Overview

Dataset statistics

Number of variables10
Number of observations352
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.0 KiB
Average record size in memory87.4 B

Variable types

Categorical3
Text1
Numeric6

Dataset

Description경기도_행정기구 및 정원 집계 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=YCYRC16AXS1FMXZCQ1PJ19374733&infSeq=1

Alerts

집계년도 has constant value ""Constant
직속기관인원수(명) is highly overall correlated with 직급명High correlation
직종명 is highly overall correlated with 직급명High correlation
직급명 is highly overall correlated with 직속기관인원수(명) and 1 other fieldsHigh correlation
직종명 is highly imbalanced (73.9%)Imbalance
본청인원수(명) has 62 (17.6%) zerosZeros
의회사무처인원수(명) has 291 (82.7%) zerosZeros
직속기관인원수(명) has 288 (81.8%) zerosZeros
출장소인원수(명) has 329 (93.5%) zerosZeros
사업소인원수(명) has 217 (61.6%) zerosZeros
합의제행정기관 has 342 (97.2%) zerosZeros

Reproduction

Analysis started2024-01-05 21:39:32.886499
Analysis finished2024-01-05 21:39:52.093935
Duration19.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023
352 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 352
100.0%

Length

2024-01-05T21:39:52.305689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-05T21:39:52.831484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 352
100.0%

직종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
일반직
318 
소방직
 
10
연구직
 
8
별정직
 
7
정무직
 
5

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반직 318
90.3%
소방직 10
 
2.8%
연구직 8
 
2.3%
별정직 7
 
2.0%
정무직 5
 
1.4%
지도직 4
 
1.1%

Length

2024-01-05T21:39:53.330588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-05T21:39:53.954477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반직 318
90.3%
소방직 10
 
2.8%
연구직 8
 
2.3%
별정직 7
 
2.0%
정무직 5
 
1.4%
지도직 4
 
1.1%

직급명
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
6급
99 
7급
85 
5급
82 
8급
31 
4급
 
7
Other values (27)
48 

Length

Max length12
Median length2
Mean length2.2897727
Min length2

Unique

Unique14 ?
Unique (%)4.0%

Sample

1st row소방정
2nd row소방령
3rd row소방경
4th row소방위
5th row소방장

Common Values

ValueCountFrequency (%)
6급 99
28.1%
7급 85
24.1%
5급 82
23.3%
8급 31
 
8.8%
4급 7
 
2.0%
연구관 6
 
1.7%
전문경력관 나군 5
 
1.4%
9급 3
 
0.9%
소방준감 2
 
0.6%
소방장 2
 
0.6%
Other values (22) 30
 
8.5%

Length

2024-01-05T21:39:54.436154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
6급 99
27.5%
7급 85
23.6%
5급 82
22.8%
8급 31
 
8.6%
4급 7
 
1.9%
연구관 6
 
1.7%
전문경력관 6
 
1.7%
나군 5
 
1.4%
9급 3
 
0.8%
소방정 2
 
0.6%
Other values (24) 34
 
9.4%

직렬명
Text

Distinct173
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-01-05T21:39:55.237522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length5.9375
Min length2

Characters and Unicode

Total characters2090
Distinct characters86
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

Unique81 ?
Unique (%)23.0%

Sample

1st row소방
2nd row소방
3rd row소방
4th row소방
5th row소방
ValueCountFrequency (%)
소방 8
 
2.3%
행정 6
 
1.7%
시설 5
 
1.4%
공업.환경 4
 
1.1%
해양수산 4
 
1.1%
시설.방재안전 4
 
1.1%
방송통신 4
 
1.1%
환경 4
 
1.1%
공업 4
 
1.1%
행정.공업 4
 
1.1%
Other values (164) 307
86.7%
2024-01-05T21:39:56.599954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 329
 
15.7%
정 124
 
5.9%
행 117
 
5.6%
업 94
 
4.5%
수 64
 
3.1%
시 63
 
3.0%
농 62
 
3.0%
설 61
 
2.9%
건 58
 
2.8%
보 58
 
2.8%
Other values (76) 1060
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1759
84.2%
Other Punctuation 329
 
15.7%
Space Separator 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 124
 
7.0%
행 117
 
6.7%
업 94
 
5.3%
수 64
 
3.6%
시 63
 
3.6%
농 62
 
3.5%
설 61
 
3.5%
건 58
 
3.3%
보 58
 
3.3%
연 56
 
3.2%
Other values (74) 1002
57.0%
Other Punctuation
ValueCountFrequency (%)
. 329
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1759
84.2%
Common 331
 
15.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 124
 
7.0%
행 117
 
6.7%
업 94
 
5.3%
수 64
 
3.6%
시 63
 
3.6%
농 62
 
3.5%
설 61
 
3.5%
건 58
 
3.3%
보 58
 
3.3%
연 56
 
3.2%
Other values (74) 1002
57.0%
Common
ValueCountFrequency (%)
. 329
99.4%
2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1759
84.2%
ASCII 331
 
15.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 329
99.4%
2
 
0.6%
Hangul
ValueCountFrequency (%)
정 124
 
7.0%
행 117
 
6.7%
업 94
 
5.3%
수 64
 
3.6%
시 63
 
3.6%
농 62
 
3.5%
설 61
 
3.5%
건 58
 
3.3%
보 58
 
3.3%
연 56
 
3.2%
Other values (74) 1002
57.0%

본청인원수(명)
Real number (ℝ)

ZEROS 

Distinct45
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.860795
Minimum0
Maximum474
Zeros62
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-01-05T21:39:57.168725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q35
95-th percentile38.45
Maximum474
Range474
Interquartile range (IQR)4

Descriptive statistics

Standard deviation42.114353
Coefficient of variation (CV)3.8776491
Kurtosis84.796813
Mean10.860795
Median Absolute Deviation (MAD)2
Skewness8.5533741
Sum3823
Variance1773.6187
MonotonicityNot monotonic
2024-01-05T21:39:57.657448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 99
28.1%
0 62
17.6%
2 43
12.2%
3 26
 
7.4%
4 22
 
6.2%
5 15
 
4.3%
8 10
 
2.8%
7 8
 
2.3%
11 6
 
1.7%
12 6
 
1.7%
Other values (35) 55
15.6%
ValueCountFrequency (%)
0 62
17.6%
1 99
28.1%
2 43
12.2%
3 26
 
7.4%
4 22
 
6.2%
5 15
 
4.3%
6 4
 
1.1%
7 8
 
2.3%
8 10
 
2.8%
9 5
 
1.4%
ValueCountFrequency (%)
474 1
0.3%
469 1
0.3%
253 1
0.3%
177 1
0.3%
158 1
0.3%
149 1
0.3%
103 1
0.3%
92 1
0.3%
89 1
0.3%
82 1
0.3%

의회사무처인원수(명)
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0539773
Minimum0
Maximum145
Zeros291
Zeros (%)82.7%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-01-05T21:39:58.144161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum145
Range145
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.7868029
Coefficient of variation (CV)8.3368049
Kurtosis214.85561
Mean1.0539773
Median Absolute Deviation (MAD)0
Skewness13.971501
Sum371
Variance77.207904
MonotonicityNot monotonic
2024-01-05T21:39:58.566802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 291
82.7%
1 37
 
10.5%
2 10
 
2.8%
3 5
 
1.4%
7 2
 
0.6%
10 1
 
0.3%
43 1
 
0.3%
145 1
 
0.3%
8 1
 
0.3%
64 1
 
0.3%
Other values (2) 2
 
0.6%
ValueCountFrequency (%)
0 291
82.7%
1 37
 
10.5%
2 10
 
2.8%
3 5
 
1.4%
4 1
 
0.3%
7 2
 
0.6%
8 1
 
0.3%
10 1
 
0.3%
11 1
 
0.3%
43 1
 
0.3%
ValueCountFrequency (%)
145 1
 
0.3%
64 1
 
0.3%
43 1
 
0.3%
11 1
 
0.3%
10 1
 
0.3%
8 1
 
0.3%
7 2
 
0.6%
4 1
 
0.3%
3 5
1.4%
2 10
2.8%

직속기관인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.357955
Minimum0
Maximum5033
Zeros288
Zeros (%)81.8%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-01-05T21:39:59.144962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile9.25
Maximum5033
Range5033
Interquartile range (IQR)0

Descriptive statistics

Standard deviation316.42131
Coefficient of variation (CV)9.7787798
Kurtosis191.51135
Mean32.357955
Median Absolute Deviation (MAD)0
Skewness13.171843
Sum11390
Variance100122.45
MonotonicityNot monotonic
2024-01-05T21:39:59.613624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 288
81.8%
1 25
 
7.1%
2 13
 
3.7%
3 4
 
1.1%
4 3
 
0.9%
21 2
 
0.6%
38 1
 
0.3%
26 1
 
0.3%
12 1
 
0.3%
94 1
 
0.3%
Other values (13) 13
 
3.7%
ValueCountFrequency (%)
0 288
81.8%
1 25
 
7.1%
2 13
 
3.7%
3 4
 
1.1%
4 3
 
0.9%
7 1
 
0.3%
12 1
 
0.3%
13 1
 
0.3%
19 1
 
0.3%
21 2
 
0.6%
ValueCountFrequency (%)
5033 1
0.3%
2577 1
0.3%
1540 1
0.3%
744 1
0.3%
718 1
0.3%
276 1
0.3%
94 1
0.3%
80 1
0.3%
50 1
0.3%
38 1
0.3%

출장소인원수(명)
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.10511364
Minimum0
Maximum6
Zeros329
Zeros (%)93.5%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-01-05T21:40:00.144295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.50948495
Coefficient of variation (CV)4.846992
Kurtosis66.432909
Mean0.10511364
Median Absolute Deviation (MAD)0
Skewness7.3199901
Sum37
Variance0.25957492
MonotonicityNot monotonic
2024-01-05T21:40:00.539506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 329
93.5%
1 17
 
4.8%
2 2
 
0.6%
3 2
 
0.6%
4 1
 
0.3%
6 1
 
0.3%
ValueCountFrequency (%)
0 329
93.5%
1 17
 
4.8%
2 2
 
0.6%
3 2
 
0.6%
4 1
 
0.3%
6 1
 
0.3%
ValueCountFrequency (%)
6 1
 
0.3%
4 1
 
0.3%
3 2
 
0.6%
2 2
 
0.6%
1 17
 
4.8%
0 329
93.5%

사업소인원수(명)
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6335227
Minimum0
Maximum40
Zeros217
Zeros (%)61.6%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-01-05T21:40:00.887503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile8.45
Maximum40
Range40
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.2135734
Coefficient of variation (CV)2.5794397
Kurtosis32.802842
Mean1.6335227
Median Absolute Deviation (MAD)0
Skewness5.0861976
Sum575
Variance17.754201
MonotonicityNot monotonic
2024-01-05T21:40:01.242602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 217
61.6%
1 50
 
14.2%
2 28
 
8.0%
3 14
 
4.0%
4 9
 
2.6%
9 6
 
1.7%
5 6
 
1.7%
8 4
 
1.1%
7 3
 
0.9%
6 3
 
0.9%
Other values (11) 12
 
3.4%
ValueCountFrequency (%)
0 217
61.6%
1 50
 
14.2%
2 28
 
8.0%
3 14
 
4.0%
4 9
 
2.6%
5 6
 
1.7%
6 3
 
0.9%
7 3
 
0.9%
8 4
 
1.1%
9 6
 
1.7%
ValueCountFrequency (%)
40 1
0.3%
30 1
0.3%
26 2
0.6%
23 1
0.3%
16 1
0.3%
15 1
0.3%
14 1
0.3%
13 1
0.3%
12 1
0.3%
11 1
0.3%

합의제행정기관
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.13636364
Minimum0
Maximum15
Zeros342
Zeros (%)97.2%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-01-05T21:40:01.583394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1614101
Coefficient of variation (CV)8.5170072
Kurtosis124.52269
Mean0.13636364
Median Absolute Deviation (MAD)0
Skewness10.848496
Sum48
Variance1.3488733
MonotonicityNot monotonic
2024-01-05T21:40:02.001992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 342
97.2%
2 5
 
1.4%
1 2
 
0.6%
8 1
 
0.3%
15 1
 
0.3%
13 1
 
0.3%
ValueCountFrequency (%)
0 342
97.2%
1 2
 
0.6%
2 5
 
1.4%
8 1
 
0.3%
13 1
 
0.3%
15 1
 
0.3%
ValueCountFrequency (%)
15 1
 
0.3%
13 1
 
0.3%
8 1
 
0.3%
2 5
 
1.4%
1 2
 
0.6%
0 342
97.2%

Interactions

2024-01-05T21:39:48.675864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:37.579509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:39.412097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:41.645053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:43.898991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:45.822093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:49.033070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:37.856643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:39.808865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:42.042793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:44.152750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:46.169535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:49.432628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:38.189865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:40.208388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:42.450329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:44.484755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:46.720291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:49.776109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:38.455188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:40.549711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:42.894489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:44.846211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:47.043613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:50.102332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:38.760817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:40.870537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:43.253582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:45.127410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:47.768352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:50.630836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:39.085852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:41.281911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:43.629598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:45.442924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T21:39:48.255572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-05T21:40:02.436994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
직종명직급명본청인원수(명)의회사무처인원수(명)직속기관인원수(명)출장소인원수(명)사업소인원수(명)합의제행정기관
직종명1.0000.9790.4790.0000.4590.0000.0000.230
직급명0.9791.0000.3770.0000.9330.0000.0000.339
본청인원수(명)0.4790.3771.0000.9230.5430.9400.8340.810
의회사무처인원수(명)0.0000.0000.9231.0000.0000.9820.7241.000
직속기관인원수(명)0.4590.9330.5430.0001.0000.0000.0000.000
출장소인원수(명)0.0000.0000.9400.9820.0001.0000.8250.876
사업소인원수(명)0.0000.0000.8340.7240.0000.8251.0000.683
합의제행정기관0.2300.3390.8101.0000.0000.8760.6831.000
2024-01-05T21:40:02.879079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
직급명직종명
직급명1.0000.857
직종명0.8571.000
2024-01-05T21:40:03.151961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본청인원수(명)의회사무처인원수(명)직속기관인원수(명)출장소인원수(명)사업소인원수(명)합의제행정기관직종명직급명
본청인원수(명)1.0000.2460.2190.3060.2520.0770.1900.169
의회사무처인원수(명)0.2461.0000.2740.3680.1570.2310.0000.000
직속기관인원수(명)0.2190.2741.0000.2330.1380.2350.3320.736
출장소인원수(명)0.3060.3680.2331.0000.2820.3160.0000.000
사업소인원수(명)0.2520.1570.1380.2821.0000.0690.0000.000
합의제행정기관0.0770.2310.2350.3160.0691.0000.1570.161
직종명0.1900.0000.3320.0000.0000.1571.0000.857
직급명0.1690.0000.7360.0000.0000.1610.8571.000

Missing values

2024-01-05T21:39:51.287118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-05T21:39:51.896792image/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

집계년도직종명직급명직렬명본청인원수(명)의회사무처인원수(명)직속기관인원수(명)출장소인원수(명)사업소인원수(명)합의제행정기관
02023소방직소방정소방7038000
12023소방직소방령소방600276010
22023소방직소방경소방820718010
32023소방직소방위소방1490744010
42023소방직소방장소방15801540010
52023소방직소방교소방9202577000
62023소방직소방사소방805033000
72023정무직도지사도지사100000
82023정무직자치경찰위원회 위원장자치경찰위원회 위원장000002
92023정무직자치경찰위원회 사무국장자치경찰위원회 사무국장000002
집계년도직종명직급명직렬명본청인원수(명)의회사무처인원수(명)직속기관인원수(명)출장소인원수(명)사업소인원수(명)합의제행정기관
3422023정무직소방준감녹지연구000090
3432023일반직소방정수의연구000040
3442023별정직소방령해양수산연구000090
3452023연구직소방경보건연구0080000
3462023지도직소방위환경연구0094000
3472023소방직소방장수의연구.보건연구000020
3482023정무직소방교녹지.녹지연구000020
3492023지도직지도관농촌지도0012000
3502023지도직지도사농촌지도0026000
3512023소방직소방준감소방603000