Overview

Dataset statistics

Number of variables5
Number of observations237
Missing cells23
Missing cells (%)1.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.6 KiB
Average record size in memory41.6 B

Variable types

Text4
Numeric1

Dataset

Description외교부에서 보유하고 있는 국가별, 지역별 ISO3166-1 표준코드(2자리, 3자리) 및 한글명칭, 영문명칭을 CSV 파일로 제공합니다.
Author외교부
URLhttps://www.data.go.kr/data/15076566/fileData.do

Alerts

국가명(영문) has 7 (3.0%) missing valuesMissing
ISO(3자리) has 7 (3.0%) missing valuesMissing
ISO(숫자) has 8 (3.4%) missing valuesMissing
국가명(국문) has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:39:39.496252
Analysis finished2023-12-12 22:39:40.000550
Duration0.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

국가명(영문)
Text

MISSING 

Distinct230
Distinct (%)100.0%
Missing7
Missing (%)3.0%
Memory size2.0 KiB
2023-12-13T07:39:40.181951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length9.2565217
Min length4

Characters and Unicode

Total characters2129
Distinct characters57
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique230 ?
Unique (%)100.0%

Sample

1st rowGhana
2nd rowGabon
3rd rowGuyana
4th rowGambia
5th rowBailiwick of Guernsey
ValueCountFrequency (%)
islands 8
 
2.5%
of 6
 
1.9%
st 5
 
1.6%
republic 4
 
1.3%
and 4
 
1.3%
4
 
1.3%
british 3
 
1.0%
new 3
 
1.0%
united 3
 
1.0%
guinea 3
 
1.0%
Other values (261) 271
86.3%
2023-12-13T07:39:40.522112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 299
 
14.0%
i 185
 
8.7%
n 163
 
7.7%
e 149
 
7.0%
r 126
 
5.9%
o 111
 
5.2%
t 87
 
4.1%
84
 
3.9%
u 80
 
3.8%
s 80
 
3.8%
Other values (47) 765
35.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1719
80.7%
Uppercase Letter 308
 
14.5%
Space Separator 84
 
3.9%
Other Punctuation 14
 
0.7%
Dash Punctuation 4
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 299
17.4%
i 185
10.8%
n 163
9.5%
e 149
8.7%
r 126
 
7.3%
o 111
 
6.5%
t 87
 
5.1%
u 80
 
4.7%
s 80
 
4.7%
l 79
 
4.6%
Other values (16) 360
20.9%
Uppercase Letter
ValueCountFrequency (%)
S 32
 
10.4%
M 27
 
8.8%
B 25
 
8.1%
C 22
 
7.1%
A 22
 
7.1%
G 21
 
6.8%
I 19
 
6.2%
T 17
 
5.5%
N 17
 
5.5%
P 16
 
5.2%
Other values (15) 90
29.2%
Other Punctuation
ValueCountFrequency (%)
. 8
57.1%
& 3
 
21.4%
: 2
 
14.3%
' 1
 
7.1%
Space Separator
ValueCountFrequency (%)
84
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2027
95.2%
Common 102
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 299
14.8%
i 185
 
9.1%
n 163
 
8.0%
e 149
 
7.4%
r 126
 
6.2%
o 111
 
5.5%
t 87
 
4.3%
u 80
 
3.9%
s 80
 
3.9%
l 79
 
3.9%
Other values (41) 668
33.0%
Common
ValueCountFrequency (%)
84
82.4%
. 8
 
7.8%
- 4
 
3.9%
& 3
 
2.9%
: 2
 
2.0%
' 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2129
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 299
 
14.0%
i 185
 
8.7%
n 163
 
7.7%
e 149
 
7.0%
r 126
 
5.9%
o 111
 
5.2%
t 87
 
4.1%
84
 
3.9%
u 80
 
3.8%
s 80
 
3.8%
Other values (47) 765
35.9%

국가명(국문)
Text

UNIQUE 

Distinct237
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-13T07:39:40.796068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length4.2700422
Min length1

Characters and Unicode

Total characters1012
Distinct characters229
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

Unique237 ?
Unique (%)100.0%

Sample

1st row가나
2nd row가봉
3rd row가이아나
4th row감비아
5th row건지
ValueCountFrequency (%)
세인트 4
 
1.5%
영국령 3
 
1.2%
섬 3
 
1.2%
국가 2
 
0.8%
제도 2
 
0.8%
아일랜드 2
 
0.8%
프랑스령 2
 
0.8%
일본 1
 
0.4%
인도네시아 1
 
0.4%
인도 1
 
0.4%
Other values (239) 239
91.9%
2023-12-13T07:39:41.133597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 63
 
6.2%
스 35
 
3.5%
리 34
 
3.4%
이 27
 
2.7%
니 27
 
2.7%
르 25
 
2.5%
23
 
2.3%
라 23
 
2.3%
도 20
 
2.0%
나 20
 
2.0%
Other values (219) 715
70.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 980
96.8%
Space Separator 23
 
2.3%
Other Punctuation 3
 
0.3%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 63
 
6.4%
스 35
 
3.6%
리 34
 
3.5%
이 27
 
2.8%
니 27
 
2.8%
르 25
 
2.6%
라 23
 
2.3%
도 20
 
2.0%
나 20
 
2.0%
국 17
 
1.7%
Other values (213) 689
70.3%
Uppercase Letter
ValueCountFrequency (%)
R 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Other Punctuation
ValueCountFrequency (%)
· 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 980
96.8%
Common 30
 
3.0%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 63
 
6.4%
스 35
 
3.6%
리 34
 
3.5%
이 27
 
2.8%
니 27
 
2.8%
르 25
 
2.6%
라 23
 
2.3%
도 20
 
2.0%
나 20
 
2.0%
국 17
 
1.7%
Other values (213) 689
70.3%
Common
ValueCountFrequency (%)
23
76.7%
· 3
 
10.0%
( 2
 
6.7%
) 2
 
6.7%
Latin
ValueCountFrequency (%)
R 1
50.0%
D 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 980
96.8%
ASCII 29
 
2.9%
None 3
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 63
 
6.4%
스 35
 
3.6%
리 34
 
3.5%
이 27
 
2.8%
니 27
 
2.8%
르 25
 
2.6%
라 23
 
2.3%
도 20
 
2.0%
나 20
 
2.0%
국 17
 
1.7%
Other values (213) 689
70.3%
ASCII
ValueCountFrequency (%)
23
79.3%
( 2
 
6.9%
) 2
 
6.9%
R 1
 
3.4%
D 1
 
3.4%
None
ValueCountFrequency (%)
· 3
100.0%

ISO(2자리)
Text

Distinct236
Distinct (%)100.0%
Missing1
Missing (%)0.4%
Memory size2.0 KiB
2023-12-13T07:39:41.547381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters472
Distinct characters27
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique236 ?
Unique (%)100.0%

Sample

1st rowGH
2nd rowGA
3rd rowGY
4th rowGM
5th rowGG
ValueCountFrequency (%)
gh 1
 
0.4%
jo 1
 
0.4%
uy 1
 
0.4%
uz 1
 
0.4%
ua 1
 
0.4%
iq 1
 
0.4%
ir 1
 
0.4%
il 1
 
0.4%
eg 1
 
0.4%
it 1
 
0.4%
Other values (226) 226
95.8%
2023-12-13T07:39:42.014642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 37
 
7.8%
G 31
 
6.6%
S 29
 
6.1%
A 27
 
5.7%
T 26
 
5.5%
C 24
 
5.1%
N 23
 
4.9%
E 23
 
4.9%
B 23
 
4.9%
R 20
 
4.2%
Other values (17) 209
44.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 470
99.6%
Decimal Number 2
 
0.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 37
 
7.9%
G 31
 
6.6%
S 29
 
6.2%
A 27
 
5.7%
T 26
 
5.5%
C 24
 
5.1%
N 23
 
4.9%
E 23
 
4.9%
B 23
 
4.9%
R 20
 
4.3%
Other values (16) 207
44.0%
Decimal Number
ValueCountFrequency (%)
9 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 470
99.6%
Common 2
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 37
 
7.9%
G 31
 
6.6%
S 29
 
6.2%
A 27
 
5.7%
T 26
 
5.5%
C 24
 
5.1%
N 23
 
4.9%
E 23
 
4.9%
B 23
 
4.9%
R 20
 
4.3%
Other values (16) 207
44.0%
Common
ValueCountFrequency (%)
9 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 472
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 37
 
7.8%
G 31
 
6.6%
S 29
 
6.1%
A 27
 
5.7%
T 26
 
5.5%
C 24
 
5.1%
N 23
 
4.9%
E 23
 
4.9%
B 23
 
4.9%
R 20
 
4.2%
Other values (17) 209
44.3%

ISO(3자리)
Text

MISSING 

Distinct230
Distinct (%)100.0%
Missing7
Missing (%)3.0%
Memory size2.0 KiB
2023-12-13T07:39:42.402146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters690
Distinct characters26
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

Unique230 ?
Unique (%)100.0%

Sample

1st rowGHA
2nd rowGAB
3rd rowGUY
4th rowGMB
5th rowGGY
ValueCountFrequency (%)
mus 1
 
0.4%
tcd 1
 
0.4%
ind 1
 
0.4%
hnd 1
 
0.4%
wlf 1
 
0.4%
jor 1
 
0.4%
uga 1
 
0.4%
ury 1
 
0.4%
uzb 1
 
0.4%
ukr 1
 
0.4%
Other values (220) 220
95.7%
2023-12-13T07:39:42.902016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 52
 
7.5%
N 49
 
7.1%
R 48
 
7.0%
M 48
 
7.0%
S 39
 
5.7%
T 38
 
5.5%
L 37
 
5.4%
G 37
 
5.4%
B 35
 
5.1%
C 30
 
4.3%
Other values (16) 277
40.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 690
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 52
 
7.5%
N 49
 
7.1%
R 48
 
7.0%
M 48
 
7.0%
S 39
 
5.7%
T 38
 
5.5%
L 37
 
5.4%
G 37
 
5.4%
B 35
 
5.1%
C 30
 
4.3%
Other values (16) 277
40.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 690
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 52
 
7.5%
N 49
 
7.1%
R 48
 
7.0%
M 48
 
7.0%
S 39
 
5.7%
T 38
 
5.5%
L 37
 
5.4%
G 37
 
5.4%
B 35
 
5.1%
C 30
 
4.3%
Other values (16) 277
40.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 690
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 52
 
7.5%
N 49
 
7.1%
R 48
 
7.0%
M 48
 
7.0%
S 39
 
5.7%
T 38
 
5.5%
L 37
 
5.4%
G 37
 
5.4%
B 35
 
5.1%
C 30
 
4.3%
Other values (16) 277
40.1%

ISO(숫자)
Real number (ℝ)

MISSING 

Distinct229
Distinct (%)100.0%
Missing8
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean435.30131
Minimum4
Maximum894
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T07:39:43.048915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile45.6
Q1214
median434
Q3654
95-th percentile831.6
Maximum894
Range890
Interquartile range (IQR)440

Descriptive statistics

Standard deviation253.83846
Coefficient of variation (CV)0.58313278
Kurtosis-1.183379
Mean435.30131
Median Absolute Deviation (MAD)220
Skewness0.0033512732
Sum99684
Variance64433.966
MonotonicityNot monotonic
2023-12-13T07:39:43.213765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
887 1
 
0.4%
40 1
 
0.4%
340 1
 
0.4%
876 1
 
0.4%
400 1
 
0.4%
800 1
 
0.4%
858 1
 
0.4%
860 1
 
0.4%
804 1
 
0.4%
368 1
 
0.4%
Other values (219) 219
92.4%
(Missing) 8
 
3.4%
ValueCountFrequency (%)
4 1
0.4%
8 1
0.4%
10 1
0.4%
12 1
0.4%
20 1
0.4%
24 1
0.4%
28 1
0.4%
31 1
0.4%
32 1
0.4%
36 1
0.4%
ValueCountFrequency (%)
894 1
0.4%
887 1
0.4%
882 1
0.4%
876 1
0.4%
862 1
0.4%
860 1
0.4%
858 1
0.4%
854 1
0.4%
840 1
0.4%
834 1
0.4%

Interactions

2023-12-13T07:39:39.702625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T07:39:39.792184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:39:39.877678image/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.
2023-12-13T07:39:39.955754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

국가명(영문)국가명(국문)ISO(2자리)ISO(3자리)ISO(숫자)
0Ghana가나GHGHA288
1Gabon가봉GAGAB266
2Guyana가이아나GYGUY328
3Gambia감비아GMGMB270
4Bailiwick of Guernsey건지GGGGY831
5Guadeloupe과들루프GPGLP312
6Guatemala과테말라GTGTM320
7Guam괌GUGUM316
8Grenada그레나다GDGRD308
9Greece그리스GRGRC300
국가명(영문)국가명(국문)ISO(2자리)ISO(3자리)ISO(숫자)
227Korea대한민국KRKOR410
228Puerto Rico푸에르토리코PRPRI630
229<NA>유럽연합EU<NA><NA>
230<NA>아세안XA<NA><NA>
231<NA>유네스코XB<NA><NA>
232<NA>국제연합UN<NA><NA>
233<NA>이슬람 국가XC<NA><NA>
234<NA>경제협력개발기구XD<NA><NA>
235Hongkong홍콩HKHKG344
236<NA>전체 국가99<NA><NA>