Overview

Dataset statistics

Number of variables9
Number of observations428
Missing cells449
Missing cells (%)11.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.9 KiB
Average record size in memory76.3 B

Variable types

Text3
Categorical4
Numeric2

Dataset

Description2020년 12월 21일 기준 연도별 인구수 정보를 바탕으로 전년대비 증감률(출처 : World Bank)에 대한 정보를 CSV파일로 제공합니다.
Author외교부
URLhttps://www.data.go.kr/data/15076564/fileData.do

Alerts

비고 has constant value ""Constant
인구증감률(전년대비) 출처 is highly overall correlated with 측정년도 and 1 other fieldsHigh correlation
측정년도 is highly overall correlated with 인구수 출처 and 1 other fieldsHigh correlation
인구수 출처 is highly overall correlated with 측정년도 and 1 other fieldsHigh correlation
인구수 is highly overall correlated with 측정월High correlation
측정월 is highly overall correlated with 인구수High correlation
측정년도 is highly imbalanced (50.8%)Imbalance
측정월 is highly imbalanced (92.5%)Imbalance
인구증감률(전년대비) has 20 (4.7%) missing valuesMissing
비고 has 427 (99.8%) missing valuesMissing
인구수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:03:04.409049
Analysis finished2023-12-12 22:03:05.962792
Duration1.55 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

국가
Text

Distinct223
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2023-12-13T07:03:06.193588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length4.1495327
Min length1

Characters and Unicode

Total characters1776
Distinct characters212
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

Unique18 ?
Unique (%)4.2%

Sample

1st row가나
2nd row가나
3rd row가봉
4th row가봉
5th row가이아나
ValueCountFrequency (%)
세인트 7
 
1.5%
섬 4
 
0.9%
아일랜드 4
 
0.9%
프랑스령 3
 
0.7%
가나 2
 
0.4%
요르단 2
 
0.4%
엘살바도르 2
 
0.4%
영국 2
 
0.4%
영국령 2
 
0.4%
버진 2
 
0.4%
Other values (223) 427
93.4%
2023-12-13T07:03:06.636053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 122
 
6.9%
리 65
 
3.7%
스 64
 
3.6%
이 51
 
2.9%
니 51
 
2.9%
르 46
 
2.6%
라 43
 
2.4%
나 37
 
2.1%
도 35
 
2.0%
바 32
 
1.8%
Other values (202) 1230
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1733
97.6%
Space Separator 29
 
1.6%
Other Punctuation 4
 
0.2%
Uppercase Letter 4
 
0.2%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 122
 
7.0%
리 65
 
3.8%
스 64
 
3.7%
이 51
 
2.9%
니 51
 
2.9%
르 46
 
2.7%
라 43
 
2.5%
나 37
 
2.1%
도 35
 
2.0%
바 32
 
1.8%
Other values (196) 1187
68.5%
Uppercase Letter
ValueCountFrequency (%)
D 2
50.0%
R 2
50.0%
Space Separator
ValueCountFrequency (%)
29
100.0%
Other Punctuation
ValueCountFrequency (%)
· 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1733
97.6%
Common 39
 
2.2%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 122
 
7.0%
리 65
 
3.8%
스 64
 
3.7%
이 51
 
2.9%
니 51
 
2.9%
르 46
 
2.7%
라 43
 
2.5%
나 37
 
2.1%
도 35
 
2.0%
바 32
 
1.8%
Other values (196) 1187
68.5%
Common
ValueCountFrequency (%)
29
74.4%
· 4
 
10.3%
( 3
 
7.7%
) 3
 
7.7%
Latin
ValueCountFrequency (%)
D 2
50.0%
R 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1733
97.6%
ASCII 39
 
2.2%
None 4
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 122
 
7.0%
리 65
 
3.8%
스 64
 
3.7%
이 51
 
2.9%
니 51
 
2.9%
르 46
 
2.7%
라 43
 
2.5%
나 37
 
2.1%
도 35
 
2.0%
바 32
 
1.8%
Other values (196) 1187
68.5%
ASCII
ValueCountFrequency (%)
29
74.4%
( 3
 
7.7%
) 3
 
7.7%
D 2
 
5.1%
R 2
 
5.1%
None
ValueCountFrequency (%)
· 4
100.0%

국가코드(ISO 2자리 코드)
Text

Distinct222
Distinct (%)52.1%
Missing2
Missing (%)0.5%
Memory size3.5 KiB
2023-12-13T07:03:07.044728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters852
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

Unique18 ?
Unique (%)4.2%

Sample

1st rowGH
2nd rowGH
3rd rowGA
4th rowGA
5th rowGY
ValueCountFrequency (%)
gh 2
 
0.5%
iq 2
 
0.5%
sv 2
 
0.5%
gb 2
 
0.5%
vg 2
 
0.5%
ye 2
 
0.5%
om 2
 
0.5%
at 2
 
0.5%
hn 2
 
0.5%
jo 2
 
0.5%
Other values (212) 406
95.3%
2023-12-13T07:03:07.635774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 69
 
8.1%
G 58
 
6.8%
S 56
 
6.6%
T 50
 
5.9%
A 46
 
5.4%
C 45
 
5.3%
B 44
 
5.2%
E 41
 
4.8%
L 40
 
4.7%
N 40
 
4.7%
Other values (16) 363
42.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 852
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 69
 
8.1%
G 58
 
6.8%
S 56
 
6.6%
T 50
 
5.9%
A 46
 
5.4%
C 45
 
5.3%
B 44
 
5.2%
E 41
 
4.8%
L 40
 
4.7%
N 40
 
4.7%
Other values (16) 363
42.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 852
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 69
 
8.1%
G 58
 
6.8%
S 56
 
6.6%
T 50
 
5.9%
A 46
 
5.4%
C 45
 
5.3%
B 44
 
5.2%
E 41
 
4.8%
L 40
 
4.7%
N 40
 
4.7%
Other values (16) 363
42.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 852
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 69
 
8.1%
G 58
 
6.8%
S 56
 
6.6%
T 50
 
5.9%
A 46
 
5.4%
C 45
 
5.3%
B 44
 
5.2%
E 41
 
4.8%
L 40
 
4.7%
N 40
 
4.7%
Other values (16) 363
42.6%

측정년도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2018
213 
2019
207 
2016
 
4
2017
 
3
2020
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row2019
2nd row2018
3rd row2019
4th row2018
5th row2019

Common Values

ValueCountFrequency (%)
2018 213
49.8%
2019 207
48.4%
2016 4
 
0.9%
2017 3
 
0.7%
2020 1
 
0.2%

Length

2023-12-13T07:03:07.765419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:03:07.849584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 213
49.8%
2019 207
48.4%
2016 4
 
0.9%
2017 3
 
0.7%
2020 1
 
0.2%

측정월
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
422 
7
 
4
12
 
2

Length

Max length4
Median length4
Mean length3.9626168
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 422
98.6%
7 4
 
0.9%
12 2
 
0.5%

Length

2023-12-13T07:03:07.957076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:03:08.050434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 422
98.6%
7 4
 
0.9%
12 2
 
0.5%

인구수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct428
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35467474
Minimum54
Maximum1.397715 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-13T07:03:08.157564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile37750.75
Q1760917.5
median6505507.5
Q325004323
95-th percentile1.2125157 × 108
Maximum1.397715 × 109
Range1.3977149 × 109
Interquartile range (IQR)24243406

Descriptive statistics

Standard deviation1.3793208 × 108
Coefficient of variation (CV)3.888974
Kurtosis82.362292
Mean35467474
Median Absolute Deviation (MAD)6301445
Skewness8.7697877
Sum1.5180079 × 1010
Variance1.9025259 × 1016
MonotonicityNot monotonic
2023-12-13T07:03:08.283668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30417856 1
 
0.2%
100388073 1
 
0.2%
9053300 1
 
0.2%
81800269 1
 
0.2%
82913906 1
 
0.2%
38433600 1
 
0.2%
39309783 1
 
0.2%
44622518 1
 
0.2%
44385155 1
 
0.2%
32956100 1
 
0.2%
Other values (418) 418
97.7%
ValueCountFrequency (%)
54 1
0.2%
800 1
0.2%
1600 1
0.2%
4000 1
0.2%
5215 1
0.2%
5471 1
0.2%
11508 1
0.2%
11646 1
0.2%
12581 1
0.2%
12704 1
0.2%
ValueCountFrequency (%)
1397715000 1
0.2%
1392730000 1
0.2%
1366417754 1
0.2%
1352617328 1
0.2%
328239523 1
0.2%
326687501 1
0.2%
270625568 1
0.2%
267663435 1
0.2%
216565318 1
0.2%
212215030 1
0.2%

인구수 출처
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
('19) World Bank (최근 수정일 : 2020.12.16.)
204 
('18) World Bank (최근 수정일 : 2020.12.16.)
204 
<NA>
 
19
('20) CIA
 
1

Length

Max length39
Median length39
Mean length37.376168
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row('19) World Bank (최근 수정일 : 2020.12.16.)
2nd row('18) World Bank (최근 수정일 : 2020.12.16.)
3rd row('19) World Bank (최근 수정일 : 2020.12.16.)
4th row('18) World Bank (최근 수정일 : 2020.12.16.)
5th row('19) World Bank (최근 수정일 : 2020.12.16.)

Common Values

ValueCountFrequency (%)
('19) World Bank (최근 수정일 : 2020.12.16.) 204
47.7%
('18) World Bank (최근 수정일 : 2020.12.16.) 204
47.7%
<NA> 19
 
4.4%
('20) CIA 1
 
0.2%

Length

2023-12-13T07:03:08.406329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:03:08.519264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
world 408
14.2%
bank 408
14.2%
최근 408
14.2%
수정일 408
14.2%
408
14.2%
2020.12.16 408
14.2%
19 204
7.1%
18 204
7.1%
na 19
 
0.7%
20 1
 
< 0.1%

인구증감률(전년대비)
Real number (ℝ)

MISSING 

Distinct260
Distinct (%)63.7%
Missing20
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean1.2444608
Minimum-1.81
Maximum4.92
Zeros2
Zeros (%)0.5%
Negative50
Negative (%)11.7%
Memory size3.9 KiB
2023-12-13T07:03:08.629486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.81
5-th percentile-0.5195
Q10.46
median1.165
Q31.995
95-th percentile2.9965
Maximum4.92
Range6.73
Interquartile range (IQR)1.535

Descriptive statistics

Standard deviation1.1177167
Coefficient of variation (CV)0.89815341
Kurtosis-0.13126378
Mean1.2444608
Median Absolute Deviation (MAD)0.765
Skewness0.17230556
Sum507.74
Variance1.2492906
MonotonicityNot monotonic
2023-12-13T07:03:08.753827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.05 6
 
1.4%
1.52 5
 
1.2%
0.49 5
 
1.2%
0.96 4
 
0.9%
0.99 4
 
0.9%
1.88 4
 
0.9%
0.36 4
 
0.9%
1.67 4
 
0.9%
-0.01 4
 
0.9%
0.61 4
 
0.9%
Other values (250) 364
85.0%
(Missing) 20
 
4.7%
ValueCountFrequency (%)
-1.81 1
0.2%
-1.8 1
0.2%
-1.79 1
0.2%
-1.34 1
0.2%
-1.24 1
0.2%
-0.97 1
0.2%
-0.95 2
0.5%
-0.89 1
0.2%
-0.83 1
0.2%
-0.78 1
0.2%
ValueCountFrequency (%)
4.92 1
0.2%
4.47 1
0.2%
3.82 1
0.2%
3.81 1
0.2%
3.79 1
0.2%
3.72 1
0.2%
3.65 2
0.5%
3.56 1
0.2%
3.53 1
0.2%
3.49 1
0.2%

인구증감률(전년대비) 출처
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
('19) World Bank (최근 수정일 : 2020.12.16.)
204 
('18) World Bank (최근 수정일 : 2020.12.16.)
204 
<NA>
 
20

Length

Max length39
Median length39
Mean length37.364486
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row('19) World Bank (최근 수정일 : 2020.12.16.)
2nd row('18) World Bank (최근 수정일 : 2020.12.16.)
3rd row('19) World Bank (최근 수정일 : 2020.12.16.)
4th row('18) World Bank (최근 수정일 : 2020.12.16.)
5th row('19) World Bank (최근 수정일 : 2020.12.16.)

Common Values

ValueCountFrequency (%)
('19) World Bank (최근 수정일 : 2020.12.16.) 204
47.7%
('18) World Bank (최근 수정일 : 2020.12.16.) 204
47.7%
<NA> 20
 
4.7%

Length

2023-12-13T07:03:08.881087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:03:09.011592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
world 408
14.2%
bank 408
14.2%
최근 408
14.2%
수정일 408
14.2%
408
14.2%
2020.12.16 408
14.2%
19 204
7.1%
18 204
7.1%
na 20
 
0.7%

비고
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing427
Missing (%)99.8%
Memory size3.5 KiB
2023-12-13T07:03:09.171314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters29
Distinct characters21
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row(＇19), 대부분 섬의 남서부 및 연안 도서에 거주
ValueCountFrequency (%)
＇19 1
12.5%
대부분 1
12.5%
섬의 1
12.5%
남서부 1
12.5%
및 1
12.5%
연안 1
12.5%
도서에 1
12.5%
거주 1
12.5%
2023-12-13T07:03:09.430881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
24.1%
부 2
 
6.9%
서 2
 
6.9%
( 1
 
3.4%
남 1
 
3.4%
거 1
 
3.4%
에 1
 
3.4%
도 1
 
3.4%
안 1
 
3.4%
연 1
 
3.4%
Other values (11) 11
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
55.2%
Space Separator 7
24.1%
Other Punctuation 2
 
6.9%
Decimal Number 2
 
6.9%
Open Punctuation 1
 
3.4%
Close Punctuation 1
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 2
12.5%
서 2
12.5%
남 1
 
6.2%
거 1
 
6.2%
에 1
 
6.2%
도 1
 
6.2%
안 1
 
6.2%
연 1
 
6.2%
및 1
 
6.2%
섬 1
 
6.2%
Other values (4) 4
25.0%
Other Punctuation
ValueCountFrequency (%)
＇ 1
50.0%
, 1
50.0%
Decimal Number
ValueCountFrequency (%)
9 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
55.2%
Common 13
44.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 2
12.5%
서 2
12.5%
남 1
 
6.2%
거 1
 
6.2%
에 1
 
6.2%
도 1
 
6.2%
안 1
 
6.2%
연 1
 
6.2%
및 1
 
6.2%
섬 1
 
6.2%
Other values (4) 4
25.0%
Common
ValueCountFrequency (%)
7
53.8%
( 1
 
7.7%
＇ 1
 
7.7%
, 1
 
7.7%
) 1
 
7.7%
9 1
 
7.7%
1 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
55.2%
ASCII 12
41.4%
None 1
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
58.3%
( 1
 
8.3%
, 1
 
8.3%
) 1
 
8.3%
9 1
 
8.3%
1 1
 
8.3%
Hangul
ValueCountFrequency (%)
부 2
12.5%
서 2
12.5%
남 1
 
6.2%
거 1
 
6.2%
에 1
 
6.2%
도 1
 
6.2%
안 1
 
6.2%
연 1
 
6.2%
및 1
 
6.2%
섬 1
 
6.2%
Other values (4) 4
25.0%
None
ValueCountFrequency (%)
＇ 1
100.0%

Interactions

2023-12-13T07:03:05.047345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:03:04.847762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:03:05.460447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:03:04.945652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:03:09.521214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정년도측정월인구수인구수 출처인구증감률(전년대비)인구증감률(전년대비) 출처
측정년도1.0000.0000.0001.0000.0001.000
측정월0.0001.000NaNNaNNaNNaN
인구수0.000NaN1.0000.0000.0000.000
인구수 출처1.000NaN0.0001.0000.0001.000
인구증감률(전년대비)0.000NaN0.0000.0001.0000.000
인구증감률(전년대비) 출처1.000NaN0.0001.0000.0001.000
2023-12-13T07:03:09.635537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인구증감률(전년대비) 출처측정월측정년도인구수 출처
인구증감률(전년대비) 출처1.000NaN0.9950.995
측정월NaN1.0000.000NaN
측정년도0.9950.0001.0001.000
인구수 출처0.995NaN1.0001.000
2023-12-13T07:03:09.740267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인구수인구증감률(전년대비)측정년도측정월인구수 출처인구증감률(전년대비) 출처
인구수1.0000.2050.0001.0000.0000.000
인구증감률(전년대비)0.2051.0000.0000.0000.0000.000
측정년도0.0000.0001.0000.0001.0000.995
측정월1.0000.0000.0001.0000.0000.000
인구수 출처0.0000.0001.0000.0001.0000.995
인구증감률(전년대비) 출처0.0000.0000.9950.0000.9951.000

Missing values

2023-12-13T07:03:05.600237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:03:05.745879image/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.
2023-12-13T07:03:05.882916image/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

국가국가코드(ISO 2자리 코드)측정년도측정월인구수인구수 출처인구증감률(전년대비)인구증감률(전년대비) 출처비고
0가나GH2019<NA>30417856('19) World Bank (최근 수정일 : 2020.12.16.)2.16('19) World Bank (최근 수정일 : 2020.12.16.)<NA>
1가나GH2018<NA>29767108('18) World Bank (최근 수정일 : 2020.12.16.)2.19('18) World Bank (최근 수정일 : 2020.12.16.)<NA>
2가봉GA2019<NA>2172579('19) World Bank (최근 수정일 : 2020.12.16.)2.48('19) World Bank (최근 수정일 : 2020.12.16.)<NA>
3가봉GA2018<NA>2119275('18) World Bank (최근 수정일 : 2020.12.16.)2.6('18) World Bank (최근 수정일 : 2020.12.16.)<NA>
4가이아나GY2019<NA>782766('19) World Bank (최근 수정일 : 2020.12.16.)0.48('19) World Bank (최근 수정일 : 2020.12.16.)<NA>
5가이아나GY2018<NA>779004('18) World Bank (최근 수정일 : 2020.12.16.)0.49('18) World Bank (최근 수정일 : 2020.12.16.)<NA>
6감비아GM2019<NA>2347706('19) World Bank (최근 수정일 : 2020.12.16.)2.92('19) World Bank (최근 수정일 : 2020.12.16.)<NA>
7감비아GM2018<NA>2280102('18) World Bank (최근 수정일 : 2020.12.16.)2.95('18) World Bank (최근 수정일 : 2020.12.16.)<NA>
8건지GG20181262506<NA><NA><NA><NA>
9과들루프GP2019<NA>488869<NA><NA><NA><NA>
국가국가코드(ISO 2자리 코드)측정년도측정월인구수인구수 출처인구증감률(전년대비)인구증감률(전년대비) 출처비고
418피지FJ2018<NA>883483('18) World Bank (최근 수정일 : 2020.12.16.)0.68('18) World Bank (최근 수정일 : 2020.12.16.)<NA>
419핀란드FI2019<NA>5520314('19) World Bank (최근 수정일 : 2020.12.16.)0.09('19) World Bank (최근 수정일 : 2020.12.16.)<NA>
420핀란드FI2018<NA>5515525('18) World Bank (최근 수정일 : 2020.12.16.)0.13('18) World Bank (최근 수정일 : 2020.12.16.)<NA>
421필리핀PH2019<NA>108116615('19) World Bank (최근 수정일 : 2020.12.16.)1.36('19) World Bank (최근 수정일 : 2020.12.16.)<NA>
422필리핀PH2018<NA>106651922('18) World Bank (최근 수정일 : 2020.12.16.)1.4('18) World Bank (최근 수정일 : 2020.12.16.)<NA>
423핏케언 섬PN2016754<NA><NA><NA><NA>
424헝가리HU2019<NA>9769949('19) World Bank (최근 수정일 : 2020.12.16.)-0.06('19) World Bank (최근 수정일 : 2020.12.16.)<NA>
425헝가리HU2018<NA>9775564('18) World Bank (최근 수정일 : 2020.12.16.)-0.13('18) World Bank (최근 수정일 : 2020.12.16.)<NA>
426호주AU2019<NA>25364307('19) World Bank (최근 수정일 : 2020.12.16.)1.52('19) World Bank (최근 수정일 : 2020.12.16.)<NA>
427호주AU2018<NA>24982688('18) World Bank (최근 수정일 : 2020.12.16.)1.54('18) World Bank (최근 수정일 : 2020.12.16.)<NA>