Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory70.3 B

Variable types

DateTime1
Numeric2
Text2
Categorical3

Dataset

Description국가철도공단에서 시행하는 철도 건설 유지보수 사업 계약에관한 입찰공고문 첨부 문서 정보입니다. 사업명, 입찰공고문, 하도급관련 입찰공고 추가사항, 설계선, 공사내역서, 공사 시방서, 신기술 사용협약서, 신기술 적용현황 등 입니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15113759/fileData.do

Alerts

공고년도 has constant value ""Constant
공고일련번호 is highly overall correlated with 공고구분High correlation
공고구분 is highly overall correlated with 공고일련번호High correlation
공고차수 is highly imbalanced (82.7%)Imbalance

Reproduction

Analysis started2024-04-21 12:24:32.014189
Analysis finished2024-04-21 12:24:33.534218
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

첨부등록일자
Date

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
Minimum2023-04-13 00:00:00
Maximum2023-04-19 00:00:00
2024-04-21T21:24:33.614558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:24:33.784964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

첨부일련번호
Real number (ℝ)

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-21T21:24:33.954997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2065101
Coefficient of variation (CV)0.61291948
Kurtosis-0.85050566
Mean3.6
Median Absolute Deviation (MAD)2
Skewness0.53997674
Sum360
Variance4.8686869
MonotonicityNot monotonic
2024-04-21T21:24:34.321304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 21
21.0%
2 19
19.0%
3 15
15.0%
4 12
12.0%
5 11
11.0%
6 8
 
8.0%
7 7
 
7.0%
8 7
 
7.0%
ValueCountFrequency (%)
1 21
21.0%
2 19
19.0%
3 15
15.0%
4 12
12.0%
5 11
11.0%
6 8
 
8.0%
7 7
 
7.0%
8 7
 
7.0%
ValueCountFrequency (%)
8 7
 
7.0%
7 7
 
7.0%
6 8
 
8.0%
5 11
11.0%
4 12
12.0%
3 15
15.0%
2 19
19.0%
1 21
21.0%

첨부파일저장명
Text

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2024-04-21T21:24:35.063614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length31
Mean length31.11
Min length31

Characters and Unicode

Total characters3111
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)96.0%

Sample

1st row2023/04/2023-01-000049-00-1.hwp
2nd row2023/04/2023-01-000049-00-2.hwp
3rd row2023/04/2023-01-000049-00-3.hwp
4th row2023/04/2023-01-000049-00-4.xlsx
5th row2023/04/2023-01-000049-00-5.pdf
ValueCountFrequency (%)
2023/04/2023-02-000207-00-3.zip 2
 
2.0%
2023/04/2023-02-000207-00-2.zip 2
 
2.0%
2023/04/2023-02-000215-00-1.hwp 1
 
1.0%
2023/04/2023-02-000203-00-6.hwp 1
 
1.0%
2023/04/2023-01-000049-00-1.hwp 1
 
1.0%
2023/04/2023-02-000211-00-2.zip 1
 
1.0%
2023/04/2023-02-000207-02-1.hwp 1
 
1.0%
2023/04/2023-02-000207-01-1.hwp 1
 
1.0%
2023/04/2023-02-000207-00-1.hwp 1
 
1.0%
2023/04/2023-02-000204-00-2.zip 1
 
1.0%
Other values (88) 88
88.0%
2024-04-21T21:24:36.196435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 978
31.4%
2 513
16.5%
- 400
12.9%
3 242
 
7.8%
/ 200
 
6.4%
4 137
 
4.4%
. 100
 
3.2%
1 94
 
3.0%
p 89
 
2.9%
h 56
 
1.8%
Other values (13) 302
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2100
67.5%
Dash Punctuation 400
 
12.9%
Lowercase Letter 311
 
10.0%
Other Punctuation 300
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 978
46.6%
2 513
24.4%
3 242
 
11.5%
4 137
 
6.5%
1 94
 
4.5%
5 42
 
2.0%
8 31
 
1.5%
6 28
 
1.3%
9 21
 
1.0%
7 14
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
p 89
28.6%
h 56
18.0%
w 56
18.0%
x 22
 
7.1%
z 21
 
6.8%
i 21
 
6.8%
d 12
 
3.9%
f 12
 
3.9%
l 11
 
3.5%
s 11
 
3.5%
Other Punctuation
ValueCountFrequency (%)
/ 200
66.7%
. 100
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 400
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2800
90.0%
Latin 311
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 978
34.9%
2 513
18.3%
- 400
14.3%
3 242
 
8.6%
/ 200
 
7.1%
4 137
 
4.9%
. 100
 
3.6%
1 94
 
3.4%
5 42
 
1.5%
8 31
 
1.1%
Other values (3) 63
 
2.2%
Latin
ValueCountFrequency (%)
p 89
28.6%
h 56
18.0%
w 56
18.0%
x 22
 
7.1%
z 21
 
6.8%
i 21
 
6.8%
d 12
 
3.9%
f 12
 
3.9%
l 11
 
3.5%
s 11
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3111
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 978
31.4%
2 513
16.5%
- 400
12.9%
3 242
 
7.8%
/ 200
 
6.4%
4 137
 
4.4%
. 100
 
3.2%
1 94
 
3.0%
p 89
 
2.9%
h 56
 
1.8%
Other values (13) 302
 
9.7%

첨부파일명
Text

Distinct79
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2024-04-21T21:24:36.946680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length37
Mean length29.9
Min length10

Characters and Unicode

Total characters2990
Distinct characters195
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)65.0%

Sample

1st row붙임1. 입찰공고문(영동선 임기~석포 등 33개소 재해예방시설 설치공사).hwp
2nd row붙임1-1. 하도급관련 입찰공고 추가사항.hwp
3rd row붙임2. 설계서(영동선 임기~석포 등 33개소 재해예방시설 설치공사).hwp
4th row붙임3. 공내역서(영동선 임기~석포 등 33개소 재해예방시설 설치공사).xlsx
5th row붙임4. 공사시방서(영동선 임기~석포 등 33개소 재해예방시설 설치공사).pdf
ValueCountFrequency (%)
등 27
 
6.6%
광역철도 12
 
2.9%
재해예방시설 12
 
2.9%
용역계약일반조건 10
 
2.4%
신기술 8
 
2.0%
설치공사).hwp 7
 
1.7%
31개소 6
 
1.5%
문단~임기 6
 
1.5%
입석리~조동 6
 
1.5%
임기~석포 6
 
1.5%
Other values (159) 310
75.6%
2024-04-21T21:24:38.348583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
310
 
10.4%
. 190
 
6.4%
p 89
 
3.0%
( 71
 
2.4%
) 71
 
2.4%
2 71
 
2.4%
w 56
 
1.9%
h 56
 
1.9%
1 53
 
1.8%
역 52
 
1.7%
Other values (185) 1971
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1677
56.1%
Lowercase Letter 312
 
10.4%
Space Separator 310
 
10.4%
Decimal Number 243
 
8.1%
Other Punctuation 192
 
6.4%
Open Punctuation 71
 
2.4%
Close Punctuation 71
 
2.4%
Connector Punctuation 37
 
1.2%
Math Symbol 28
 
0.9%
Uppercase Letter 27
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 52
 
3.1%
설 50
 
3.0%
임 50
 
3.0%
공 47
 
2.8%
계 47
 
2.8%
등 45
 
2.7%
서 42
 
2.5%
사 41
 
2.4%
기 40
 
2.4%
조 39
 
2.3%
Other values (143) 1224
73.0%
Uppercase Letter
ValueCountFrequency (%)
V 6
22.2%
I 5
18.5%
D 5
18.5%
T 2
 
7.4%
C 2
 
7.4%
S 1
 
3.7%
P 1
 
3.7%
M 1
 
3.7%
B 1
 
3.7%
G 1
 
3.7%
Other values (2) 2
 
7.4%
Lowercase Letter
ValueCountFrequency (%)
p 89
28.5%
w 56
17.9%
h 56
17.9%
x 22
 
7.1%
i 21
 
6.7%
z 21
 
6.7%
d 12
 
3.8%
f 12
 
3.8%
s 11
 
3.5%
l 11
 
3.5%
Decimal Number
ValueCountFrequency (%)
2 71
29.2%
1 53
21.8%
3 41
16.9%
0 28
 
11.5%
5 16
 
6.6%
4 13
 
5.3%
6 9
 
3.7%
7 6
 
2.5%
8 5
 
2.1%
9 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 190
99.0%
, 2
 
1.0%
Math Symbol
ValueCountFrequency (%)
~ 27
96.4%
+ 1
 
3.6%
Space Separator
ValueCountFrequency (%)
310
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Close Punctuation
ValueCountFrequency (%)
) 71
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1677
56.1%
Common 974
32.6%
Latin 339
 
11.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 52
 
3.1%
설 50
 
3.0%
임 50
 
3.0%
공 47
 
2.8%
계 47
 
2.8%
등 45
 
2.7%
서 42
 
2.5%
사 41
 
2.4%
기 40
 
2.4%
조 39
 
2.3%
Other values (143) 1224
73.0%
Latin
ValueCountFrequency (%)
p 89
26.3%
w 56
16.5%
h 56
16.5%
x 22
 
6.5%
i 21
 
6.2%
z 21
 
6.2%
d 12
 
3.5%
f 12
 
3.5%
s 11
 
3.2%
l 11
 
3.2%
Other values (13) 28
 
8.3%
Common
ValueCountFrequency (%)
310
31.8%
. 190
19.5%
( 71
 
7.3%
) 71
 
7.3%
2 71
 
7.3%
1 53
 
5.4%
3 41
 
4.2%
_ 37
 
3.8%
0 28
 
2.9%
~ 27
 
2.8%
Other values (9) 75
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1677
56.1%
ASCII 1313
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
310
23.6%
. 190
14.5%
p 89
 
6.8%
( 71
 
5.4%
) 71
 
5.4%
2 71
 
5.4%
w 56
 
4.3%
h 56
 
4.3%
1 53
 
4.0%
3 41
 
3.1%
Other values (32) 305
23.2%
Hangul
ValueCountFrequency (%)
역 52
 
3.1%
설 50
 
3.0%
임 50
 
3.0%
공 47
 
2.8%
계 47
 
2.8%
등 45
 
2.7%
서 42
 
2.5%
사 41
 
2.4%
기 40
 
2.4%
조 39
 
2.3%
Other values (143) 1224
73.0%

공고년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2023
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2023 100
100.0%

Length

2024-04-21T21:24:38.561661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T21:24:38.716674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 100
100.0%

공고구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2
49 
1
32 
3
19 

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 (%)
2 49
49.0%
1 32
32.0%
3 19
 
19.0%

Length

2024-04-21T21:24:38.875203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T21:24:39.043375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 49
49.0%
1 32
32.0%
3 19
 
19.0%

공고일련번호
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.43
Minimum46
Maximum216
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-21T21:24:39.207422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile47.9
Q150
median52
Q3202
95-th percentile211.15
Maximum216
Range170
Interquartile range (IQR)152

Descriptive statistics

Standard deviation74.921272
Coefficient of variation (CV)0.61195191
Kurtosis-1.9824689
Mean122.43
Median Absolute Deviation (MAD)6
Skewness0.082345678
Sum12243
Variance5613.1971
MonotonicityNot monotonic
2024-04-21T21:24:39.406129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
49 13
13.0%
52 13
13.0%
51 9
9.0%
198 8
8.0%
50 8
8.0%
203 8
8.0%
186 8
8.0%
207 7
7.0%
168 5
 
5.0%
46 5
 
5.0%
Other values (8) 16
16.0%
ValueCountFrequency (%)
46 5
 
5.0%
48 3
 
3.0%
49 13
13.0%
50 8
8.0%
51 9
9.0%
52 13
13.0%
168 5
 
5.0%
186 8
8.0%
198 8
8.0%
201 1
 
1.0%
ValueCountFrequency (%)
216 2
 
2.0%
215 1
 
1.0%
214 2
 
2.0%
211 2
 
2.0%
207 7
7.0%
204 2
 
2.0%
203 8
8.0%
202 3
 
3.0%
201 1
 
1.0%
198 8
8.0%

공고차수
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
0
96 
1
 
3
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 96
96.0%
1 3
 
3.0%
2 1
 
1.0%

Length

2024-04-21T21:24:39.617131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T21:24:39.782666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 96
96.0%
1 3
 
3.0%
2 1
 
1.0%

Interactions

2024-04-21T21:24:32.849531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:24:32.501113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:24:33.008838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:24:32.695756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T21:24:39.895725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
첨부등록일자첨부일련번호첨부파일저장명첨부파일명공고구분공고일련번호공고차수
첨부등록일자1.0000.0001.0000.9230.4250.6680.000
첨부일련번호0.0001.0001.0001.0000.0000.0000.000
첨부파일저장명1.0001.0001.0001.0001.0001.0000.000
첨부파일명0.9231.0001.0001.0001.0000.9840.000
공고구분0.4250.0001.0001.0001.0000.6670.137
공고일련번호0.6680.0001.0000.9840.6671.0000.165
공고차수0.0000.0000.0000.0000.1370.1651.000
2024-04-21T21:24:40.077702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공고구분공고차수
공고구분1.0000.039
공고차수0.0391.000
2024-04-21T21:24:40.312315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
첨부일련번호공고일련번호공고구분공고차수
첨부일련번호1.000-0.2130.0000.000
공고일련번호-0.2131.0000.6920.154
공고구분0.0000.6921.0000.039
공고차수0.0000.1540.0391.000

Missing values

2024-04-21T21:24:33.212380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T21:24:33.430669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

첨부등록일자첨부일련번호첨부파일저장명첨부파일명공고년도공고구분공고일련번호공고차수
02023-04-1712023/04/2023-01-000049-00-1.hwp붙임1. 입찰공고문(영동선 임기~석포 등 33개소 재해예방시설 설치공사).hwp20231490
12023-04-1722023/04/2023-01-000049-00-2.hwp붙임1-1. 하도급관련 입찰공고 추가사항.hwp20231490
22023-04-1732023/04/2023-01-000049-00-3.hwp붙임2. 설계서(영동선 임기~석포 등 33개소 재해예방시설 설치공사).hwp20231490
32023-04-1742023/04/2023-01-000049-00-4.xlsx붙임3. 공내역서(영동선 임기~석포 등 33개소 재해예방시설 설치공사).xlsx20231490
42023-04-1752023/04/2023-01-000049-00-5.pdf붙임4. 공사시방서(영동선 임기~석포 등 33개소 재해예방시설 설치공사).pdf20231490
52023-04-1762023/04/2023-01-000049-00-6.pdf붙임5-1. 신기술 사용협약서(영동선 임기~석포 등 33개소).pdf20231490
62023-04-1772023/04/2023-01-000049-00-7.pdf붙임5-2. 신기술 적용현황(영동선 임기~석포 등 33개소).pdf20231490
72023-04-1782023/04/2023-01-000049-00-8.zip붙임6. 계약관련 규정 등_20230213 시행.zip20231490
82023-04-1712023/04/2023-01-000050-00-1.hwp붙임1.입찰공고문(태백선 입석리~조동 등 21개소 재해예방시설 설치공사).hwp20231500
92023-04-1722023/04/2023-01-000050-00-2.hwp붙임1-1.하도급관련 입찰공고 추가사항.hwp20231500
첨부등록일자첨부일련번호첨부파일저장명첨부파일명공고년도공고구분공고일련번호공고차수
902023-04-1722023/04/2023-03-000049-00-2.hwp붙임2. 제안요청서(스마트워크시스템(VDI)).hwp20233490
912023-04-1732023/04/2023-03-000049-00-3.xlsx붙임3. 가격제안 세부내역서(스마트워크시스템(VDI)).xlsx20233490
922023-04-1742023/04/2023-03-000049-00-4.hwp붙임4. 설계서(스마트워크시스템(VDI)).hwp20233490
932023-04-1752023/04/2023-03-000049-00-5.hwp붙임5. 물품구매계약 추가특수조건(스마트워크시스템(VDI)).hwp20233490
942023-04-1462023/04/2023-03-000051-00-6.hwp1. 수의시담 요청공고(호남본부 5공구 혼합골재).hwp20233510
952023-04-1912023/04/2023-03-000052-00-1.hwp1._입찰공고문(대구권 광역철도 조명제어장치).hwp20233520
962023-04-1922023/04/2023-03-000052-00-2.xlsx2._(공내역)물품구매산출내역서(대구권 광역철도 조명제어장치 제조구매).xlsx20233520
972023-04-1932023/04/2023-03-000052-00-3.hwp3._물품구매계약 추가특수조건(대구권 광역철도 조명제어장치 제조구매).hwp20233520
982023-04-1942023/04/2023-03-000052-00-4.pdf4._도면(대구권 광역철도 조명제어장치 제조구매).pdf20233520
992023-04-1952023/04/2023-03-000052-00-5.hwp5._물품구매제작사양서(대구권 광역철도 조명제어장치 제조구매).hwp20233520