Overview

Dataset statistics

Number of variables5
Number of observations8454
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory355.1 KiB
Average record size in memory43.0 B

Variable types

Numeric3
Text1
Categorical1

Dataset

Description국민연금의 연도말 기준 해외채권 투자 종목별 금액, 자산군 내 비중, 종류 등 투자 현황에 대한 정보 (단위: 억 원, %)
Author국민연금공단
URLhttps://www.data.go.kr/data/15044505/fileData.do

Alerts

번호 is highly overall correlated with 금액(억 원) and 1 other fieldsHigh correlation
금액(억 원) is highly overall correlated with 번호 and 1 other fieldsHigh correlation
비중(퍼센트) is highly overall correlated with 번호 and 1 other fieldsHigh correlation
번호 has unique valuesUnique
금액(억 원) has 281 (3.3%) zerosZeros
비중(퍼센트) has 4158 (49.2%) zerosZeros

Reproduction

Analysis started2023-12-11 23:20:28.319514
Analysis finished2023-12-11 23:20:29.749687
Duration1.43 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct8454
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4227.5
Minimum1
Maximum8454
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.4 KiB
2023-12-12T08:20:29.827492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile423.65
Q12114.25
median4227.5
Q36340.75
95-th percentile8031.35
Maximum8454
Range8453
Interquartile range (IQR)4226.5

Descriptive statistics

Standard deviation2440.6039
Coefficient of variation (CV)0.57731613
Kurtosis-1.2
Mean4227.5
Median Absolute Deviation (MAD)2113.5
Skewness0
Sum35739285
Variance5956547.5
MonotonicityStrictly increasing
2023-12-12T08:20:29.961237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5633 1
 
< 0.1%
5647 1
 
< 0.1%
5646 1
 
< 0.1%
5645 1
 
< 0.1%
5644 1
 
< 0.1%
5643 1
 
< 0.1%
5642 1
 
< 0.1%
5641 1
 
< 0.1%
5640 1
 
< 0.1%
Other values (8444) 8444
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
8454 1
< 0.1%
8453 1
< 0.1%
8452 1
< 0.1%
8451 1
< 0.1%
8450 1
< 0.1%
8449 1
< 0.1%
8448 1
< 0.1%
8447 1
< 0.1%
8446 1
< 0.1%
8445 1
< 0.1%

종목명
Text

Distinct7019
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
2023-12-12T08:20:30.299384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length15.743198
Min length7

Characters and Unicode

Total characters133093
Distinct characters52
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5916 ?
Unique (%)70.0%

Sample

1st rowT 1 ¾ 05/15/23
2nd rowT 3 ½ 09/15/25
3rd rowT 3 ⅛ 08/15/25
4th rowT 2 ¾ 04/30/27
5th rowT 2 ⅞ 04/30/29
ValueCountFrequency (%)
0 846
 
3.1%
1 760
 
2.7%
fn 656
 
2.4%
2 650
 
2.4%
3 614
 
2.2%
½ 603
 
2.2%
¾ 512
 
1.9%
¼ 509
 
1.8%
4 449
 
1.6%
⅜ 353
 
1.3%
Other values (7324) 21703
78.5%
2023-12-12T08:20:31.025562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19202
14.4%
/ 12537
 
9.4%
0 11224
 
8.4%
2 10639
 
8.0%
1 10097
 
7.6%
3 6232
 
4.7%
5 5472
 
4.1%
4 4311
 
3.2%
A 3081
 
2.3%
6 3006
 
2.3%
Other values (42) 47292
35.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59085
44.4%
Uppercase Letter 35861
26.9%
Space Separator 19202
 
14.4%
Other Punctuation 15441
 
11.6%
Other Number 2976
 
2.2%
Dash Punctuation 436
 
0.3%
Lowercase Letter 92
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 3081
 
8.6%
B 2875
 
8.0%
N 2729
 
7.6%
C 2171
 
6.1%
S 2155
 
6.0%
F 2132
 
5.9%
G 2082
 
5.8%
T 1954
 
5.4%
R 1933
 
5.4%
M 1690
 
4.7%
Other values (16) 13059
36.4%
Decimal Number
ValueCountFrequency (%)
0 11224
19.0%
2 10639
18.0%
1 10097
17.1%
3 6232
10.5%
5 5472
9.3%
4 4311
 
7.3%
6 3006
 
5.1%
7 2837
 
4.8%
9 2721
 
4.6%
8 2546
 
4.3%
Other Number
ValueCountFrequency (%)
½ 603
20.3%
¾ 512
17.2%
¼ 509
17.1%
⅜ 353
11.9%
⅞ 342
11.5%
⅛ 335
11.3%
⅝ 322
10.8%
Lowercase Letter
ValueCountFrequency (%)
l 23
25.0%
o 23
25.0%
a 23
25.0%
t 23
25.0%
Other Punctuation
ValueCountFrequency (%)
/ 12537
81.2%
. 2626
 
17.0%
# 278
 
1.8%
Space Separator
ValueCountFrequency (%)
19202
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 436
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97140
73.0%
Latin 35953
 
27.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 3081
 
8.6%
B 2875
 
8.0%
N 2729
 
7.6%
C 2171
 
6.0%
S 2155
 
6.0%
F 2132
 
5.9%
G 2082
 
5.8%
T 1954
 
5.4%
R 1933
 
5.4%
M 1690
 
4.7%
Other values (20) 13151
36.6%
Common
ValueCountFrequency (%)
19202
19.8%
/ 12537
12.9%
0 11224
11.6%
2 10639
11.0%
1 10097
10.4%
3 6232
 
6.4%
5 5472
 
5.6%
4 4311
 
4.4%
6 3006
 
3.1%
7 2837
 
2.9%
Other values (12) 11583
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130117
97.8%
None 1624
 
1.2%
Number Forms 1352
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19202
14.8%
/ 12537
 
9.6%
0 11224
 
8.6%
2 10639
 
8.2%
1 10097
 
7.8%
3 6232
 
4.8%
5 5472
 
4.2%
4 4311
 
3.3%
A 3081
 
2.4%
6 3006
 
2.3%
Other values (35) 44316
34.1%
None
ValueCountFrequency (%)
½ 603
37.1%
¾ 512
31.5%
¼ 509
31.3%
Number Forms
ValueCountFrequency (%)
⅜ 353
26.1%
⅞ 342
25.3%
⅛ 335
24.8%
⅝ 322
23.8%

금액(억 원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct556
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.957062
Minimum0
Maximum3519
Zeros281
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size74.4 KiB
2023-12-12T08:20:31.155523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q111
median32
Q378
95-th percentile256
Maximum3519
Range3519
Interquartile range (IQR)67

Descriptive statistics

Standard deviation162.16844
Coefficient of variation (CV)2.1634845
Kurtosis105.90253
Mean74.957062
Median Absolute Deviation (MAD)26
Skewness8.2999522
Sum633687
Variance26298.604
MonotonicityDecreasing
2023-12-12T08:20:31.279814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 281
 
3.3%
1 244
 
2.9%
2 236
 
2.8%
3 190
 
2.2%
4 173
 
2.0%
5 171
 
2.0%
9 163
 
1.9%
6 156
 
1.8%
8 143
 
1.7%
11 140
 
1.7%
Other values (546) 6557
77.6%
ValueCountFrequency (%)
0 281
3.3%
1 244
2.9%
2 236
2.8%
3 190
2.2%
4 173
2.0%
5 171
2.0%
6 156
1.8%
7 136
1.6%
8 143
1.7%
9 163
1.9%
ValueCountFrequency (%)
3519 1
< 0.1%
3515 1
< 0.1%
2398 1
< 0.1%
2294 1
< 0.1%
2267 1
< 0.1%
2233 1
< 0.1%
2226 1
< 0.1%
2178 2
< 0.1%
2107 1
< 0.1%
2087 1
< 0.1%

비중(퍼센트)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.011353206
Minimum0
Maximum0.56
Zeros4158
Zeros (%)49.2%
Negative0
Negative (%)0.0%
Memory size74.4 KiB
2023-12-12T08:20:31.411062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.01
Q30.01
95-th percentile0.04
Maximum0.56
Range0.56
Interquartile range (IQR)0.01

Descriptive statistics

Standard deviation0.025911787
Coefficient of variation (CV)2.2823322
Kurtosis100.73399
Mean0.011353206
Median Absolute Deviation (MAD)0.01
Skewness8.0021911
Sum95.98
Variance0.00067142072
MonotonicityDecreasing
2023-12-12T08:20:31.513639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0.0 4158
49.2%
0.01 2578
30.5%
0.02 885
 
10.5%
0.03 279
 
3.3%
0.04 196
 
2.3%
0.05 67
 
0.8%
0.06 59
 
0.7%
0.07 48
 
0.6%
0.09 36
 
0.4%
0.08 27
 
0.3%
Other values (28) 121
 
1.4%
ValueCountFrequency (%)
0.0 4158
49.2%
0.01 2578
30.5%
0.02 885
 
10.5%
0.03 279
 
3.3%
0.04 196
 
2.3%
0.05 67
 
0.8%
0.06 59
 
0.7%
0.07 48
 
0.6%
0.08 27
 
0.3%
0.09 36
 
0.4%
ValueCountFrequency (%)
0.56 1
 
< 0.1%
0.55 1
 
< 0.1%
0.38 1
 
< 0.1%
0.36 2
< 0.1%
0.35 2
< 0.1%
0.34 2
< 0.1%
0.33 3
< 0.1%
0.31 1
 
< 0.1%
0.3 2
< 0.1%
0.28 1
 
< 0.1%

종류
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
Corporate
3831 
Securitized
2026 
Treasury
1457 
Government-Related
1123 
Municipals
 
17

Length

Max length18
Median length11
Mean length10.504495
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Corporate 3831
45.3%
Securitized 2026
24.0%
Treasury 1457
 
17.2%
Government-Related 1123
 
13.3%
Municipals 17
 
0.2%

Length

2023-12-12T08:20:31.617217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:20:31.705663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
corporate 3831
45.3%
securitized 2026
24.0%
treasury 1457
 
17.2%
government-related 1123
 
13.3%
municipals 17
 
0.2%

Interactions

2023-12-12T08:20:29.313531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:20:28.745800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:20:29.035488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:20:29.418869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:20:28.822751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:20:29.119272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:20:29.527023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:20:28.947738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:20:29.207932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:20:31.773151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호금액(억 원)비중(퍼센트)종류
번호1.0000.4120.4140.584
금액(억 원)0.4121.0001.0000.251
비중(퍼센트)0.4141.0001.0000.251
종류0.5840.2510.2511.000
2023-12-12T08:20:31.848850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호금액(억 원)비중(퍼센트)종류
번호1.000-1.000-0.9230.280
금액(억 원)-1.0001.0000.9230.156
비중(퍼센트)-0.9230.9231.0000.156
종류0.2800.1560.1561.000

Missing values

2023-12-12T08:20:29.629790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:20:29.713947image/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

번호종목명금액(억 원)비중(퍼센트)종류
01T 1 ¾ 05/15/2335190.56Treasury
12T 3 ½ 09/15/2535150.55Treasury
23T 3 ⅛ 08/15/2523980.38Treasury
34T 2 ¾ 04/30/2722940.36Treasury
45T 2 ⅞ 04/30/2922670.36Treasury
56T 2 ⅜ 02/15/4222330.35Treasury
67BKO 0.2 06/14/2422260.35Treasury
78OBL 0 10/13/23 #17821780.34Treasury
89FNCL 4 1/2321780.34Securitized
910JGB0.005 06/20/26 #14821070.33Treasury
번호종목명금액(억 원)비중(퍼센트)종류
84448445NDASS 1 ½ 10/01/53 IO00.0Securitized
84458446NYKRE 1 10/01/5000.0Securitized
84468447NYKRE 1 ½ 10/01/53 IO00.0Securitized
84478448RDKRE 1 ½ 10/01/53 IO00.0Securitized
84488449NYKRE 1 10/01/53 IO00.0Securitized
84498450NYKRE 2 10/01/53 IO00.0Securitized
84508451NDASS 1 ½ 10/01/5300.0Securitized
84518452NDASS 2 10/01/53 IO00.0Securitized
84528453GNR 2011-10 IO00.0Securitized
84538454GNR 2016-22 IX00.0Securitized