
 
2.4%
세 2
 
2.4%
계 2
 
2.4%
위 2
 
2.4%
준 1
 
1.2%
기 1
 
1.2%
Other values (5) 5
 
6.1%

언어 설명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:43.763054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length103
Median length27.5
Mean length21.944444
Min length3

Characters and Unicode

Total characters790
Distinct characters181
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row할흐 몽골어 90%, 키릴문자, 문맹률 5% 이하
2nd row마케도니아어, 알바니아어
3rd row러시아어, 문맹률 0.3%
4th row한어(漢語; Chinese)[표준어: 보통화(普通話; Mandarin)]
5th row라오어(태국어와 유사)
ValueCountFrequency (%)
영어 8
 
5.2%
사용 4
 
2.6%
중국어 3
 
1.9%
3
 
1.9%
공용어 3
 
1.9%
일부 3
 
1.9%
타밀어 2
 
1.3%
말레이어 2
 
1.3%
러시아어(공용어 2
 
1.3%
광범위하게 2
 
1.3%
Other values (114) 122
79.2%
2023-12-10T19:19:44.433541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
 
15.2%
어 103
 
13.0%
, 37
 
4.7%
용 25
 
3.2%
) 24
 
3.0%
( 24
 
3.0%
영 17
 
2.2%
국 14
 
1.8%
공 14
 
1.8%
이 11
 
1.4%
Other values (171) 401
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 511
64.7%
Space Separator 120
 
15.2%
Other Punctuation 51
 
6.5%
Lowercase Letter 40
 
5.1%
Close Punctuation 25
 
3.2%
Open Punctuation 25
 
3.2%
Decimal Number 11
 
1.4%
Uppercase Letter 7
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 103
 
20.2%
용 25
 
4.9%
영 17
 
3.3%
국 14
 
2.7%
공 14
 
2.7%
이 11
 
2.2%
아 11
 
2.2%
지 8
 
1.6%
사 8
 
1.6%
통 7
 
1.4%
Other values (136) 293
57.3%
Lowercase Letter
ValueCountFrequency (%)
a 8
20.0%
n 7
17.5%
r 4
10.0%
d 4
10.0%
e 4
10.0%
i 4
10.0%
s 3
 
7.5%
h 3
 
7.5%
o 1
 
2.5%
m 1
 
2.5%
Decimal Number
ValueCountFrequency (%)
5 2
18.2%
0 2
18.2%
9 2
18.2%
8 1
9.1%
4 1
9.1%
3 1
9.1%
1 1
9.1%
2 1
9.1%
Uppercase Letter
ValueCountFrequency (%)
M 2
28.6%
B 1
14.3%
I 1
14.3%
K 1
14.3%
C 1
14.3%
U 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 37
72.5%
: 7
 
13.7%
% 4
 
7.8%
; 2
 
3.9%
. 1
 
2.0%
Close Punctuation
ValueCountFrequency (%)
) 24
96.0%
] 1
 
4.0%
Open Punctuation
ValueCountFrequency (%)
( 24
96.0%
[ 1
 
4.0%
Space Separator
ValueCountFrequency (%)
120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 506
64.1%
Common 232
29.4%
Latin 47
 
5.9%
Han 5
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 103
 
20.4%
용 25
 
4.9%
영 17
 
3.4%
국 14
 
2.8%
공 14
 
2.8%
이 11
 
2.2%
아 11
 
2.2%
지 8
 
1.6%
사 8
 
1.6%
통 7
 
1.4%
Other values (131) 288
56.9%
Common
ValueCountFrequency (%)
120
51.7%
, 37
 
15.9%
) 24
 
10.3%
( 24
 
10.3%
: 7
 
3.0%
% 4
 
1.7%
; 2
 
0.9%
5 2
 
0.9%
0 2
 
0.9%
9 2
 
0.9%
Other values (8) 8
 
3.4%
Latin
ValueCountFrequency (%)
a 8
17.0%
n 7
14.9%
r 4
8.5%
d 4
8.5%
e 4
8.5%
i 4
8.5%
s 3
 
6.4%
h 3
 
6.4%
M 2
 
4.3%
B 1
 
2.1%
Other values (7) 7
14.9%
Han
ValueCountFrequency (%)
普 1
20.0%
通 1
20.0%
話 1
20.0%
語 1
20.0%
漢 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 506
64.1%
ASCII 279
35.3%
CJK 5
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
43.0%
, 37
 
13.3%
) 24
 
8.6%
( 24
 
8.6%
a 8
 
2.9%
n 7
 
2.5%
: 7
 
2.5%
r 4
 
1.4%
d 4
 
1.4%
e 4
 
1.4%
Other values (25) 40
 
14.3%
Hangul
ValueCountFrequency (%)
어 103
 
20.4%
용 25
 
4.9%
영 17
 
3.4%
국 14
 
2.8%
공 14
 
2.8%
이 11
 
2.2%
아 11
 
2.2%
지 8
 
1.6%
사 8
 
1.6%
통 7
 
1.4%
Other values (131) 288
56.9%
CJK
ValueCountFrequency (%)
普 1
20.0%
通 1
20.0%
話 1
20.0%
語 1
20.0%
漢 1
20.0%

종교 설명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:44.952824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length48.5
Mean length39.444444
Min length5

Characters and Unicode

Total characters1420
Distinct characters117
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row라마불교(90%), 무슬림(5%), 무속 및 기독교(5%)
2nd row마케도니아 정교(64.8%), 회교(33.3%), 기타(1.9%)
3rd row러시아 정교(이외 이슬람, 가톨릭, 기독교, 유대교 등)
4th row5대 종교: 불교(B.C.2), 도교(2c경), 천주교, 이슬람교(7c경), 기독교(19c경) 등
5th row불교(90%), 정령신앙, 기독교(포교 불허)
ValueCountFrequency (%)
기타 10
 
4.6%
이슬람교 9
 
4.2%
등 8
 
3.7%
기독교 8
 
3.7%
힌두교 4
 
1.9%
및 4
 
1.9%
불교 4
 
1.9%
종교 4
 
1.9%
수니파 3
 
1.4%
러시아 3
 
1.4%
Other values (150) 159
73.6%
2023-12-10T19:19:45.795840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
182
 
12.8%
교 119
 
8.4%
% 110
 
7.7%
, 95
 
6.7%
) 92
 
6.5%
( 91
 
6.4%
. 70
 
4.9%
기 39
 
2.7%
0 36
 
2.5%
1 34
 
2.4%
Other values (107) 552
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 520
36.6%
Other Punctuation 277
19.5%
Decimal Number 242
17.0%
Space Separator 182
 
12.8%
Close Punctuation 92
 
6.5%
Open Punctuation 91
 
6.4%
Lowercase Letter 12
 
0.8%
Uppercase Letter 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 119
22.9%
기 39
 
7.5%
이 22
 
4.2%
독 22
 
4.2%
불 21
 
4.0%
슬 20
 
3.8%
람 18
 
3.5%
타 17
 
3.3%
두 11
 
2.1%
힌 11
 
2.1%
Other values (76) 220
42.3%
Decimal Number
ValueCountFrequency (%)
0 36
14.9%
1 34
14.0%
3 29
12.0%
9 27
11.2%
8 27
11.2%
5 25
10.3%
2 19
7.9%
4 18
7.4%
6 18
7.4%
7 9
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
c 3
25.0%
a 2
16.7%
s 1
 
8.3%
l 1
 
8.3%
r 1
 
8.3%
u 1
 
8.3%
p 1
 
8.3%
k 1
 
8.3%
m 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
% 110
39.7%
, 95
34.3%
. 70
25.3%
? 1
 
0.4%
: 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
I 1
25.0%
D 1
25.0%
C 1
25.0%
B 1
25.0%
Space Separator
ValueCountFrequency (%)
182
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 91
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 884
62.3%
Hangul 520
36.6%
Latin 16
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 119
22.9%
기 39
 
7.5%
이 22
 
4.2%
독 22
 
4.2%
불 21
 
4.0%
슬 20
 
3.8%
람 18
 
3.5%
타 17
 
3.3%
두 11
 
2.1%
힌 11
 
2.1%
Other values (76) 220
42.3%
Common
ValueCountFrequency (%)
182
20.6%
% 110
12.4%
, 95
10.7%
) 92
10.4%
( 91
10.3%
. 70
 
7.9%
0 36
 
4.1%
1 34
 
3.8%
3 29
 
3.3%
9 27
 
3.1%
Other values (8) 118
13.3%
Latin
ValueCountFrequency (%)
c 3
18.8%
a 2
12.5%
I 1
 
6.2%
s 1
 
6.2%
l 1
 
6.2%
D 1
 
6.2%
r 1
 
6.2%
u 1
 
6.2%
p 1
 
6.2%
k 1
 
6.2%
Other values (3) 3
18.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 900
63.4%
Hangul 520
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
182
20.2%
% 110
12.2%
, 95
10.6%
) 92
10.2%
( 91
10.1%
. 70
 
7.8%
0 36
 
4.0%
1 34
 
3.8%
3 29
 
3.2%
9 27
 
3.0%
Other values (21) 134
14.9%
Hangul
ValueCountFrequency (%)
교 119
22.9%
기 39
 
7.5%
이 22
 
4.2%
독 22
 
4.2%
불 21
 
4.0%
슬 20
 
3.8%
람 18
 
3.5%
타 17
 
3.3%
두 11
 
2.1%
힌 11
 
2.1%
Other values (76) 220
42.3%

기후 설명
Text

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:46.255835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length141
Median length42.5
Mean length26.888889
Min length5

Characters and Unicode

Total characters968
Distinct characters152
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)94.4%

Sample

1st row건성냉대기후
2nd row온난한 대륙성 기후
3rd row광범위한 기후대(겨울 길고 여름 짧은 대륙성기후) 1월 평균 -16~-9℃, 7월 평균 13~23℃
4th row광대한 영토(남북 거리 약 5,500㎞, 동서 거리 약 5,200㎞)로 인해 지역별로 다양한 기후대가 분포. 주로 최남단지역의 열대기후, 서부지역의 건조기후, 동북지역의 한대 기후 등으로 구분. 전체적으로 사계절이 뚜렷한 계절풍기후의 특징을 보이고 있음
5th row연중 고온 다습한 열대몬순기후
ValueCountFrequency (%)
기후 19
 
8.7%
고온 8
 
3.7%
대륙성 7
 
3.2%
열대 6
 
2.7%
아열대 5
 
2.3%
4
 
1.8%
몬순기후 4
 
1.8%
구분 4
 
1.8%
몬순 4
 
1.8%
기후로 3
 
1.4%
Other values (137) 155
70.8%
2023-12-10T19:19:47.006653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
191
 
19.7%
기 55
 
5.7%
후 46
 
4.8%
대 44
 
4.5%
, 29
 
3.0%
열 25
 
2.6%
성 22
 
2.3%
온 20
 
2.1%
고 17
 
1.8%
1 17
 
1.8%
Other values (142) 502
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 599
61.9%
Space Separator 191
 
19.7%
Decimal Number 70
 
7.2%
Other Punctuation 36
 
3.7%
Open Punctuation 15
 
1.5%
Close Punctuation 15
 
1.5%
Other Symbol 11
 
1.1%
Math Symbol 10
 
1.0%
Lowercase Letter 10
 
1.0%
Dash Punctuation 5
 
0.5%
Other values (4) 6
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 55
 
9.2%
후 46
 
7.7%
대 44
 
7.3%
열 25
 
4.2%
성 22
 
3.7%
온 20
 
3.3%
고 17
 
2.8%
로 16
 
2.7%
월 14
 
2.3%
순 13
 
2.2%
Other values (107) 327
54.6%
Decimal Number
ValueCountFrequency (%)
1 17
24.3%
0 12
17.1%
3 9
12.9%
5 9
12.9%
6 7
10.0%
2 6
 
8.6%
4 4
 
5.7%
8 3
 
4.3%
7 2
 
2.9%
9 1
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
a 3
30.0%
r 2
20.0%
m 1
 
10.0%
u 1
 
10.0%
g 1
 
10.0%
o 1
 
10.0%
t 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 29
80.6%
. 3
 
8.3%
\ 2
 
5.6%
? 1
 
2.8%
% 1
 
2.8%
Other Symbol
ValueCountFrequency (%)
℃ 8
72.7%
㎞ 3
 
27.3%
Dash Punctuation
ValueCountFrequency (%)
- 4
80.0%
－ 1
 
20.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
191
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 599
61.9%
Common 357
36.9%
Latin 12
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 55
 
9.2%
후 46
 
7.7%
대 44
 
7.3%
열 25
 
4.2%
성 22
 
3.7%
온 20
 
3.3%
고 17
 
2.8%
로 16
 
2.7%
월 14
 
2.3%
순 13
 
2.2%
Other values (107) 327
54.6%
Common
ValueCountFrequency (%)
191
53.5%
, 29
 
8.1%
1 17
 
4.8%
( 15
 
4.2%
) 15
 
4.2%
0 12
 
3.4%
~ 10
 
2.8%
3 9
 
2.5%
5 9
 
2.5%
℃ 8
 
2.2%
Other values (16) 42
 
11.8%
Latin
ValueCountFrequency (%)
a 3
25.0%
r 2
16.7%
m 1
 
8.3%
u 1
 
8.3%
g 1
 
8.3%
G 1
 
8.3%
K 1
 
8.3%
o 1
 
8.3%
t 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 599
61.9%
ASCII 355
36.7%
Letterlike Symbols 8
 
0.8%
CJK Compat 3
 
0.3%
Punctuation 2
 
0.2%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
191
53.8%
, 29
 
8.2%
1 17
 
4.8%
( 15
 
4.2%
) 15
 
4.2%
0 12
 
3.4%
~ 10
 
2.8%
3 9
 
2.5%
5 9
 
2.5%
6 7
 
2.0%
Other values (20) 41
 
11.5%
Hangul
ValueCountFrequency (%)
기 55
 
9.2%
후 46
 
7.7%
대 44
 
7.3%
열 25
 
4.2%
성 22
 
3.7%
온 20
 
3.3%
고 17
 
2.8%
로 16
 
2.7%
월 14
 
2.3%
순 13
 
2.2%
Other values (107) 327
54.6%
Letterlike Symbols
ValueCountFrequency (%)
℃ 8
100.0%
CJK Compat
ValueCountFrequency (%)
㎞ 3
100.0%
Punctuation
ValueCountFrequency (%)
” 1
50.0%
“ 1
50.0%
None
ValueCountFrequency (%)
－ 1
100.0%

정부 설명
Text

Distinct25
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:47.434495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length23
Mean length11.5
Min length3

Characters and Unicode

Total characters414
Distinct characters84
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)52.8%

Sample

1st row민주공화제
2nd row공화제
3rd row연방제, 대통령제(6년 중임제)
4th row인민민주독재의 사회주의 국가
5th row사회주의공화국 (공산주의체제)
ValueCountFrequency (%)
공화제 5
 
5.7%
내각책임제 4
 
4.6%
대통령 4
 
4.6%
중심제 4
 
4.6%
공화국 4
 
4.6%
대통령제 4
 
4.6%
사회주의 3
 
3.4%
입헌군주제 3
 
3.4%
국가 3
 
3.4%
2
 
2.3%
Other values (48) 51
58.6%
2023-12-10T19:19:48.078050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51
 
12.3%
제 35
 
8.5%
공 18
 
4.3%
주 17
 
4.1%
화 17
 
4.1%
국 16
 
3.9%
( 10
 
2.4%
, 10
 
2.4%
대 10
 
2.4%
통 10
 
2.4%
Other values (74) 220
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 292
70.5%
Space Separator 51
 
12.3%
Decimal Number 26
 
6.3%
Open Punctuation 10
 
2.4%
Other Punctuation 10
 
2.4%
Close Punctuation 10
 
2.4%
Math Symbol 6
 
1.4%
Lowercase Letter 5
 
1.2%
Other Symbol 3
 
0.7%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 35
 
12.0%
공 18
 
6.2%
주 17
 
5.8%
화 17
 
5.8%
국 16
 
5.5%
대 10
 
3.4%
통 10
 
3.4%
령 10
 
3.4%
의 9
 
3.1%
중 8
 
2.7%
Other values (54) 142
48.6%
Decimal Number
ValueCountFrequency (%)
1 6
23.1%
2 6
23.1%
3 4
15.4%
6 3
11.5%
5 3
11.5%
8 2
 
7.7%
0 1
 
3.8%
4 1
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
u 1
20.0%
l 1
20.0%
t 1
20.0%
a 1
20.0%
n 1
20.0%
Space Separator
ValueCountFrequency (%)
51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 292
70.5%
Common 116
 
28.0%
Latin 6
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 35
 
12.0%
공 18
 
6.2%
주 17
 
5.8%
화 17
 
5.8%
국 16
 
5.5%
대 10
 
3.4%
통 10
 
3.4%
령 10
 
3.4%
의 9
 
3.1%
중 8
 
2.7%
Other values (54) 142
48.6%
Common
ValueCountFrequency (%)
51
44.0%
( 10
 
8.6%
, 10
 
8.6%
) 10
 
8.6%
1 6
 
5.2%
~ 6
 
5.2%
2 6
 
5.2%
3 4
 
3.4%
6 3
 
2.6%
5 3
 
2.6%
Other values (4) 7
 
6.0%
Latin
ValueCountFrequency (%)
S 1
16.7%
u 1
16.7%
l 1
16.7%
t 1
16.7%
a 1
16.7%
n 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 292
70.5%
ASCII 119
28.7%
Letterlike Symbols 3
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51
42.9%
( 10
 
8.4%
, 10
 
8.4%
) 10
 
8.4%
1 6
 
5.0%
~ 6
 
5.0%
2 6
 
5.0%
3 4
 
3.4%
6 3
 
2.5%
5 3
 
2.5%
Other values (9) 10
 
8.4%
Hangul
ValueCountFrequency (%)
제 35
 
12.0%
공 18
 
6.2%
주 17
 
5.8%
화 17
 
5.8%
국 16
 
5.5%
대 10
 
3.4%
통 10
 
3.4%
령 10
 
3.4%
의 9
 
3.1%
중 8
 
2.7%
Other values (54) 142
48.6%
Letterlike Symbols
ValueCountFrequency (%)
℃ 3
100.0%

의회 설명
Text

Distinct24
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:48.419965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length34
Mean length8.5277778
Min length2

Characters and Unicode

Total characters307
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

Unique22 ?
Unique (%)61.1%

Sample

1st row국가대의회
2nd row단원제
3rd row의회민주제
4th row공산당 일당독재
5th row임기 5년의 단임제 국회(라오 인민혁명당 1당 독재)
ValueCountFrequency (%)
단원제 11
 
15.5%
양원제 5
 
7.0%
임기 2
 
2.8%
하원 2
 
2.8%
5년의 2
 
2.8%
일원제 2
 
2.8%
n 1
 
1.4%
대통령제 1
 
1.4%
국가대의회 1
 
1.4%
입헌군주제,양원제 1
 
1.4%
Other values (43) 43
60.6%
2023-12-10T19:19:49.012299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
11.4%
제 33
 
10.7%
원 26
 
8.5%
단 12
 
3.9%
양 9
 
2.9%
의 9
 
2.9%
, 8
 
2.6%
당 7
 
2.3%
국 6
 
2.0%
) 5
 
1.6%
Other values (73) 157
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 232
75.6%
Space Separator 35
 
11.4%
Decimal Number 16
 
5.2%
Other Punctuation 10
 
3.3%
Close Punctuation 5
 
1.6%
Open Punctuation 5
 
1.6%
Dash Punctuation 3
 
1.0%
Uppercase Letter 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 33
 
14.2%
원 26
 
11.2%
단 12
 
5.2%
양 9
 
3.9%
의 9
 
3.9%
당 7
 
3.0%
국 6
 
2.6%
상 5
 
2.2%
하 5
 
2.2%
일 5
 
2.2%
Other values (58) 115
49.6%
Decimal Number
ValueCountFrequency (%)
1 4
25.0%
0 3
18.8%
2 3
18.8%
5 2
12.5%
6 2
12.5%
3 1
 
6.2%
8 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 8
80.0%
\ 1
 
10.0%
· 1
 
10.0%
Space Separator
ValueCountFrequency (%)
35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 232
75.6%
Common 74
 
24.1%
Latin 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 33
 
14.2%
원 26
 
11.2%
단 12
 
5.2%
양 9
 
3.9%
의 9
 
3.9%
당 7
 
3.0%
국 6
 
2.6%
상 5
 
2.2%
하 5
 
2.2%
일 5
 
2.2%
Other values (58) 115
49.6%
Common
ValueCountFrequency (%)
35
47.3%
, 8
 
10.8%
) 5
 
6.8%
( 5
 
6.8%
1 4
 
5.4%
0 3
 
4.1%
- 3
 
4.1%
2 3
 
4.1%
5 2
 
2.7%
6 2
 
2.7%
Other values (4) 4
 
5.4%
Latin
ValueCountFrequency (%)
N 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 232
75.6%
ASCII 74
 
24.1%
None 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
47.3%
, 8
 
10.8%
) 5
 
6.8%
( 5
 
6.8%
1 4
 
5.4%
0 3
 
4.1%
- 3
 
4.1%
2 3
 
4.1%
5 2
 
2.7%
6 2
 
2.7%
Other values (4) 4
 
5.4%
Hangul
ValueCountFrequency (%)
제 33
 
14.2%
원 26
 
11.2%
단 12
 
5.2%
양 9
 
3.9%
의 9
 
3.9%
당 7
 
3.0%
국 6
 
2.6%
상 5
 
2.2%
하 5
 
2.2%
일 5
 
2.2%
Other values (58) 115
49.6%
None
ValueCountFrequency (%)
· 1
100.0%

시차 설명
Text

Distinct28
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:49.680316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.8333333
Min length5

Characters and Unicode

Total characters318
Distinct characters34
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

Unique24 ?
Unique (%)66.7%

Sample

1st rowGMT+9시간
2nd rowGMT+17시간
3rd rowGMT +4시간(모스크바)
4th rowGMT+8시간
5th rowGMT+8시간
ValueCountFrequency (%)
gmt 11
21.6%
gmt+8시간 5
 
9.8%
5시간 3
 
5.9%
gmt+10시간 2
 
3.9%
8시간 2
 
3.9%
7시간 2
 
3.9%
2
 
3.9%
gmt+10시간00분 1
 
2.0%
없음 1
 
2.0%
gmt+8시간30분 1
 
2.0%
Other values (21) 21
41.2%
2023-12-10T19:19:50.473422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 35
11.0%
G 34
10.7%
시 34
10.7%
M 34
10.7%
+ 34
10.7%
간 33
10.4%
0 21
 
6.6%
15
 
4.7%
1 15
 
4.7%
8 9
 
2.8%
Other values (24) 54
17.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 103
32.4%
Other Letter 85
26.7%
Decimal Number 69
21.7%
Math Symbol 36
 
11.3%
Space Separator 15
 
4.7%
Lowercase Letter 4
 
1.3%
Close Punctuation 2
 
0.6%
Open Punctuation 2
 
0.6%
Other Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 34
40.0%
간 33
38.8%
분 9
 
10.6%
바 1
 
1.2%
텡 1
 
1.2%
게 1
 
1.2%
스 1
 
1.2%
모 1
 
1.2%
차 1
 
1.2%
없 1
 
1.2%
Other values (2) 2
 
2.4%
Decimal Number
ValueCountFrequency (%)
0 21
30.4%
1 15
21.7%
8 9
13.0%
5 5
 
7.2%
7 5
 
7.2%
3 5
 
7.2%
6 3
 
4.3%
9 3
 
4.3%
4 2
 
2.9%
2 1
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
T 35
34.0%
G 34
33.0%
M 34
33.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
50.0%
n 1
25.0%
g 1
25.0%
Math Symbol
ValueCountFrequency (%)
+ 34
94.4%
~ 2
 
5.6%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
: 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 126
39.6%
Latin 107
33.6%
Hangul 85
26.7%

Most frequent character per script

Common
ValueCountFrequency (%)
+ 34
27.0%
0 21
16.7%
15
11.9%
1 15
11.9%
8 9
 
7.1%
5 5
 
4.0%
7 5
 
4.0%
3 5
 
4.0%
6 3
 
2.4%
9 3
 
2.4%
Other values (6) 11
 
8.7%
Hangul
ValueCountFrequency (%)
시 34
40.0%
간 33
38.8%
분 9
 
10.6%
바 1
 
1.2%
텡 1
 
1.2%
게 1
 
1.2%
스 1
 
1.2%
모 1
 
1.2%
차 1
 
1.2%
없 1
 
1.2%
Other values (2) 2
 
2.4%
Latin
ValueCountFrequency (%)
T 35
32.7%
G 34
31.8%
M 34
31.8%
e 2
 
1.9%
n 1
 
0.9%
g 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 233
73.3%
Hangul 85
 
26.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 35
15.0%
G 34
14.6%
M 34
14.6%
+ 34
14.6%
0 21
9.0%
15
6.4%
1 15
6.4%
8 9
 
3.9%
5 5
 
2.1%
7 5
 
2.1%
Other values (12) 26
11.2%
Hangul
ValueCountFrequency (%)
시 34
40.0%
간 33
38.8%
분 9
 
10.6%
바 1
 
1.2%
텡 1
 
1.2%
게 1
 
1.2%
스 1
 
1.2%
모 1
 
1.2%
차 1
 
1.2%
없 1
 
1.2%
Other values (2) 2
 
2.4%

화폐 설명
Text

Distinct34
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:50.996641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length24
Mean length13.333333
Min length2

Characters and Unicode

Total characters480
Distinct characters130
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)88.9%

Sample

1st row투그릭(Tugrik)
2nd row마케도니아 데나르(denar)
3rd row루블(ruble)
4th row위안
5th row키프(LAK, Kip)
ValueCountFrequency (%)
루피 2
 
2.6%
dollar 2
 
2.6%
미국달러(usd 2
 
2.6%
마나트(manat 1
 
1.3%
1,000 1
 
1.3%
짜트(kyat 1
 
1.3%
고정환율 1
 
1.3%
0.3845 1
 
1.3%
1-ro 1
 
1.3%
투그릭(tugrik 1
 
1.3%
Other values (64) 64
83.1%
2023-12-10T19:19:51.886320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
 
8.8%
) 32
 
6.7%
( 31
 
6.5%
a 26
 
5.4%
n 16
 
3.3%
i 15
 
3.1%
R 13
 
2.7%
e 13
 
2.7%
o 11
 
2.3%
l 10
 
2.1%
Other values (120) 271
56.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 148
30.8%
Other Letter 114
23.8%
Uppercase Letter 84
17.5%
Space Separator 42
 
8.8%
Close Punctuation 32
 
6.7%
Open Punctuation 31
 
6.5%
Other Punctuation 12
 
2.5%
Decimal Number 12
 
2.5%
Dash Punctuation 2
 
0.4%
Currency Symbol 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
루 6
 
5.3%
러 6
 
5.3%
달 6
 
5.3%
피 5
 
4.4%
트 5
 
4.4%
미 4
 
3.5%
국 3
 
2.6%
나 3
 
2.6%
니 3
 
2.6%
키 2
 
1.8%
Other values (62) 71
62.3%
Lowercase Letter
ValueCountFrequency (%)
a 26
17.6%
n 16
10.8%
i 15
10.1%
e 13
8.8%
o 11
 
7.4%
l 10
 
6.8%
r 9
 
6.1%
p 7
 
4.7%
s 7
 
4.7%
g 6
 
4.1%
Other values (11) 28
18.9%
Uppercase Letter
ValueCountFrequency (%)
R 13
15.5%
K 9
10.7%
N 7
 
8.3%
T 7
 
8.3%
D 7
 
8.3%
S 6
 
7.1%
B 4
 
4.8%
U 4
 
4.8%
M 4
 
4.8%
H 3
 
3.6%
Other values (10) 20
23.8%
Decimal Number
ValueCountFrequency (%)
0 4
33.3%
1 3
25.0%
3 1
 
8.3%
8 1
 
8.3%
5 1
 
8.3%
4 1
 
8.3%
7 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 10
83.3%
. 1
 
8.3%
: 1
 
8.3%
Currency Symbol
ValueCountFrequency (%)
￥ 1
50.0%
$ 1
50.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 232
48.3%
Common 134
27.9%
Hangul 114
23.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
루 6
 
5.3%
러 6
 
5.3%
달 6
 
5.3%
피 5
 
4.4%
트 5
 
4.4%
미 4
 
3.5%
국 3
 
2.6%
나 3
 
2.6%
니 3
 
2.6%
키 2
 
1.8%
Other values (62) 71
62.3%
Latin
ValueCountFrequency (%)
a 26
 
11.2%
n 16
 
6.9%
i 15
 
6.5%
R 13
 
5.6%
e 13
 
5.6%
o 11
 
4.7%
l 10
 
4.3%
K 9
 
3.9%
r 9
 
3.9%
N 7
 
3.0%
Other values (31) 103
44.4%
Common
ValueCountFrequency (%)
42
31.3%
) 32
23.9%
( 31
23.1%
, 10
 
7.5%
0 4
 
3.0%
1 3
 
2.2%
- 2
 
1.5%
. 1
 
0.7%
3 1
 
0.7%
￥ 1
 
0.7%
Other values (7) 7
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 365
76.0%
Hangul 114
 
23.8%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
 
11.5%
) 32
 
8.8%
( 31
 
8.5%
a 26
 
7.1%
n 16
 
4.4%
i 15
 
4.1%
R 13
 
3.6%
e 13
 
3.6%
o 11
 
3.0%
l 10
 
2.7%
Other values (47) 156
42.7%
Hangul
ValueCountFrequency (%)
루 6
 
5.3%
러 6
 
5.3%
달 6
 
5.3%
피 5
 
4.4%
트 5
 
4.4%
미 4
 
3.5%
국 3
 
2.6%
나 3
 
2.6%
니 3
 
2.6%
키 2
 
1.8%
Other values (62) 71
62.3%
None
ValueCountFrequency (%)
￥ 1
100.0%

인당 GDP 설명($)
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T19:19:52.149043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length6.8611111
Min length4

Characters and Unicode

Total characters247
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row3,357$
2nd row5,276$
3rd row8,447 $
4th row8,929$
5th row2,051$
ValueCountFrequency (%)
15
28.8%
3,357 1
 
1.9%
1,800 1
 
1.9%
6,622 1
 
1.9%
21,000 1
 
1.9%
3,114 1
 
1.9%
11,307.1 1
 
1.9%
5,662 1
 
1.9%
5,215 1
 
1.9%
36,221 1
 
1.9%
Other values (28) 28
53.8%
2023-12-10T19:19:52.675463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
$ 36
14.6%
, 33
13.4%
26
10.5%
1 23
9.3%
2 21
8.5%
0 18
7.3%
3 15
6.1%
6 14
 
5.7%
5 13
 
5.3%
8 12
 
4.9%
Other values (5) 36
14.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150
60.7%
Currency Symbol 36
 
14.6%
Other Punctuation 34
 
13.8%
Space Separator 26
 
10.5%
Other Letter 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23
15.3%
2 21
14.0%
0 18
12.0%
3 15
10.0%
6 14
9.3%
5 13
8.7%
8 12
8.0%
9 12
8.0%
7 11
7.3%
4 11
7.3%
Other Punctuation
ValueCountFrequency (%)
, 33
97.1%
. 1
 
2.9%
Currency Symbol
ValueCountFrequency (%)
$ 36
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Other Letter
ValueCountFrequency (%)
만 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 246
99.6%
Hangul 1
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
$ 36
14.6%
, 33
13.4%
26
10.6%
1 23
9.3%
2 21
8.5%
0 18
7.3%
3 15
6.1%
6 14
 
5.7%
5 13
 
5.3%
8 12
 
4.9%
Other values (4) 35
14.2%
Hangul
ValueCountFrequency (%)
만 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 246
99.6%
Hangul 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
$ 36
14.6%
, 33
13.4%
26
10.6%
1 23
9.3%
2 21
8.5%
0 18
7.3%
3 15
6.1%
6 14
 
5.7%
5 13
 
5.3%
8 12
 
4.9%
Other values (4) 35
14.2%
Hangul
ValueCountFrequency (%)
만 1
100.0%

출처 설명
Categorical

Distinct8
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
KOTRA 해외시장뉴스
16 
수자원공사 물정보포털
10 
네이버
5 
외교부 홈페이지
 
1
KOTRA
 
1
Other values (3)
3 

Length

Max length12
Median length11
Mean length10.055556
Min length3

Unique

Unique5 ?
Unique (%)13.9%

Sample

1st rowKOTRA 해외시장뉴스
2nd row외교부 홈페이지
3rd rowKOTRA 해외시장뉴스
4th rowKOTRA 해외시장뉴스
5th rowKOTRA 해외시장뉴스

Common Values

ValueCountFrequency (%)
KOTRA 해외시장뉴스 16
44.4%
수자원공사 물정보포털 10
27.8%
네이버 5
 
13.9%
외교부 홈페이지 1
 
2.8%
KOTRA 1
 
2.8%
Google 포털 1
 
2.8%
해외건설종합정보서비스 1
 
2.8%
수자원공사 물정보포털” 1
 
2.8%

Length

2023-12-10T19:19:52.944823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:19:53.157859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kotra 17
26.2%
해외시장뉴스 16
24.6%
수자원공사 11
16.9%
물정보포털 10
15.4%
네이버 5
 
7.7%
외교부 1
 
1.5%
홈페이지 1
 
1.5%
google 1
 
1.5%
포털 1
 
1.5%
해외건설종합정보서비스 1
 
1.5%

Correlations

2023-12-10T19:19:53.342039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
GDP 설명(억 $)국가 코드국가 한글 명국가 영문 명면적(㎢ )수도 설명인구 설명(명)언어 설명종교 설명기후 설명정부 설명의회 설명시차 설명화폐 설명인당 GDP 설명($)출처 설명
GDP 설명(억 $)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
국가 코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
국가 한글 명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
국가 영문 명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
면적(㎢ )1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
수도 설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
인구 설명(명)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
언어 설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
종교 설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
기후 설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.9770.9100.9580.9791.0000.982
정부 설명1.0001.0001.0001.0001.0001.0001.0001.0001.0000.9771.0000.9410.5040.8951.0000.356
의회 설명1.0001.0001.0001.0001.0001.0001.0001.0001.0000.9100.9411.0000.8750.9841.0000.000
시차 설명1.0001.0001.0001.0001.0001.0001.0001.0001.0000.9580.5040.8751.0000.9211.0000.908
화폐 설명1.0001.0001.0001.0001.0001.0001.0001.0001.0000.9790.8950.9840.9211.0001.0000.000
인당 GDP 설명($)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
출처 설명1.0001.0001.0001.0001.0001.0001.0001.0001.0000.9820.3560.0000.9080.0001.0001.000

Missing values

2023-12-10T19:19:36.186498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:19:36.570423image/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

GDP 설명(억 $)국가 코드국가 한글 명국가 영문 명면적(㎢ )수도 설명인구 설명(명)언어 설명종교 설명기후 설명정부 설명의회 설명시차 설명화폐 설명인당 GDP 설명($)출처 설명
0102억$MG몽골(Mongolia)Mongolia156만 4,116㎢울란바토르(Ulaanbaatar)312만 902명할흐 몽골어 90%, 키릴문자, 문맹률 5% 이하라마불교(90%), 무슬림(5%), 무속 및 기독교(5%)건성냉대기후민주공화제국가대의회GMT+9시간투그릭(Tugrik)3,357$KOTRA 해외시장뉴스
1109억$MK구유고슬라비아 마케도니아 공화국(Former Yugoslav Republic of Macedonia)Makedonia25,713㎦(한반도의 약 1/8)스코피예(Skopje)209만명마케도니아어, 알바니아어마케도니아 정교(64.8%), 회교(33.3%), 기타(1.9%)온난한 대륙성 기후공화제단원제GMT+17시간마케도니아 데나르(denar)5,276$외교부 홈페이지
212,358억 $RS러시아(Russia)Russian1,712만 5,407㎢모스크바1억 4,650만 명러시아어, 문맹률 0.3%러시아 정교(이외 이슬람, 가톨릭, 기독교, 유대교 등)광범위한 기후대(겨울 길고 여름 짧은 대륙성기후) 1월 평균 -16~-9℃, 7월 평균 13~23℃연방제, 대통령제(6년 중임제)의회민주제GMT +4시간(모스크바)루블(ruble)8,447 $KOTRA 해외시장뉴스
3123,617억$CH중화인민공화국(中華人民共和國, The People’s Republic of China: P.R.C.)China약 960만㎢(면적: 세계 제4위, 한반도의 약 44배)베이징13억 7,462만 명한어(漢語; Chinese)[표준어: 보통화(普通話; Mandarin)]5대 종교: 불교(B.C.2), 도교(2c경), 천주교, 이슬람교(7c경), 기독교(19c경) 등광대한 영토(남북 거리 약 5,500㎞, 동서 거리 약 5,200㎞)로 인해 지역별로 다양한 기후대가 분포. 주로 최남단지역의 열대기후, 서부지역의 건조기후, 동북지역의 한대 기후 등으로 구분. 전체적으로 사계절이 뚜렷한 계절풍기후의 특징을 보이고 있음인민민주독재의 사회주의 국가공산당 일당독재GMT+8시간위안8,929$KOTRA 해외시장뉴스
4149억$LALao PDR)Laos236,800㎢(한반도의 약 1.1배), 국토의 70%가 산악지대비엔티안(Vientiane)649만 2,400명라오어(태국어와 유사)불교(90%), 정령신앙, 기독교(포교 불허)연중 고온 다습한 열대몬순기후사회주의공화국 (공산주의체제)임기 5년의 단임제 국회(라오 인민혁명당 1당 독재)GMT+8시간키프(LAK, Kip)2,051$KOTRA 해외시장뉴스
51조 4980억$KS대한민국Korea, Republic of99,720㎢ 세계109위 (CIA 기준)서울약 51,722,903명 (2017.04. 행정자치부기준)한국어불교(22.8%), 개신교(18.3%), 천주교(10.9%), 기타(1.1%), 종교없음(46.9%)온대성 기후대통령제단원제GMT+10시간원(WON)29,115$네이버
61,578억$KZ카자흐스탄 공화국(Republic of Kazakhstan)Kazakstan272만 ㎢(면적 세계 9위, 한반도의 12배, 한국의 27배)아스타나(Astana)1,775만 3,184명카자흐어(러시아어는 공용어)이슬람교, 러시아정교(국교는 없음)대륙성 기후대통령 중심제상하 양원제텡게 (Tenge)GMT+7시간8,667$KOTRA 해외시장뉴스
7160.9억$PPPapua New GuineaPapua New Guinea462,840km2(세계 55위)포트모르즈비(Port Moresby)약 6,791,317명(세계 106위)피지어, 영어기독교 90%, 기타 토착신앙열대우림 기후입헌군주제단원제GMT +10시간키나(Kina)2,700$네이버
81억 7,840만 $PSRepublic of PalauPalau458㎢멜레케오크(Melekeok)2만 956명영어와 팔라우어, 일부는 일본어 사용기독교 80%(천주교 40%, 개신교 40%), 토착 종교 20%열대성 해양 기후로 고온 다습대통령제상·하 양원제GMT +9시간미국달러8,941 $KOTRA 해외시장뉴스
9200억$AF아프가니스탄이슬람공화국, Islamic Republic of AfghanistanAfghanistan652,230㎢Kabul33,332,025명파슈토어, 다리어, 터키어이슬람교 (수니파 80%, 시아파 19%)대륙성기후로서 기온의 차가 커서 최고 38℃에서 최저 －18℃공화제 (대통령 중심제)양원제GMT+4시간30분아프가니(Afghanis : Af)184$수자원공사 물정보포털
GDP 설명(억 $)국가 코드국가 한글 명국가 영문 명면적(㎢ )수도 설명인구 설명(명)언어 설명종교 설명기후 설명정부 설명의회 설명시차 설명화폐 설명인당 GDP 설명($)출처 설명
26482억 $TX투르크메니스탄(Turkmenistan)Turkmenistan488,840㎢(한반도의 2.2배)아쉬하바드 (Ashgabat)5,291,317명투르크멘어이슬람교(89%), 동방정교(9%)대륙성 사막 기후 \ - 전 면적의 80% 이상이 Garagum(“검은 사막”) \ - 연평균기온 14~15℃, 여름평균기온 35℃, 겨울평균기온 ?4℃공화제단원제GMT +5시간마나트(Manat)6,622 $수자원공사 물정보포털
27503억$KNDPRK 약칭)Korea, Dem. People's Rep.122,138㎢(세계 96위, 2015년, CIA), 한반도 전체면적 222,784㎢의평양직할시(Pyongyang)2,515만 5,000명(세계 50위, 2015년, CIA)한국어(서북 방언에 기초한 문화어를 표준어로 삼음)실질적인 종교는 존재하지 않음대륙성 한랭기후사회주의 공화국(사실상 1인 독재체제), 주체사상 국가다당제(사실상 일당제)GMT+8시간30분북한 원1,800$네이버
285,485억$TW대만(臺灣, Taiwan)Taiwan36,193㎢타이베이 (Taipei)23,551,000명 (2016)공용어는 Mandarin(중국 표준어)이나 현지어인 민남어가 광범위하게 사용불교(35%), 도교(33%), 기독교(2.6%), 천주교(1.3%), 회교(0.2%) 등아열대 동북 몬순 기후권입헌민주공화국이원집정부제GMT+8시간New Taiwan Dollar(NT$)23,374$수자원공사 물정보포털
296,000백만$KG키르기스스탄(Kyrgyzstan), 키르기스 공화국(Kyrgyz Republic)Kyrgyzstan199,951㎢비슈케크(Bishkek)5,895,100명키르기스스어(공용어), 러시아어(공용어)이슬람교 75%, 러시아 정교회 25%대륙성 기후의원 내각제120석의 일원제GMT+10시간00분솜 (KGS)995$수자원공사 물정보포털
30626억 $UZ우즈베키스탄 공화국 (Republic of Uzbekistan)Uzbekistan447,400㎢타슈켄트(Tashkent)30,757,700명우즈베키스탄어, 러시아어(공용어)이슬람교 88% (수니파 70%), 러시아 정교 (9%), 기타 3%고온건조한 사막성 기후대통령중심제 (임기 5년) 단일 국가, 대통령제 공화국입법, 행정, 사법의 삼권이 분리GMT+11시간00분숨 (SUM)2,090 $수자원공사 물정보포털”
3164,330백만$BM미얀마 연방 공화국(Republic of the Union of Myanmar)Myanmar76,577㎢네피도(Nay Pyi Taw)53.4 millions (2016)미얀마어(공용어), 통용가능어(영어 : 양곤 일부, 중국어 : 만달레이, 중국 접경지역, 태국어 : 태국 접경 일부 지역)불교(89.4%), 기독교(4.9%), 이슬람교(3.9%), 토속신앙(1.2%), 힌두교(0.5%) 등고온다습한 열대 몬순기후이나, 북부지방은 아열대성 기후공화제대통령제GMT+6:30시간짜트(Kyat)1,269$수자원공사 물정보포털
32702.5억 $MU오만 왕국 (The Sultanate of Oman)Oman309,500 ㎢무스카트 (Muscat)3,286,936명공용어는 아랍어이며, 영어가 비교적 광범위하게 통용되나, 수도권 이외의 지역에서는 경찰들과도 영어로 의사소통이 어려운 경우가 있음 (기타 스와힐리어, 우르두어, 힌디어 등도 일부 사용)Islam건조 기후(5~10월 고온 건조, 남부 일부는 몬순기후)군주제(Sultan 왕정)\NGMT+12시간00분Baisa), RO 1-Bz 1,000 (USD 1-RO 0.3845, 고정환율)15,645 $수자원공사 물정보포털
33840억$CE스리랑카 민주 사회주의 공화국(Democratic Socialist Republic of Sri Lanka)Sri Lanka6만 5,600㎢Sri Jayawardenepura Kotte2,097만 명싱할라 및 타밀어(국어), 영어(상용어)불교(70.1%), 힌두교(12.6%), 이슬람교(9.7%), 기독교(7.6%), 기타(0.0%)열대 몬순기후, 고온다습이원집정부제단원제GMT+7시간루피3,927$KOTRA 해외시장뉴스
348,885억$ID인도네시아 공화국(Republic of Indonesia)Indonesia190만㎢자카르타약 2억 5,220만인도네시아어(Bahasa Indonesia)이슬람교(86%), 기독교(6%), 가톨릭(3%), 불교(2%), 힌두교(1.8%)열대성 몬순기후, 고온 무풍다습대통령 중심제공화제GMT+7~9시간Rupiah(Rp)3,377$KOTRA 해외시장뉴스
3592억 $TITajikistanTajikistan143,100km2두샨베(Dushanbe)8,330,946명타지크어, 러시아어이슬람교 90%(수니파 85%, 시아파 5%), 러시아정교 등 기타 10%건조한 대륙성 기후공화제단원제GMT +5시간소모니(somoni)1,099 $KOTRA 해외시장뉴스