Overview

Dataset statistics

Number of variables4
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory36.8 B

Variable types

Numeric2
Text1
Categorical1

Dataset

Description공무원연금 연령별 가입자 현황 통계 자료입니다. (1세 단위로 구분되어 있으며 18세 이하 및 65세 이상은 일괄로 표시합니다.)
URLhttps://www.data.go.kr/data/15095355/fileData.do

Alerts

기준일 has constant value ""Constant
순번 has unique valuesUnique
구분 has unique valuesUnique
인원수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:51:41.598569
Analysis finished2023-12-12 05:51:42.226956
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.5
Minimum1
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T14:51:42.304336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.35
Q112.75
median24.5
Q336.25
95-th percentile45.65
Maximum48
Range47
Interquartile range (IQR)23.5

Descriptive statistics

Standard deviation14
Coefficient of variation (CV)0.57142857
Kurtosis-1.2
Mean24.5
Median Absolute Deviation (MAD)12
Skewness0
Sum1176
Variance196
MonotonicityStrictly increasing
2023-12-12T14:51:42.453000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
1 1
 
2.1%
26 1
 
2.1%
28 1
 
2.1%
29 1
 
2.1%
30 1
 
2.1%
31 1
 
2.1%
32 1
 
2.1%
33 1
 
2.1%
34 1
 
2.1%
35 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
1 1
2.1%
2 1
2.1%
3 1
2.1%
4 1
2.1%
5 1
2.1%
6 1
2.1%
7 1
2.1%
8 1
2.1%
9 1
2.1%
10 1
2.1%
ValueCountFrequency (%)
48 1
2.1%
47 1
2.1%
46 1
2.1%
45 1
2.1%
44 1
2.1%
43 1
2.1%
42 1
2.1%
41 1
2.1%
40 1
2.1%
39 1
2.1%

구분
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-12T14:51:42.716229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.125
Min length3

Characters and Unicode

Total characters150
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)100.0%

Sample

1st row18세 이상
2nd row19세
3rd row20세
4th row21세
5th row22세
ValueCountFrequency (%)
이상 2
 
4.0%
52세 1
 
2.0%
43세 1
 
2.0%
53세 1
 
2.0%
44세 1
 
2.0%
45세 1
 
2.0%
46세 1
 
2.0%
47세 1
 
2.0%
48세 1
 
2.0%
49세 1
 
2.0%
Other values (39) 39
78.0%
2023-12-12T14:51:43.142494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 48
32.0%
2 15
 
10.0%
3 15
 
10.0%
4 15
 
10.0%
5 15
 
10.0%
6 10
 
6.7%
1 7
 
4.7%
8 5
 
3.3%
9 5
 
3.3%
0 5
 
3.3%
Other values (4) 10
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96
64.0%
Other Letter 52
34.7%
Space Separator 2
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
15.6%
3 15
15.6%
4 15
15.6%
5 15
15.6%
6 10
10.4%
1 7
7.3%
8 5
 
5.2%
9 5
 
5.2%
0 5
 
5.2%
7 4
 
4.2%
Other Letter
ValueCountFrequency (%)
세 48
92.3%
이 2
 
3.8%
상 2
 
3.8%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98
65.3%
Hangul 52
34.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
15.3%
3 15
15.3%
4 15
15.3%
5 15
15.3%
6 10
10.2%
1 7
7.1%
8 5
 
5.1%
9 5
 
5.1%
0 5
 
5.1%
7 4
 
4.1%
Hangul
ValueCountFrequency (%)
세 48
92.3%
이 2
 
3.8%
상 2
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 98
65.3%
Hangul 52
34.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 48
92.3%
이 2
 
3.8%
상 2
 
3.8%
ASCII
ValueCountFrequency (%)
2 15
15.3%
3 15
15.3%
4 15
15.3%
5 15
15.3%
6 10
10.2%
1 7
7.1%
8 5
 
5.1%
9 5
 
5.1%
0 5
 
5.1%
7 4
 
4.1%

인원수
Real number (ℝ)

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26687.375
Minimum15
Maximum44190
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T14:51:43.333713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile738.45
Q111739.75
median34799.5
Q337867.5
95-th percentile43060.9
Maximum44190
Range44175
Interquartile range (IQR)26127.75

Descriptive statistics

Standard deviation15536.131
Coefficient of variation (CV)0.58215285
Kurtosis-1.0632425
Mean26687.375
Median Absolute Deviation (MAD)5758.5
Skewness-0.77326555
Sum1280994
Variance2.4137138 × 108
MonotonicityNot monotonic
2023-12-12T14:51:43.520835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
15 1
 
2.1%
43063 1
 
2.1%
38190 1
 
2.1%
36196 1
 
2.1%
35247 1
 
2.1%
38289 1
 
2.1%
38458 1
 
2.1%
37481 1
 
2.1%
39132 1
 
2.1%
37760 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
15 1
2.1%
528 1
2.1%
652 1
2.1%
899 1
2.1%
1005 1
2.1%
1079 1
2.1%
1301 1
2.1%
1645 1
2.1%
2288 1
2.1%
4647 1
2.1%
ValueCountFrequency (%)
44190 1
2.1%
43953 1
2.1%
43063 1
2.1%
43057 1
2.1%
42465 1
2.1%
41606 1
2.1%
39132 1
2.1%
38458 1
2.1%
38368 1
2.1%
38359 1
2.1%

기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
2022-12-31
48 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-31
2nd row2022-12-31
3rd row2022-12-31
4th row2022-12-31
5th row2022-12-31

Common Values

ValueCountFrequency (%)
2022-12-31 48
100.0%

Length

2023-12-12T14:51:43.690731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:51:43.797159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-31 48
100.0%

Interactions

2023-12-12T14:51:41.905564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:51:41.707118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:51:41.992582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:51:41.810931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:51:43.872605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번구분인원수
순번1.0001.0000.790
구분1.0001.0001.000
인원수0.7901.0001.000
2023-12-12T14:51:43.987514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번인원수
순번1.0000.058
인원수0.0581.000

Missing values

2023-12-12T14:51:42.105347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:51:42.194906image/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

순번구분인원수기준일
0118세 이상152022-12-31
1219세5282022-12-31
2320세6522022-12-31
3421세8992022-12-31
4522세16452022-12-31
5623세46472022-12-31
6724세98552022-12-31
7825세167692022-12-31
8926세232072022-12-31
91027세296262022-12-31
순번구분인원수기준일
383956세294812022-12-31
394057세286012022-12-31
404158세254412022-12-31
414259세214672022-12-31
424360세123682022-12-31
434461세57932022-12-31
444562세22882022-12-31
454663세10792022-12-31
464764세10052022-12-31
474865세 이상13012022-12-31