Overview

Dataset statistics

Number of variables10
Number of observations63
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory88.1 B

Variable types

Text2
Numeric3
Categorical5

Dataset

Description근로복지공단 지역별 퇴직연금 업무 담당 현황 데이터입니다.(2023.7.17.기준) - 소속기관, 관할지역, 담당자 전화번호, 업무내용
URLhttps://www.data.go.kr/data/15051511/fileData.do

Alerts

교육컨텐츠_과정명 has constant value ""Constant
직원관리_업무 has constant value ""Constant
직원관리_지역번호 has constant value ""Constant
직원관리_전화번호1 has constant value ""Constant
직원관리_전화번호2 has constant value ""Constant
소속기관_관할지역 has unique valuesUnique
소속기관_소속기관 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:23:33.757503
Analysis finished2023-12-12 09:23:37.687165
Duration3.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

소속기관_관할지역
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-12T18:23:37.905578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length24
Mean length14.031746
Min length3

Characters and Unicode

Total characters884
Distinct characters142
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

Unique63 ?
Unique (%)100.0%

Sample

1st row강릉시,속초시,동해시,양양군,고성군
2nd row원주시,횡성군
3rd row경산시,영천시,청도군
4th row인천중구,동구,미추홀구,연수구,남동구,옹진군
5th row고양시
ValueCountFrequency (%)
강릉시,속초시,동해시,양양군,고성군 1
 
1.4%
양산시 1
 
1.4%
울산광역시 1
 
1.4%
용인시,여주시,이천시 1
 
1.4%
영주시,상주시,문경시,봉화군 1
 
1.4%
영월군,평창군,정선군 1
 
1.4%
여수시,광양시 1
 
1.4%
밀양시 1
 
1.4%
광명시,안양시,과천시,의왕시,군포시 1
 
1.4%
성동구 1
 
1.4%
Other values (60) 60
85.7%
2023-12-12T18:23:38.370672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 162
18.3%
군 84
 
9.5%
시 78
 
8.8%
구 74
 
8.4%
천 24
 
2.7%
주 21
 
2.4%
산 21
 
2.4%
성 18
 
2.0%
양 18
 
2.0%
서 17
 
1.9%
Other values (132) 367
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 715
80.9%
Other Punctuation 162
 
18.3%
Space Separator 7
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 84
 
11.7%
시 78
 
10.9%
구 74
 
10.3%
천 24
 
3.4%
주 21
 
2.9%
산 21
 
2.9%
성 18
 
2.5%
양 18
 
2.5%
서 17
 
2.4%
동 16
 
2.2%
Other values (130) 344
48.1%
Other Punctuation
ValueCountFrequency (%)
, 162
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 715
80.9%
Common 169
 
19.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 84
 
11.7%
시 78
 
10.9%
구 74
 
10.3%
천 24
 
3.4%
주 21
 
2.9%
산 21
 
2.9%
성 18
 
2.5%
양 18
 
2.5%
서 17
 
2.4%
동 16
 
2.2%
Other values (130) 344
48.1%
Common
ValueCountFrequency (%)
, 162
95.9%
7
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 715
80.9%
ASCII 169
 
19.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 162
95.9%
7
 
4.1%
Hangul
ValueCountFrequency (%)
군 84
 
11.7%
시 78
 
10.9%
구 74
 
10.3%
천 24
 
3.4%
주 21
 
2.9%
산 21
 
2.9%
성 18
 
2.5%
양 18
 
2.5%
서 17
 
2.4%
동 16
 
2.2%
Other values (130) 344
48.1%

소속기관_소속기관
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-12T18:23:38.681272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.7619048
Min length4

Characters and Unicode

Total characters300
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)100.0%

Sample

1st row강릉지사
2nd row강원지역본부
3rd row경산지사
4th row경인지역본부
5th row고양지사
ValueCountFrequency (%)
강릉지사 1
 
1.6%
서울성동지사 1
 
1.6%
성남지사 1
 
1.6%
수원지사 1
 
1.6%
순천지사 1
 
1.6%
안동지사 1
 
1.6%
안산지사 1
 
1.6%
안양지사 1
 
1.6%
양산지사 1
 
1.6%
여수지사 1
 
1.6%
Other values (53) 53
84.1%
2023-12-12T18:23:39.221962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 63
21.0%
사 56
18.7%
부 25
 
8.3%
서 14
 
4.7%
산 12
 
4.0%
울 10
 
3.3%
주 9
 
3.0%
역 7
 
2.3%
본 7
 
2.3%
대 6
 
2.0%
Other values (51) 91
30.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 300
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 63
21.0%
사 56
18.7%
부 25
 
8.3%
서 14
 
4.7%
산 12
 
4.0%
울 10
 
3.3%
주 9
 
3.0%
역 7
 
2.3%
본 7
 
2.3%
대 6
 
2.0%
Other values (51) 91
30.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 300
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 63
21.0%
사 56
18.7%
부 25
 
8.3%
서 14
 
4.7%
산 12
 
4.0%
울 10
 
3.3%
주 9
 
3.0%
역 7
 
2.3%
본 7
 
2.3%
대 6
 
2.0%
Other values (51) 91
30.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 300
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 63
21.0%
사 56
18.7%
부 25
 
8.3%
서 14
 
4.7%
산 12
 
4.0%
울 10
 
3.3%
주 9
 
3.0%
역 7
 
2.3%
본 7
 
2.3%
대 6
 
2.0%
Other values (51) 91
30.3%

소속기관_지사전화지역번호
Real number (ℝ)

Distinct16
Distinct (%)25.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.269841
Minimum2
Maximum64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T18:23:39.366596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q131
median42
Q354
95-th percentile62.9
Maximum64
Range62
Interquartile range (IQR)23

Descriptive statistics

Standard deviation18.833058
Coefficient of variation (CV)0.4795807
Kurtosis-0.22713735
Mean39.269841
Median Absolute Deviation (MAD)11
Skewness-0.78241552
Sum2474
Variance354.68408
MonotonicityNot monotonic
2023-12-12T18:23:39.483851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
31 11
17.5%
2 9
14.3%
33 5
7.9%
55 5
7.9%
51 4
 
6.3%
54 4
 
6.3%
53 4
 
6.3%
61 3
 
4.8%
41 3
 
4.8%
42 3
 
4.8%
Other values (6) 12
19.0%
ValueCountFrequency (%)
2 9
14.3%
31 11
17.5%
32 3
 
4.8%
33 5
7.9%
41 3
 
4.8%
42 3
 
4.8%
43 2
 
3.2%
51 4
 
6.3%
52 1
 
1.6%
53 4
 
6.3%
ValueCountFrequency (%)
64 1
 
1.6%
63 3
4.8%
62 2
 
3.2%
61 3
4.8%
55 5
7.9%
54 4
6.3%
53 4
6.3%
52 1
 
1.6%
51 4
6.3%
43 2
 
3.2%

소속기관_지사전화앞자리
Real number (ℝ)

Distinct57
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean874.69841
Minimum226
Maximum6250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T18:23:39.641653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum226
5-th percentile240
Q1471
median640
Q3824
95-th percentile2223.5
Maximum6250
Range6024
Interquartile range (IQR)353

Descriptive statistics

Standard deviation944.94741
Coefficient of variation (CV)1.0803122
Kurtosis17.678535
Mean874.69841
Median Absolute Deviation (MAD)180
Skewness3.8342855
Sum55106
Variance892925.6
MonotonicityNot monotonic
2023-12-12T18:23:39.786163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
240 3
 
4.8%
640 2
 
3.2%
608 2
 
3.2%
550 2
 
3.2%
547 2
 
3.2%
720 1
 
1.6%
231 1
 
1.6%
805 1
 
1.6%
850 1
 
1.6%
481 1
 
1.6%
Other values (47) 47
74.6%
ValueCountFrequency (%)
226 1
 
1.6%
229 1
 
1.6%
231 1
 
1.6%
240 3
4.8%
268 1
 
1.6%
288 1
 
1.6%
320 1
 
1.6%
371 1
 
1.6%
380 1
 
1.6%
419 1
 
1.6%
ValueCountFrequency (%)
6250 1
1.6%
3459 1
1.6%
3433 1
1.6%
2230 1
1.6%
2165 1
1.6%
2109 1
1.6%
2077 1
1.6%
944 1
1.6%
939 1
1.6%
934 1
1.6%

소속기관_지사전화뒷자리
Real number (ℝ)

Distinct61
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4131.7143
Minimum109
Maximum9712
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T18:23:39.963953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum109
5-th percentile142.3
Q1750
median4164
Q37057.5
95-th percentile9175.5
Maximum9712
Range9603
Interquartile range (IQR)6307.5

Descriptive statistics

Standard deviation3141.8192
Coefficient of variation (CV)0.76041541
Kurtosis-1.2983021
Mean4131.7143
Median Absolute Deviation (MAD)2967
Skewness0.18005633
Sum260298
Variance9871027.9
MonotonicityNot monotonic
2023-12-12T18:23:40.182451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4112 2
 
3.2%
154 2
 
3.2%
9108 1
 
1.6%
1683 1
 
1.6%
4204 1
 
1.6%
204 1
 
1.6%
5415 1
 
1.6%
573 1
 
1.6%
8465 1
 
1.6%
6120 1
 
1.6%
Other values (51) 51
81.0%
ValueCountFrequency (%)
109 1
1.6%
123 1
1.6%
131 1
1.6%
141 1
1.6%
154 2
3.2%
168 1
1.6%
187 1
1.6%
204 1
1.6%
350 1
1.6%
365 1
1.6%
ValueCountFrequency (%)
9712 1
1.6%
9476 1
1.6%
9246 1
1.6%
9183 1
1.6%
9108 1
1.6%
8661 1
1.6%
8465 1
1.6%
8132 1
1.6%
8119 1
1.6%
8117 1
1.6%

교육컨텐츠_과정명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
가입자별 법정교육 등
63 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가입자별 법정교육 등
2nd row가입자별 법정교육 등
3rd row가입자별 법정교육 등
4th row가입자별 법정교육 등
5th row가입자별 법정교육 등

Common Values

ValueCountFrequency (%)
가입자별 법정교육 등 63
100.0%

Length

2023-12-12T18:23:40.360170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:23:40.462754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가입자별 63
33.3%
법정교육 63
33.3%
등 63
33.3%

직원관리_업무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
가입(계약체결) 및 부담금 산정 등
63 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가입(계약체결) 및 부담금 산정 등
2nd row가입(계약체결) 및 부담금 산정 등
3rd row가입(계약체결) 및 부담금 산정 등
4th row가입(계약체결) 및 부담금 산정 등
5th row가입(계약체결) 및 부담금 산정 등

Common Values

ValueCountFrequency (%)
가입(계약체결) 및 부담금 산정 등 63
100.0%

Length

2023-12-12T18:23:40.589406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:23:40.728085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가입(계약체결 63
20.0%
및 63
20.0%
부담금 63
20.0%
산정 63
20.0%
등 63
20.0%

직원관리_지역번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
52
63 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row52
2nd row52
3rd row52
4th row52
5th row52

Common Values

ValueCountFrequency (%)
52 63
100.0%

Length

2023-12-12T18:23:40.862581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:23:40.976865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
52 63
100.0%

직원관리_전화번호1
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
704
63 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row704
2nd row704
3rd row704
4th row704
5th row704

Common Values

ValueCountFrequency (%)
704 63
100.0%

Length

2023-12-12T18:23:41.088362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:23:41.199191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
704 63
100.0%

직원관리_전화번호2
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
7371
63 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7371
2nd row7371
3rd row7371
4th row7371
5th row7371

Common Values

ValueCountFrequency (%)
7371 63
100.0%

Length

2023-12-12T18:23:41.314461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:23:41.436105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7371 63
100.0%

Interactions

2023-12-12T18:23:37.100792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:36.386283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:36.765072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:37.206602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:36.536093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:36.887937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:37.304171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:36.645995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:36.998706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:23:41.516437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소속기관_관할지역소속기관_소속기관소속기관_지사전화지역번호소속기관_지사전화앞자리소속기관_지사전화뒷자리
소속기관_관할지역1.0001.0001.0001.0001.000
소속기관_소속기관1.0001.0001.0001.0001.000
소속기관_지사전화지역번호1.0001.0001.0000.5110.260
소속기관_지사전화앞자리1.0001.0000.5111.0000.311
소속기관_지사전화뒷자리1.0001.0000.2600.3111.000
2023-12-12T18:23:41.647153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소속기관_지사전화지역번호소속기관_지사전화앞자리소속기관_지사전화뒷자리
소속기관_지사전화지역번호1.000-0.326-0.183
소속기관_지사전화앞자리-0.3261.000-0.106
소속기관_지사전화뒷자리-0.183-0.1061.000

Missing values

2023-12-12T18:23:37.431044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:23:37.604378image/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

소속기관_관할지역소속기관_소속기관소속기관_지사전화지역번호소속기관_지사전화앞자리소속기관_지사전화뒷자리교육컨텐츠_과정명직원관리_업무직원관리_지역번호직원관리_전화번호1직원관리_전화번호2
0강릉시,속초시,동해시,양양군,고성군강릉지사336409108가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
1원주시,횡성군강원지역본부337492378가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
2경산시,영천시,청도군경산지사538192114가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
3인천중구,동구,미추홀구,연수구,남동구,옹진군경인지역본부324519712가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
4고양시고양지사31931919가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
5광주광산구,나주시,장성군,영광군,함평군광산지사62608414가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
6광주동구,서구,남구,북구,화순군,곡성군,구례군,담양군광주지역본부62608385가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
7구미시,김천시,구미국가산업단지구미지사544799183가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
8군산시,부안군,고창군군산지사63450141가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
9김해시김해지사557238011가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
소속기관_관할지역소속기관_소속기관소속기관_지사전화지역번호소속기관_지사전화앞자리소속기관_지사전화뒷자리교육컨텐츠_과정명직원관리_업무직원관리_지역번호직원관리_전화번호1직원관리_전화번호2
53춘천시,홍천군,인제군,화천군,양구군,가평군춘천지사332406165가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
54충주시,제천시,음성군,단양군충주지사43840365가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
55태백시,삼척시태백지사33550581가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
56통영시,거제시,고성군통영지사556407110가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
57평택시,오산시,안성시평택지사316698661가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
58포항시,경주시,영덕군,울릉군,울진군포항지사542885207가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
59화성시화성지사315474706가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
60제주특별자치도제주지사647546773가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
61진주시,사천시,합천군,거창군,산청군,하동군,함양군,남해군진주지사55760154가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371
62유성구,세종특별자치시,공주시,논산시,계룡시대전서부지사428205447가입자별 법정교육 등가입(계약체결) 및 부담금 산정 등527047371