Overview

Dataset statistics

Number of variables14
Number of observations5460
Missing cells10368
Missing cells (%)13.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory624.0 KiB
Average record size in memory117.0 B

Variable types

Numeric3
Categorical4
Text7

Dataset

Description경상남도 공사대장의 예산과목 데이터입니다. 공사년도, 공사구분, 부서, 부서장 단위사업, 세부사업 편성목, 통계목, 세목등의 데이터를 포함하고있습니다.
Author경상남도
URLhttps://www.data.go.kr/data/15049530/fileData.do

Alerts

부서코드 has constant value ""Constant
공사년도 is highly overall correlated with 공사번호High correlation
공사번호 is highly overall correlated with 공사년도High correlation
순번 is highly imbalanced (91.1%)Imbalance
정책/관 has 97 (1.8%) missing valuesMissing
단위(회계)/항 has 98 (1.8%) missing valuesMissing
세부사업/세항 has 95 (1.7%) missing valuesMissing
편성목/세세항 has 378 (6.9%) missing valuesMissing
통계목/목 has 1333 (24.4%) missing valuesMissing
세목 has 4064 (74.4%) missing valuesMissing
금액 has 4302 (78.8%) missing valuesMissing

Reproduction

Analysis started2023-12-12 00:25:32.035269
Analysis finished2023-12-12 00:25:34.846382
Duration2.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공사년도
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2004.5941
Minimum1990
Maximum2013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.1 KiB
2023-12-12T09:25:34.908282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1990
5-th percentile1992
Q12002
median2006
Q32009
95-th percentile2011
Maximum2013
Range23
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.6916333
Coefficient of variation (CV)0.0028392946
Kurtosis0.012243461
Mean2004.5941
Median Absolute Deviation (MAD)3
Skewness-0.91178086
Sum10945084
Variance32.39469
MonotonicityNot monotonic
2023-12-12T09:25:35.024879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2007 543
 
9.9%
2010 533
 
9.8%
2011 451
 
8.3%
2006 417
 
7.6%
2004 415
 
7.6%
2008 380
 
7.0%
2005 380
 
7.0%
2009 372
 
6.8%
2003 303
 
5.5%
2012 201
 
3.7%
Other values (14) 1465
26.8%
ValueCountFrequency (%)
1990 88
1.6%
1991 119
2.2%
1992 85
1.6%
1993 99
1.8%
1994 79
1.4%
1995 97
1.8%
1996 106
1.9%
1997 94
1.7%
1998 95
1.7%
1999 158
2.9%
ValueCountFrequency (%)
2013 16
 
0.3%
2012 201
 
3.7%
2011 451
8.3%
2010 533
9.8%
2009 372
6.8%
2008 380
7.0%
2007 543
9.9%
2006 417
7.6%
2005 380
7.0%
2004 415
7.6%

공사구분
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.8 KiB
용역
2719 
공사
2205 
기타
314 
구매
 
222

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용역 2719
49.8%
공사 2205
40.4%
기타 314
 
5.8%
구매 222
 
4.1%

Length

2023-12-12T09:25:35.137243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:25:35.234987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용역 2719
49.8%
공사 2205
40.4%
기타 314
 
5.8%
구매 222
 
4.1%

공사번호
Real number (ℝ)

HIGH CORRELATION 

Distinct543
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.987
Minimum1
Maximum619
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.1 KiB
2023-12-12T09:25:35.353966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q139
median82
Q3174
95-th percentile370.05
Maximum619
Range618
Interquartile range (IQR)135

Descriptive statistics

Standard deviation117.00471
Coefficient of variation (CV)0.95135836
Kurtosis1.832101
Mean122.987
Median Absolute Deviation (MAD)53
Skewness1.4765422
Sum671509
Variance13690.101
MonotonicityNot monotonic
2023-12-12T09:25:35.484814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 38
 
0.7%
5 37
 
0.7%
4 37
 
0.7%
1 37
 
0.7%
6 37
 
0.7%
2 37
 
0.7%
9 37
 
0.7%
39 37
 
0.7%
63 37
 
0.7%
52 36
 
0.7%
Other values (533) 5090
93.2%
ValueCountFrequency (%)
1 37
0.7%
2 37
0.7%
3 38
0.7%
4 37
0.7%
5 37
0.7%
6 37
0.7%
7 36
0.7%
8 35
0.6%
9 37
0.7%
10 36
0.7%
ValueCountFrequency (%)
619 1
< 0.1%
618 1
< 0.1%
617 1
< 0.1%
616 1
< 0.1%
615 1
< 0.1%
614 1
< 0.1%
607 1
< 0.1%
604 1
< 0.1%
601 1
< 0.1%
595 1
< 0.1%

부서코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.8 KiB
1
5460 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 5460
100.0%

Length

2023-12-12T09:25:35.655802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:25:35.740982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5460
100.0%

순번
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.8 KiB
1
5324 
2
 
128
3
 
7
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 5324
97.5%
2 128
 
2.3%
3 7
 
0.1%
4 1
 
< 0.1%

Length

2023-12-12T09:25:35.834993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:25:35.966653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5324
97.5%
2 128
 
2.3%
3 7
 
0.1%
4 1
 
< 0.1%

구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.8 KiB
일반
3331 
<NA>
2112 
특별
 
17

Length

Max length4
Median length2
Mean length2.7736264
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
일반 3331
61.0%
<NA> 2112
38.7%
특별 17
 
0.3%

Length

2023-12-12T09:25:36.120339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:25:36.248329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 3331
61.0%
na 2112
38.7%
특별 17
 
0.3%

부서/장
Text

Distinct219
Distinct (%)4.0%
Missing1
Missing (%)< 0.1%
Memory size42.8 KiB
2023-12-12T09:25:36.535737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length5
Mean length4.7534347
Min length1

Characters and Unicode

Total characters25949
Distinct characters214
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)1.7%

Sample

1st row재무행정비
2nd row지역개발
3rd row건설부일반
4th row지역개발비
5th row경제개발
ValueCountFrequency (%)
경제개발 1119
20.5%
경제개발비 980
17.9%
일반행정비 474
 
8.7%
치수방재과 206
 
3.8%
도로과 204
 
3.7%
회계과 186
 
3.4%
지역개발비 158
 
2.9%
사회개발비 156
 
2.9%
생태하천과 129
 
2.4%
소방행정과 114
 
2.1%
Other values (209) 1742
31.9%
2023-12-12T09:25:37.033509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
개 2569
 
9.9%
발 2563
 
9.9%
경 2264
 
8.7%
제 2257
 
8.7%
비 2148
 
8.3%
과 1482
 
5.7%
정 1014
 
3.9%
행 757
 
2.9%
일 582
 
2.2%
반 578
 
2.2%
Other values (204) 9735
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25706
99.1%
Decimal Number 219
 
0.8%
Space Separator 10
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 2569
 
10.0%
발 2563
 
10.0%
경 2264
 
8.8%
제 2257
 
8.8%
비 2148
 
8.4%
과 1482
 
5.8%
정 1014
 
3.9%
행 757
 
2.9%
일 582
 
2.3%
반 578
 
2.2%
Other values (188) 9492
36.9%
Decimal Number
ValueCountFrequency (%)
1 64
29.2%
0 47
21.5%
9 31
14.2%
2 22
 
10.0%
5 17
 
7.8%
4 16
 
7.3%
3 14
 
6.4%
8 8
 
3.7%
Close Punctuation
ValueCountFrequency (%)
) 3
75.0%
] 1
 
25.0%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
? 1
50.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25706
99.1%
Common 242
 
0.9%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 2569
 
10.0%
발 2563
 
10.0%
경 2264
 
8.8%
제 2257
 
8.8%
비 2148
 
8.4%
과 1482
 
5.8%
정 1014
 
3.9%
행 757
 
2.9%
일 582
 
2.3%
반 578
 
2.2%
Other values (188) 9492
36.9%
Common
ValueCountFrequency (%)
1 64
26.4%
0 47
19.4%
9 31
12.8%
2 22
 
9.1%
5 17
 
7.0%
4 16
 
6.6%
3 14
 
5.8%
10
 
4.1%
8 8
 
3.3%
( 5
 
2.1%
Other values (5) 8
 
3.3%
Latin
ValueCountFrequency (%)
G 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25702
99.0%
ASCII 243
 
0.9%
Compat Jamo 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
개 2569
 
10.0%
발 2563
 
10.0%
경 2264
 
8.8%
제 2257
 
8.8%
비 2148
 
8.4%
과 1482
 
5.8%
정 1014
 
3.9%
행 757
 
2.9%
일 582
 
2.3%
반 578
 
2.2%
Other values (184) 9488
36.9%
ASCII
ValueCountFrequency (%)
1 64
26.3%
0 47
19.3%
9 31
12.8%
2 22
 
9.1%
5 17
 
7.0%
4 16
 
6.6%
3 14
 
5.8%
10
 
4.1%
8 8
 
3.3%
( 5
 
2.1%
Other values (6) 9
 
3.7%
Compat Jamo
ValueCountFrequency (%)
ㅘ 1
25.0%
ㅊ 1
25.0%
ㅂ 1
25.0%
ㄹ 1
25.0%

정책/관
Text

MISSING 

Distinct396
Distinct (%)7.4%
Missing97
Missing (%)1.8%
Memory size42.8 KiB
2023-12-12T09:25:37.360174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length18
Mean length7.6315495
Min length1

Characters and Unicode

Total characters40928
Distinct characters253
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique184 ?
Unique (%)3.4%

Sample

1st row회계및재산관리
2nd row도로치수
3rd row국토자원보존개발
4th row도로치수
5th row국토자원보존개발
ValueCountFrequency (%)
국토자원보존개발 1001
 
15.8%
국토자원보존개발비 604
 
9.5%
일반행정비 531
 
8.4%
하천및수자원관리 312
 
4.9%
농수산개발비 192
 
3.0%
및 192
 
3.0%
농수산개발 178
 
2.8%
지방도건설확포장 176
 
2.8%
회계및재산관리 157
 
2.5%
도로치수사업 101
 
1.6%
Other values (445) 2911
45.8%
2023-12-12T09:25:37.890516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
개 2393
 
5.8%
발 2250
 
5.5%
원 2122
 
5.2%
자 2092
 
5.1%
보 2033
 
5.0%
비 1806
 
4.4%
국 1661
 
4.1%
토 1646
 
4.0%
존 1628
 
4.0%
및 1111
 
2.7%
Other values (243) 22186
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39615
96.8%
Space Separator 1007
 
2.5%
Decimal Number 272
 
0.7%
Other Punctuation 17
 
< 0.1%
Open Punctuation 8
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 2393
 
6.0%
발 2250
 
5.7%
원 2122
 
5.4%
자 2092
 
5.3%
보 2033
 
5.1%
비 1806
 
4.6%
국 1661
 
4.2%
토 1646
 
4.2%
존 1628
 
4.1%
및 1111
 
2.8%
Other values (226) 20873
52.7%
Decimal Number
ValueCountFrequency (%)
1 62
22.8%
2 51
18.8%
0 45
16.5%
9 30
11.0%
3 29
10.7%
8 19
 
7.0%
5 19
 
7.0%
4 16
 
5.9%
7 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 8
47.1%
. 5
29.4%
？ 2
 
11.8%
? 2
 
11.8%
Space Separator
ValueCountFrequency (%)
1007
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39615
96.8%
Common 1313
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 2393
 
6.0%
발 2250
 
5.7%
원 2122
 
5.4%
자 2092
 
5.3%
보 2033
 
5.1%
비 1806
 
4.6%
국 1661
 
4.2%
토 1646
 
4.2%
존 1628
 
4.1%
및 1111
 
2.8%
Other values (226) 20873
52.7%
Common
ValueCountFrequency (%)
1007
76.7%
1 62
 
4.7%
2 51
 
3.9%
0 45
 
3.4%
9 30
 
2.3%
3 29
 
2.2%
8 19
 
1.4%
5 19
 
1.4%
4 16
 
1.2%
, 8
 
0.6%
Other values (7) 27
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39611
96.8%
ASCII 1311
 
3.2%
Compat Jamo 4
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
개 2393
 
6.0%
발 2250
 
5.7%
원 2122
 
5.4%
자 2092
 
5.3%
보 2033
 
5.1%
비 1806
 
4.6%
국 1661
 
4.2%
토 1646
 
4.2%
존 1628
 
4.1%
및 1111
 
2.8%
Other values (222) 20869
52.7%
ASCII
ValueCountFrequency (%)
1007
76.8%
1 62
 
4.7%
2 51
 
3.9%
0 45
 
3.4%
9 30
 
2.3%
3 29
 
2.2%
8 19
 
1.4%
5 19
 
1.4%
4 16
 
1.2%
, 8
 
0.6%
Other values (6) 25
 
1.9%
None
ValueCountFrequency (%)
？ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
25.0%
ㅊ 1
25.0%
ㄹ 1
25.0%
ㅗ 1
25.0%

단위(회계)/항
Text

MISSING 

Distinct572
Distinct (%)10.7%
Missing98
Missing (%)1.8%
Memory size42.8 KiB
2023-12-12T09:25:38.266417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length6.2804924
Min length1

Characters and Unicode

Total characters33676
Distinct characters301
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique279 ?
Unique (%)5.2%

Sample

1st row재산관리
2nd row치수사업
3rd row치수및재해대책
4th row치수사업
5th row치수및재해대책
ValueCountFrequency (%)
건설관리 751
 
11.1%
치수및재해대책 501
 
7.4%
재해대책 323
 
4.8%
치수및 314
 
4.6%
하천정비 301
 
4.5%
재무행정 275
 
4.1%
수산진흥 186
 
2.8%
기획관리 184
 
2.7%
해양수산 172
 
2.5%
및 153
 
2.3%
Other values (680) 3593
53.2%
2023-12-12T09:25:38.856038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 1641
 
4.9%
리 1556
 
4.6%
수 1518
 
4.5%
1409
 
4.2%
재 1211
 
3.6%
해 1159
 
3.4%
및 1125
 
3.3%
정 1041
 
3.1%
대 988
 
2.9%
치 980
 
2.9%
Other values (291) 21048
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31816
94.5%
Space Separator 1409
 
4.2%
Decimal Number 138
 
0.4%
Open Punctuation 115
 
0.3%
Close Punctuation 115
 
0.3%
Uppercase Letter 61
 
0.2%
Other Punctuation 18
 
0.1%
Dash Punctuation 3
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 1641
 
5.2%
리 1556
 
4.9%
수 1518
 
4.8%
재 1211
 
3.8%
해 1159
 
3.6%
및 1125
 
3.5%
정 1041
 
3.3%
대 988
 
3.1%
치 980
 
3.1%
설 928
 
2.9%
Other values (267) 19669
61.8%
Decimal Number
ValueCountFrequency (%)
0 60
43.5%
1 26
18.8%
2 22
 
15.9%
7 17
 
12.3%
3 5
 
3.6%
5 4
 
2.9%
9 4
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
C 18
29.5%
I 12
19.7%
T 11
18.0%
V 11
18.0%
D 3
 
4.9%
N 3
 
4.9%
U 3
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 12
66.7%
. 3
 
16.7%
? 1
 
5.6%
？ 1
 
5.6%
· 1
 
5.6%
Space Separator
ValueCountFrequency (%)
1409
100.0%
Open Punctuation
ValueCountFrequency (%)
( 115
100.0%
Close Punctuation
ValueCountFrequency (%)
) 115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Symbol
ValueCountFrequency (%)
㉯ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31816
94.5%
Common 1798
 
5.3%
Latin 61
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 1641
 
5.2%
리 1556
 
4.9%
수 1518
 
4.8%
재 1211
 
3.8%
해 1159
 
3.6%
및 1125
 
3.5%
정 1041
 
3.3%
대 988
 
3.1%
치 980
 
3.1%
설 928
 
2.9%
Other values (267) 19669
61.8%
Common
ValueCountFrequency (%)
1409
78.4%
( 115
 
6.4%
) 115
 
6.4%
0 60
 
3.3%
1 26
 
1.4%
2 22
 
1.2%
7 17
 
0.9%
, 12
 
0.7%
3 5
 
0.3%
5 4
 
0.2%
Other values (6) 13
 
0.7%
Latin
ValueCountFrequency (%)
C 18
29.5%
I 12
19.7%
T 11
18.0%
V 11
18.0%
D 3
 
4.9%
N 3
 
4.9%
U 3
 
4.9%
Han
ValueCountFrequency (%)
岵 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31814
94.5%
ASCII 1857
 
5.5%
None 3
 
< 0.1%
CJK 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 1641
 
5.2%
리 1556
 
4.9%
수 1518
 
4.8%
재 1211
 
3.8%
해 1159
 
3.6%
및 1125
 
3.5%
정 1041
 
3.3%
대 988
 
3.1%
치 980
 
3.1%
설 928
 
2.9%
Other values (265) 19667
61.8%
ASCII
ValueCountFrequency (%)
1409
75.9%
( 115
 
6.2%
) 115
 
6.2%
0 60
 
3.2%
1 26
 
1.4%
2 22
 
1.2%
C 18
 
1.0%
7 17
 
0.9%
I 12
 
0.6%
, 12
 
0.6%
Other values (11) 51
 
2.7%
None
ValueCountFrequency (%)
㉯ 1
33.3%
？ 1
33.3%
· 1
33.3%
CJK
ValueCountFrequency (%)
岵 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅋ 1
100.0%

세부사업/세항
Text

MISSING 

Distinct881
Distinct (%)16.4%
Missing95
Missing (%)1.7%
Memory size42.8 KiB
2023-12-12T09:25:39.284916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length6.709972
Min length1

Characters and Unicode

Total characters35999
Distinct characters377
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique481 ?
Unique (%)9.0%

Sample

1st row공유재산관리
2nd row재해방제
3rd row치수
4th row재해방제
5th row재해대책
ValueCountFrequency (%)
도로건설 608
 
9.0%
재해대책 337
 
5.0%
치수관리 241
 
3.6%
회계및재산관리 230
 
3.4%
수해상습지개선 147
 
2.2%
도로건설사업 144
 
2.1%
치수재난관리 144
 
2.1%
항만수산 102
 
1.5%
치수재난 101
 
1.5%
해양수산 101
 
1.5%
Other values (1087) 4569
68.0%
2023-12-12T09:25:39.880975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1381
 
3.8%
관 1339
 
3.7%
수 1311
 
3.6%
리 1241
 
3.4%
도 1234
 
3.4%
설 1168
 
3.2%
지 1028
 
2.9%
재 1027
 
2.9%
로 977
 
2.7%
건 937
 
2.6%
Other values (367) 24356
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33802
93.9%
Space Separator 1381
 
3.8%
Decimal Number 282
 
0.8%
Open Punctuation 132
 
0.4%
Close Punctuation 129
 
0.4%
Dash Punctuation 124
 
0.3%
Uppercase Letter 61
 
0.2%
Other Punctuation 58
 
0.2%
Math Symbol 30
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 1339
 
4.0%
수 1311
 
3.9%
리 1241
 
3.7%
도 1234
 
3.7%
설 1168
 
3.5%
지 1028
 
3.0%
재 1027
 
3.0%
로 977
 
2.9%
건 937
 
2.8%
산 928
 
2.7%
Other values (338) 22612
66.9%
Decimal Number
ValueCountFrequency (%)
1 95
33.7%
7 62
22.0%
2 35
 
12.4%
4 28
 
9.9%
3 17
 
6.0%
0 16
 
5.7%
6 12
 
4.3%
5 7
 
2.5%
8 5
 
1.8%
9 5
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
C 27
44.3%
I 20
32.8%
D 4
 
6.6%
N 3
 
4.9%
U 3
 
4.9%
B 1
 
1.6%
T 1
 
1.6%
V 1
 
1.6%
P 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 30
51.7%
, 17
29.3%
· 7
 
12.1%
？ 3
 
5.2%
? 1
 
1.7%
Space Separator
ValueCountFrequency (%)
1381
100.0%
Open Punctuation
ValueCountFrequency (%)
( 132
100.0%
Close Punctuation
ValueCountFrequency (%)
) 129
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%
Math Symbol
ValueCountFrequency (%)
~ 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33801
93.9%
Common 2136
 
5.9%
Latin 61
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 1339
 
4.0%
수 1311
 
3.9%
리 1241
 
3.7%
도 1234
 
3.7%
설 1168
 
3.5%
지 1028
 
3.0%
재 1027
 
3.0%
로 977
 
2.9%
건 937
 
2.8%
산 928
 
2.7%
Other values (337) 22611
66.9%
Common
ValueCountFrequency (%)
1381
64.7%
( 132
 
6.2%
) 129
 
6.0%
- 124
 
5.8%
1 95
 
4.4%
7 62
 
2.9%
2 35
 
1.6%
~ 30
 
1.4%
. 30
 
1.4%
4 28
 
1.3%
Other values (10) 90
 
4.2%
Latin
ValueCountFrequency (%)
C 27
44.3%
I 20
32.8%
D 4
 
6.6%
N 3
 
4.9%
U 3
 
4.9%
B 1
 
1.6%
T 1
 
1.6%
V 1
 
1.6%
P 1
 
1.6%
Han
ValueCountFrequency (%)
贄 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33799
93.9%
ASCII 2187
 
6.1%
None 10
 
< 0.1%
Compat Jamo 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1381
63.1%
( 132
 
6.0%
) 129
 
5.9%
- 124
 
5.7%
1 95
 
4.3%
7 62
 
2.8%
2 35
 
1.6%
~ 30
 
1.4%
. 30
 
1.4%
4 28
 
1.3%
Other values (17) 141
 
6.4%
Hangul
ValueCountFrequency (%)
관 1339
 
4.0%
수 1311
 
3.9%
리 1241
 
3.7%
도 1234
 
3.7%
설 1168
 
3.5%
지 1028
 
3.0%
재 1027
 
3.0%
로 977
 
2.9%
건 937
 
2.8%
산 928
 
2.7%
Other values (336) 22609
66.9%
None
ValueCountFrequency (%)
· 7
70.0%
？ 3
30.0%
Compat Jamo
ValueCountFrequency (%)
ㅎ 2
100.0%
CJK
ValueCountFrequency (%)
贄 1
100.0%

편성목/세세항
Text

MISSING 

Distinct181
Distinct (%)3.6%
Missing378
Missing (%)6.9%
Memory size42.8 KiB
2023-12-12T09:25:40.095245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length4.8711137
Min length1

Characters and Unicode

Total characters24755
Distinct characters183
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)1.8%

Sample

1st row시
2nd row준용하천정비
3rd row낙
4th row준용하천정비
5th row양묘관리
ValueCountFrequency (%)
시설비및부대비 1043
20.3%
자체사업 970
18.9%
보조사업 883
17.2%
일반운영비 497
9.7%
보조사 351
 
6.8%
연구개발비 253
 
4.9%
경상적경비 244
 
4.8%
시설비 72
 
1.4%
주요 60
 
1.2%
주요사업 37
 
0.7%
Other values (172) 724
14.1%
2023-12-12T09:25:40.437745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 3343
 
13.5%
사 2501
 
10.1%
업 2058
 
8.3%
보 1360
 
5.5%
조 1292
 
5.2%
시 1244
 
5.0%
설 1226
 
5.0%
대 1102
 
4.5%
부 1093
 
4.4%
및 1082
 
4.4%
Other values (173) 8454
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24413
98.6%
Decimal Number 90
 
0.4%
Open Punctuation 77
 
0.3%
Close Punctuation 76
 
0.3%
Space Separator 62
 
0.3%
Other Punctuation 33
 
0.1%
Math Symbol 3
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 3343
13.7%
사 2501
 
10.2%
업 2058
 
8.4%
보 1360
 
5.6%
조 1292
 
5.3%
시 1244
 
5.1%
설 1226
 
5.0%
대 1102
 
4.5%
부 1093
 
4.5%
및 1082
 
4.4%
Other values (160) 8112
33.2%
Decimal Number
ValueCountFrequency (%)
2 28
31.1%
1 20
22.2%
0 14
15.6%
4 13
14.4%
3 7
 
7.8%
5 6
 
6.7%
6 2
 
2.2%
Open Punctuation
ValueCountFrequency (%)
( 77
100.0%
Close Punctuation
ValueCountFrequency (%)
) 76
100.0%
Space Separator
ValueCountFrequency (%)
62
100.0%
Other Punctuation
ValueCountFrequency (%)
, 33
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24413
98.6%
Common 342
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 3343
13.7%
사 2501
 
10.2%
업 2058
 
8.4%
보 1360
 
5.6%
조 1292
 
5.3%
시 1244
 
5.1%
설 1226
 
5.0%
대 1102
 
4.5%
부 1093
 
4.5%
및 1082
 
4.4%
Other values (160) 8112
33.2%
Common
ValueCountFrequency (%)
( 77
22.5%
) 76
22.2%
62
18.1%
, 33
9.6%
2 28
 
8.2%
1 20
 
5.8%
0 14
 
4.1%
4 13
 
3.8%
3 7
 
2.0%
5 6
 
1.8%
Other values (3) 6
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24412
98.6%
ASCII 342
 
1.4%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 3343
13.7%
사 2501
 
10.2%
업 2058
 
8.4%
보 1360
 
5.6%
조 1292
 
5.3%
시 1244
 
5.1%
설 1226
 
5.0%
대 1102
 
4.5%
부 1093
 
4.5%
및 1082
 
4.4%
Other values (159) 8111
33.2%
ASCII
ValueCountFrequency (%)
( 77
22.5%
) 76
22.2%
62
18.1%
, 33
9.6%
2 28
 
8.2%
1 20
 
5.8%
0 14
 
4.1%
4 13
 
3.8%
3 7
 
2.0%
5 6
 
1.8%
Other values (3) 6
 
1.8%
Compat Jamo
ValueCountFrequency (%)
ㅂ 1
100.0%

통계목/목
Text

MISSING 

Distinct111
Distinct (%)2.7%
Missing1333
Missing (%)24.4%
Memory size42.8 KiB
2023-12-12T09:25:40.639041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length5.6028592
Min length1

Characters and Unicode

Total characters23123
Distinct characters125
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)1.3%

Sample

1st row시
2nd row시
3rd row시
4th row시
5th row시설
ValueCountFrequency (%)
시설비 935
22.6%
시설비및부대비 915
22.1%
일반운영비 363
 
8.8%
사무관리비 248
 
6.0%
연구개발비 208
 
5.0%
시설비및부대비(시설비 192
 
4.6%
연구용역비 186
 
4.5%
공공운영비 149
 
3.6%
시설비등(시설비 143
 
3.5%
행사운영비 98
 
2.4%
Other values (101) 704
17.0%
2023-12-12T09:25:41.007767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 5586
24.2%
시 2861
12.4%
설 2826
12.2%
부 1293
 
5.6%
대 1287
 
5.6%
및 1261
 
5.5%
운 647
 
2.8%
영 643
 
2.8%
) 451
 
2.0%
( 450
 
1.9%
Other values (115) 5818
25.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22136
95.7%
Close Punctuation 451
 
2.0%
Open Punctuation 450
 
1.9%
Decimal Number 59
 
0.3%
Space Separator 19
 
0.1%
Other Punctuation 5
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 5586
25.2%
시 2861
12.9%
설 2826
12.8%
부 1293
 
5.8%
대 1287
 
5.8%
및 1261
 
5.7%
운 647
 
2.9%
영 643
 
2.9%
구 435
 
2.0%
연 433
 
2.0%
Other values (98) 4864
22.0%
Decimal Number
ValueCountFrequency (%)
0 22
37.3%
4 20
33.9%
5 6
 
10.2%
6 5
 
8.5%
2 2
 
3.4%
1 2
 
3.4%
9 1
 
1.7%
8 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
; 2
40.0%
: 1
20.0%
, 1
20.0%
. 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 451
100.0%
Open Punctuation
ValueCountFrequency (%)
( 450
100.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22136
95.7%
Common 987
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 5586
25.2%
시 2861
12.9%
설 2826
12.8%
부 1293
 
5.8%
대 1287
 
5.8%
및 1261
 
5.7%
운 647
 
2.9%
영 643
 
2.9%
구 435
 
2.0%
연 433
 
2.0%
Other values (98) 4864
22.0%
Common
ValueCountFrequency (%)
) 451
45.7%
( 450
45.6%
0 22
 
2.2%
4 20
 
2.0%
19
 
1.9%
5 6
 
0.6%
6 5
 
0.5%
- 2
 
0.2%
2 2
 
0.2%
1 2
 
0.2%
Other values (7) 8
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22134
95.7%
ASCII 987
 
4.3%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 5586
25.2%
시 2861
12.9%
설 2826
12.8%
부 1293
 
5.8%
대 1287
 
5.8%
및 1261
 
5.7%
운 647
 
2.9%
영 643
 
2.9%
구 435
 
2.0%
연 433
 
2.0%
Other values (97) 4862
22.0%
ASCII
ValueCountFrequency (%)
) 451
45.7%
( 450
45.6%
0 22
 
2.2%
4 20
 
2.0%
19
 
1.9%
5 6
 
0.6%
6 5
 
0.5%
- 2
 
0.2%
2 2
 
0.2%
1 2
 
0.2%
Other values (7) 8
 
0.8%
Compat Jamo
ValueCountFrequency (%)
ㅣ 2
100.0%

세목
Text

MISSING 

Distinct51
Distinct (%)3.7%
Missing4064
Missing (%)74.4%
Memory size42.8 KiB
2023-12-12T09:25:41.180934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length3
Mean length3.6561605
Min length1

Characters and Unicode

Total characters5104
Distinct characters78
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)1.9%

Sample

1st row시
2nd row학술용역비
3rd row민간위탁금
4th row일반수용비
5th row시설비
ValueCountFrequency (%)
시설비 845
60.5%
용역비 122
 
8.7%
감리비 95
 
6.8%
시설장비유지비 89
 
6.4%
시설부대비 51
 
3.7%
전산개발비 43
 
3.1%
학술용역비 31
 
2.2%
민간위탁금 25
 
1.8%
임차료 18
 
1.3%
사무관리비 17
 
1.2%
Other values (37) 61
 
4.4%
2023-12-12T09:25:41.458856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 1435
28.1%
시 999
19.6%
설 999
19.6%
용 165
 
3.2%
역 157
 
3.1%
리 114
 
2.2%
지 96
 
1.9%
감 95
 
1.9%
장 93
 
1.8%
유 93
 
1.8%
Other values (68) 858
16.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5010
98.2%
Open Punctuation 36
 
0.7%
Close Punctuation 36
 
0.7%
Decimal Number 20
 
0.4%
Other Punctuation 1
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 1435
28.6%
시 999
19.9%
설 999
19.9%
용 165
 
3.3%
역 157
 
3.1%
리 114
 
2.3%
지 96
 
1.9%
감 95
 
1.9%
장 93
 
1.9%
유 93
 
1.9%
Other values (59) 764
15.2%
Decimal Number
ValueCountFrequency (%)
0 9
45.0%
2 5
25.0%
1 3
 
15.0%
9 2
 
10.0%
8 1
 
5.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5010
98.2%
Common 94
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 1435
28.6%
시 999
19.9%
설 999
19.9%
용 165
 
3.3%
역 157
 
3.1%
리 114
 
2.3%
지 96
 
1.9%
감 95
 
1.9%
장 93
 
1.9%
유 93
 
1.9%
Other values (59) 764
15.2%
Common
ValueCountFrequency (%)
( 36
38.3%
) 36
38.3%
0 9
 
9.6%
2 5
 
5.3%
1 3
 
3.2%
9 2
 
2.1%
, 1
 
1.1%
8 1
 
1.1%
1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5010
98.2%
ASCII 94
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 1435
28.6%
시 999
19.9%
설 999
19.9%
용 165
 
3.3%
역 157
 
3.1%
리 114
 
2.3%
지 96
 
1.9%
감 95
 
1.9%
장 93
 
1.9%
유 93
 
1.9%
Other values (59) 764
15.2%
ASCII
ValueCountFrequency (%)
( 36
38.3%
) 36
38.3%
0 9
 
9.6%
2 5
 
5.3%
1 3
 
3.2%
9 2
 
2.1%
, 1
 
1.1%
8 1
 
1.1%
1
 
1.1%

금액
Real number (ℝ)

MISSING 

Distinct933
Distinct (%)80.6%
Missing4302
Missing (%)78.8%
Infinite0
Infinite (%)0.0%
Mean1.5572469 × 108
Minimum-6100000
Maximum7.6889 × 109
Zeros3
Zeros (%)0.1%
Negative2
Negative (%)< 0.1%
Memory size48.1 KiB
2023-12-12T09:25:41.590789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-6100000
5-th percentile1285000
Q14764000
median33629500
Q31.387359 × 108
95-th percentile6.45369 × 108
Maximum7.6889 × 109
Range7.695 × 109
Interquartile range (IQR)1.339719 × 108

Descriptive statistics

Standard deviation4.2253466 × 108
Coefficient of variation (CV)2.7133441
Kurtosis198.65948
Mean1.5572469 × 108
Median Absolute Deviation (MAD)31746000
Skewness12.144206
Sum1.8032919 × 1011
Variance1.7853554 × 1017
MonotonicityNot monotonic
2023-12-12T09:25:41.737146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300000000 12
 
0.2%
3600000 9
 
0.2%
1300000 7
 
0.1%
350000000 7
 
0.1%
3000000 7
 
0.1%
200000000 7
 
0.1%
1400000 7
 
0.1%
2500000 6
 
0.1%
370000000 6
 
0.1%
4700000 6
 
0.1%
Other values (923) 1084
 
19.9%
(Missing) 4302
78.8%
ValueCountFrequency (%)
-6100000 1
 
< 0.1%
-2950000 1
 
< 0.1%
0 3
0.1%
315000 1
 
< 0.1%
330000 1
 
< 0.1%
446000 1
 
< 0.1%
500000 2
< 0.1%
550000 4
0.1%
600000 1
 
< 0.1%
660000 1
 
< 0.1%
ValueCountFrequency (%)
7688900000 1
< 0.1%
7660200000 1
< 0.1%
5741000000 1
< 0.1%
1716850000 1
< 0.1%
1490637300 1
< 0.1%
1456800000 1
< 0.1%
1386000000 1
< 0.1%
1320000000 2
< 0.1%
1294378000 1
< 0.1%
1233327000 1
< 0.1%

Interactions

2023-12-12T09:25:33.813726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:25:33.227017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:25:33.496235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:25:33.912217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:25:33.306728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:25:33.583662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:25:34.003696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:25:33.397290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:25:33.696174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:25:41.833503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공사년도공사구분공사번호순번구분세목금액
공사년도1.0000.5970.6120.1750.0000.8250.000
공사구분0.5971.0000.4790.1790.0140.5580.157
공사번호0.6120.4791.0000.1420.0300.6870.046
순번0.1750.1790.1421.0000.0000.2400.000
구분0.0000.0140.0300.0001.0000.0000.000
세목0.8250.5580.6870.2400.0001.0000.096
금액0.0000.1570.0460.0000.0000.0961.000
2023-12-12T09:25:41.933376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공사구분순번구분
공사구분1.0000.0710.010
순번0.0711.0000.000
구분0.0100.0001.000
2023-12-12T09:25:42.028891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공사년도공사번호금액공사구분순번구분
공사년도1.0000.5090.0530.4080.1060.000
공사번호0.5091.000-0.2230.3060.0850.023
금액0.053-0.2231.0000.1290.0000.000
공사구분0.4080.3060.1291.0000.0710.010
순번0.1060.0850.0000.0711.0000.000
구분0.0000.0230.0000.0100.0001.000

Missing values

2023-12-12T09:25:34.411343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:25:34.584266image/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.
2023-12-12T09:25:34.746738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

공사년도공사구분공사번호부서코드순번구분부서/장정책/관단위(회계)/항세부사업/세항편성목/세세항통계목/목세목금액
01990공사511<NA>재무행정비회계및재산관리재산관리공유재산관리시<NA><NA><NA>
11990공사211<NA>지역개발도로치수치수사업재해방제준용하천정비<NA><NA><NA>
21990공사411<NA>건설부일반국토자원보존개발치수및재해대책치수낙<NA><NA><NA>
31990공사111<NA>지역개발비도로치수치수사업재해방제준용하천정비<NA><NA><NA>
41990공사311<NA>경제개발국토자원보존개발치수및재해대책재해대책<NA><NA><NA><NA>
51990공사611<NA>농수산비임업비조림사방관리조림관리양묘관리시<NA><NA>
61990공사711<NA>지역개발비도로치수치수사업재해방제준용하천정비<NA><NA><NA>
71990공사811<NA>지역개발비도로치수사업치수사업재해방제중용하천<NA><NA><NA>
81990공사1011<NA>일반행정비재무행정비회계및재산관리재산관리공유<NA><NA><NA>
91990공사1211<NA>일반행정비재무행정비재산관리회계및재산관리공유<NA><NA><NA>
공사년도공사구분공사번호부서코드순번구분부서/장정책/관단위(회계)/항세부사업/세항편성목/세세항통계목/목세목금액
54502008용역111일반정보화담당관첨단정보경남실현전자도정추진행정정보시스템운영일반운영비공공운영비<NA><NA>
54512004용역211<NA>경제개발국토자원보존개발산림녹지운영산림녹지사업자체사업일반운영비<NA><NA>
54522000용역5611<NA>경제개발국토자원보존개발치수및재해대책재해대책보조사업시설비및부대비<NA><NA>
54532006기타4611특별가나다라마<NA><NA>1000000
54542011구매1611일반정보통계담당관첨단정보경남실현정보보호운영정보보호운영지원일반운영비사무관리비<NA><NA>
54552011공사27311일반어업진흥과연근해어업자원회복 및 구조개편연근해어업 질서 확립어업지도선운영시설비및부대비시설비<NA><NA>
54562011공사27811일반회계과회계및재산관리쾌적한청사관리별관 청사증축 및 본관개보수(계속비)시설비및부대비시설비<NA><NA>
54572012공사18111일반소방행정과소방력 보강소방청사 시설확충 및 개선소방청사 신·증축시설비및부대비시설비<NA><NA>
54582010용역9711일반공보관도정홍보기능강화도정시책인터넷및케이블TV를통한홍보인터넷방송콘텐츠구축및운영일반운영비사무관리비<NA><NA>
54592011공사27011일반인사과만족하는 직장생활 조성효율적이고과학적인기록물관리행정자료실운영시설비및부대비시설비<NA><NA>