Overview

Dataset statistics

Number of variables3
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory27.8 B

Variable types

Text1
Categorical1
Numeric1

Dataset

Description한국자산관리공사 공사채권 통화별 매입차주 현황("금융기관","통화코드","매입차주건수")
Author한국자산관리공사
URLhttps://www.data.go.kr/data/15074428/fileData.do

Reproduction

Analysis started2023-12-13 00:58:47.927677
Analysis finished2023-12-13 00:58:48.213901
Duration0.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

금융기관
Text

Distinct29
Distinct (%)60.4%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T09:58:48.320912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length5.5
Min length4

Characters and Unicode

Total characters264
Distinct characters54
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)41.7%

Sample

1st row산업은행
2nd row산업은행
3rd row산업은행
4th row산업은행
5th row산업은행
ValueCountFrequency (%)
산업은행 5
 
10.4%
우리은행(한일 5
 
10.4%
국민은행 3
 
6.2%
하나(외환)은행 3
 
6.2%
신한은행 3
 
6.2%
기업은행 3
 
6.2%
신한은행(조흥 2
 
4.2%
경기은행 2
 
4.2%
하나은행(보람 2
 
4.2%
평화은행 1
 
2.1%
Other values (19) 19
39.6%
2023-12-13T09:58:48.586367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
은 45
17.0%
행 45
17.0%
) 17
 
6.4%
( 17
 
6.4%
한 11
 
4.2%
업 9
 
3.4%
기 6
 
2.3%
나 6
 
2.3%
하 6
 
2.3%
산 6
 
2.3%
Other values (44) 96
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 227
86.0%
Close Punctuation 17
 
6.4%
Open Punctuation 17
 
6.4%
Uppercase Letter 3
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
은 45
19.8%
행 45
19.8%
한 11
 
4.8%
업 9
 
4.0%
기 6
 
2.6%
나 6
 
2.6%
하 6
 
2.6%
산 6
 
2.6%
우 6
 
2.6%
리 6
 
2.6%
Other values (39) 81
35.7%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
E 1
33.3%
K 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 227
86.0%
Common 34
 
12.9%
Latin 3
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
은 45
19.8%
행 45
19.8%
한 11
 
4.8%
업 9
 
4.0%
기 6
 
2.6%
나 6
 
2.6%
하 6
 
2.6%
산 6
 
2.6%
우 6
 
2.6%
리 6
 
2.6%
Other values (39) 81
35.7%
Latin
ValueCountFrequency (%)
B 1
33.3%
E 1
33.3%
K 1
33.3%
Common
ValueCountFrequency (%)
) 17
50.0%
( 17
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 227
86.0%
ASCII 37
 
14.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
은 45
19.8%
행 45
19.8%
한 11
 
4.8%
업 9
 
4.0%
기 6
 
2.6%
나 6
 
2.6%
하 6
 
2.6%
산 6
 
2.6%
우 6
 
2.6%
리 6
 
2.6%
Other values (39) 81
35.7%
ASCII
ValueCountFrequency (%)
) 17
45.9%
( 17
45.9%
B 1
 
2.7%
E 1
 
2.7%
K 1
 
2.7%

통화코드
Categorical

Distinct11
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Memory size516.0 B
달러 (미국)
29 
엔 (일본)
7 
마르크 (독일)
 
2
달러 (홍콩)
 
2
파운드 (영국)
 
2
Other values (6)
6 

Length

Max length10
Median length7
Mean length7.1666667
Min length6

Unique

Unique6 ?
Unique (%)12.5%

Sample

1st row달러 (미국)
2nd row마르크 (독일)
3rd row프랑 (스위스)
4th row길더 (네덜란드)
5th row엔 (일본)

Common Values

ValueCountFrequency (%)
달러 (미국) 29
60.4%
엔 (일본) 7
 
14.6%
마르크 (독일) 2
 
4.2%
달러 (홍콩) 2
 
4.2%
파운드 (영국) 2
 
4.2%
프랑 (스위스) 1
 
2.1%
길더 (네덜란드) 1
 
2.1%
프랑 (프랑스) 1
 
2.1%
달러 (캐나다) 1
 
2.1%
루피아(인도네시아) 1
 
2.1%

Length

2023-12-13T09:58:48.699326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
달러 32
33.7%
미국 29
30.5%
엔 7
 
7.4%
일본 7
 
7.4%
파운드 2
 
2.1%
영국 2
 
2.1%
프랑 2
 
2.1%
홍콩 2
 
2.1%
독일 2
 
2.1%
마르크 2
 
2.1%
Other values (8) 8
 
8.4%

매입차주건수
Real number (ℝ)

Distinct22
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.416667
Minimum1
Maximum204
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T09:58:48.787072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q322.25
95-th percentile156.35
Maximum204
Range203
Interquartile range (IQR)20.25

Descriptive statistics

Standard deviation47.529983
Coefficient of variation (CV)1.8700321
Kurtosis7.2962531
Mean25.416667
Median Absolute Deviation (MAD)4
Skewness2.7929367
Sum1220
Variance2259.0993
MonotonicityNot monotonic
2023-12-13T09:58:48.881065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 10
20.8%
2 7
14.6%
3 3
 
6.2%
29 3
 
6.2%
4 3
 
6.2%
15 2
 
4.2%
16 2
 
4.2%
51 2
 
4.2%
5 2
 
4.2%
20 2
 
4.2%
Other values (12) 12
25.0%
ValueCountFrequency (%)
1 10
20.8%
2 7
14.6%
3 3
 
6.2%
4 3
 
6.2%
5 2
 
4.2%
7 1
 
2.1%
8 1
 
2.1%
9 1
 
2.1%
11 1
 
2.1%
15 2
 
4.2%
ValueCountFrequency (%)
204 1
 
2.1%
181 1
 
2.1%
177 1
 
2.1%
118 1
 
2.1%
67 1
 
2.1%
51 2
4.2%
38 1
 
2.1%
37 1
 
2.1%
29 3
6.2%
20 2
4.2%

Interactions

2023-12-13T09:58:48.024657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:58:48.945971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
금융기관통화코드매입차주건수
금융기관1.0000.0000.000
통화코드0.0001.0000.000
매입차주건수0.0000.0001.000
2023-12-13T09:58:49.013968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
매입차주건수통화코드
매입차주건수1.0000.000
통화코드0.0001.000

Missing values

2023-12-13T09:58:48.133075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:58:48.192106image/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

금융기관통화코드매입차주건수
0산업은행달러 (미국)177
1산업은행마르크 (독일)2
2산업은행프랑 (스위스)2
3산업은행길더 (네덜란드)1
4산업은행엔 (일본)38
5하나(외환)은행달러 (미국)118
6하나(외환)은행프랑 (프랑스)1
7하나(외환)은행엔 (일본)3
8기업은행달러 (미국)204
9기업은행달러 (캐나다)1
금융기관통화코드매입차주건수
38동남은행달러 (미국)29
39동화은행달러 (미국)16
40대동은행달러 (미국)29
41하나은행(보람)달러 (미국)11
42하나은행(보람)실링 (오스트리아)1
43평화은행달러 (미국)20
44KEB하나은행달러 (미국)2
45농협중앙달러 (미국)4
46수협중앙회달러 (미국)3
47축협중앙달러 (미국)1