Overview

Dataset statistics

Number of variables15
Number of observations772
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory91.4 KiB
Average record size in memory121.2 B

Variable types

Categorical2
Numeric1
Text6
DateTime5
Boolean1

Dataset

Description국가철도공단에서 시행하는 철도건설사업에 관보고시 기본정보입니다. 지역본부, 사업명, 고시번호, 고시기관, 고시명 등이 포함되어있습니다.
URLhttps://www.data.go.kr/data/15114027/fileData.do

Alerts

사업시작일자 has constant value ""Constant
고시기관명 is highly imbalanced (51.0%)Imbalance

Reproduction

Analysis started2023-12-11 23:09:41.385729
Analysis finished2023-12-11 23:09:42.829350
Duration1.44 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역본부코드
Categorical

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
BP01
272 
BP02
197 
BP04
111 
BP05
104 
BP03
88 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBP01
2nd rowBP01
3rd rowBP01
4th rowBP01
5th rowBP01

Common Values

ValueCountFrequency (%)
BP01 272
35.2%
BP02 197
25.5%
BP04 111
14.4%
BP05 104
 
13.5%
BP03 88
 
11.4%

Length

2023-12-12T08:09:42.887820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:09:42.982087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bp01 272
35.2%
bp02 197
25.5%
bp04 111
14.4%
bp05 104
 
13.5%
bp03 88
 
11.4%

사업코드
Real number (ℝ)

Distinct57
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1608.2927
Minimum1020
Maximum3100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2023-12-12T08:09:43.093859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1020
5-th percentile1020
Q11250
median1460
Q32030
95-th percentile2359
Maximum3100
Range2080
Interquartile range (IQR)780

Descriptive statistics

Standard deviation445.87796
Coefficient of variation (CV)0.27723682
Kurtosis-0.40557055
Mean1608.2927
Median Absolute Deviation (MAD)240
Skewness0.714766
Sum1241602
Variance198807.15
MonotonicityNot monotonic
2023-12-12T08:09:43.212486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1610 51
 
6.6%
2210 44
 
5.7%
1020 44
 
5.7%
2030 35
 
4.5%
1430 33
 
4.3%
1080 32
 
4.1%
1420 30
 
3.9%
1330 29
 
3.8%
1460 28
 
3.6%
1210 23
 
3.0%
Other values (47) 423
54.8%
ValueCountFrequency (%)
1020 44
5.7%
1021 11
 
1.4%
1080 32
4.1%
1200 19
2.5%
1201 7
 
0.9%
1210 23
3.0%
1220 22
2.8%
1230 11
 
1.4%
1240 18
2.3%
1250 10
 
1.3%
ValueCountFrequency (%)
3100 1
 
0.1%
3000 1
 
0.1%
2930 1
 
0.1%
2890 2
 
0.3%
2790 2
 
0.3%
2780 1
 
0.1%
2770 1
 
0.1%
2710 1
 
0.1%
2680 2
 
0.3%
2650 7
0.9%

관보고시번호
Text

Distinct687
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2023-12-12T08:09:43.540162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.9974093
Min length6

Characters and Unicode

Total characters6174
Distinct characters14
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

Unique616 ?
Unique (%)79.8%

Sample

1st row2015-982
2nd row2003-53
3rd row2015-325
4th row2008-129
5th row2010-25
ValueCountFrequency (%)
2021-1209 5
 
0.6%
2020-229 5
 
0.6%
2022-530 4
 
0.5%
2015-688 3
 
0.4%
2020-512 3
 
0.4%
2010-121 3
 
0.4%
2012-598 3
 
0.4%
2016-668 3
 
0.4%
2011-67 3
 
0.4%
2008-912 2
 
0.3%
Other values (677) 738
95.6%
2023-12-12T08:09:44.022117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1282
20.8%
0 1146
18.6%
1 923
14.9%
- 772
12.5%
6 303
 
4.9%
5 301
 
4.9%
8 300
 
4.9%
3 297
 
4.8%
7 296
 
4.8%
4 280
 
4.5%
Other values (4) 274
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5398
87.4%
Dash Punctuation 772
 
12.5%
Other Letter 4
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1282
23.7%
0 1146
21.2%
1 923
17.1%
6 303
 
5.6%
5 301
 
5.6%
8 300
 
5.6%
3 297
 
5.5%
7 296
 
5.5%
4 280
 
5.2%
9 270
 
5.0%
Other Letter
ValueCountFrequency (%)
정 2
50.0%
추 1
25.0%
가 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 772
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6170
99.9%
Hangul 4
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1282
20.8%
0 1146
18.6%
1 923
15.0%
- 772
12.5%
6 303
 
4.9%
5 301
 
4.9%
8 300
 
4.9%
3 297
 
4.8%
7 296
 
4.8%
4 280
 
4.5%
Hangul
ValueCountFrequency (%)
정 2
50.0%
추 1
25.0%
가 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6170
99.9%
Hangul 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1282
20.8%
0 1146
18.6%
1 923
15.0%
- 772
12.5%
6 303
 
4.9%
5 301
 
4.9%
8 300
 
4.9%
3 297
 
4.8%
7 296
 
4.8%
4 280
 
4.5%
Hangul
ValueCountFrequency (%)
정 2
50.0%
추 1
25.0%
가 1
25.0%

고시기관명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
국토교통부
545 
국토해양부
177 
건설교통부
 
44
철도청
 
5
국토교통부
 
1

Length

Max length6
Median length5
Mean length4.988342
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row국토교통부
2nd row건설교통부
3rd row국토교통부
4th row국토해양부
5th row국토해양부

Common Values

ValueCountFrequency (%)
국토교통부 545
70.6%
국토해양부 177
 
22.9%
건설교통부 44
 
5.7%
철도청 5
 
0.6%
국토교통부 1
 
0.1%

Length

2023-12-12T08:09:44.150064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:09:44.256090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국토교통부 546
70.7%
국토해양부 177
 
22.9%
건설교통부 44
 
5.7%
철도청 5
 
0.6%

고시명
Text

Distinct334
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2023-12-12T08:09:44.496014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39
Mean length27.645078
Min length5

Characters and Unicode

Total characters21342
Distinct characters204
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique232 ?
Unique (%)30.1%

Sample

1st row경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인
2nd row경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인
3rd row경춘선 금곡~춘천간 복선전철 건설사업 변경고시
4th row경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인
5th row경춘선 금곡~춘천간 복선전철 건설사업 실시게획 변경승인
ValueCountFrequency (%)
실시계획 553
 
13.9%
승인 438
 
11.0%
변경 371
 
9.3%
건설사업 335
 
8.4%
복선전철 292
 
7.3%
변경승인 76
 
1.9%
경부고속철도 55
 
1.4%
호남고속철도 52
 
1.3%
고시 46
 
1.2%
구간 45
 
1.1%
Other values (271) 1718
43.2%
2023-12-12T08:09:44.885345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3227
 
15.1%
사 786
 
3.7%
시 776
 
3.6%
철 742
 
3.5%
업 722
 
3.4%
~ 716
 
3.4%
설 703
 
3.3%
경 682
 
3.2%
선 663
 
3.1%
건 642
 
3.0%
Other values (194) 11683
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16564
77.6%
Space Separator 3227
 
15.1%
Math Symbol 749
 
3.5%
Close Punctuation 321
 
1.5%
Open Punctuation 319
 
1.5%
Decimal Number 91
 
0.4%
Other Punctuation 41
 
0.2%
Uppercase Letter 12
 
0.1%
Dash Punctuation 10
 
< 0.1%
Connector Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 786
 
4.7%
시 776
 
4.7%
철 742
 
4.5%
업 722
 
4.4%
설 703
 
4.2%
경 682
 
4.1%
선 663
 
4.0%
건 642
 
3.9%
계 636
 
3.8%
획 612
 
3.7%
Other values (156) 9600
58.0%
Decimal Number
ValueCountFrequency (%)
2 29
31.9%
1 28
30.8%
6 8
 
8.8%
7 7
 
7.7%
8 4
 
4.4%
4 4
 
4.4%
9 4
 
4.4%
5 3
 
3.3%
3 2
 
2.2%
0 2
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
T 3
25.0%
X 2
16.7%
K 2
16.7%
L 1
 
8.3%
P 1
 
8.3%
B 1
 
8.3%
F 1
 
8.3%
R 1
 
8.3%
Math Symbol
ValueCountFrequency (%)
~ 716
95.6%
∼ 22
 
2.9%
～ 7
 
0.9%
< 2
 
0.3%
> 2
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 30
73.2%
. 6
 
14.6%
? 3
 
7.3%
: 2
 
4.9%
Close Punctuation
ValueCountFrequency (%)
) 317
98.8%
〉 2
 
0.6%
] 2
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 315
98.7%
〈 2
 
0.6%
[ 2
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
m 1
50.0%
Space Separator
ValueCountFrequency (%)
3227
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16564
77.6%
Common 4764
 
22.3%
Latin 14
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 786
 
4.7%
시 776
 
4.7%
철 742
 
4.5%
업 722
 
4.4%
설 703
 
4.2%
경 682
 
4.1%
선 663
 
4.0%
건 642
 
3.9%
계 636
 
3.8%
획 612
 
3.7%
Other values (156) 9600
58.0%
Common
ValueCountFrequency (%)
3227
67.7%
~ 716
 
15.0%
) 317
 
6.7%
( 315
 
6.6%
, 30
 
0.6%
2 29
 
0.6%
1 28
 
0.6%
∼ 22
 
0.5%
- 10
 
0.2%
6 8
 
0.2%
Other values (18) 62
 
1.3%
Latin
ValueCountFrequency (%)
T 3
21.4%
X 2
14.3%
K 2
14.3%
L 1
 
7.1%
k 1
 
7.1%
P 1
 
7.1%
m 1
 
7.1%
B 1
 
7.1%
F 1
 
7.1%
R 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16564
77.6%
ASCII 4745
 
22.2%
Math Operators 22
 
0.1%
None 11
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3227
68.0%
~ 716
 
15.1%
) 317
 
6.7%
( 315
 
6.6%
, 30
 
0.6%
2 29
 
0.6%
1 28
 
0.6%
- 10
 
0.2%
6 8
 
0.2%
7 7
 
0.1%
Other values (24) 58
 
1.2%
Hangul
ValueCountFrequency (%)
사 786
 
4.7%
시 776
 
4.7%
철 742
 
4.5%
업 722
 
4.4%
설 703
 
4.2%
경 682
 
4.1%
선 663
 
4.0%
건 642
 
3.9%
계 636
 
3.8%
획 612
 
3.7%
Other values (156) 9600
58.0%
Math Operators
ValueCountFrequency (%)
∼ 22
100.0%
None
ValueCountFrequency (%)
～ 7
63.6%
〉 2
 
18.2%
〈 2
 
18.2%

고시일자
Date

Distinct563
Distinct (%)72.9%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
Minimum2001-06-27 00:00:00
Maximum2023-04-05 00:00:00
2023-12-12T08:09:45.018867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:09:45.165130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

고시내용
Text

Distinct334
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2023-12-12T08:09:45.553496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39
Mean length27.645078
Min length5

Characters and Unicode

Total characters21342
Distinct characters204
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique232 ?
Unique (%)30.1%

Sample

1st row경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인
2nd row경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인
3rd row경춘선 금곡~춘천간 복선전철 건설사업 변경고시
4th row경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인
5th row경춘선 금곡~춘천간 복선전철 건설사업 실시게획 변경승인
ValueCountFrequency (%)
실시계획 553
 
13.9%
승인 438
 
11.0%
변경 371
 
9.3%
건설사업 335
 
8.4%
복선전철 292
 
7.3%
변경승인 76
 
1.9%
경부고속철도 55
 
1.4%
호남고속철도 52
 
1.3%
고시 46
 
1.2%
구간 45
 
1.1%
Other values (271) 1718
43.2%
2023-12-12T08:09:46.111627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3227
 
15.1%
사 786
 
3.7%
시 776
 
3.6%
철 742
 
3.5%
업 722
 
3.4%
~ 716
 
3.4%
설 703
 
3.3%
경 682
 
3.2%
선 663
 
3.1%
건 642
 
3.0%
Other values (194) 11683
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16564
77.6%
Space Separator 3227
 
15.1%
Math Symbol 749
 
3.5%
Close Punctuation 321
 
1.5%
Open Punctuation 319
 
1.5%
Decimal Number 91
 
0.4%
Other Punctuation 41
 
0.2%
Uppercase Letter 12
 
0.1%
Dash Punctuation 10
 
< 0.1%
Connector Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 786
 
4.7%
시 776
 
4.7%
철 742
 
4.5%
업 722
 
4.4%
설 703
 
4.2%
경 682
 
4.1%
선 663
 
4.0%
건 642
 
3.9%
계 636
 
3.8%
획 612
 
3.7%
Other values (156) 9600
58.0%
Decimal Number
ValueCountFrequency (%)
2 29
31.9%
1 28
30.8%
6 8
 
8.8%
7 7
 
7.7%
8 4
 
4.4%
4 4
 
4.4%
9 4
 
4.4%
5 3
 
3.3%
3 2
 
2.2%
0 2
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
T 3
25.0%
X 2
16.7%
K 2
16.7%
L 1
 
8.3%
P 1
 
8.3%
B 1
 
8.3%
F 1
 
8.3%
R 1
 
8.3%
Math Symbol
ValueCountFrequency (%)
~ 716
95.6%
∼ 22
 
2.9%
～ 7
 
0.9%
< 2
 
0.3%
> 2
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 30
73.2%
. 6
 
14.6%
? 3
 
7.3%
: 2
 
4.9%
Close Punctuation
ValueCountFrequency (%)
) 317
98.8%
〉 2
 
0.6%
] 2
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 315
98.7%
〈 2
 
0.6%
[ 2
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
m 1
50.0%
Space Separator
ValueCountFrequency (%)
3227
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16564
77.6%
Common 4764
 
22.3%
Latin 14
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 786
 
4.7%
시 776
 
4.7%
철 742
 
4.5%
업 722
 
4.4%
설 703
 
4.2%
경 682
 
4.1%
선 663
 
4.0%
건 642
 
3.9%
계 636
 
3.8%
획 612
 
3.7%
Other values (156) 9600
58.0%
Common
ValueCountFrequency (%)
3227
67.7%
~ 716
 
15.0%
) 317
 
6.7%
( 315
 
6.6%
, 30
 
0.6%
2 29
 
0.6%
1 28
 
0.6%
∼ 22
 
0.5%
- 10
 
0.2%
6 8
 
0.2%
Other values (18) 62
 
1.3%
Latin
ValueCountFrequency (%)
T 3
21.4%
X 2
14.3%
K 2
14.3%
L 1
 
7.1%
k 1
 
7.1%
P 1
 
7.1%
m 1
 
7.1%
B 1
 
7.1%
F 1
 
7.1%
R 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16564
77.6%
ASCII 4745
 
22.2%
Math Operators 22
 
0.1%
None 11
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3227
68.0%
~ 716
 
15.1%
) 317
 
6.7%
( 315
 
6.6%
, 30
 
0.6%
2 29
 
0.6%
1 28
 
0.6%
- 10
 
0.2%
6 8
 
0.2%
7 7
 
0.1%
Other values (24) 58
 
1.2%
Hangul
ValueCountFrequency (%)
사 786
 
4.7%
시 776
 
4.7%
철 742
 
4.5%
업 722
 
4.4%
설 703
 
4.2%
경 682
 
4.1%
선 663
 
4.0%
건 642
 
3.9%
계 636
 
3.8%
획 612
 
3.7%
Other values (156) 9600
58.0%
Math Operators
ValueCountFrequency (%)
∼ 22
100.0%
None
ValueCountFrequency (%)
～ 7
63.6%
〉 2
 
18.2%
〈 2
 
18.2%

사업시작일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
Minimum2002-01-01 00:00:00
Maximum2002-01-01 00:00:00
2023-12-12T08:09:46.269607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:09:46.376203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

사업종료일자
Date

Distinct70
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
Minimum2006-12-31 00:00:00
Maximum2046-08-11 00:00:00
2023-12-12T08:09:46.515636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:09:46.670669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대민게시여부
Boolean

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size904.0 B
True
499 
False
273 
ValueCountFrequency (%)
True 499
64.6%
False 273
35.4%
2023-12-12T08:09:46.820604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

첨부파일번호
Text

Distinct656
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2023-12-12T08:09:47.042814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters15440
Distinct characters19
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

Unique557 ?
Unique (%)72.2%

Sample

1st rowOFCTT_00000000000332
2nd rowOFCTT_00000000000152
3rd rowOFCTT_00000000000346
4th rowOFCTT_00000000000345
5th rowOFCTT_00000000000298
ValueCountFrequency (%)
ofctt_00000000000185 4
 
0.5%
ofctt_00000000000238 4
 
0.5%
ofctt_00000000000419 4
 
0.5%
ofctt_00000000000052 4
 
0.5%
ofctt_00000000000231 4
 
0.5%
ofctt_00000000000169 3
 
0.4%
ofctt_00000000000495 3
 
0.4%
ofctt_00000000000051 3
 
0.4%
ofctt_00000000000095 3
 
0.4%
ofctt_00000000000166 3
 
0.4%
Other values (646) 737
95.5%
2023-12-12T08:09:47.426499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7886
51.1%
T 1088
 
7.0%
_ 1000
 
6.5%
F 772
 
5.0%
O 544
 
3.5%
C 544
 
3.5%
2 457
 
3.0%
I 456
 
3.0%
5 366
 
2.4%
1 362
 
2.3%
Other values (9) 1965
 
12.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10352
67.0%
Uppercase Letter 4088
 
26.5%
Connector Punctuation 1000
 
6.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7886
76.2%
2 457
 
4.4%
5 366
 
3.5%
1 362
 
3.5%
4 290
 
2.8%
3 260
 
2.5%
6 201
 
1.9%
9 187
 
1.8%
7 178
 
1.7%
8 165
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
T 1088
26.6%
F 772
18.9%
O 544
13.3%
C 544
13.3%
I 456
11.2%
L 228
 
5.6%
E 228
 
5.6%
D 228
 
5.6%
Connector Punctuation
ValueCountFrequency (%)
_ 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11352
73.5%
Latin 4088
 
26.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7886
69.5%
_ 1000
 
8.8%
2 457
 
4.0%
5 366
 
3.2%
1 362
 
3.2%
4 290
 
2.6%
3 260
 
2.3%
6 201
 
1.8%
9 187
 
1.6%
7 178
 
1.6%
Latin
ValueCountFrequency (%)
T 1088
26.6%
F 772
18.9%
O 544
13.3%
C 544
13.3%
I 456
11.2%
L 228
 
5.6%
E 228
 
5.6%
D 228
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7886
51.1%
T 1088
 
7.0%
_ 1000
 
6.5%
F 772
 
5.0%
O 544
 
3.5%
C 544
 
3.5%
2 457
 
3.0%
I 456
 
3.0%
5 366
 
2.4%
1 362
 
2.3%
Other values (9) 1965
 
12.7%

입력인ID
Text

Distinct67
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2023-12-12T08:09:47.680866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.5362694
Min length6

Characters and Unicode

Total characters5046
Distinct characters16
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

Unique32 ?
Unique (%)4.1%

Sample

1st rowSYSTEM
2nd rowSYSTEM
3rd rowSYSTEM
4th rowSYSTEM
5th rowSYSTEM
ValueCountFrequency (%)
system 565
73.2%
t6013463 21
 
2.7%
10001409 20
 
2.6%
10001505 18
 
2.3%
10001352 11
 
1.4%
10001706 9
 
1.2%
t6013464 9
 
1.2%
10004063 7
 
0.9%
10002826 6
 
0.8%
10000973 6
 
0.8%
Other values (57) 100
 
13.0%
2023-12-12T08:09:48.119740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 1130
22.4%
0 653
12.9%
Y 565
11.2%
T 565
11.2%
E 565
11.2%
M 565
11.2%
1 360
 
7.1%
3 120
 
2.4%
4 116
 
2.3%
6 110
 
2.2%
Other values (6) 297
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3390
67.2%
Decimal Number 1622
32.1%
Lowercase Letter 34
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 653
40.3%
1 360
22.2%
3 120
 
7.4%
4 116
 
7.2%
6 110
 
6.8%
5 68
 
4.2%
2 60
 
3.7%
9 52
 
3.2%
7 45
 
2.8%
8 38
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
S 1130
33.3%
Y 565
16.7%
T 565
16.7%
E 565
16.7%
M 565
16.7%
Lowercase Letter
ValueCountFrequency (%)
t 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3424
67.9%
Common 1622
32.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 653
40.3%
1 360
22.2%
3 120
 
7.4%
4 116
 
7.2%
6 110
 
6.8%
5 68
 
4.2%
2 60
 
3.7%
9 52
 
3.2%
7 45
 
2.8%
8 38
 
2.3%
Latin
ValueCountFrequency (%)
S 1130
33.0%
Y 565
16.5%
T 565
16.5%
E 565
16.5%
M 565
16.5%
t 34
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5046
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 1130
22.4%
0 653
12.9%
Y 565
11.2%
T 565
11.2%
E 565
11.2%
M 565
11.2%
1 360
 
7.1%
3 120
 
2.4%
4 116
 
2.3%
6 110
 
2.2%
Other values (6) 297
 
5.9%

입력일시
Date

Distinct173
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
Minimum2018-03-13 00:00:00
Maximum2023-04-05 00:00:00
2023-12-12T08:09:48.298615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:09:48.465268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

변경인ID
Text

Distinct71
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2023-12-12T08:09:48.746087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.753886
Min length6

Characters and Unicode

Total characters5214
Distinct characters16
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

Unique25 ?
Unique (%)3.2%

Sample

1st rowSYSTEM
2nd rowSYSTEM
3rd rowSYSTEM
4th rowSYSTEM
5th rowSYSTEM
ValueCountFrequency (%)
system 481
62.3%
10001505 23
 
3.0%
10001352 21
 
2.7%
t6013463 20
 
2.6%
10001409 19
 
2.5%
10001706 13
 
1.7%
10001201 12
 
1.6%
10001504 11
 
1.4%
10000721 10
 
1.3%
t6013464 9
 
1.2%
Other values (61) 153
 
19.8%
2023-12-12T08:09:49.199074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 962
18.5%
0 934
17.9%
1 527
10.1%
Y 481
9.2%
T 481
9.2%
E 481
9.2%
M 481
9.2%
4 156
 
3.0%
6 136
 
2.6%
3 128
 
2.5%
Other values (6) 447
8.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2886
55.4%
Decimal Number 2287
43.9%
Lowercase Letter 41
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 934
40.8%
1 527
23.0%
4 156
 
6.8%
6 136
 
5.9%
3 128
 
5.6%
2 112
 
4.9%
5 104
 
4.5%
7 77
 
3.4%
9 67
 
2.9%
8 46
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
S 962
33.3%
Y 481
16.7%
T 481
16.7%
E 481
16.7%
M 481
16.7%
Lowercase Letter
ValueCountFrequency (%)
t 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2927
56.1%
Common 2287
43.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 934
40.8%
1 527
23.0%
4 156
 
6.8%
6 136
 
5.9%
3 128
 
5.6%
2 112
 
4.9%
5 104
 
4.5%
7 77
 
3.4%
9 67
 
2.9%
8 46
 
2.0%
Latin
ValueCountFrequency (%)
S 962
32.9%
Y 481
16.4%
T 481
16.4%
E 481
16.4%
M 481
16.4%
t 41
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5214
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 962
18.5%
0 934
17.9%
1 527
10.1%
Y 481
9.2%
T 481
9.2%
E 481
9.2%
M 481
9.2%
4 156
 
3.0%
6 136
 
2.6%
3 128
 
2.5%
Other values (6) 447
8.6%

변경일자
Date

Distinct216
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
Minimum2018-03-13 00:00:00
Maximum2023-04-21 00:00:00
2023-12-12T08:09:49.362044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:09:49.557618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T08:09:42.172111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:09:49.707493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역본부코드사업코드고시기관명사업종료일자대민게시여부입력인ID변경인ID
지역본부코드1.0000.5950.2800.7570.2060.8000.885
사업코드0.5951.0000.2380.7720.3640.8220.820
고시기관명0.2800.2381.0000.8800.3140.3640.297
사업종료일자0.7570.7720.8801.0000.8480.8620.876
대민게시여부0.2060.3640.3140.8481.0000.8940.821
입력인ID0.8000.8220.3640.8620.8941.0000.992
변경인ID0.8850.8200.2970.8760.8210.9921.000
2023-12-12T08:09:49.854320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역본부코드대민게시여부고시기관명
지역본부코드1.0000.2510.108
대민게시여부0.2511.0000.382
고시기관명0.1080.3821.000
2023-12-12T08:09:49.959754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업코드지역본부코드고시기관명대민게시여부
사업코드1.0000.3900.1370.342
지역본부코드0.3901.0000.1080.251
고시기관명0.1370.1081.0000.382
대민게시여부0.3420.2510.3821.000

Missing values

2023-12-12T08:09:42.575299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:09:42.760829image/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

지역본부코드사업코드관보고시번호고시기관명고시명고시일자고시내용사업시작일자사업종료일자대민게시여부첨부파일번호입력인ID입력일시변경인ID변경일자
0BP0110802015-982국토교통부경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인2015-12-28경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인2002-01-012016-06-30YOFCTT_00000000000332SYSTEM2018-06-08SYSTEM2018-06-08
1BP0110802003-53건설교통부경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인2003-03-20경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인2002-01-012009-12-31YOFCTT_00000000000152SYSTEM2018-06-07SYSTEM2018-06-07
2BP0110802015-325국토교통부경춘선 금곡~춘천간 복선전철 건설사업 변경고시2015-05-28경춘선 금곡~춘천간 복선전철 건설사업 변경고시2002-01-012015-12-31YOFCTT_00000000000346SYSTEM2018-06-08SYSTEM2018-06-08
3BP0110802008-129국토해양부경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인2008-05-08경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인2002-01-012009-12-31YOFCTT_00000000000345SYSTEM2018-06-07SYSTEM2018-06-07
4BP0110802010-25국토해양부경춘선 금곡~춘천간 복선전철 건설사업 실시게획 변경승인2010-01-21경춘선 금곡~춘천간 복선전철 건설사업 실시게획 변경승인2002-01-012011-12-31YOFCTT_00000000000298SYSTEM2018-06-07SYSTEM2018-06-07
5BP0110802014-439국토교통부경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경승인2014-07-21경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경승인2002-01-012014-09-30YOFCTT_00000000000148SYSTEM2018-06-07SYSTEM2020-10-12
6BP0110802013-938국토교통부경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인2014-01-06경춘선 금곡~춘천간 복선전철 건설사업 실시계획 변경 승인2002-01-012014-09-30YOFCTT_00000000000147SYSTEM2018-06-07SYSTEM2018-06-07
7BP0110802011-159국토해양부경춘선 금곡~춘천간 복선전철 건설사업 실시계획 승인2011-04-25경춘선 금곡~춘천간 복선전철 건설사업 실시계획 승인2002-01-012011-12-31YOFCTT_00000000000251SYSTEM2018-06-07SYSTEM2018-06-07
8BP0110802015-381국토교통부경춘선 금곡~춘천간 복선전철 건설사업 준공고시2015-06-16경춘선 금곡~춘천간 복선전철 건설사업 준공고시2002-01-012015-06-30YOFCTT_00000000000288SYSTEM2018-06-08SYSTEM2018-06-08
9BP0110802012-283국토해양부경춘선 금곡~춘천간 복선전철 건설사업 실시계획 승인2012-06-07경춘선 금곡~춘천간 복선전철 건설사업 실시계획 승인2002-01-012012-12-31YOFCTT_00000000000286SYSTEM2018-06-07SYSTEM2018-06-07
지역본부코드사업코드관보고시번호고시기관명고시명고시일자고시내용사업시작일자사업종료일자대민게시여부첨부파일번호입력인ID입력일시변경인ID변경일자
762BP0522102021-1209국토교통부도담~영천복선전철건설사업2021-11-09도담~영천복선전철건설사업2002-01-012022-12-31NFILE_ID_000000025236100009732022-03-14100009732022-03-14
763BP0522102017-227국토교통부중앙선 도담~영천 복선전철건설사업2017-05-26중앙선 도담~영천 복선전철건설사업2002-01-012022-12-30NFILE_ID_000000025235100014092021-11-11100014092021-11-11
764BP0522102121-1209국토교통부도담-영천복선전철사업2021-11-09도담-영천복선전철사업2002-01-012022-12-31NOFCTT_00000000000385100009732022-03-28100009732022-03-28
765BP0523502015-386국토교통부경북선 예천~어등간 철도이설 건설사업 실시계획 변경승인2015-06-22경북선 예천~어등간 철도이설 건설사업 실시계획 변경승인2002-01-012015-12-31YOFCTT_00000000000455SYSTEM2018-05-24SYSTEM2020-08-20
766BP0523502016-788국토교통부경북선 예천~어등간 철도이설 건설사업 준공고시2016-12-01경북선 예천~어등간 철도이설 건설사업 준공고시2002-01-012016-12-31YOFCTT_00000000000451SYSTEM2018-05-24SYSTEM2020-08-20
767BP0523502014-450국토교통부경북선 예천~어등간 철도이설 건설사업 실시계획 승인2014-07-29경북선 예천~어등간 철도이설 건설사업 실시계획 승인2002-01-012015-08-31YOFCTT_00000000000453SYSTEM2018-05-24SYSTEM2020-08-20
768BP0523502016-490국토교통부경북선 예천~어등간 철도이설 건설사업 실시계획 변경승인2016-07-28경북선 예천~어등간 철도이설 건설사업 실시계획 변경승인2002-01-012016-12-31YOFCTT_00000000000460SYSTEM2018-05-24SYSTEM2020-08-20
769BP0523502015-993국토교통부경북선 예천~어등간 철도이설 건설사업 실시계획 변경승인2015-12-29경북선 예천~어등간 철도이설 건설사업 실시계획 변경승인2002-01-012016-07-30YOFCTT_00000000000458SYSTEM2018-05-24SYSTEM2018-05-24
770BP0527902023-175국토교통부춘천~속초 철도건설사업(제1~7공구) 실시계획 변경 승인2023-04-05춘천~속초 철도건설사업(제1~7공구) 실시계획 변경 승인2002-01-012027-12-31NOFCTT_00000000000016100039702023-04-05100039702023-04-11
771BP0527902022-288국토교통부춘천~속초 철도건설사업(제1~7공구) 실시계획 승인2022-06-02춘천~속초 철도건설사업(제1~7공구) 실시계획 승인2002-01-012027-12-31NOFCTT_00000000000419100013522022-08-11100013522023-04-19