Overview

Dataset statistics

Number of variables41
Number of observations519
Missing cells2760
Missing cells (%)13.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory171.9 KiB
Average record size in memory339.3 B

Variable types

Numeric8
Text14
DateTime3
Categorical13
Boolean3

Dataset

Description본 데이터는 2006 ~ 2018년도 환경신기술 인검증 사후평가 관리현황(사후평가ID, 공사명, 주소, 발주처, 계약일자, 준공일자, 신기술공종 공사금액 등) 정보를 제공합니다.
Author한국환경산업기술원
URLhttps://www.data.go.kr/data/15071537/fileData.do

Alerts

시공단계_1 has constant value ""Constant
운전단계_1 has constant value ""Constant
승인여부 has constant value ""Constant
계약형태_기타 is highly imbalanced (84.1%)Imbalance
시공단계_기타 is highly imbalanced (74.3%)Imbalance
시공단계_발생건수 is highly imbalanced (51.4%)Imbalance
시공단계_조치결과 is highly imbalanced (75.8%)Imbalance
운전단계_조치결과 is highly imbalanced (73.0%)Imbalance
주소1 has 173 (33.3%) missing valuesMissing
주소2 has 330 (63.6%) missing valuesMissing
착공일자 has 27 (5.2%) missing valuesMissing
용량(수량) has 14 (2.7%) missing valuesMissing
계약번호 has 171 (32.9%) missing valuesMissing
입찰공고번호 has 320 (61.7%) missing valuesMissing
공사비_계획 has 16 (3.1%) missing valuesMissing
공사비_실제 has 13 (2.5%) missing valuesMissing
공사기간_계획 has 21 (4.0%) missing valuesMissing
공사기간_실제 has 17 (3.3%) missing valuesMissing
시공단계 has 47 (9.1%) missing valuesMissing
운전단계 has 96 (18.5%) missing valuesMissing
운전단계_기타 has 382 (73.6%) missing valuesMissing
시공단계_1 has 451 (86.9%) missing valuesMissing
운전단계_1 has 441 (85.0%) missing valuesMissing
운전단계_발생건수 has 241 (46.4%) missing valuesMissing
공사비_실제 is highly skewed (γ1 = 22.40825755)Skewed
사후평가순번 has unique valuesUnique
신기술공종 공사금액 has 7 (1.3%) zerosZeros
공사비_계획 has 51 (9.8%) zerosZeros
공사비_실제 has 58 (11.2%) zerosZeros
운전단계_발생건수 has 258 (49.7%) zerosZeros

Reproduction

Analysis started2023-12-11 23:05:58.895347
Analysis finished2023-12-11 23:06:00.216002
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

신청서ID
Real number (ℝ)

Distinct138
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8438.0501
Minimum572
Maximum15429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T08:06:00.278912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum572
5-th percentile884
Q14238
median9284
Q312149
95-th percentile15377.9
Maximum15429
Range14857
Interquartile range (IQR)7911

Descriptive statistics

Standard deviation4687.2244
Coefficient of variation (CV)0.55548668
Kurtosis-1.172407
Mean8438.0501
Median Absolute Deviation (MAD)3547
Skewness-0.25497609
Sum4379348
Variance21970073
MonotonicityNot monotonic
2023-12-12T08:06:00.434592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9598 42
 
8.1%
12149 39
 
7.5%
11985 29
 
5.6%
15386 24
 
4.6%
9284 22
 
4.2%
13066 13
 
2.5%
11299 12
 
2.3%
884 12
 
2.3%
13989 11
 
2.1%
3922 11
 
2.1%
Other values (128) 304
58.6%
ValueCountFrequency (%)
572 1
0.2%
654 2
0.4%
659 1
0.2%
737 2
0.4%
751 1
0.2%
763 1
0.2%
772 1
0.2%
780 1
0.2%
786 1
0.2%
801 1
0.2%
ValueCountFrequency (%)
15429 2
 
0.4%
15386 24
4.6%
15377 2
 
0.4%
15366 4
 
0.8%
15331 1
 
0.2%
15295 1
 
0.2%
15105 2
 
0.4%
15084 1
 
0.2%
15065 5
 
1.0%
14898 3
 
0.6%

사후평가순번
Real number (ℝ)

UNIQUE 

Distinct519
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean389.36802
Minimum15
Maximum734
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T08:06:00.560474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile44.9
Q1161.5
median440
Q3591.5
95-th percentile708.1
Maximum734
Range719
Interquartile range (IQR)430

Descriptive statistics

Standard deviation229.63145
Coefficient of variation (CV)0.58975428
Kurtosis-1.473787
Mean389.36802
Median Absolute Deviation (MAD)215
Skewness-0.17613546
Sum202082
Variance52730.604
MonotonicityNot monotonic
2023-12-12T08:06:00.682269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
477 1
 
0.2%
52 1
 
0.2%
39 1
 
0.2%
31 1
 
0.2%
24 1
 
0.2%
15 1
 
0.2%
84 1
 
0.2%
82 1
 
0.2%
80 1
 
0.2%
77 1
 
0.2%
Other values (509) 509
98.1%
ValueCountFrequency (%)
15 1
0.2%
18 1
0.2%
21 1
0.2%
22 1
0.2%
23 1
0.2%
24 1
0.2%
25 1
0.2%
26 1
0.2%
27 1
0.2%
28 1
0.2%
ValueCountFrequency (%)
734 1
0.2%
733 1
0.2%
732 1
0.2%
731 1
0.2%
730 1
0.2%
729 1
0.2%
728 1
0.2%
727 1
0.2%
726 1
0.2%
725 1
0.2%

공사명
Text

Distinct488
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2023-12-12T08:06:00.918182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length45
Mean length24.549133
Min length8

Characters and Unicode

Total characters12741
Distinct characters441
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique462 ?
Unique (%)89.0%

Sample

1st row복대동일원 하수관 비굴착 보수공사 중 비굴착 전체보수(SEPR공법),부분보수(PRSP공법)공사
2nd row흥덕구 가경동 하수관 비굴착 전체보수공사
3rd row도시계획시설 내 맨홀인상공사
4th row2015년도 하수도 맨홀 인상 공사
5th row2015년 하반기 검단지역 불량맨홀 정비공사
ValueCountFrequency (%)
정비공사 58
 
2.6%
보수공사 41
 
1.8%
중 33
 
1.5%
관내 32
 
1.4%
주변 29
 
1.3%
외 28
 
1.2%
폐기물처리용역 25
 
1.1%
및 25
 
1.1%
비굴착 25
 
1.1%
일원 24
 
1.1%
Other values (1137) 1924
85.7%
2023-12-12T08:06:01.303197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1727
 
13.6%
공 579
 
4.5%
사 538
 
4.2%
수 419
 
3.3%
설 237
 
1.9%
2 209
 
1.6%
시 203
 
1.6%
( 201
 
1.6%
) 201
 
1.6%
1 199
 
1.6%
Other values (431) 8228
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9444
74.1%
Space Separator 1727
 
13.6%
Decimal Number 863
 
6.8%
Open Punctuation 205
 
1.6%
Close Punctuation 205
 
1.6%
Uppercase Letter 105
 
0.8%
Dash Punctuation 80
 
0.6%
Other Punctuation 46
 
0.4%
Lowercase Letter 38
 
0.3%
Math Symbol 26
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 579
 
6.1%
사 538
 
5.7%
수 419
 
4.4%
설 237
 
2.5%
시 203
 
2.1%
비 196
 
2.1%
구 192
 
2.0%
관 186
 
2.0%
하 182
 
1.9%
정 179
 
1.9%
Other values (372) 6533
69.2%
Uppercase Letter
ValueCountFrequency (%)
S 16
15.2%
T 13
12.4%
B 13
12.4%
P 12
11.4%
R 9
8.6%
L 9
8.6%
M 7
6.7%
A 5
 
4.8%
F 4
 
3.8%
D 4
 
3.8%
Other values (8) 13
12.4%
Lowercase Letter
ValueCountFrequency (%)
e 8
21.1%
i 7
18.4%
n 4
10.5%
r 3
 
7.9%
t 3
 
7.9%
o 2
 
5.3%
s 2
 
5.3%
a 2
 
5.3%
k 1
 
2.6%
d 1
 
2.6%
Other values (5) 5
13.2%
Decimal Number
ValueCountFrequency (%)
2 209
24.2%
1 199
23.1%
0 116
13.4%
3 66
 
7.6%
6 57
 
6.6%
4 49
 
5.7%
8 49
 
5.7%
5 47
 
5.4%
7 43
 
5.0%
9 28
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 22
47.8%
; 5
 
10.9%
& 5
 
10.9%
# 5
 
10.9%
. 4
 
8.7%
/ 2
 
4.3%
: 2
 
4.3%
· 1
 
2.2%
Open Punctuation
ValueCountFrequency (%)
( 201
98.0%
[ 4
 
2.0%
Close Punctuation
ValueCountFrequency (%)
) 201
98.0%
] 4
 
2.0%
Space Separator
ValueCountFrequency (%)
1727
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Math Symbol
ValueCountFrequency (%)
~ 26
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9444
74.1%
Common 3154
 
24.8%
Latin 143
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 579
 
6.1%
사 538
 
5.7%
수 419
 
4.4%
설 237
 
2.5%
시 203
 
2.1%
비 196
 
2.1%
구 192
 
2.0%
관 186
 
2.0%
하 182
 
1.9%
정 179
 
1.9%
Other values (372) 6533
69.2%
Latin
ValueCountFrequency (%)
S 16
 
11.2%
T 13
 
9.1%
B 13
 
9.1%
P 12
 
8.4%
R 9
 
6.3%
L 9
 
6.3%
e 8
 
5.6%
M 7
 
4.9%
i 7
 
4.9%
A 5
 
3.5%
Other values (23) 44
30.8%
Common
ValueCountFrequency (%)
1727
54.8%
2 209
 
6.6%
( 201
 
6.4%
) 201
 
6.4%
1 199
 
6.3%
0 116
 
3.7%
- 80
 
2.5%
3 66
 
2.1%
6 57
 
1.8%
4 49
 
1.6%
Other values (16) 249
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9444
74.1%
ASCII 3296
 
25.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1727
52.4%
2 209
 
6.3%
( 201
 
6.1%
) 201
 
6.1%
1 199
 
6.0%
0 116
 
3.5%
- 80
 
2.4%
3 66
 
2.0%
6 57
 
1.7%
4 49
 
1.5%
Other values (48) 391
 
11.9%
Hangul
ValueCountFrequency (%)
공 579
 
6.1%
사 538
 
5.7%
수 419
 
4.4%
설 237
 
2.5%
시 203
 
2.1%
비 196
 
2.1%
구 192
 
2.0%
관 186
 
2.0%
하 182
 
1.9%
정 179
 
1.9%
Other values (372) 6533
69.2%
None
ValueCountFrequency (%)
· 1
100.0%

주소1
Text

MISSING 

Distinct301
Distinct (%)87.0%
Missing173
Missing (%)33.3%
Memory size4.2 KiB
2023-12-12T08:06:01.625629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length38
Mean length18.690751
Min length2

Characters and Unicode

Total characters6467
Distinct characters277
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique270 ?
Unique (%)78.0%

Sample

1st row충북 청주시 흥덕구 복대동 일원
2nd row충북 청주시 흥덕구 가경동 일원
3rd row인천 부평구 부개동 경인로 1056 2층 서울특별시 금천구 두산로 70, 현대지식산업센터 B-1307
4th row인천 계양구 작전동 주부토로 399 일원
5th row인천 서구 심곡동
ValueCountFrequency (%)
일원 61
 
3.8%
경기 56
 
3.5%
서울 44
 
2.8%
인천 34
 
2.1%
경기도 29
 
1.8%
충남 20
 
1.3%
전남 20
 
1.3%
서구 17
 
1.1%
인천광역시 17
 
1.1%
화성시 16
 
1.0%
Other values (765) 1283
80.3%
2023-12-12T08:06:02.124623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1256
 
19.4%
동 220
 
3.4%
구 216
 
3.3%
시 213
 
3.3%
경 135
 
2.1%
리 129
 
2.0%
1 128
 
2.0%
천 125
 
1.9%
서 115
 
1.8%
원 112
 
1.7%
Other values (267) 3818
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4359
67.4%
Space Separator 1256
 
19.4%
Decimal Number 677
 
10.5%
Dash Punctuation 52
 
0.8%
Other Punctuation 40
 
0.6%
Close Punctuation 21
 
0.3%
Open Punctuation 21
 
0.3%
Math Symbol 14
 
0.2%
Uppercase Letter 14
 
0.2%
Lowercase Letter 13
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 220
 
5.0%
구 216
 
5.0%
시 213
 
4.9%
경 135
 
3.1%
리 129
 
3.0%
천 125
 
2.9%
서 115
 
2.6%
원 112
 
2.6%
남 107
 
2.5%
면 104
 
2.4%
Other values (240) 2883
66.1%
Decimal Number
ValueCountFrequency (%)
1 128
18.9%
2 102
15.1%
3 93
13.7%
0 70
10.3%
4 64
9.5%
5 51
 
7.5%
8 51
 
7.5%
6 41
 
6.1%
7 41
 
6.1%
9 36
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
B 6
42.9%
A 2
 
14.3%
G 2
 
14.3%
I 2
 
14.3%
L 2
 
14.3%
Lowercase Letter
ValueCountFrequency (%)
i 3
23.1%
e 3
23.1%
z 3
23.1%
t 2
15.4%
p 2
15.4%
Other Punctuation
ValueCountFrequency (%)
, 38
95.0%
. 2
 
5.0%
Space Separator
ValueCountFrequency (%)
1256
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4359
67.4%
Common 2081
32.2%
Latin 27
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 220
 
5.0%
구 216
 
5.0%
시 213
 
4.9%
경 135
 
3.1%
리 129
 
3.0%
천 125
 
2.9%
서 115
 
2.6%
원 112
 
2.6%
남 107
 
2.5%
면 104
 
2.4%
Other values (240) 2883
66.1%
Common
ValueCountFrequency (%)
1256
60.4%
1 128
 
6.2%
2 102
 
4.9%
3 93
 
4.5%
0 70
 
3.4%
4 64
 
3.1%
- 52
 
2.5%
5 51
 
2.5%
8 51
 
2.5%
6 41
 
2.0%
Other values (7) 173
 
8.3%
Latin
ValueCountFrequency (%)
B 6
22.2%
i 3
11.1%
e 3
11.1%
z 3
11.1%
t 2
 
7.4%
p 2
 
7.4%
A 2
 
7.4%
G 2
 
7.4%
I 2
 
7.4%
L 2
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4359
67.4%
ASCII 2108
32.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1256
59.6%
1 128
 
6.1%
2 102
 
4.8%
3 93
 
4.4%
0 70
 
3.3%
4 64
 
3.0%
- 52
 
2.5%
5 51
 
2.4%
8 51
 
2.4%
6 41
 
1.9%
Other values (17) 200
 
9.5%
Hangul
ValueCountFrequency (%)
동 220
 
5.0%
구 216
 
5.0%
시 213
 
4.9%
경 135
 
3.1%
리 129
 
3.0%
천 125
 
2.9%
서 115
 
2.6%
원 112
 
2.6%
남 107
 
2.5%
면 104
 
2.4%
Other values (240) 2883
66.1%

주소2
Text

MISSING 

Distinct152
Distinct (%)80.4%
Missing330
Missing (%)63.6%
Memory size4.2 KiB
2023-12-12T08:06:02.354841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length26
Mean length13.047619
Min length2

Characters and Unicode

Total characters2466
Distinct characters218
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)67.2%

Sample

1st row중구 관내
2nd row남구
3rd row가평군
4th row남부
5th row금천구 두산로
ValueCountFrequency (%)
일원 42
 
7.2%
인천광역시 14
 
2.4%
경기도 13
 
2.2%
관내 10
 
1.7%
부평구 8
 
1.4%
서울특별시 8
 
1.4%
충남 8
 
1.4%
화성시 7
 
1.2%
양산시 7
 
1.2%
중구 6
 
1.0%
Other values (316) 459
78.9%
2023-12-12T08:06:02.679638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
393
 
15.9%
시 116
 
4.7%
구 96
 
3.9%
동 78
 
3.2%
원 62
 
2.5%
천 53
 
2.1%
일 47
 
1.9%
1 47
 
1.9%
도 47
 
1.9%
서 46
 
1.9%
Other values (208) 1481
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1769
71.7%
Space Separator 393
 
15.9%
Decimal Number 224
 
9.1%
Other Punctuation 23
 
0.9%
Dash Punctuation 19
 
0.8%
Close Punctuation 15
 
0.6%
Open Punctuation 15
 
0.6%
Math Symbol 3
 
0.1%
Uppercase Letter 3
 
0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 116
 
6.6%
구 96
 
5.4%
동 78
 
4.4%
원 62
 
3.5%
천 53
 
3.0%
일 47
 
2.7%
도 47
 
2.7%
서 46
 
2.6%
로 44
 
2.5%
리 44
 
2.5%
Other values (187) 1136
64.2%
Decimal Number
ValueCountFrequency (%)
1 47
21.0%
2 41
18.3%
3 25
11.2%
6 23
10.3%
5 20
8.9%
7 19
8.5%
0 17
 
7.6%
9 14
 
6.2%
4 13
 
5.8%
8 5
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 20
87.0%
/ 3
 
13.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
393
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1769
71.7%
Common 694
 
28.1%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 116
 
6.6%
구 96
 
5.4%
동 78
 
4.4%
원 62
 
3.5%
천 53
 
3.0%
일 47
 
2.7%
도 47
 
2.7%
서 46
 
2.6%
로 44
 
2.5%
리 44
 
2.5%
Other values (187) 1136
64.2%
Common
ValueCountFrequency (%)
393
56.6%
1 47
 
6.8%
2 41
 
5.9%
3 25
 
3.6%
6 23
 
3.3%
5 20
 
2.9%
, 20
 
2.9%
7 19
 
2.7%
- 19
 
2.7%
0 17
 
2.4%
Other values (9) 70
 
10.1%
Latin
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1769
71.7%
ASCII 695
 
28.2%
Punctuation 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
393
56.5%
1 47
 
6.8%
2 41
 
5.9%
3 25
 
3.6%
6 23
 
3.3%
5 20
 
2.9%
, 20
 
2.9%
7 19
 
2.7%
- 19
 
2.7%
0 17
 
2.4%
Other values (9) 71
 
10.2%
Hangul
ValueCountFrequency (%)
시 116
 
6.6%
구 96
 
5.4%
동 78
 
4.4%
원 62
 
3.5%
천 53
 
3.0%
일 47
 
2.7%
도 47
 
2.7%
서 46
 
2.6%
로 44
 
2.5%
리 44
 
2.5%
Other values (187) 1136
64.2%
Punctuation
ValueCountFrequency (%)
’ 1
50.0%
‘ 1
50.0%

발주처기관코드
Text

Distinct139
Distinct (%)26.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2023-12-12T08:06:02.890604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4152
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)11.9%

Sample

1st rowSIGU0135
2nd rowSIGU0135
3rd rowSIGU0107
4th rowSIGU0053
5th rowSIGU0053
ValueCountFrequency (%)
sigu0248 43
 
8.3%
sigu0053 27
 
5.2%
sigu0001 25
 
4.8%
sigu0251 21
 
4.0%
sigu0257 18
 
3.5%
sigu0044 15
 
2.9%
sigu0249 14
 
2.7%
sigu0109 12
 
2.3%
sigu0135 10
 
1.9%
sigu0150 10
 
1.9%
Other values (129) 324
62.4%
2023-12-12T08:06:03.203740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 892
21.5%
S 519
12.5%
I 519
12.5%
G 519
12.5%
U 519
12.5%
2 262
 
6.3%
1 230
 
5.5%
5 159
 
3.8%
4 135
 
3.3%
8 108
 
2.6%
Other values (4) 290
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2076
50.0%
Uppercase Letter 2076
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 892
43.0%
2 262
 
12.6%
1 230
 
11.1%
5 159
 
7.7%
4 135
 
6.5%
8 108
 
5.2%
3 89
 
4.3%
7 79
 
3.8%
9 75
 
3.6%
6 47
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
S 519
25.0%
I 519
25.0%
G 519
25.0%
U 519
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2076
50.0%
Latin 2076
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 892
43.0%
2 262
 
12.6%
1 230
 
11.1%
5 159
 
7.7%
4 135
 
6.5%
8 108
 
5.2%
3 89
 
4.3%
7 79
 
3.8%
9 75
 
3.6%
6 47
 
2.3%
Latin
ValueCountFrequency (%)
S 519
25.0%
I 519
25.0%
G 519
25.0%
U 519
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4152
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 892
21.5%
S 519
12.5%
I 519
12.5%
G 519
12.5%
U 519
12.5%
2 262
 
6.3%
1 230
 
5.5%
5 159
 
3.8%
4 135
 
3.3%
8 108
 
2.6%
Other values (4) 290
 
7.0%

발주처부서
Text

Distinct256
Distinct (%)49.3%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2023-12-12T08:06:03.398078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length6.8998073
Min length3

Characters and Unicode

Total characters3581
Distinct characters209
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique178 ?
Unique (%)34.3%

Sample

1st row흥덕구청 건설교통과
2nd row흥덕구청 건설교통과
3rd row건설과
4th row계양구청 건설과
5th row서구청 검단출장소
ValueCountFrequency (%)
건설과 49
 
7.2%
치수과 21
 
3.1%
하수과 19
 
2.8%
공원녹지과 15
 
2.2%
안전치수과 12
 
1.8%
상하수도사업소 12
 
1.8%
환경시설처 10
 
1.5%
기후변화대응과 10
 
1.5%
도로과 10
 
1.5%
수도과 9
 
1.3%
Other values (292) 518
75.6%
2023-12-12T08:06:03.684921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 295
 
8.2%
수 176
 
4.9%
167
 
4.7%
사 158
 
4.4%
부 141
 
3.9%
업 135
 
3.8%
도 134
 
3.7%
설 115
 
3.2%
지 90
 
2.5%
관 89
 
2.5%
Other values (199) 2081
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3391
94.7%
Space Separator 167
 
4.7%
Decimal Number 16
 
0.4%
Uppercase Letter 3
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 295
 
8.7%
수 176
 
5.2%
사 158
 
4.7%
부 141
 
4.2%
업 135
 
4.0%
도 134
 
4.0%
설 115
 
3.4%
지 90
 
2.7%
관 89
 
2.6%
리 85
 
2.5%
Other values (189) 1973
58.2%
Decimal Number
ValueCountFrequency (%)
1 7
43.8%
2 5
31.2%
3 3
18.8%
7 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
X 1
33.3%
B 1
33.3%
I 1
33.3%
Space Separator
ValueCountFrequency (%)
167
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3391
94.7%
Common 187
 
5.2%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 295
 
8.7%
수 176
 
5.2%
사 158
 
4.7%
부 141
 
4.2%
업 135
 
4.0%
도 134
 
4.0%
설 115
 
3.4%
지 90
 
2.7%
관 89
 
2.6%
리 85
 
2.5%
Other values (189) 1973
58.2%
Common
ValueCountFrequency (%)
167
89.3%
1 7
 
3.7%
2 5
 
2.7%
3 3
 
1.6%
( 2
 
1.1%
) 2
 
1.1%
7 1
 
0.5%
Latin
ValueCountFrequency (%)
X 1
33.3%
B 1
33.3%
I 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3391
94.7%
ASCII 190
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 295
 
8.7%
수 176
 
5.2%
사 158
 
4.7%
부 141
 
4.2%
업 135
 
4.0%
도 134
 
4.0%
설 115
 
3.4%
지 90
 
2.7%
관 89
 
2.6%
리 85
 
2.5%
Other values (189) 1973
58.2%
ASCII
ValueCountFrequency (%)
167
87.9%
1 7
 
3.7%
2 5
 
2.6%
3 3
 
1.6%
( 2
 
1.1%
) 2
 
1.1%
X 1
 
0.5%
B 1
 
0.5%
I 1
 
0.5%
7 1
 
0.5%

계약일자
Date

Distinct426
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum2006-05-29 00:00:00
Maximum2018-12-21 00:00:00
2023-12-12T08:06:03.804584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:03.917536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공일자
Date

MISSING 

Distinct397
Distinct (%)80.7%
Missing27
Missing (%)5.2%
Memory size4.2 KiB
Minimum2007-01-09 00:00:00
Maximum2018-12-21 00:00:00
2023-12-12T08:06:04.288599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:04.404290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

준공일자
Date

Distinct390
Distinct (%)75.1%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum2008-04-17 00:00:00
Maximum2018-12-31 00:00:00
2023-12-12T08:06:04.516898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:04.632360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

용량(수량)
Text

MISSING 

Distinct442
Distinct (%)87.5%
Missing14
Missing (%)2.7%
Memory size4.2 KiB
2023-12-12T08:06:04.988725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length35
Mean length8.0079208
Min length1

Characters and Unicode

Total characters4044
Distinct characters170
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique407 ?
Unique (%)80.6%

Sample

1st row하수관 D400~D600, L=168m
2nd row하수관 D400, L=51m
3rd row94EA
4th row33개소
5th rowD450,L=881m
ValueCountFrequency (%)
1 13
 
1.9%
톤/일 12
 
1.7%
1식 12
 
1.7%
9
 
1.3%
정비 8
 
1.1%
불량맨홀 8
 
1.1%
d=700mm 7
 
1.0%
1대 7
 
1.0%
d450mm 6
 
0.9%
맨홀 6
 
0.9%
Other values (528) 612
87.4%
2023-12-12T08:06:05.590801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 517
 
12.8%
1 293
 
7.2%
m 272
 
6.7%
2 213
 
5.3%
195
 
4.8%
5 180
 
4.5%
3 168
 
4.2%
8 139
 
3.4%
4 127
 
3.1%
6 125
 
3.1%
Other values (160) 1815
44.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1969
48.7%
Other Letter 732
 
18.1%
Lowercase Letter 374
 
9.2%
Other Punctuation 263
 
6.5%
Uppercase Letter 228
 
5.6%
Space Separator 195
 
4.8%
Math Symbol 137
 
3.4%
Other Symbol 57
 
1.4%
Open Punctuation 39
 
1.0%
Close Punctuation 39
 
1.0%
Other values (3) 11
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 95
 
13.0%
소 82
 
11.2%
톤 73
 
10.0%
일 53
 
7.2%
포 29
 
4.0%
수 25
 
3.4%
비 20
 
2.7%
맨 18
 
2.5%
홀 18
 
2.5%
정 17
 
2.3%
Other values (102) 302
41.3%
Lowercase Letter
ValueCountFrequency (%)
m 272
72.7%
d 17
 
4.5%
a 12
 
3.2%
y 11
 
2.9%
k 10
 
2.7%
n 10
 
2.7%
t 9
 
2.4%
o 7
 
1.9%
g 7
 
1.9%
i 4
 
1.1%
Other values (6) 15
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
D 110
48.2%
L 77
33.8%
M 10
 
4.4%
A 8
 
3.5%
E 6
 
2.6%
T 4
 
1.8%
N 3
 
1.3%
R 2
 
0.9%
W 2
 
0.9%
C 2
 
0.9%
Other values (4) 4
 
1.8%
Decimal Number
ValueCountFrequency (%)
0 517
26.3%
1 293
14.9%
2 213
10.8%
5 180
 
9.1%
3 168
 
8.5%
8 139
 
7.1%
4 127
 
6.4%
6 125
 
6.3%
9 107
 
5.4%
7 100
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 122
46.4%
/ 83
31.6%
. 43
 
16.3%
: 14
 
5.3%
* 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
= 105
76.6%
~ 28
 
20.4%
∼ 4
 
2.9%
Other Symbol
ValueCountFrequency (%)
㎥ 24
42.1%
㎡ 23
40.4%
㎜ 10
17.5%
Other Number
ValueCountFrequency (%)
³ 5
71.4%
² 2
 
28.6%
Space Separator
ValueCountFrequency (%)
195
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2711
67.0%
Hangul 732
 
18.1%
Latin 601
 
14.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 95
 
13.0%
소 82
 
11.2%
톤 73
 
10.0%
일 53
 
7.2%
포 29
 
4.0%
수 25
 
3.4%
비 20
 
2.7%
맨 18
 
2.5%
홀 18
 
2.5%
정 17
 
2.3%
Other values (102) 302
41.3%
Common
ValueCountFrequency (%)
0 517
19.1%
1 293
10.8%
2 213
 
7.9%
195
 
7.2%
5 180
 
6.6%
3 168
 
6.2%
8 139
 
5.1%
4 127
 
4.7%
6 125
 
4.6%
, 122
 
4.5%
Other values (19) 632
23.3%
Latin
ValueCountFrequency (%)
m 272
45.3%
D 110
18.3%
L 77
 
12.8%
d 17
 
2.8%
a 12
 
2.0%
y 11
 
1.8%
M 10
 
1.7%
k 10
 
1.7%
n 10
 
1.7%
t 9
 
1.5%
Other values (19) 63
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3243
80.2%
Hangul 732
 
18.1%
CJK Compat 57
 
1.4%
None 7
 
0.2%
Math Operators 4
 
0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 517
15.9%
1 293
 
9.0%
m 272
 
8.4%
2 213
 
6.6%
195
 
6.0%
5 180
 
5.6%
3 168
 
5.2%
8 139
 
4.3%
4 127
 
3.9%
6 125
 
3.9%
Other values (41) 1014
31.3%
Hangul
ValueCountFrequency (%)
개 95
 
13.0%
소 82
 
11.2%
톤 73
 
10.0%
일 53
 
7.2%
포 29
 
4.0%
수 25
 
3.4%
비 20
 
2.7%
맨 18
 
2.5%
홀 18
 
2.5%
정 17
 
2.3%
Other values (102) 302
41.3%
CJK Compat
ValueCountFrequency (%)
㎥ 24
42.1%
㎡ 23
40.4%
㎜ 10
17.5%
None
ValueCountFrequency (%)
³ 5
71.4%
² 2
 
28.6%
Math Operators
ValueCountFrequency (%)
∼ 4
100.0%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 1
100.0%

총공사금액
Real number (ℝ)

Distinct485
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12864770
Minimum0
Maximum1.0670462 × 109
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T08:06:05.810203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5525.9
Q129308.5
median171732
Q31000263
95-th percentile69795804
Maximum1.0670462 × 109
Range1.0670462 × 109
Interquartile range (IQR)970954.5

Descriptive statistics

Standard deviation60895774
Coefficient of variation (CV)4.7335301
Kurtosis180.93403
Mean12864770
Median Absolute Deviation (MAD)164062
Skewness11.660787
Sum6.6768155 × 109
Variance3.7082953 × 1015
MonotonicityNot monotonic
2023-12-12T08:06:06.095814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
145696504 3
 
0.6%
2000483 3
 
0.6%
50468 3
 
0.6%
63151000 3
 
0.6%
69795804 2
 
0.4%
1214290 2
 
0.4%
73067 2
 
0.4%
32176000 2
 
0.4%
14051416 2
 
0.4%
101452 2
 
0.4%
Other values (475) 495
95.4%
ValueCountFrequency (%)
0 1
0.2%
436 1
0.2%
459 2
0.4%
795 1
0.2%
918 1
0.2%
979 1
0.2%
1118 1
0.2%
1638 1
0.2%
2409 1
0.2%
3083 1
0.2%
ValueCountFrequency (%)
1067046200 1
 
0.2%
426800000 1
 
0.2%
381015000 1
 
0.2%
289316265 1
 
0.2%
199045000 1
 
0.2%
189021280 1
 
0.2%
181636000 2
0.4%
161130000 1
 
0.2%
159050000 1
 
0.2%
145696504 3
0.6%

신기술공종 공사금액
Real number (ℝ)

ZEROS 

Distinct493
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3798439.9
Minimum0
Maximum1.0670462 × 109
Zeros7
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T08:06:06.270669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3718.8
Q119569
median80300
Q3365095
95-th percentile2317455
Maximum1.0670462 × 109
Range1.0670462 × 109
Interquartile range (IQR)345526

Descriptive statistics

Standard deviation50747514
Coefficient of variation (CV)13.360094
Kurtosis382.82934
Mean3798439.9
Median Absolute Deviation (MAD)72878
Skewness18.977792
Sum1.9713903 × 109
Variance2.5753102 × 1015
MonotonicityNot monotonic
2023-12-12T08:06:06.416286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7
 
1.3%
50468 3
 
0.6%
207000 2
 
0.4%
2317455 2
 
0.4%
40338 2
 
0.4%
52752 2
 
0.4%
5135000 2
 
0.4%
803700 2
 
0.4%
19800 2
 
0.4%
484000 2
 
0.4%
Other values (483) 493
95.0%
ValueCountFrequency (%)
0 7
1.3%
1 1
 
0.2%
7 1
 
0.2%
459 2
 
0.4%
795 1
 
0.2%
918 1
 
0.2%
979 1
 
0.2%
1118 1
 
0.2%
1302 1
 
0.2%
1638 1
 
0.2%
ValueCountFrequency (%)
1067046200 1
0.2%
426800000 1
0.2%
132000000 1
0.2%
30199900 1
0.2%
20451000 1
0.2%
18310000 1
0.2%
17250220 1
0.2%
16800000 1
0.2%
13867920 1
0.2%
13816090 1
0.2%

원도급자
Text

Distinct488
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2023-12-12T08:06:06.699507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length45
Mean length24.526012
Min length8

Characters and Unicode

Total characters12729
Distinct characters443
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique462 ?
Unique (%)89.0%

Sample

1st row복대동일원 하수관 비굴착 보수공사 중 비굴착 전체보수(SEPR공법),부분보수(PRSP공법)공사
2nd row흥덕구 가경동 하수관 비굴착 전체보수공사
3rd row도시계획시설 내 맨홀인상공사
4th row2015년도 하수도 맨홀 인상 공사
5th row2015년 하반기 검단지역 불량맨홀 정비공사
ValueCountFrequency (%)
정비공사 58
 
2.6%
보수공사 41
 
1.8%
중 33
 
1.5%
관내 32
 
1.4%
주변 29
 
1.3%
외 28
 
1.2%
및 25
 
1.1%
비굴착 25
 
1.1%
폐기물처리용역 25
 
1.1%
일원 24
 
1.1%
Other values (1139) 1923
85.7%
2023-12-12T08:06:07.173624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1726
 
13.6%
공 578
 
4.5%
사 538
 
4.2%
수 416
 
3.3%
설 238
 
1.9%
2 209
 
1.6%
시 202
 
1.6%
) 201
 
1.6%
( 201
 
1.6%
1 199
 
1.6%
Other values (433) 8221
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9434
74.1%
Space Separator 1726
 
13.6%
Decimal Number 863
 
6.8%
Open Punctuation 205
 
1.6%
Close Punctuation 204
 
1.6%
Uppercase Letter 105
 
0.8%
Dash Punctuation 80
 
0.6%
Other Punctuation 46
 
0.4%
Lowercase Letter 38
 
0.3%
Math Symbol 25
 
0.2%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 578
 
6.1%
사 538
 
5.7%
수 416
 
4.4%
설 238
 
2.5%
시 202
 
2.1%
비 196
 
2.1%
구 191
 
2.0%
관 185
 
2.0%
하 182
 
1.9%
정 179
 
1.9%
Other values (373) 6529
69.2%
Uppercase Letter
ValueCountFrequency (%)
S 16
15.2%
B 13
12.4%
T 13
12.4%
P 12
11.4%
L 9
8.6%
R 9
8.6%
M 7
6.7%
A 5
 
4.8%
D 4
 
3.8%
F 4
 
3.8%
Other values (8) 13
12.4%
Lowercase Letter
ValueCountFrequency (%)
e 8
21.1%
i 7
18.4%
n 4
10.5%
r 3
 
7.9%
t 3
 
7.9%
a 2
 
5.3%
s 2
 
5.3%
o 2
 
5.3%
k 1
 
2.6%
b 1
 
2.6%
Other values (5) 5
13.2%
Decimal Number
ValueCountFrequency (%)
2 209
24.2%
1 199
23.1%
0 116
13.4%
3 66
 
7.6%
6 57
 
6.6%
8 49
 
5.7%
4 49
 
5.7%
5 47
 
5.4%
7 43
 
5.0%
9 28
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 22
47.8%
& 5
 
10.9%
# 5
 
10.9%
; 5
 
10.9%
. 4
 
8.7%
/ 2
 
4.3%
: 2
 
4.3%
· 1
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 201
98.5%
] 3
 
1.5%
Open Punctuation
ValueCountFrequency (%)
( 201
98.0%
[ 4
 
2.0%
Space Separator
ValueCountFrequency (%)
1726
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Math Symbol
ValueCountFrequency (%)
~ 25
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9435
74.1%
Common 3151
 
24.8%
Latin 143
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 578
 
6.1%
사 538
 
5.7%
수 416
 
4.4%
설 238
 
2.5%
시 202
 
2.1%
비 196
 
2.1%
구 191
 
2.0%
관 185
 
2.0%
하 182
 
1.9%
정 179
 
1.9%
Other values (374) 6530
69.2%
Latin
ValueCountFrequency (%)
S 16
 
11.2%
B 13
 
9.1%
T 13
 
9.1%
P 12
 
8.4%
L 9
 
6.3%
R 9
 
6.3%
e 8
 
5.6%
M 7
 
4.9%
i 7
 
4.9%
A 5
 
3.5%
Other values (23) 44
30.8%
Common
ValueCountFrequency (%)
1726
54.8%
2 209
 
6.6%
) 201
 
6.4%
( 201
 
6.4%
1 199
 
6.3%
0 116
 
3.7%
- 80
 
2.5%
3 66
 
2.1%
6 57
 
1.8%
8 49
 
1.6%
Other values (16) 247
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9434
74.1%
ASCII 3293
 
25.9%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1726
52.4%
2 209
 
6.3%
) 201
 
6.1%
( 201
 
6.1%
1 199
 
6.0%
0 116
 
3.5%
- 80
 
2.4%
3 66
 
2.0%
6 57
 
1.7%
8 49
 
1.5%
Other values (48) 389
 
11.8%
Hangul
ValueCountFrequency (%)
공 578
 
6.1%
사 538
 
5.7%
수 416
 
4.4%
설 238
 
2.5%
시 202
 
2.1%
비 196
 
2.1%
구 191
 
2.0%
관 185
 
2.0%
하 182
 
1.9%
정 179
 
1.9%
Other values (373) 6529
69.2%
None
ValueCountFrequency (%)
· 1
50.0%
㈜ 1
50.0%

계약형태
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
RELA0004
186 
RELA0002
129 
RELA0001
110 
RELA0005
67 
RELA0003
27 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRELA0002
2nd rowRELA0004
3rd rowRELA0004
4th rowRELA0004
5th rowRELA0004

Common Values

ValueCountFrequency (%)
RELA0004 186
35.8%
RELA0002 129
24.9%
RELA0001 110
21.2%
RELA0005 67
 
12.9%
RELA0003 27
 
5.2%

Length

2023-12-12T08:06:07.321005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:07.434169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
rela0004 186
35.8%
rela0002 129
24.9%
rela0001 110
21.2%
rela0005 67
 
12.9%
rela0003 27
 
5.2%

계약형태_기타
Categorical

IMBALANCE 

Distinct20
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
479 
지자체 미작성
 
10
조달 3자계약
 
3
납품
 
3
턴키계약
 
3
Other values (15)
 
21

Length

Max length25
Median length4
Mean length4.3429672
Min length2

Unique

Unique9 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 479
92.3%
지자체 미작성 10
 
1.9%
조달 3자계약 3
 
0.6%
납품 3
 
0.6%
턴키계약 3
 
0.6%
조달청 수의계약 2
 
0.4%
조달청 제3자 단가 구매 계약 2
 
0.4%
다수공급자(3자단가) 계약에 의한 물품 납품 2
 
0.4%
설계, 시공 일괄입찰 2
 
0.4%
정보없음 2
 
0.4%
Other values (10) 11
 
2.1%

Length

2023-12-12T08:06:07.590415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 479
84.9%
미작성 10
 
1.8%
지자체 10
 
1.8%
납품 6
 
1.1%
조달청 5
 
0.9%
계약 3
 
0.5%
의한 3
 
0.5%
계약에 3
 
0.5%
다수공급자(3자단가 3
 
0.5%
물품 3
 
0.5%
Other values (24) 39
 
6.9%

계약번호
Text

MISSING 

Distinct267
Distinct (%)76.7%
Missing171
Missing (%)32.9%
Memory size4.2 KiB
2023-12-12T08:06:07.892703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length38
Mean length13.206897
Min length4

Characters and Unicode

Total characters4596
Distinct characters55
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique251 ?
Unique (%)72.1%

Sample

1st row2020000000000
2nd row2020000000000
3rd row202000000000
4th row20140469945-00
5th row20130467564-00
ValueCountFrequency (%)
2020000000000 34
 
9.4%
202000000000 25
 
6.9%
2010000000000 6
 
1.7%
201000000000 6
 
1.7%
4
 
1.1%
00 3
 
0.8%
20130456933-00 3
 
0.8%
20080904097-05 3
 
0.8%
127040502 2
 
0.6%
135099501 2
 
0.6%
Other values (264) 275
75.8%
2023-12-12T08:06:08.338883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1816
39.5%
2 535
 
11.6%
1 515
 
11.2%
3 241
 
5.2%
- 204
 
4.4%
5 183
 
4.0%
4 167
 
3.6%
6 162
 
3.5%
8 151
 
3.3%
146
 
3.2%
Other values (45) 476
 
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4040
87.9%
Dash Punctuation 204
 
4.4%
Space Separator 146
 
3.2%
Uppercase Letter 101
 
2.2%
Other Letter 79
 
1.7%
Other Punctuation 14
 
0.3%
Open Punctuation 6
 
0.1%
Close Punctuation 5
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 23
22.8%
A 13
12.9%
D 13
12.9%
F 9
 
8.9%
E 9
 
8.9%
B 8
 
7.9%
H 6
 
5.9%
R 3
 
3.0%
L 3
 
3.0%
S 2
 
2.0%
Other values (8) 12
11.9%
Other Letter
ValueCountFrequency (%)
호 22
27.8%
공 17
21.5%
사 16
20.3%
제 11
13.9%
품 2
 
2.5%
물 2
 
2.5%
증 1
 
1.3%
접 1
 
1.3%
번 1
 
1.3%
수 1
 
1.3%
Other values (5) 5
 
6.3%
Decimal Number
ValueCountFrequency (%)
0 1816
45.0%
2 535
 
13.2%
1 515
 
12.7%
3 241
 
6.0%
5 183
 
4.5%
4 167
 
4.1%
6 162
 
4.0%
8 151
 
3.7%
7 145
 
3.6%
9 125
 
3.1%
Other Punctuation
ValueCountFrequency (%)
/ 9
64.3%
. 2
 
14.3%
, 1
 
7.1%
' 1
 
7.1%
: 1
 
7.1%
Close Punctuation
ValueCountFrequency (%)
) 3
60.0%
] 2
40.0%
Open Punctuation
ValueCountFrequency (%)
[ 3
50.0%
( 3
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 204
100.0%
Space Separator
ValueCountFrequency (%)
146
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4416
96.1%
Latin 101
 
2.2%
Hangul 79
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1816
41.1%
2 535
 
12.1%
1 515
 
11.7%
3 241
 
5.5%
- 204
 
4.6%
5 183
 
4.1%
4 167
 
3.8%
6 162
 
3.7%
8 151
 
3.4%
146
 
3.3%
Other values (12) 296
 
6.7%
Latin
ValueCountFrequency (%)
C 23
22.8%
A 13
12.9%
D 13
12.9%
F 9
 
8.9%
E 9
 
8.9%
B 8
 
7.9%
H 6
 
5.9%
R 3
 
3.0%
L 3
 
3.0%
S 2
 
2.0%
Other values (8) 12
11.9%
Hangul
ValueCountFrequency (%)
호 22
27.8%
공 17
21.5%
사 16
20.3%
제 11
13.9%
품 2
 
2.5%
물 2
 
2.5%
증 1
 
1.3%
접 1
 
1.3%
번 1
 
1.3%
수 1
 
1.3%
Other values (5) 5
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4517
98.3%
Hangul 79
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1816
40.2%
2 535
 
11.8%
1 515
 
11.4%
3 241
 
5.3%
- 204
 
4.5%
5 183
 
4.1%
4 167
 
3.7%
6 162
 
3.6%
8 151
 
3.3%
146
 
3.2%
Other values (30) 397
 
8.8%
Hangul
ValueCountFrequency (%)
호 22
27.8%
공 17
21.5%
사 16
20.3%
제 11
13.9%
품 2
 
2.5%
물 2
 
2.5%
증 1
 
1.3%
접 1
 
1.3%
번 1
 
1.3%
수 1
 
1.3%
Other values (5) 5
 
6.3%

입찰공고번호
Text

MISSING 

Distinct177
Distinct (%)88.9%
Missing320
Missing (%)61.7%
Memory size4.2 KiB
2023-12-12T08:06:08.666983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length14
Mean length13.356784
Min length7

Characters and Unicode

Total characters2658
Distinct characters80
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique170 ?
Unique (%)85.4%

Sample

1st row2020000000000
2nd row2020000000000
3rd row20140407617-00
4th row20130337197-00
5th row20150510980
ValueCountFrequency (%)
2020000000000 16
 
6.9%
공고 7
 
3.0%
5
 
2.1%
00 5
 
2.1%
20130419527 3
 
1.3%
20150618348-00 2
 
0.9%
20150530035-01 2
 
0.9%
2017-1148 2
 
0.9%
20161004178-00 2
 
0.9%
20130336222-00 2
 
0.9%
Other values (187) 187
80.3%
2023-12-12T08:06:09.160291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 811
30.5%
2 345
13.0%
1 328
12.3%
3 152
 
5.7%
- 146
 
5.5%
4 129
 
4.9%
5 121
 
4.6%
6 111
 
4.2%
7 109
 
4.1%
8 88
 
3.3%
Other values (70) 318
 
12.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2271
85.4%
Other Letter 149
 
5.6%
Dash Punctuation 146
 
5.5%
Space Separator 81
 
3.0%
Uppercase Letter 6
 
0.2%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 21
 
14.1%
제 19
 
12.8%
공 14
 
9.4%
고 12
 
8.1%
사 5
 
3.4%
수 5
 
3.4%
시 5
 
3.4%
군 3
 
2.0%
소 3
 
2.0%
업 3
 
2.0%
Other values (49) 59
39.6%
Decimal Number
ValueCountFrequency (%)
0 811
35.7%
2 345
15.2%
1 328
14.4%
3 152
 
6.7%
4 129
 
5.7%
5 121
 
5.3%
6 111
 
4.9%
7 109
 
4.8%
8 88
 
3.9%
9 77
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
E 1
16.7%
A 1
16.7%
L 1
16.7%
Q 1
16.7%
C 1
16.7%
B 1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 146
100.0%
Space Separator
ValueCountFrequency (%)
81
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2503
94.2%
Hangul 149
 
5.6%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 21
 
14.1%
제 19
 
12.8%
공 14
 
9.4%
고 12
 
8.1%
사 5
 
3.4%
수 5
 
3.4%
시 5
 
3.4%
군 3
 
2.0%
소 3
 
2.0%
업 3
 
2.0%
Other values (49) 59
39.6%
Common
ValueCountFrequency (%)
0 811
32.4%
2 345
13.8%
1 328
13.1%
3 152
 
6.1%
- 146
 
5.8%
4 129
 
5.2%
5 121
 
4.8%
6 111
 
4.4%
7 109
 
4.4%
8 88
 
3.5%
Other values (5) 163
 
6.5%
Latin
ValueCountFrequency (%)
E 1
16.7%
A 1
16.7%
L 1
16.7%
Q 1
16.7%
C 1
16.7%
B 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2509
94.4%
Hangul 149
 
5.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 811
32.3%
2 345
13.8%
1 328
13.1%
3 152
 
6.1%
- 146
 
5.8%
4 129
 
5.1%
5 121
 
4.8%
6 111
 
4.4%
7 109
 
4.3%
8 88
 
3.5%
Other values (11) 169
 
6.7%
Hangul
ValueCountFrequency (%)
호 21
 
14.1%
제 19
 
12.8%
공 14
 
9.4%
고 12
 
8.1%
사 5
 
3.4%
수 5
 
3.4%
시 5
 
3.4%
군 3
 
2.0%
소 3
 
2.0%
업 3
 
2.0%
Other values (49) 59
39.6%

설비유형
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
EQPT0001
228 
EQPT0003
189 
EQPT0002
102 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEQPT0002
2nd rowEQPT0002
3rd rowEQPT0001
4th rowEQPT0001
5th rowEQPT0003

Common Values

ValueCountFrequency (%)
EQPT0001 228
43.9%
EQPT0003 189
36.4%
EQPT0002 102
19.7%

Length

2023-12-12T08:06:09.297193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:09.394679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
eqpt0001 228
43.9%
eqpt0003 189
36.4%
eqpt0002 102
19.7%

공사비_계획
Real number (ℝ)

MISSING  ZEROS 

Distinct425
Distinct (%)84.5%
Missing16
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean666044.87
Minimum0
Maximum30199900
Zeros51
Zeros (%)9.8%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T08:06:09.529079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114717
median70128
Q3378553
95-th percentile2665231.3
Maximum30199900
Range30199900
Interquartile range (IQR)363836

Descriptive statistics

Standard deviation2463507.1
Coefficient of variation (CV)3.6987105
Kurtosis64.692742
Mean666044.87
Median Absolute Deviation (MAD)65981
Skewness7.3654777
Sum3.3502057 × 108
Variance6.0688675 × 1012
MonotonicityNot monotonic
2023-12-12T08:06:09.674713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 51
 
9.8%
50000 4
 
0.8%
7500 4
 
0.8%
500000 3
 
0.6%
20000 3
 
0.6%
10000 3
 
0.6%
803700 2
 
0.4%
44000 2
 
0.4%
240215 2
 
0.4%
484000 2
 
0.4%
Other values (415) 427
82.3%
(Missing) 16
 
3.1%
ValueCountFrequency (%)
0 51
9.8%
2133 1
 
0.2%
2409 1
 
0.2%
2891 1
 
0.2%
2957 1
 
0.2%
3083 1
 
0.2%
3139 1
 
0.2%
3547 1
 
0.2%
3740 1
 
0.2%
3978 1
 
0.2%
ValueCountFrequency (%)
30199900 1
0.2%
20451000 1
0.2%
18310000 1
0.2%
17250220 1
0.2%
16800000 1
0.2%
13867920 1
0.2%
13816090 1
0.2%
11750000 1
0.2%
7233600 1
0.2%
6970000 1
0.2%

공사비_실제
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct432
Distinct (%)85.4%
Missing13
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean2709102.7
Minimum0
Maximum1.0670462 × 109
Zeros58
Zeros (%)11.2%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T08:06:09.832177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114614
median61057.5
Q3308783
95-th percentile2061367.2
Maximum1.0670462 × 109
Range1.0670462 × 109
Interquartile range (IQR)294169

Descriptive statistics

Standard deviation47470426
Coefficient of variation (CV)17.522564
Kurtosis503.38144
Mean2709102.7
Median Absolute Deviation (MAD)60828
Skewness22.408258
Sum1.370806 × 109
Variance2.2534414 × 1015
MonotonicityNot monotonic
2023-12-12T08:06:09.996503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 58
 
11.2%
158795 2
 
0.4%
459 2
 
0.4%
71000 2
 
0.4%
3672969 2
 
0.4%
484000 2
 
0.4%
803700 2
 
0.4%
44000 2
 
0.4%
240215 2
 
0.4%
40338 2
 
0.4%
Other values (422) 430
82.9%
(Missing) 13
 
2.5%
ValueCountFrequency (%)
0 58
11.2%
459 2
 
0.4%
918 1
 
0.2%
1118 1
 
0.2%
2409 1
 
0.2%
2891 1
 
0.2%
2957 1
 
0.2%
3083 1
 
0.2%
3139 1
 
0.2%
3528 1
 
0.2%
ValueCountFrequency (%)
1067046200 1
0.2%
30199900 1
0.2%
20451000 1
0.2%
18310000 1
0.2%
17250220 1
0.2%
16800000 1
0.2%
13867920 1
0.2%
13816090 1
0.2%
8967346 1
0.2%
7233600 1
0.2%

공사기간_계획
Text

MISSING 

Distinct57
Distinct (%)11.4%
Missing21
Missing (%)4.0%
Memory size4.2 KiB
2023-12-12T08:06:10.184038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.5883534
Min length1

Characters and Unicode

Total characters791
Distinct characters12
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

Unique15 ?
Unique (%)3.0%

Sample

1st row180
2nd row120
3rd row60
4th row30
5th row45
ValueCountFrequency (%)
1 65
 
13.1%
0 55
 
11.0%
2 38
 
7.6%
30 35
 
7.0%
3 29
 
5.8%
6 28
 
5.6%
90 23
 
4.6%
60 21
 
4.2%
4 21
 
4.2%
12 16
 
3.2%
Other values (47) 167
33.5%
2023-12-12T08:06:10.466732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 218
27.6%
1 150
19.0%
2 95
12.0%
3 93
11.8%
6 63
 
8.0%
4 40
 
5.1%
9 37
 
4.7%
5 33
 
4.2%
8 21
 
2.7%
. 20
 
2.5%
Other values (2) 21
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 769
97.2%
Other Punctuation 20
 
2.5%
Other Letter 2
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 218
28.3%
1 150
19.5%
2 95
12.4%
3 93
12.1%
6 63
 
8.2%
4 40
 
5.2%
9 37
 
4.8%
5 33
 
4.3%
8 21
 
2.7%
7 19
 
2.5%
Other Punctuation
ValueCountFrequency (%)
. 20
100.0%
Other Letter
ValueCountFrequency (%)
약 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 789
99.7%
Hangul 2
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 218
27.6%
1 150
19.0%
2 95
12.0%
3 93
11.8%
6 63
 
8.0%
4 40
 
5.1%
9 37
 
4.7%
5 33
 
4.2%
8 21
 
2.7%
. 20
 
2.5%
Hangul
ValueCountFrequency (%)
약 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 789
99.7%
Hangul 2
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 218
27.6%
1 150
19.0%
2 95
12.0%
3 93
11.8%
6 63
 
8.0%
4 40
 
5.1%
9 37
 
4.7%
5 33
 
4.2%
8 21
 
2.7%
. 20
 
2.5%
Hangul
ValueCountFrequency (%)
약 2
100.0%

공사기간_실제
Text

MISSING 

Distinct64
Distinct (%)12.7%
Missing17
Missing (%)3.3%
Memory size4.2 KiB
2023-12-12T08:06:10.652906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.5936255
Min length1

Characters and Unicode

Total characters800
Distinct characters12
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

Unique23 ?
Unique (%)4.6%

Sample

1st row60
2nd row30
3rd row60
4th row30
5th row45
ValueCountFrequency (%)
1 73
14.5%
0 60
 
12.0%
30 40
 
8.0%
2 37
 
7.4%
3 27
 
5.4%
4 23
 
4.6%
6 20
 
4.0%
90 19
 
3.8%
60 17
 
3.4%
12 14
 
2.8%
Other values (54) 172
34.3%
2023-12-12T08:06:10.986807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 217
27.1%
1 158
19.8%
3 100
12.5%
2 87
10.9%
6 52
 
6.5%
5 42
 
5.2%
4 41
 
5.1%
9 30
 
3.8%
8 25
 
3.1%
. 25
 
3.1%
Other values (2) 23
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 773
96.6%
Other Punctuation 25
 
3.1%
Other Letter 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 217
28.1%
1 158
20.4%
3 100
12.9%
2 87
11.3%
6 52
 
6.7%
5 42
 
5.4%
4 41
 
5.3%
9 30
 
3.9%
8 25
 
3.2%
7 21
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 25
100.0%
Other Letter
ValueCountFrequency (%)
약 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 798
99.8%
Hangul 2
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 217
27.2%
1 158
19.8%
3 100
12.5%
2 87
10.9%
6 52
 
6.5%
5 42
 
5.3%
4 41
 
5.1%
9 30
 
3.8%
8 25
 
3.1%
. 25
 
3.1%
Hangul
ValueCountFrequency (%)
약 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 798
99.8%
Hangul 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 217
27.2%
1 158
19.8%
3 100
12.5%
2 87
10.9%
6 52
 
6.5%
5 42
 
5.3%
4 41
 
5.1%
9 30
 
3.8%
8 25
 
3.1%
. 25
 
3.1%
Hangul
ValueCountFrequency (%)
약 2
100.0%

시공용이성
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
EVLT0004
224 
EVLT0005
197 
EVLT0001
92 
EVLT0003
 
6

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEVLT0005
2nd rowEVLT0005
3rd rowEVLT0004
4th rowEVLT0004
5th rowEVLT0005

Common Values

ValueCountFrequency (%)
EVLT0004 224
43.2%
EVLT0005 197
38.0%
EVLT0001 92
17.7%
EVLT0003 6
 
1.2%

Length

2023-12-12T08:06:11.134031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:11.250138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
evlt0004 224
43.2%
evlt0005 197
38.0%
evlt0001 92
17.7%
evlt0003 6
 
1.2%

유지관리용이성
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
EVLT0004
209 
EVLT0005
182 
EVLT0001
117 
EVLT0003
 
9
<NA>
 
1

Length

Max length8
Median length8
Mean length7.9922929
Min length4

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st rowEVLT0005
2nd rowEVLT0005
3rd rowEVLT0004
4th rowEVLT0004
5th rowEVLT0005

Common Values

ValueCountFrequency (%)
EVLT0004 209
40.3%
EVLT0005 182
35.1%
EVLT0001 117
22.5%
EVLT0003 9
 
1.7%
<NA> 1
 
0.2%
EVLT0002 1
 
0.2%

Length

2023-12-12T08:06:11.389898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:11.515614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
evlt0004 209
40.3%
evlt0005 182
35.1%
evlt0001 117
22.5%
evlt0003 9
 
1.7%
na 1
 
0.2%
evlt0002 1
 
0.2%

시공단계
Text

MISSING 

Distinct56
Distinct (%)11.9%
Missing47
Missing (%)9.1%
Memory size4.2 KiB
2023-12-12T08:06:11.693929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length45
Mean length15.942797
Min length8

Characters and Unicode

Total characters7525
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)3.6%

Sample

1st rowEVEF0004,
2nd rowEVEF0004,
3rd rowEVEF0004,EVEF0005
4th rowEVEF0004,EVEF0005,
5th rowEVEF0005,
ValueCountFrequency (%)
evef0006 99
21.0%
evef0005 58
12.3%
evef0004,evef0005 52
11.0%
evef0001,evef0004 45
9.5%
evef0004 43
9.1%
evef0003 24
 
5.1%
evef0001,evef0002,evef0004,evef0005 22
 
4.7%
evef0001 22
 
4.7%
evef0001,evef0002,evef0003,evef0004,evef0005 14
 
3.0%
evef0001,evef0004,evef0005 11
 
2.3%
Other values (23) 82
17.4%
2023-12-12T08:06:12.007706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2577
34.2%
E 1718
22.8%
V 859
 
11.4%
F 859
 
11.4%
, 653
 
8.7%
4 239
 
3.2%
5 196
 
2.6%
1 145
 
1.9%
6 117
 
1.6%
3 83
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3436
45.7%
Uppercase Letter 3436
45.7%
Other Punctuation 653
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2577
75.0%
4 239
 
7.0%
5 196
 
5.7%
1 145
 
4.2%
6 117
 
3.4%
3 83
 
2.4%
2 79
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
E 1718
50.0%
V 859
25.0%
F 859
25.0%
Other Punctuation
ValueCountFrequency (%)
, 653
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4089
54.3%
Latin 3436
45.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2577
63.0%
, 653
 
16.0%
4 239
 
5.8%
5 196
 
4.8%
1 145
 
3.5%
6 117
 
2.9%
3 83
 
2.0%
2 79
 
1.9%
Latin
ValueCountFrequency (%)
E 1718
50.0%
V 859
25.0%
F 859
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7525
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2577
34.2%
E 1718
22.8%
V 859
 
11.4%
F 859
 
11.4%
, 653
 
8.7%
4 239
 
3.2%
5 196
 
2.6%
1 145
 
1.9%
6 117
 
1.6%
3 83
 
1.1%

시공단계_기타
Categorical

IMBALANCE 

Distinct40
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
438 
지자체 미작성
 
10
수목생육환경개선
 
9
화학비료 등 사용량 절감, 침출수 감소 등
 
7
내용없음
 
6
Other values (35)
49 

Length

Max length36
Median length4
Mean length5.0712909
Min length4

Unique

Unique24 ?
Unique (%)4.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 438
84.4%
지자체 미작성 10
 
1.9%
수목생육환경개선 9
 
1.7%
화학비료 등 사용량 절감, 침출수 감소 등 7
 
1.3%
내용없음 6
 
1.2%
토양개량 3
 
0.6%
오염물질 저감 3
 
0.6%
누수방지 3
 
0.6%
하수관 누수저감, 내구성 향상 2
 
0.4%
수질오염물질 저감 2
 
0.4%
Other values (30) 36
 
6.9%

Length

2023-12-12T08:06:12.169995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 438
65.7%
등 17
 
2.5%
저감 12
 
1.8%
절감 11
 
1.6%
미작성 10
 
1.5%
지자체 10
 
1.5%
수목생육환경개선 9
 
1.3%
화학비료 8
 
1.2%
사용량 8
 
1.2%
침출수 8
 
1.2%
Other values (85) 136
 
20.4%

운전단계
Text

MISSING 

Distinct52
Distinct (%)12.3%
Missing96
Missing (%)18.5%
Memory size4.2 KiB
2023-12-12T08:06:12.335138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length45
Mean length13.853428
Min length8

Characters and Unicode

Total characters5860
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)4.0%

Sample

1st rowEVEF0005,
2nd rowEVEF0005,
3rd rowEVEF0004,EVEF0005
4th rowEVEF0005,
5th rowEVEF0001,EVEF0002,EVEF0004,EVEF0005
ValueCountFrequency (%)
evef0006 130
30.7%
evef0005 65
15.4%
evef0001,evef0004 45
 
10.6%
evef0004 36
 
8.5%
evef0001 21
 
5.0%
evef0001,evef0002,evef0004,evef0005 18
 
4.3%
evef0003 14
 
3.3%
evef0004,evef0005 13
 
3.1%
evef0002 11
 
2.6%
evef0003,evef0004,evef0005 8
 
1.9%
Other values (24) 62
14.7%
2023-12-12T08:06:12.656557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2010
34.3%
E 1340
22.9%
V 670
 
11.4%
F 670
 
11.4%
, 500
 
8.5%
4 157
 
2.7%
6 150
 
2.6%
5 137
 
2.3%
1 111
 
1.9%
2 63
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2680
45.7%
Uppercase Letter 2680
45.7%
Other Punctuation 500
 
8.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2010
75.0%
4 157
 
5.9%
6 150
 
5.6%
5 137
 
5.1%
1 111
 
4.1%
2 63
 
2.4%
3 52
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
E 1340
50.0%
V 670
25.0%
F 670
25.0%
Other Punctuation
ValueCountFrequency (%)
, 500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3180
54.3%
Latin 2680
45.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2010
63.2%
, 500
 
15.7%
4 157
 
4.9%
6 150
 
4.7%
5 137
 
4.3%
1 111
 
3.5%
2 63
 
2.0%
3 52
 
1.6%
Latin
ValueCountFrequency (%)
E 1340
50.0%
V 670
25.0%
F 670
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5860
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2010
34.3%
E 1340
22.9%
V 670
 
11.4%
F 670
 
11.4%
, 500
 
8.5%
4 157
 
2.7%
6 150
 
2.6%
5 137
 
2.3%
1 111
 
1.9%
2 63
 
1.1%

운전단계_기타
Text

MISSING 

Distinct60
Distinct (%)43.8%
Missing382
Missing (%)73.6%
Memory size4.2 KiB
2023-12-12T08:06:13.209711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length29
Mean length10.824818
Min length3

Characters and Unicode

Total characters1483
Distinct characters163
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

Unique42 ?
Unique (%)30.7%

Sample

1st row수질상태 개선
2nd row미세먼지 자동측정기 정도관리
3rd row악취발생 저감
4th row수목생육환경개선
5th row수목생육환경개선
ValueCountFrequency (%)
해당없음 27
 
7.0%
저감 17
 
4.4%
증대 14
 
3.6%
향상 13
 
3.4%
미작성 10
 
2.6%
지자체 10
 
2.6%
및 10
 
2.6%
하자 10
 
2.6%
감소 9
 
2.3%
등 9
 
2.3%
Other values (153) 257
66.6%
2023-12-12T08:06:13.649333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
249
 
16.8%
수 68
 
4.6%
감 42
 
2.8%
음 39
 
2.6%
없 36
 
2.4%
생 30
 
2.0%
저 29
 
2.0%
해 28
 
1.9%
질 28
 
1.9%
자 28
 
1.9%
Other values (153) 906
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1210
81.6%
Space Separator 249
 
16.8%
Other Punctuation 24
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 68
 
5.6%
감 42
 
3.5%
음 39
 
3.2%
없 36
 
3.0%
생 30
 
2.5%
저 29
 
2.4%
해 28
 
2.3%
질 28
 
2.3%
자 28
 
2.3%
성 28
 
2.3%
Other values (150) 854
70.6%
Other Punctuation
ValueCountFrequency (%)
, 23
95.8%
. 1
 
4.2%
Space Separator
ValueCountFrequency (%)
249
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1210
81.6%
Common 273
 
18.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 68
 
5.6%
감 42
 
3.5%
음 39
 
3.2%
없 36
 
3.0%
생 30
 
2.5%
저 29
 
2.4%
해 28
 
2.3%
질 28
 
2.3%
자 28
 
2.3%
성 28
 
2.3%
Other values (150) 854
70.6%
Common
ValueCountFrequency (%)
249
91.2%
, 23
 
8.4%
. 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1210
81.6%
ASCII 273
 
18.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
249
91.2%
, 23
 
8.4%
. 1
 
0.4%
Hangul
ValueCountFrequency (%)
수 68
 
5.6%
감 42
 
3.5%
음 39
 
3.2%
없 36
 
3.0%
생 30
 
2.5%
저 29
 
2.4%
해 28
 
2.3%
질 28
 
2.3%
자 28
 
2.3%
성 28
 
2.3%
Other values (150) 854
70.6%

시공단계_1
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.5%
Missing451
Missing (%)86.9%
Memory size1.1 KiB
True
68 
(Missing)
451 
ValueCountFrequency (%)
True 68
 
13.1%
(Missing) 451
86.9%
2023-12-12T08:06:13.778992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시공단계_발생건수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
0
264 
<NA>
246 
1
 
6
2
 
2
12
 
1

Length

Max length4
Median length1
Mean length2.4238921
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
0 264
50.9%
<NA> 246
47.4%
1 6
 
1.2%
2 2
 
0.4%
12 1
 
0.2%

Length

2023-12-12T08:06:13.889337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:13.988223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 264
50.9%
na 246
47.4%
1 6
 
1.2%
2 2
 
0.4%
12 1
 
0.2%

시공단계_조치결과
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
482 
2
 
36
1
 
1

Length

Max length4
Median length4
Mean length3.7861272
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row2
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 482
92.9%
2 36
 
6.9%
1 1
 
0.2%

Length

2023-12-12T08:06:14.091113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:14.221972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 482
92.9%
2 36
 
6.9%
1 1
 
0.2%

운전단계_1
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.3%
Missing441
Missing (%)85.0%
Memory size1.1 KiB
True
78 
(Missing)
441 
ValueCountFrequency (%)
True 78
 
15.0%
(Missing) 441
85.0%
2023-12-12T08:06:14.307717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

운전단계_발생건수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)2.9%
Missing241
Missing (%)46.4%
Infinite0
Infinite (%)0.0%
Mean0.67625899
Minimum0
Maximum119
Zeros258
Zeros (%)49.7%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T08:06:14.391665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum119
Range119
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.2532486
Coefficient of variation (CV)10.725548
Kurtosis258.29046
Mean0.67625899
Median Absolute Deviation (MAD)0
Skewness15.826247
Sum188
Variance52.609615
MonotonicityNot monotonic
2023-12-12T08:06:14.493242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 258
49.7%
1 10
 
1.9%
2 3
 
0.6%
10 3
 
0.6%
3 1
 
0.2%
8 1
 
0.2%
12 1
 
0.2%
119 1
 
0.2%
(Missing) 241
46.4%
ValueCountFrequency (%)
0 258
49.7%
1 10
 
1.9%
2 3
 
0.6%
3 1
 
0.2%
8 1
 
0.2%
10 3
 
0.6%
12 1
 
0.2%
119 1
 
0.2%
ValueCountFrequency (%)
119 1
 
0.2%
12 1
 
0.2%
10 3
 
0.6%
8 1
 
0.2%
3 1
 
0.2%
2 3
 
0.6%
1 10
 
1.9%
0 258
49.7%

운전단계_조치결과
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
477 
2
 
40
1
 
2

Length

Max length4
Median length4
Mean length3.7572254
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row2
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 477
91.9%
2 40
 
7.7%
1 2
 
0.4%

Length

2023-12-12T08:06:14.606101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:14.694502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 477
91.9%
2 40
 
7.7%
1 2
 
0.4%

만족도_경제성
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
STSF0004
222 
STSF0005
157 
STSF0001
109 
STSF0003
 
22
STSF0002
 
8

Length

Max length8
Median length8
Mean length7.9922929
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowSTSF0005
2nd rowSTSF0005
3rd rowSTSF0004
4th rowSTSF0004
5th rowSTSF0005

Common Values

ValueCountFrequency (%)
STSF0004 222
42.8%
STSF0005 157
30.3%
STSF0001 109
21.0%
STSF0003 22
 
4.2%
STSF0002 8
 
1.5%
<NA> 1
 
0.2%

Length

2023-12-12T08:06:14.795665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:14.897252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
stsf0004 222
42.8%
stsf0005 157
30.3%
stsf0001 109
21.0%
stsf0003 22
 
4.2%
stsf0002 8
 
1.5%
na 1
 
0.2%

만족도_기술성
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
STSF0004
238 
STSF0005
194 
STSF0001
82 
STSF0003
 
4
STSF0002
 
1

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowSTSF0005
2nd rowSTSF0005
3rd rowSTSF0004
4th rowSTSF0004
5th rowSTSF0005

Common Values

ValueCountFrequency (%)
STSF0004 238
45.9%
STSF0005 194
37.4%
STSF0001 82
 
15.8%
STSF0003 4
 
0.8%
STSF0002 1
 
0.2%

Length

2023-12-12T08:06:15.014815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:15.100309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
stsf0004 238
45.9%
stsf0005 194
37.4%
stsf0001 82
 
15.8%
stsf0003 4
 
0.8%
stsf0002 1
 
0.2%

만족도_환경성
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
STSF0004
215 
STSF0005
208 
STSF0001
92 
STSF0003
 
3
STSF0002
 
1

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowSTSF0005
2nd rowSTSF0005
3rd rowSTSF0004
4th rowSTSF0004
5th rowSTSF0005

Common Values

ValueCountFrequency (%)
STSF0004 215
41.4%
STSF0005 208
40.1%
STSF0001 92
17.7%
STSF0003 3
 
0.6%
STSF0002 1
 
0.2%

Length

2023-12-12T08:06:15.203246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:15.293090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
stsf0004 215
41.4%
stsf0005 208
40.1%
stsf0001 92
17.7%
stsf0003 3
 
0.6%
stsf0002 1
 
0.2%

만족도_현장적용성
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
STSF0004
231 
STSF0005
212 
STSF0001
62 
STSF0003
 
11
STSF0002
 
2

Length

Max length8
Median length8
Mean length7.9922929
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowSTSF0005
2nd rowSTSF0005
3rd rowSTSF0004
4th rowSTSF0004
5th rowSTSF0005

Common Values

ValueCountFrequency (%)
STSF0004 231
44.5%
STSF0005 212
40.8%
STSF0001 62
 
11.9%
STSF0003 11
 
2.1%
STSF0002 2
 
0.4%
<NA> 1
 
0.2%

Length

2023-12-12T08:06:15.407004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:15.508143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
stsf0004 231
44.5%
stsf0005 212
40.8%
stsf0001 62
 
11.9%
stsf0003 11
 
2.1%
stsf0002 2
 
0.4%
na 1
 
0.2%

승인여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size651.0 B
True
519 
ValueCountFrequency (%)
True 519
100.0%
2023-12-12T08:06:15.594074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

적용 년
Real number (ℝ)

Distinct13
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.2543
Minimum2006
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T08:06:15.667466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2006
5-th percentile2008
Q12013
median2015
Q32017
95-th percentile2018
Maximum2018
Range12
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.0575016
Coefficient of variation (CV)0.0015179322
Kurtosis-0.12833193
Mean2014.2543
Median Absolute Deviation (MAD)2
Skewness-0.85399795
Sum1045398
Variance9.3483161
MonotonicityNot monotonic
2023-12-12T08:06:15.770622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2015 91
17.5%
2016 83
16.0%
2017 70
13.5%
2018 64
12.3%
2013 52
10.0%
2011 39
7.5%
2014 36
 
6.9%
2008 25
 
4.8%
2009 20
 
3.9%
2012 18
 
3.5%
Other values (3) 21
 
4.0%
ValueCountFrequency (%)
2006 4
 
0.8%
2007 12
 
2.3%
2008 25
 
4.8%
2009 20
 
3.9%
2010 5
 
1.0%
2011 39
7.5%
2012 18
 
3.5%
2013 52
10.0%
2014 36
 
6.9%
2015 91
17.5%
ValueCountFrequency (%)
2018 64
12.3%
2017 70
13.5%
2016 83
16.0%
2015 91
17.5%
2014 36
 
6.9%
2013 52
10.0%
2012 18
 
3.5%
2011 39
7.5%
2010 5
 
1.0%
2009 20
 
3.9%

Sample

신청서ID사후평가순번공사명주소1주소2발주처기관코드발주처부서계약일자착공일자준공일자용량(수량)총공사금액신기술공종 공사금액원도급자계약형태계약형태_기타계약번호입찰공고번호설비유형공사비_계획공사비_실제공사기간_계획공사기간_실제시공용이성유지관리용이성시공단계시공단계_기타운전단계운전단계_기타시공단계_1시공단계_발생건수시공단계_조치결과운전단계_1운전단계_발생건수운전단계_조치결과만족도_경제성만족도_기술성만족도_환경성만족도_현장적용성승인여부적용 년
011834477복대동일원 하수관 비굴착 보수공사 중 비굴착 전체보수(SEPR공법),부분보수(PRSP공법)공사충북 청주시 흥덕구 복대동 일원<NA>SIGU0135흥덕구청 건설교통과2015-03-242015-03-242015-05-02하수관 D400~D600, L=168m6455064550복대동일원 하수관 비굴착 보수공사 중 비굴착 전체보수(SEPR공법),부분보수(PRSP공법)공사RELA0002<NA>20200000000002020000000000EQPT00022000006455018060EVLT0005EVLT0005EVEF0004,<NA>EVEF0005,<NA><NA><NA><NA><NA><NA><NA>STSF0005STSF0005STSF0005STSF0005Y2015
111834478흥덕구 가경동 하수관 비굴착 전체보수공사충북 청주시 흥덕구 가경동 일원<NA>SIGU0135흥덕구청 건설교통과2015-02-232015-02-232015-03-24하수관 D400, L=51m1782017820흥덕구 가경동 하수관 비굴착 전체보수공사RELA0004<NA>2020000000000<NA>EQPT0002500001782012030EVLT0005EVLT0005EVEF0004,<NA>EVEF0005,<NA><NA><NA><NA><NA><NA><NA>STSF0005STSF0005STSF0005STSF0005Y2015
211985480도시계획시설 내 맨홀인상공사인천 부평구 부개동 경인로 1056 2층 서울특별시 금천구 두산로 70, 현대지식산업센터 B-1307<NA>SIGU0107건설과2015-07-292015-07-302015-09-2794EA4976049760도시계획시설 내 맨홀인상공사RELA0004<NA><NA><NA>EQPT000150000497606060EVLT0004EVLT0004EVEF0004,EVEF0005<NA>EVEF0004,EVEF0005<NA><NA>0<NA><NA>0<NA>STSF0004STSF0004STSF0004STSF0004Y2015
3119854812015년도 하수도 맨홀 인상 공사인천 계양구 작전동 주부토로 399 일원<NA>SIGU0053계양구청 건설과2015-03-122015-03-122015-04-0833개소17712177122015년도 하수도 맨홀 인상 공사RELA0004<NA><NA><NA>EQPT000117712177123030EVLT0004EVLT0004EVEF0004,EVEF0005,<NA><NA><NA>Y02Y02STSF0004STSF0004STSF0004STSF0004Y2015
4119854842015년 하반기 검단지역 불량맨홀 정비공사인천 서구 심곡동<NA>SIGU0053서구청 검단출장소2015-07-032015-07-072015-08-03<NA>19546195462015년 하반기 검단지역 불량맨홀 정비공사RELA0004<NA><NA><NA>EQPT0003<NA><NA><NA><NA>EVLT0005EVLT0005EVEF0005,<NA>EVEF0005,<NA><NA><NA><NA><NA><NA><NA>STSF0005STSF0005STSF0005STSF0005Y2015
511985485관내 일원 불량 맨홀 정비공사 중 BTT공법 맨홀정비공사인천 서구 심곡동<NA>SIGU0053서구청 건설과2015-10-192015-10-192015-11-26<NA>6968559598관내 일원 불량 맨홀 정비공사 중 BTT공법 맨홀정비공사RELA0002<NA><NA><NA>EQPT000169685696854545EVLT0004EVLT0004EVEF0001,EVEF0002,EVEF0004,EVEF0005<NA>EVEF0001,EVEF0002,EVEF0004,EVEF0005<NA><NA>0<NA><NA>0<NA>STSF0004STSF0004STSF0004STSF0004Y2015
6117404872015년 관내 하수시설물 유지보수공사 중 비굴착공서울 광진구 자양동<NA>SIGU0007안전치수방재과2015-04-072015-04-072015-08-14D450,L=881m5423775423772015년 관내 하수시설물 유지보수공사 중 비굴착공RELA0001<NA>2020000000002020000000000EQPT0001542377542377120120EVLT0004EVLT0004EVEF0004,EVEF0005,<NA>EVEF0005,EVEF0006,<NA><NA><NA><NA><NA><NA><NA>STSF0004STSF0004STSF0004STSF0005Y2015
712831488세종호수 퇴적물 제거 용역세종 연기 세종 1201 세종호수공원<NA>SIGU0277시설관리사업소 공원녹지과2015-08-192015-08-192015-12-16147,090m2165680165680세종호수 퇴적물 제거 용역RELA0004<NA><NA><NA>EQPT000117549016568012090EVLT0001EVLT0001EVEF0006,시공단계 해당없음EVEF0006,수질상태 개선<NA><NA><NA>Y02STSF0005STSF0005STSF0005STSF0005Y2015
83991393동교동삼거리~합정역간 송배수관 정비공사서울시 구로구 디지털로 33길 28 우림이비즈센타 1차 1205호<NA>SIGU0001급수운영과2015-03-052015-03-092015-07-20130m817790151000동교동삼거리~합정역간 송배수관 정비공사RELA0002<NA>20140469945-0020140407617-00EQPT00011800001510006030EVLT0005EVLT0005EVEF0004,EVEF0005<NA>EVEF0004,EVEF0005<NA><NA>0<NA><NA>0<NA>STSF0005STSF0005STSF0005STSF0005Y2015
94238397초미세먼지연속채취기(22320) 인천광역시 중구 서해대로 471 인천광역시 보건환경연구원<NA>SIGU0053환경조사과2015-07-032015-07-032015-10-017대186080186080초미세먼지연속채취기RELA0002<NA><NA><NA>EQPT00031908701860809090EVLT0005EVLT0005EVEF0006,미세먼지 자동측정기 정도관리EVEF0006,미세먼지 자동측정기 정도관리Y02Y02STSF0005STSF0005STSF0005STSF0005Y2015
신청서ID사후평가순번공사명주소1주소2발주처기관코드발주처부서계약일자착공일자준공일자용량(수량)총공사금액신기술공종 공사금액원도급자계약형태계약형태_기타계약번호입찰공고번호설비유형공사비_계획공사비_실제공사기간_계획공사기간_실제시공용이성유지관리용이성시공단계시공단계_기타운전단계운전단계_기타시공단계_1시공단계_발생건수시공단계_조치결과운전단계_1운전단계_발생건수운전단계_조치결과만족도_경제성만족도_기술성만족도_환경성만족도_현장적용성승인여부적용 년
50915386687태백수도사업소 상수도시설물 보수공사<NA>태백시SIGU0257본사 물환경본부 수도통합운영센터 태백수도사업소2018-08-212018-08-242018-09-10맨홀 및 제수변 30EA1919719197태백수도사업소 상수도시설물 보수공사RELA0004<NA><NA><NA>EQPT000119197191973030EVLT0005EVLT0005EVEF0002,EVEF0004,EVEF0005<NA><NA><NA><NA>0<NA><NA>0<NA>STSF0005STSF0005STSF0005STSF0005Y2018
51014898690월미도 일원 하수관 정비공사<NA>북성동SIGU0063건설과2018-04-302018-05-042018-06-1817447561710월미도 일원 하수관 정비공사RELA0004<NA><NA><NA>EQPT000174475617103030EVLT0004EVLT0004EVEF0001,EVEF0002,EVEF0004,EVEF0005<NA>EVEF0001,EVEF0002,EVEF0004,EVEF0005<NA><NA>0<NA><NA>0<NA>STSF0004STSF0004STSF0004STSF0004Y2018
51115429692서면특성화거리일원 오수 노후관로 정비공사서울특별시 서초구 청계산로 59<NA>SIGU0034건설과2018-05-022018-05-082018-12-03L=861.3m530000530000서면특성화거리일원 오수 노후관로 정비공사RELA0002<NA>20180415208-0220180412142-01EQPT0001530000530000180210EVLT0004EVLT0004EVEF0001,EVEF0004,EVEF0005<NA>EVEF0002,EVEF0004<NA><NA>0<NA><NA>0<NA>STSF0004STSF0005STSF0005STSF0004Y2018
512117406932018년 북한산 우이지구 하수관로 정비공사<NA>북한산국립공원 내 (우이분소~도선광장 구간 중 우이분소 일원)SIGU0001탐방시설과2018-09-102018-09-122018-09-2033m994499442018년 북한산 우이지구 하수관로 정비공사RELA0004<NA>2018090375A-00<NA>EQPT0001132009944312EVLT0005EVLT0004EVEF0004,EVEF0005<NA>EVEF0004,EVEF0005<NA><NA>0<NA><NA>0<NA>STSF0004STSF0005STSF0005STSF0005Y2018
51313448694안양공공하수처리시설 약품(철-킬레이트)구입경기도 안양시 만안구 석천로 1안양공공하수처리장SIGU0098하수과2018-04-062018-04-062018-05-0912200kg5046850468안양공공하수처리시설 약품(철-킬레이트)구입RELA0004<NA><NA><NA>EQPT00020000EVLT0001EVLT0001<NA><NA>EVEF0004<NA><NA>0<NA><NA>0<NA>STSF0001STSF0001STSF0001STSF0004Y2018
51413448696안양공공하수처리시설 약품(철-킬레이트)구입경기도 안양시 만안구 석천로 1안양공공하수처리장SIGU0098하수과2018-11-272018-11-272018-12-0612200kg5046850468안양공공하수처리시설 약품(철-킬레이트)구입RELA0004<NA><NA><NA>EQPT00020000EVLT0001EVLT0001<NA><NA>EVEF0004<NA><NA>0<NA><NA>0<NA>STSF0001STSF0001STSF0001STSF0004Y2018
515150657092017년 하반기 성곡동 일원 노후관 갱생공사(신기술 특허공법)<NA>부천시SIGU0092수도과2017-12-062017-12-082018-06-12692m4146602797602017년 하반기 성곡동 일원 노후관 갱생공사(신기술 특허공법)RELA0002<NA>2017111245B-0020171118564-00EQPT00014161664146609090EVLT0001EVLT0001EVEF0004<NA><NA><NA><NA>0<NA><NA>0<NA>STSF0001STSF0004STSF0001STSF0004Y2018
51692847102018년 불량맨홀정비공사<NA>강동구 관내SIGU0003도로과2018-05-212018-05-242018-11-29123개소87920879202018년 불량맨홀정비공사RELA0003<NA>2018050C0B5-0020180503320EQPT00018792087920180180EVLT0004EVLT0004EVEF0005<NA><NA><NA><NA>0<NA><NA>0<NA>STSF0004STSF0004STSF0004STSF0004Y2018
51715065712경인로 202일원 하수관 정비공사(비굴착)<NA><NA>SIGU0092하수과2018-12-132018-12-132018-12-27130127659108630경인로 202일원 하수관 정비공사(비굴착)RELA0002<NA>20181204CAF-0020181132378-00EQPT00011287081286593030EVLT0001EVLT0001EVEF0004<NA><NA><NA><NA>0<NA><NA>0<NA>STSF0001STSF0001STSF0001STSF0001Y2018
51811684728지주형 흡착분해식 악취저감장치 제작구매 설치<NA><NA>SIGU0013치수과2018-11-292018-12-102018-12-101CMM(6set)8130081300지주형 흡착분해식 악취저감장치 제작구매 설치RELA0004<NA><NA><NA>EQPT000185800813003030EVLT0005EVLT0005EVEF0006악취발생 저감EVEF0006악취발생 저감<NA>0<NA><NA>0<NA>STSF0005STSF0005STSF0005STSF0005Y2018