Overview

Dataset statistics

Number of variables4
Number of observations140
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory33.9 B

Variable types

Text1
DateTime1
Boolean1
Numeric1

Dataset

Description근로복지공단이 보유하고 있는 종합정보분석시스템DB자료 중 퇴직연금사업장 관련 운영현황입니다.
Author근로복지공단
URLhttps://www.data.go.kr/data/15051515/fileData.do

Alerts

자산관리기관코드_적재일시 has constant value ""Constant
자산관리기관코드_사용여부 has constant value ""Constant
자산관리기관코드_자산관리기관코드 has unique valuesUnique
자산관리기관코드_정렬순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:43:45.791302
Analysis finished2023-12-12 21:43:46.277089
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자산관리기관코드_자산관리기관코드
Text

UNIQUE 

Distinct140
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T06:43:46.636813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.9642857
Min length1

Characters and Unicode

Total characters555
Distinct characters20
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

Unique140 ?
Unique (%)100.0%

Sample

1st row*
2nd row없음
3rd rowB001
4th rowB002
5th rowB003
ValueCountFrequency (%)
1
 
0.7%
s017 1
 
0.7%
s036 1
 
0.7%
s035 1
 
0.7%
s034 1
 
0.7%
s033 1
 
0.7%
s031 1
 
0.7%
s030 1
 
0.7%
s029 1
 
0.7%
s016 1
 
0.7%
Other values (130) 130
92.9%
2023-12-13T06:43:47.122376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 131
23.6%
S 66
11.9%
3 39
 
7.0%
2 39
 
7.0%
1 38
 
6.8%
I 37
 
6.7%
8 28
 
5.0%
B 27
 
4.9%
5 27
 
4.9%
4 25
 
4.5%
Other values (10) 98
17.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 377
67.9%
Uppercase Letter 175
31.5%
Other Letter 2
 
0.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 131
34.7%
3 39
 
10.3%
2 39
 
10.3%
1 38
 
10.1%
8 28
 
7.4%
5 27
 
7.2%
4 25
 
6.6%
7 21
 
5.6%
6 17
 
4.5%
9 12
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
S 66
37.7%
I 37
21.1%
B 27
15.4%
L 22
 
12.6%
N 15
 
8.6%
J 6
 
3.4%
R 2
 
1.1%
Other Letter
ValueCountFrequency (%)
없 1
50.0%
음 1
50.0%
Other Punctuation
ValueCountFrequency (%)
* 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 378
68.1%
Latin 175
31.5%
Hangul 2
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 131
34.7%
3 39
 
10.3%
2 39
 
10.3%
1 38
 
10.1%
8 28
 
7.4%
5 27
 
7.1%
4 25
 
6.6%
7 21
 
5.6%
6 17
 
4.5%
9 12
 
3.2%
Latin
ValueCountFrequency (%)
S 66
37.7%
I 37
21.1%
B 27
15.4%
L 22
 
12.6%
N 15
 
8.6%
J 6
 
3.4%
R 2
 
1.1%
Hangul
ValueCountFrequency (%)
없 1
50.0%
음 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 553
99.6%
Hangul 2
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 131
23.7%
S 66
11.9%
3 39
 
7.1%
2 39
 
7.1%
1 38
 
6.9%
I 37
 
6.7%
8 28
 
5.1%
B 27
 
4.9%
5 27
 
4.9%
4 25
 
4.5%
Other values (8) 96
17.4%
Hangul
ValueCountFrequency (%)
없 1
50.0%
음 1
50.0%

자산관리기관코드_적재일시
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2019-09-09 20:50:07
Maximum2019-09-09 20:50:07
2023-12-13T06:43:47.223503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:43:47.296163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

자산관리기관코드_사용여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size272.0 B
True
140 
ValueCountFrequency (%)
True 140
100.0%
2023-12-13T06:43:47.373614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

자산관리기관코드_정렬순번
Real number (ℝ)

UNIQUE 

Distinct140
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14285783
Minimum1
Maximum1 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T06:43:47.466382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.95
Q135.75
median70.5
Q3105.25
95-th percentile133.05
Maximum1 × 109
Range1 × 109
Interquartile range (IQR)69.5

Descriptive statistics

Standard deviation1.1909214 × 108
Coefficient of variation (CV)8.3364097
Kurtosis67.441714
Mean14285783
Median Absolute Deviation (MAD)35
Skewness8.2751657
Sum2.0000096 × 109
Variance1.4182937 × 1016
MonotonicityNot monotonic
2023-12-13T06:43:47.609310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
999999998 1
 
0.7%
90 1
 
0.7%
84 1
 
0.7%
85 1
 
0.7%
86 1
 
0.7%
87 1
 
0.7%
88 1
 
0.7%
89 1
 
0.7%
91 1
 
0.7%
82 1
 
0.7%
Other values (130) 130
92.9%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
999999999 1
0.7%
999999998 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%
131 1
0.7%

Interactions

2023-12-13T06:43:45.891658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T06:43:46.074278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:43:46.218619image/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

자산관리기관코드_자산관리기관코드자산관리기관코드_적재일시자산관리기관코드_사용여부자산관리기관코드_정렬순번
0*2019-09-09 20:50:07Y999999998
1없음2019-09-09 20:50:07Y999999999
2B0012019-09-09 20:50:07Y3
3B0022019-09-09 20:50:07Y4
4B0032019-09-09 20:50:07Y5
5B0042019-09-09 20:50:07Y6
6B0052019-09-09 20:50:07Y7
7B0062019-09-09 20:50:07Y8
8B0072019-09-09 20:50:07Y9
9B0112019-09-09 20:50:07Y10
자산관리기관코드_자산관리기관코드자산관리기관코드_적재일시자산관리기관코드_사용여부자산관리기관코드_정렬순번
130S8192019-09-09 20:50:07Y123
131S8202019-09-09 20:50:07Y124
132S8222019-09-09 20:50:07Y125
133S8252019-09-09 20:50:07Y126
134S8262019-09-09 20:50:07Y127
135S8272019-09-09 20:50:07Y128
136S8282019-09-09 20:50:07Y129
137S8292019-09-09 20:50:07Y130
138S8312019-09-09 20:50:07Y131
139S8322019-09-09 20:50:07Y132