Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory576.2 KiB
Average record size in memory59.0 B

Variable types

Categorical3
Numeric2
Text1

Dataset

Description데이터 제공요청의 따른 공무원연금공단의 직종별 성별 연령별 공무상요양 통원치료 현황에 대한 데이터 입니다.통원치료 일수 등이 포함됩니다.
Author공무원연금공단
URLhttps://www.data.go.kr/data/15124243/fileData.do

Reproduction

Analysis started2023-12-12 08:41:03.076862
Analysis finished2023-12-12 08:41:04.349556
Duration1.27 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

접수연도
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2019
2658 
2020
2440 
2018
1832 
2016
1565 
2017
1505 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2018
3rd row2016
4th row2016
5th row2018

Common Values

ValueCountFrequency (%)
2019 2658
26.6%
2020 2440
24.4%
2018 1832
18.3%
2016 1565
15.7%
2017 1505
15.0%

Length

2023-12-12T17:41:04.434249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:41:04.609084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 2658
26.6%
2020 2440
24.4%
2018 1832
18.3%
2016 1565
15.7%
2017 1505
15.0%

직종
Categorical

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경찰
2716 
일반직
1972 
교육직
1791 
소방직
1375 
우정직
878 
Other values (20)
1268 

Length

Max length10
Median length3
Mean length2.752
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반직
2nd row교육직
3rd row군무원
4th row경찰
5th row경찰

Common Values

ValueCountFrequency (%)
경찰 2716
27.2%
일반직 1972
19.7%
교육직 1791
17.9%
소방직 1375
13.8%
우정직 878
 
8.8%
공안 367
 
3.7%
군무원 305
 
3.0%
청원경찰 107
 
1.1%
임기제 85
 
0.9%
기타직 82
 
0.8%
Other values (15) 322
 
3.2%

Length

2023-12-12T17:41:04.796194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경찰 2716
26.9%
일반직 1972
19.6%
교육직 1791
17.8%
소방직 1375
13.6%
우정직 878
 
8.7%
공안 367
 
3.6%
군무원 305
 
3.0%
청원경찰 107
 
1.1%
임기제 85
 
0.8%
기타직 82
 
0.8%
Other values (17) 407
 
4.0%

성별
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남
7275 
여
2725 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남
2nd row여
3rd row여
4th row남
5th row남

Common Values

ValueCountFrequency (%)
남 7275
72.8%
여 2725
 
27.3%

Length

2023-12-12T17:41:04.997536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:41:05.111457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 7275
72.8%
여 2725
 
27.3%

연령(상병당시기준)
Real number (ℝ)

Distinct51
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.2478
Minimum20
Maximum73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:41:05.249522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile27
Q134
median42
Q350
95-th percentile58
Maximum73
Range53
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.7395319
Coefficient of variation (CV)0.23053347
Kurtosis-1.0114496
Mean42.2478
Median Absolute Deviation (MAD)8
Skewness-0.004630748
Sum422478
Variance94.858481
MonotonicityNot monotonic
2023-12-12T17:41:05.428277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48 358
 
3.6%
45 333
 
3.3%
51 331
 
3.3%
44 328
 
3.3%
39 328
 
3.3%
50 322
 
3.2%
46 316
 
3.2%
40 312
 
3.1%
42 312
 
3.1%
43 311
 
3.1%
Other values (41) 6749
67.5%
ValueCountFrequency (%)
20 5
 
0.1%
21 2
 
< 0.1%
22 7
 
0.1%
23 30
 
0.3%
24 69
 
0.7%
25 131
1.3%
26 187
1.9%
27 230
2.3%
28 241
2.4%
29 263
2.6%
ValueCountFrequency (%)
73 1
 
< 0.1%
72 1
 
< 0.1%
71 2
 
< 0.1%
68 2
 
< 0.1%
66 2
 
< 0.1%
65 1
 
< 0.1%
64 3
 
< 0.1%
63 1
 
< 0.1%
62 21
0.2%
61 26
0.3%

통원치료일수
Text

Distinct427
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T17:41:05.959774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.226
Min length1

Characters and Unicode

Total characters22260
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)1.5%

Sample

1st row43
2nd row180
3rd row325
4th row60
5th row69
ValueCountFrequency (%)
60 806
 
8.1%
180 628
 
6.3%
90 466
 
4.7%
14 398
 
4.0%
15 268
 
2.7%
21 265
 
2.6%
입원대상자 234
 
2.3%
30 208
 
2.1%
42 199
 
2.0%
28 175
 
1.8%
Other values (417) 6353
63.5%
2023-12-12T17:41:06.641286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3965
17.8%
0 2975
13.4%
2 2429
10.9%
6 2129
9.6%
3 1880
8.4%
4 1798
8.1%
8 1795
8.1%
5 1468
 
6.6%
9 1465
 
6.6%
7 1186
 
5.3%
Other values (5) 1170
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21090
94.7%
Other Letter 1170
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3965
18.8%
0 2975
14.1%
2 2429
11.5%
6 2129
10.1%
3 1880
8.9%
4 1798
8.5%
8 1795
8.5%
5 1468
 
7.0%
9 1465
 
6.9%
7 1186
 
5.6%
Other Letter
ValueCountFrequency (%)
입 234
20.0%
원 234
20.0%
대 234
20.0%
상 234
20.0%
자 234
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21090
94.7%
Hangul 1170
 
5.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3965
18.8%
0 2975
14.1%
2 2429
11.5%
6 2129
10.1%
3 1880
8.9%
4 1798
8.5%
8 1795
8.5%
5 1468
 
7.0%
9 1465
 
6.9%
7 1186
 
5.6%
Hangul
ValueCountFrequency (%)
입 234
20.0%
원 234
20.0%
대 234
20.0%
상 234
20.0%
자 234
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21090
94.7%
Hangul 1170
 
5.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3965
18.8%
0 2975
14.1%
2 2429
11.5%
6 2129
10.1%
3 1880
8.9%
4 1798
8.5%
8 1795
8.5%
5 1468
 
7.0%
9 1465
 
6.9%
7 1186
 
5.6%
Hangul
ValueCountFrequency (%)
입 234
20.0%
원 234
20.0%
대 234
20.0%
상 234
20.0%
자 234
20.0%

승인건수
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5771
Minimum1
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:41:06.839293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile4
Maximum37
Range36
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.9987634
Coefficient of variation (CV)1.2673663
Kurtosis81.216444
Mean1.5771
Median Absolute Deviation (MAD)0
Skewness7.570595
Sum15771
Variance3.9950551
MonotonicityNot monotonic
2023-12-12T17:41:07.009720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 7944
79.4%
2 1041
 
10.4%
3 395
 
4.0%
4 199
 
2.0%
5 120
 
1.2%
8 56
 
0.6%
6 48
 
0.5%
7 48
 
0.5%
9 38
 
0.4%
11 21
 
0.2%
Other values (21) 90
 
0.9%
ValueCountFrequency (%)
1 7944
79.4%
2 1041
 
10.4%
3 395
 
4.0%
4 199
 
2.0%
5 120
 
1.2%
6 48
 
0.5%
7 48
 
0.5%
8 56
 
0.6%
9 38
 
0.4%
10 16
 
0.2%
ValueCountFrequency (%)
37 1
 
< 0.1%
33 1
 
< 0.1%
32 3
< 0.1%
31 1
 
< 0.1%
28 3
< 0.1%
27 3
< 0.1%
26 1
 
< 0.1%
25 2
< 0.1%
24 3
< 0.1%
23 1
 
< 0.1%

Interactions

2023-12-12T17:41:03.853172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:03.597606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:03.986814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:03.728876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:41:07.135056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
접수연도직종성별연령(상병당시기준)승인건수
접수연도1.0000.1560.0000.0650.179
직종0.1561.0000.5300.3540.000
성별0.0000.5301.0000.1130.075
연령(상병당시기준)0.0650.3540.1131.0000.000
승인건수0.1790.0000.0750.0001.000
2023-12-12T17:41:07.279870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
직종접수연도성별
직종1.0000.0680.460
접수연도0.0681.0000.000
성별0.4600.0001.000
2023-12-12T17:41:07.421684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령(상병당시기준)승인건수접수연도직종성별
연령(상병당시기준)1.0000.0110.0270.1320.087
승인건수0.0111.0000.0750.0000.057
접수연도0.0270.0751.0000.0680.000
직종0.1320.0000.0681.0000.460
성별0.0870.0570.0000.4601.000

Missing values

2023-12-12T17:41:04.157804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:41:04.281145image/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

접수연도직종성별연령(상병당시기준)통원치료일수승인건수
52952017일반직남38431
71222018교육직여251805
16902016군무원여473251
22016경찰남23602
62232018경찰남42691
24732016일반직남497303
22222016우정직남59601
170172020소방직여26151
41932017교육직여34311
24132016일반직남45281
접수연도직종성별연령(상병당시기준)통원치료일수승인건수
150692020경찰남54881
14672016교육직여48603
185512020지도직남49491
148492020경찰남48431
154112020공안남48751
74122018교육직여52681
88302018일반직여341803
8862016공안남321801
6242016경찰남50981
35392017경찰남52903