Overview

Dataset statistics

Number of variables6
Number of observations1596
Missing cells313
Missing cells (%)3.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory78.1 KiB
Average record size in memory50.1 B

Variable types

Numeric2
Text3
DateTime1

Dataset

Description성남시청 홈페이지에 게재된 성남시 직원(임기제, 공무직, 기간제 등) 및 산하기관 직원 채용 정보에 대한 데이터로 제목, 접수기간, 조회수, 부서 등의 항목을 제공합니다.
Author경기도 성남시
URLhttps://www.data.go.kr/data/15004886/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
번호 is highly overall correlated with 조회수High correlation
조회수 is highly overall correlated with 번호High correlation
접수기간 has 313 (19.6%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:34:23.118863
Analysis finished2023-12-12 02:34:24.116103
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1596
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean798.5
Minimum1
Maximum1596
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2023-12-12T11:34:24.183194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile80.75
Q1399.75
median798.5
Q31197.25
95-th percentile1516.25
Maximum1596
Range1595
Interquartile range (IQR)797.5

Descriptive statistics

Standard deviation460.86983
Coefficient of variation (CV)0.57716948
Kurtosis-1.2
Mean798.5
Median Absolute Deviation (MAD)399
Skewness0
Sum1274406
Variance212401
MonotonicityStrictly decreasing
2023-12-12T11:34:24.322001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1596 1
 
0.1%
523 1
 
0.1%
525 1
 
0.1%
526 1
 
0.1%
527 1
 
0.1%
528 1
 
0.1%
529 1
 
0.1%
530 1
 
0.1%
531 1
 
0.1%
532 1
 
0.1%
Other values (1586) 1586
99.4%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1596 1
0.1%
1595 1
0.1%
1594 1
0.1%
1593 1
0.1%
1592 1
0.1%
1591 1
0.1%
1590 1
0.1%
1589 1
0.1%
1588 1
0.1%
1587 1
0.1%

제목
Text

Distinct1433
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
2023-12-12T11:34:24.559201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length115
Median length60
Mean length33.52193
Min length12

Characters and Unicode

Total characters53501
Distinct characters416
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1345 ?
Unique (%)84.3%

Sample

1st row2023년도 제2차 성남시정연구원 직원 채용 재공고
2nd row성남시외국인주민복지지원센터 상담사 채용 공고
3rd row성남종합운동장 기간제근로자 채용공고
4th row2023년 성남시청소년재단 기간제근로자(보조인력) 채용 재공고
5th row2023년도 제15회 성남시 임기제공무원 임용시험 시행계획 공고
ValueCountFrequency (%)
공고 1069
 
10.4%
채용 637
 
6.2%
성남시 545
 
5.3%
임용시험 362
 
3.5%
임기제공무원 328
 
3.2%
및 244
 
2.4%
재공고 213
 
2.1%
시행계획 191
 
1.9%
직원 185
 
1.8%
기간제근로자 143
 
1.4%
Other values (1113) 6331
61.8%
2023-12-12T11:34:24.947673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8652
 
16.2%
공 2466
 
4.6%
시 1898
 
3.5%
2 1787
 
3.3%
고 1482
 
2.8%
제 1430
 
2.7%
용 1404
 
2.6%
원 1346
 
2.5%
성 1287
 
2.4%
남 1263
 
2.4%
Other values (406) 30486
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38506
72.0%
Space Separator 8652
 
16.2%
Decimal Number 4674
 
8.7%
Open Punctuation 673
 
1.3%
Close Punctuation 671
 
1.3%
Other Punctuation 260
 
0.5%
Uppercase Letter 32
 
0.1%
Lowercase Letter 16
 
< 0.1%
Dash Punctuation 7
 
< 0.1%
Math Symbol 4
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 2466
 
6.4%
시 1898
 
4.9%
고 1482
 
3.8%
제 1430
 
3.7%
용 1404
 
3.6%
원 1346
 
3.5%
성 1287
 
3.3%
남 1263
 
3.3%
년 1165
 
3.0%
채 951
 
2.5%
Other values (353) 23814
61.8%
Uppercase Letter
ValueCountFrequency (%)
D 6
18.8%
B 3
9.4%
P 3
9.4%
C 3
9.4%
H 2
 
6.2%
T 2
 
6.2%
O 2
 
6.2%
J 2
 
6.2%
R 2
 
6.2%
F 2
 
6.2%
Other values (5) 5
15.6%
Decimal Number
ValueCountFrequency (%)
2 1787
38.2%
0 1097
23.5%
1 808
17.3%
3 229
 
4.9%
9 222
 
4.7%
7 154
 
3.3%
8 146
 
3.1%
4 106
 
2.3%
5 64
 
1.4%
6 61
 
1.3%
Other Punctuation
ValueCountFrequency (%)
, 126
48.5%
· 48
 
18.5%
. 39
 
15.0%
' 26
 
10.0%
" 16
 
6.2%
& 3
 
1.2%
: 1
 
0.4%
/ 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
o 4
25.0%
c 4
25.0%
v 2
12.5%
b 2
12.5%
g 2
12.5%
t 2
12.5%
Open Punctuation
ValueCountFrequency (%)
( 654
97.2%
[ 10
 
1.5%
「 7
 
1.0%
『 2
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 652
97.2%
] 10
 
1.5%
」 7
 
1.0%
』 2
 
0.3%
Math Symbol
ValueCountFrequency (%)
> 2
50.0%
< 2
50.0%
Space Separator
ValueCountFrequency (%)
8652
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 3
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38506
72.0%
Common 14947
 
27.9%
Latin 48
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 2466
 
6.4%
시 1898
 
4.9%
고 1482
 
3.8%
제 1430
 
3.7%
용 1404
 
3.6%
원 1346
 
3.5%
성 1287
 
3.3%
남 1263
 
3.3%
년 1165
 
3.0%
채 951
 
2.5%
Other values (353) 23814
61.8%
Common
ValueCountFrequency (%)
8652
57.9%
2 1787
 
12.0%
0 1097
 
7.3%
1 808
 
5.4%
( 654
 
4.4%
) 652
 
4.4%
3 229
 
1.5%
9 222
 
1.5%
7 154
 
1.0%
8 146
 
1.0%
Other values (22) 546
 
3.7%
Latin
ValueCountFrequency (%)
D 6
 
12.5%
o 4
 
8.3%
c 4
 
8.3%
B 3
 
6.2%
P 3
 
6.2%
C 3
 
6.2%
H 2
 
4.2%
v 2
 
4.2%
T 2
 
4.2%
O 2
 
4.2%
Other values (11) 17
35.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38506
72.0%
ASCII 14923
 
27.9%
None 66
 
0.1%
Punctuation 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8652
58.0%
2 1787
 
12.0%
0 1097
 
7.4%
1 808
 
5.4%
( 654
 
4.4%
) 652
 
4.4%
3 229
 
1.5%
9 222
 
1.5%
7 154
 
1.0%
8 146
 
1.0%
Other values (36) 522
 
3.5%
Hangul
ValueCountFrequency (%)
공 2466
 
6.4%
시 1898
 
4.9%
고 1482
 
3.8%
제 1430
 
3.7%
용 1404
 
3.6%
원 1346
 
3.5%
성 1287
 
3.3%
남 1263
 
3.3%
년 1165
 
3.0%
채 951
 
2.5%
Other values (353) 23814
61.8%
None
ValueCountFrequency (%)
· 48
72.7%
」 7
 
10.6%
「 7
 
10.6%
』 2
 
3.0%
『 2
 
3.0%
Punctuation
ValueCountFrequency (%)
’ 3
50.0%
‘ 3
50.0%

접수기간
Text

MISSING 

Distinct1101
Distinct (%)85.8%
Missing313
Missing (%)19.6%
Memory size12.6 KiB
2023-12-12T11:34:25.138983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters26943
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique968 ?
Unique (%)75.4%

Sample

1st row2023-10-05~2023-10-15
2nd row2023-10-05~2023-10-18
3rd row2023-10-04~2023-10-11
4th row2023-09-22~2023-10-06
5th row2023-10-04~2023-10-11
ValueCountFrequency (%)
2023-08-28~2023-09-01 5
 
0.4%
2020-01-06~2020-01-08 5
 
0.4%
2023-01-09~2023-01-13 5
 
0.4%
2023-03-13~2023-03-17 5
 
0.4%
2023-07-31~2023-08-04 4
 
0.3%
2021-12-01~2021-12-07 4
 
0.3%
2022-04-04~2022-04-08 4
 
0.3%
2023-01-30~2023-02-03 4
 
0.3%
2021-12-14~2021-12-20 4
 
0.3%
2021-09-16~2021-09-27 4
 
0.3%
Other values (1091) 1239
96.6%
2023-12-12T11:34:25.437797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 6569
24.4%
0 6117
22.7%
- 5132
19.0%
1 3355
12.5%
~ 1283
 
4.8%
3 1092
 
4.1%
9 959
 
3.6%
8 589
 
2.2%
4 492
 
1.8%
5 467
 
1.7%
Other values (2) 888
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20528
76.2%
Dash Punctuation 5132
 
19.0%
Math Symbol 1283
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6569
32.0%
0 6117
29.8%
1 3355
16.3%
3 1092
 
5.3%
9 959
 
4.7%
8 589
 
2.9%
4 492
 
2.4%
5 467
 
2.3%
7 460
 
2.2%
6 428
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 5132
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1283
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26943
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 6569
24.4%
0 6117
22.7%
- 5132
19.0%
1 3355
12.5%
~ 1283
 
4.8%
3 1092
 
4.1%
9 959
 
3.6%
8 589
 
2.2%
4 492
 
1.8%
5 467
 
1.7%
Other values (2) 888
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26943
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 6569
24.4%
0 6117
22.7%
- 5132
19.0%
1 3355
12.5%
~ 1283
 
4.8%
3 1092
 
4.1%
9 959
 
3.6%
8 589
 
2.2%
4 492
 
1.8%
5 467
 
1.7%
Other values (2) 888
 
3.3%

조회수
Real number (ℝ)

HIGH CORRELATION 

Distinct1256
Distinct (%)78.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1659.3409
Minimum18
Maximum30542
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2023-12-12T11:34:25.563366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile328.75
Q1694
median1187
Q32141.5
95-th percentile4366.75
Maximum30542
Range30524
Interquartile range (IQR)1447.5

Descriptive statistics

Standard deviation1623.2223
Coefficient of variation (CV)0.97823321
Kurtosis69.679997
Mean1659.3409
Median Absolute Deviation (MAD)601
Skewness5.4384543
Sum2648308
Variance2634850.7
MonotonicityNot monotonic
2023-12-12T11:34:25.682938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
544 5
 
0.3%
1254 5
 
0.3%
935 4
 
0.3%
693 4
 
0.3%
556 4
 
0.3%
1187 4
 
0.3%
971 4
 
0.3%
784 4
 
0.3%
514 4
 
0.3%
694 4
 
0.3%
Other values (1246) 1554
97.4%
ValueCountFrequency (%)
18 1
0.1%
27 1
0.1%
51 1
0.1%
52 1
0.1%
73 1
0.1%
113 1
0.1%
133 1
0.1%
141 1
0.1%
142 1
0.1%
149 1
0.1%
ValueCountFrequency (%)
30542 1
0.1%
14876 1
0.1%
12611 1
0.1%
11146 1
0.1%
10424 1
0.1%
10000 1
0.1%
9311 1
0.1%
9268 1
0.1%
9146 1
0.1%
9052 1
0.1%

부서
Text

Distinct63
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
2023-12-12T11:34:25.873667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.2550125
Min length3

Characters and Unicode

Total characters8387
Distinct characters106
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

Unique12 ?
Unique (%)0.8%

Sample

1st row정책기획과
2nd row여성가족과
3rd row체육진흥과
4th row청년청소년과
5th row인사과
ValueCountFrequency (%)
자치행정과 455
28.5%
교육청소년과 191
12.0%
인사행정과 104
 
6.5%
공공의료정책과 100
 
6.3%
정보통신과 97
 
6.1%
체육진흥과 85
 
5.3%
여성가족과 82
 
5.1%
문화예술과 69
 
4.3%
산업지원과 38
 
2.4%
건강증진과 34
 
2.1%
Other values (53) 341
21.4%
2023-12-12T11:34:26.177682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 1579
18.8%
정 863
 
10.3%
행 608
 
7.2%
자 474
 
5.7%
치 455
 
5.4%
육 283
 
3.4%
청 257
 
3.1%
년 238
 
2.8%
소 230
 
2.7%
공 207
 
2.5%
Other values (96) 3193
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8386
> 99.9%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 1579
18.8%
정 863
 
10.3%
행 608
 
7.3%
자 474
 
5.7%
치 455
 
5.4%
육 283
 
3.4%
청 257
 
3.1%
년 238
 
2.8%
소 230
 
2.7%
공 207
 
2.5%
Other values (95) 3192
38.1%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8386
> 99.9%
Common 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 1579
18.8%
정 863
 
10.3%
행 608
 
7.3%
자 474
 
5.7%
치 455
 
5.4%
육 283
 
3.4%
청 257
 
3.1%
년 238
 
2.8%
소 230
 
2.7%
공 207
 
2.5%
Other values (95) 3192
38.1%
Common
ValueCountFrequency (%)
1 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8386
> 99.9%
ASCII 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 1579
18.8%
정 863
 
10.3%
행 608
 
7.3%
자 474
 
5.7%
치 455
 
5.4%
육 283
 
3.4%
청 257
 
3.1%
년 238
 
2.8%
소 230
 
2.7%
공 207
 
2.5%
Other values (95) 3192
38.1%
ASCII
ValueCountFrequency (%)
1 1
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
Minimum2023-10-04 00:00:00
Maximum2023-10-04 00:00:00
2023-12-12T11:34:26.288238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:34:26.468622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T11:34:23.761788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:34:23.547044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:34:23.869766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:34:23.656202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:34:26.561841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호조회수부서
번호1.0000.3130.777
조회수0.3131.0000.215
부서0.7770.2151.000
2023-12-12T11:34:26.660346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호조회수
번호1.000-0.542
조회수-0.5421.000

Missing values

2023-12-12T11:34:23.984954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:34:24.075439image/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

번호제목접수기간조회수부서데이터기준일자
015962023년도 제2차 성남시정연구원 직원 채용 재공고2023-10-05~2023-10-1518정책기획과2023-10-04
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