Overview

Dataset statistics

Number of variables7
Number of observations131
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.8 KiB
Average record size in memory61.0 B

Variable types

Numeric4
DateTime1
Categorical1
Text1

Dataset

Description한국에너지공단의 채용공고에 따른 채용 관련 데이터로 채용 공고명, 공고일, 채용연도, 채용전형, 채용규모, 지원지원, 경쟁률에 대한 데이터 개방
URLhttps://www.data.go.kr/data/15086119/fileData.do

Alerts

채용연도 is highly overall correlated with 공고명High correlation
채용규모 is highly overall correlated with 지원인원High correlation
지원인원 is highly overall correlated with 채용규모 and 1 other fieldsHigh correlation
경쟁률 is highly overall correlated with 지원인원High correlation
공고명 is highly overall correlated with 채용연도High correlation
채용규모 has 5 (3.8%) zerosZeros
지원인원 has 49 (37.4%) zerosZeros
경쟁률 has 49 (37.4%) zerosZeros

Reproduction

Analysis started2023-12-12 07:36:14.668534
Analysis finished2023-12-12 07:36:16.993679
Duration2.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

채용연도
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.1985
Minimum2016
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T16:36:17.054313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2016.5
Q12019
median2020
Q32022
95-th percentile2023
Maximum2023
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.0733468
Coefficient of variation (CV)0.0010263085
Kurtosis-1.0159686
Mean2020.1985
Median Absolute Deviation (MAD)2
Skewness-0.24870612
Sum264646
Variance4.2987669
MonotonicityIncreasing
2023-12-12T16:36:17.204174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2022 27
20.6%
2019 22
16.8%
2018 21
16.0%
2023 21
16.0%
2020 16
12.2%
2021 13
9.9%
2016 7
 
5.3%
2017 4
 
3.1%
ValueCountFrequency (%)
2016 7
 
5.3%
2017 4
 
3.1%
2018 21
16.0%
2019 22
16.8%
2020 16
12.2%
2021 13
9.9%
2022 27
20.6%
2023 21
16.0%
ValueCountFrequency (%)
2023 21
16.0%
2022 27
20.6%
2021 13
9.9%
2020 16
12.2%
2019 22
16.8%
2018 21
16.0%
2017 4
 
3.1%
2016 7
 
5.3%

공고일자
Date

Distinct46
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2016-05-17 00:00:00
Maximum2023-05-17 00:00:00
2023-12-12T16:36:17.377119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:17.518330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

공고명
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)35.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
한국에너지공단 청년인턴(체험형) 채용 공고
26 
한국에너지공단 신입직원 채용 공고
9 
2016년도 한국에너지공단 NCS기반 채용 공고
 
5
한국에너지공단 본사 공무직(비서, 경비, 미화, 시설관리(기계), 안내) 채용 공고
 
5
한국에너지공단 대전 에너지관 공무직(경비, 미화, 시설관리(기계/전기), 안내) 채용 공고
 
5
Other values (42)
81 

Length

Max length50
Median length40
Mean length30.748092
Min length18

Unique

Unique18 ?
Unique (%)13.7%

Sample

1st row2016년도 한국에너지공단 NCS기반 채용 공고
2nd row2016년도 한국에너지공단 NCS기반 채용 공고
3rd row2016년도 한국에너지공단 NCS기반 채용 공고
4th row2016년도 한국에너지공단 NCS기반 채용 공고
5th row2016년도 한국에너지공단 NCS기반 채용 공고

Common Values

ValueCountFrequency (%)
한국에너지공단 청년인턴(체험형) 채용 공고 26
19.8%
한국에너지공단 신입직원 채용 공고 9
 
6.9%
2016년도 한국에너지공단 NCS기반 채용 공고 5
 
3.8%
한국에너지공단 본사 공무직(비서, 경비, 미화, 시설관리(기계), 안내) 채용 공고 5
 
3.8%
한국에너지공단 대전 에너지관 공무직(경비, 미화, 시설관리(기계/전기), 안내) 채용 공고 5
 
3.8%
한국에너지공단 신입직원(전문경력직 및 채용형 인턴) 채용 공고 5
 
3.8%
한국에너지공단 신입(전문경력직 및 시간선택제) 및 채용형 청년인턴 채용 공고 5
 
3.8%
한국에너지공단 본사 공무직(미화) 채용 공고 4
 
3.1%
한국에너지공단 신입직원(채용형 인턴) 채용 공고 4
 
3.1%
한국에너지공단 자동차연비센터(진천) 공무직(시설관리(전기)) 채용 공고 3
 
2.3%
Other values (37) 60
45.8%

Length

2023-12-12T16:36:17.684592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한국에너지공단 131
18.1%
채용 131
18.1%
공고 121
16.8%
청년인턴(체험형 26
 
3.6%
및 23
 
3.2%
본사 19
 
2.6%
공무직(경비 19
 
2.6%
미화 17
 
2.4%
공무직(미화 15
 
2.1%
자동차연비센터(진천 14
 
1.9%
Other values (49) 206
28.5%

채용전형
Text

Distinct54
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T16:36:17.936288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length8.6793893
Min length2

Characters and Unicode

Total characters1137
Distinct characters92
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)31.3%

Sample

1st row전문직
2nd row시간선택제일자리
3rd row채용형 인턴(일반)
4th row채용형 인턴(장애)
5th row채용형 인턴(고졸)
ValueCountFrequency (%)
채용형 22
 
13.2%
미화 17
 
10.2%
시설관리(기계 14
 
8.4%
경비 11
 
6.6%
시설관리(전기 10
 
6.0%
인턴(일반 9
 
5.4%
안내 5
 
3.0%
인턴(장애 5
 
3.0%
인턴(고졸 4
 
2.4%
전문경력직 4
 
2.4%
Other values (53) 66
39.5%
2023-12-12T16:36:18.662120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 97
 
8.5%
( 97
 
8.5%
36
 
3.2%
기 33
 
2.9%
시 31
 
2.7%
사 30
 
2.6%
리 29
 
2.6%
정 29
 
2.6%
무 29
 
2.6%
경 27
 
2.4%
Other values (82) 699
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 881
77.5%
Close Punctuation 97
 
8.5%
Open Punctuation 97
 
8.5%
Space Separator 36
 
3.2%
Dash Punctuation 26
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 33
 
3.7%
시 31
 
3.5%
사 30
 
3.4%
리 29
 
3.3%
정 29
 
3.3%
무 29
 
3.3%
경 27
 
3.1%
관 26
 
3.0%
행 26
 
3.0%
인 26
 
3.0%
Other values (78) 595
67.5%
Close Punctuation
ValueCountFrequency (%)
) 97
100.0%
Open Punctuation
ValueCountFrequency (%)
( 97
100.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 881
77.5%
Common 256
 
22.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 33
 
3.7%
시 31
 
3.5%
사 30
 
3.4%
리 29
 
3.3%
정 29
 
3.3%
무 29
 
3.3%
경 27
 
3.1%
관 26
 
3.0%
행 26
 
3.0%
인 26
 
3.0%
Other values (78) 595
67.5%
Common
ValueCountFrequency (%)
) 97
37.9%
( 97
37.9%
36
 
14.1%
- 26
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 881
77.5%
ASCII 256
 
22.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 97
37.9%
( 97
37.9%
36
 
14.1%
- 26
 
10.2%
Hangul
ValueCountFrequency (%)
기 33
 
3.7%
시 31
 
3.5%
사 30
 
3.4%
리 29
 
3.3%
정 29
 
3.3%
무 29
 
3.3%
경 27
 
3.1%
관 26
 
3.0%
행 26
 
3.0%
인 26
 
3.0%
Other values (78) 595
67.5%

채용규모
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2290076
Minimum0
Maximum45
Zeros5
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T16:36:18.853346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile26.5
Maximum45
Range45
Interquartile range (IQR)1

Descriptive statistics

Standard deviation8.7623011
Coefficient of variation (CV)2.0719521
Kurtosis10.833576
Mean4.2290076
Median Absolute Deviation (MAD)0
Skewness3.3869824
Sum554
Variance76.777921
MonotonicityNot monotonic
2023-12-12T16:36:18.974484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 71
54.2%
2 25
 
19.1%
5 7
 
5.3%
3 6
 
4.6%
0 5
 
3.8%
6 3
 
2.3%
41 1
 
0.8%
7 1
 
0.8%
12 1
 
0.8%
45 1
 
0.8%
Other values (10) 10
 
7.6%
ValueCountFrequency (%)
0 5
 
3.8%
1 71
54.2%
2 25
 
19.1%
3 6
 
4.6%
4 1
 
0.8%
5 7
 
5.3%
6 3
 
2.3%
7 1
 
0.8%
10 1
 
0.8%
12 1
 
0.8%
ValueCountFrequency (%)
45 1
0.8%
43 1
0.8%
41 1
0.8%
36 1
0.8%
35 1
0.8%
33 1
0.8%
29 1
0.8%
24 1
0.8%
22 1
0.8%
21 1
0.8%

지원인원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct55
Distinct (%)42.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean198.03053
Minimum0
Maximum4253
Zeros49
Zeros (%)37.4%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T16:36:19.143813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median12
Q337
95-th percentile711
Maximum4253
Range4253
Interquartile range (IQR)37

Descriptive statistics

Standard deviation745.09332
Coefficient of variation (CV)3.7625174
Kurtosis18.972052
Mean198.03053
Median Absolute Deviation (MAD)12
Skewness4.4500102
Sum25942
Variance555164.06
MonotonicityNot monotonic
2023-12-12T16:36:19.338481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49
37.4%
2 4
 
3.1%
12 4
 
3.1%
35 3
 
2.3%
3 3
 
2.3%
28 3
 
2.3%
37 3
 
2.3%
29 3
 
2.3%
16 3
 
2.3%
15 2
 
1.5%
Other values (45) 54
41.2%
ValueCountFrequency (%)
0 49
37.4%
1 1
 
0.8%
2 4
 
3.1%
3 3
 
2.3%
4 1
 
0.8%
5 2
 
1.5%
6 2
 
1.5%
7 1
 
0.8%
9 1
 
0.8%
12 4
 
3.1%
ValueCountFrequency (%)
4253 1
0.8%
4127 1
0.8%
3686 1
0.8%
3089 1
0.8%
3024 1
0.8%
2893 1
0.8%
766 1
0.8%
656 1
0.8%
485 1
0.8%
301 1
0.8%

경쟁률
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct60
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.202748
Minimum0
Maximum153.2
Zeros49
Zeros (%)37.4%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T16:36:19.515746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q319.75
95-th percentile88.855
Maximum153.2
Range153.2
Interquartile range (IQR)19.75

Descriptive statistics

Standard deviation30.020303
Coefficient of variation (CV)1.6492182
Kurtosis6.4628818
Mean18.202748
Median Absolute Deviation (MAD)6
Skewness2.5131003
Sum2384.56
Variance901.21858
MonotonicityNot monotonic
2023-12-12T16:36:19.697382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 49
37.4%
12.0 4
 
3.1%
2.0 4
 
3.1%
13.0 4
 
3.1%
6.0 3
 
2.3%
3.0 3
 
2.3%
14.0 3
 
2.3%
29.0 2
 
1.5%
17.0 2
 
1.5%
35.0 2
 
1.5%
Other values (50) 55
42.0%
ValueCountFrequency (%)
0.0 49
37.4%
1.0 1
 
0.8%
2.0 4
 
3.1%
3.0 3
 
2.3%
3.5 1
 
0.8%
3.6 1
 
0.8%
3.8 1
 
0.8%
4.0 2
 
1.5%
5.0 2
 
1.5%
6.0 3
 
2.3%
ValueCountFrequency (%)
153.2 1
0.8%
131.5 1
0.8%
131.2 1
0.8%
121.51 1
0.8%
102.4 1
0.8%
97.0 1
0.8%
91.71 1
0.8%
86.0 1
0.8%
83.0 1
0.8%
73.8 1
0.8%

Interactions

2023-12-12T16:36:16.340450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:15.033695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:15.444173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:15.955382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.455826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:15.140727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:15.564005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.048188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.558498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:15.223797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:15.656823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.131436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.665220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:15.324390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:15.789149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.210871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:36:19.792734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
채용연도공고일자공고명채용전형채용규모지원인원경쟁률
채용연도1.0001.0000.9590.0000.4210.0000.000
공고일자1.0001.0000.9910.0000.0000.6170.000
공고명0.9590.9911.0000.0000.0000.3900.193
채용전형0.0000.0000.0001.0000.0000.0000.584
채용규모0.4210.0000.0000.0001.0000.8060.704
지원인원0.0000.6170.3900.0000.8061.0000.920
경쟁률0.0000.0000.1930.5840.7040.9201.000
2023-12-12T16:36:19.896940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
채용연도채용규모지원인원경쟁률공고명
채용연도1.000-0.0570.2720.2950.683
채용규모-0.0571.0000.5310.3620.000
지원인원0.2720.5311.0000.9570.136
경쟁률0.2950.3620.9571.0000.016
공고명0.6830.0000.1360.0161.000

Missing values

2023-12-12T16:36:16.809644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:36:16.943523image/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

채용연도공고일자공고명채용전형채용규모지원인원경쟁률
020162016-05-172016년도 한국에너지공단 NCS기반 채용 공고전문직000.0
120162016-05-172016년도 한국에너지공단 NCS기반 채용 공고시간선택제일자리000.0
220162016-05-172016년도 한국에너지공단 NCS기반 채용 공고채용형 인턴(일반)000.0
320162016-05-172016년도 한국에너지공단 NCS기반 채용 공고채용형 인턴(장애)000.0
420162016-05-172016년도 한국에너지공단 NCS기반 채용 공고채용형 인턴(고졸)000.0
520162016-11-15한국에너지공단 NCS기반 신입직원 채용 공고전문경력직300.0
620162016-11-15한국에너지공단 NCS기반 신입직원 채용 공고채용형 인턴(일반)2900.0
720172017-03-24한국에너지공단 정규직 경력직원(여신관리 및 자원개발사업관리) 채용 공고전문경력직200.0
820172017-07-12한국에너지공단 신입직원 채용 공고채용형 인턴(일반)2400.0
920172017-07-12한국에너지공단 신입직원 채용 공고채용형 인턴(고졸)200.0
채용연도공고일자공고명채용전형채용규모지원인원경쟁률
12120232023-04-18한국에너지공단 청년인턴(체험형) 채용 공고사무행정-세종충북지역본부(충북 청주)100.0
12220232023-04-18한국에너지공단 청년인턴(체험형) 채용 공고사무행정-경기지역본부(경기 수원)11212.0
12320232023-04-18한국에너지공단 청년인턴(체험형) 채용 공고사무행정-강원지역본부(강원 춘천)166.0
12420232023-04-18한국에너지공단 청년인턴(체험형) 채용 공고사무행정-경남지역본부(경남 창원)11212.0
12520232023-04-18한국에너지공단 청년인턴(체험형) 채용 공고기술행정-한국에너지공단 본사(울산)711917.0
12620232023-04-18한국에너지공단 청년인턴(체험형) 채용 공고기술행정-녹색건축센터(서울)23517.5
12720232023-05-16한국에너지공단 본사 공무직(경비) 채용 공고경비11616.0
12820232023-05-16한국에너지공단 본사 공무직(미화) 채용 공고미화13838.0
12920232023-05-16한국에너지공단 서울지역본부 공무직(운전) 채용 공고운전11616.0
13020232023-05-17한국에너지공단 개방형 계약직(법무윤리팀장) 채용 공고개방형 계약직(법무윤리팀장)100.0