Overview

Dataset statistics

Number of variables7
Number of observations36
Missing cells76
Missing cells (%)30.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory59.7 B

Variable types

Text5
Unsupported2

Dataset

Description대전상수도사업본부 시설물관리 구역별 년가계약 정보
Author대전광역시 상수도사업본부
URLhttps://www.data.go.kr/data/15061972/fileData.do

Alerts

Unnamed: 6 has constant value ""Constant
년가 계약정보 (공무과, 지역사업소) has 28 (77.8%) missing valuesMissing
Unnamed: 1 has 2 (5.6%) missing valuesMissing
Unnamed: 2 has 8 (22.2%) missing valuesMissing
Unnamed: 3 has 1 (2.8%) missing valuesMissing
Unnamed: 4 has 1 (2.8%) missing valuesMissing
Unnamed: 5 has 1 (2.8%) missing valuesMissing
Unnamed: 6 has 35 (97.2%) missing valuesMissing
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 11:31:09.318907
Analysis finished2023-12-12 11:31:10.539429
Duration1.22 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년가 계약정보 (공무과, 지역사업소)
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing28
Missing (%)77.8%
Memory size420.0 B
2023-12-12T20:31:10.726523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.375
Min length2

Characters and Unicode

Total characters19
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st row구별
2nd row합계
3rd row수도 시설
4th row동구
5th row중구
ValueCountFrequency (%)
구별 1
11.1%
합계 1
11.1%
수도 1
11.1%
시설 1
11.1%
동구 1
11.1%
중구 1
11.1%
서구 1
11.1%
유성 1
11.1%
대덕 1
11.1%
2023-12-12T20:31:11.314553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 4
21.1%
별 1
 
5.3%
합 1
 
5.3%
계 1
 
5.3%
수 1
 
5.3%
도 1
 
5.3%
1
 
5.3%
시 1
 
5.3%
설 1
 
5.3%
동 1
 
5.3%
Other values (6) 6
31.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18
94.7%
Control 1
 
5.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 4
22.2%
별 1
 
5.6%
합 1
 
5.6%
계 1
 
5.6%
수 1
 
5.6%
도 1
 
5.6%
시 1
 
5.6%
설 1
 
5.6%
동 1
 
5.6%
중 1
 
5.6%
Other values (5) 5
27.8%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18
94.7%
Common 1
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 4
22.2%
별 1
 
5.6%
합 1
 
5.6%
계 1
 
5.6%
수 1
 
5.6%
도 1
 
5.6%
시 1
 
5.6%
설 1
 
5.6%
동 1
 
5.6%
중 1
 
5.6%
Other values (5) 5
27.8%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18
94.7%
ASCII 1
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 4
22.2%
별 1
 
5.6%
합 1
 
5.6%
계 1
 
5.6%
수 1
 
5.6%
도 1
 
5.6%
시 1
 
5.6%
설 1
 
5.6%
동 1
 
5.6%
중 1
 
5.6%
Other values (5) 5
27.8%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 1
Text

MISSING 

Distinct29
Distinct (%)85.3%
Missing2
Missing (%)5.6%
Memory size420.0 B
2023-12-12T20:31:11.644711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.9705882
Min length2

Characters and Unicode

Total characters169
Distinct characters65
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)82.4%

Sample

1st row업체명
2nd row소계
3rd row㈜삼복
4th row㈜명지공영
5th row㈜물꼬건설
ValueCountFrequency (%)
소계 6
 
17.6%
미루건설(자 1
 
2.9%
덕영건설㈜ 1
 
2.9%
㈜주안건설 1
 
2.9%
㈜덕성건설 1
 
2.9%
㈜범창건설 1
 
2.9%
㈜명지건설 1
 
2.9%
경훈건설㈜ 1
 
2.9%
㈜삼현건설 1
 
2.9%
유)태안건설 1
 
2.9%
Other values (19) 19
55.9%
2023-12-12T20:31:12.204550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 22
 
13.0%
설 19
 
11.2%
건 19
 
11.2%
소 7
 
4.1%
계 6
 
3.6%
이 6
 
3.6%
( 5
 
3.0%
) 5
 
3.0%
엔 3
 
1.8%
업 3
 
1.8%
Other values (55) 74
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 136
80.5%
Other Symbol 22
 
13.0%
Open Punctuation 5
 
3.0%
Close Punctuation 5
 
3.0%
Space Separator 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 19
 
14.0%
건 19
 
14.0%
소 7
 
5.1%
계 6
 
4.4%
이 6
 
4.4%
엔 3
 
2.2%
업 3
 
2.2%
자 3
 
2.2%
유 3
 
2.2%
지 3
 
2.2%
Other values (51) 64
47.1%
Other Symbol
ValueCountFrequency (%)
㈜ 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 158
93.5%
Common 11
 
6.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 22
 
13.9%
설 19
 
12.0%
건 19
 
12.0%
소 7
 
4.4%
계 6
 
3.8%
이 6
 
3.8%
엔 3
 
1.9%
업 3
 
1.9%
자 3
 
1.9%
유 3
 
1.9%
Other values (52) 67
42.4%
Common
ValueCountFrequency (%)
( 5
45.5%
) 5
45.5%
1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136
80.5%
None 22
 
13.0%
ASCII 11
 
6.5%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 22
100.0%
Hangul
ValueCountFrequency (%)
설 19
 
14.0%
건 19
 
14.0%
소 7
 
5.1%
계 6
 
4.4%
이 6
 
4.4%
엔 3
 
2.2%
업 3
 
2.2%
자 3
 
2.2%
유 3
 
2.2%
지 3
 
2.2%
Other values (51) 64
47.1%
ASCII
ValueCountFrequency (%)
( 5
45.5%
) 5
45.5%
1
 
9.1%

Unnamed: 2
Text

MISSING 

Distinct27
Distinct (%)96.4%
Missing8
Missing (%)22.2%
Memory size420.0 B
2023-12-12T20:31:12.550858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters84
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)92.9%

Sample

1st row대표자
2nd row김우섭
3rd row김효철
4th row박은남
5th row신현옥
ValueCountFrequency (%)
윤수영 2
 
7.1%
강다영 1
 
3.6%
김영목 1
 
3.6%
성시천 1
 
3.6%
두병록 1
 
3.6%
김석진 1
 
3.6%
이광희 1
 
3.6%
한경원 1
 
3.6%
송상현 1
 
3.6%
김영성 1
 
3.6%
Other values (17) 17
60.7%
2023-12-12T20:31:13.037596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 7
 
8.3%
영 6
 
7.1%
정 4
 
4.8%
이 3
 
3.6%
규 3
 
3.6%
박 3
 
3.6%
수 3
 
3.6%
현 2
 
2.4%
대 2
 
2.4%
송 2
 
2.4%
Other values (42) 49
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 7
 
8.3%
영 6
 
7.1%
정 4
 
4.8%
이 3
 
3.6%
규 3
 
3.6%
박 3
 
3.6%
수 3
 
3.6%
현 2
 
2.4%
대 2
 
2.4%
송 2
 
2.4%
Other values (42) 49
58.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 7
 
8.3%
영 6
 
7.1%
정 4
 
4.8%
이 3
 
3.6%
규 3
 
3.6%
박 3
 
3.6%
수 3
 
3.6%
현 2
 
2.4%
대 2
 
2.4%
송 2
 
2.4%
Other values (42) 49
58.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 7
 
8.3%
영 6
 
7.1%
정 4
 
4.8%
이 3
 
3.6%
규 3
 
3.6%
박 3
 
3.6%
수 3
 
3.6%
현 2
 
2.4%
대 2
 
2.4%
송 2
 
2.4%
Other values (42) 49
58.3%

Unnamed: 3
Text

MISSING 

Distinct30
Distinct (%)85.7%
Missing1
Missing (%)2.8%
Memory size420.0 B
2023-12-12T20:31:13.396680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length18
Mean length12.628571
Min length3

Characters and Unicode

Total characters442
Distinct characters80
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)71.4%

Sample

1st row소재지
2nd row25개 업체
3rd row 2개 업체
4th row충청남도 아산시 온천대로 1515, 2층(온천동)
5th row서구 벌곡로 1349번길 45-0(가수원동)
ValueCountFrequency (%)
서구 9
 
8.5%
업체 7
 
6.6%
유성구 6
 
5.7%
대덕구 5
 
4.7%
동구 3
 
2.8%
중구 3
 
2.8%
5개 2
 
1.9%
덕암로 2
 
1.9%
215 2
 
1.9%
괴정로 2
 
1.9%
Other values (61) 65
61.3%
2023-12-12T20:31:13.993544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
17.0%
로 26
 
5.9%
구 26
 
5.9%
1 19
 
4.3%
6 18
 
4.1%
2 16
 
3.6%
5 14
 
3.2%
동 14
 
3.2%
대 11
 
2.5%
길 11
 
2.5%
Other values (70) 212
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 233
52.7%
Decimal Number 116
26.2%
Space Separator 75
 
17.0%
Dash Punctuation 9
 
2.0%
Close Punctuation 4
 
0.9%
Open Punctuation 4
 
0.9%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 26
 
11.2%
구 26
 
11.2%
동 14
 
6.0%
대 11
 
4.7%
길 11
 
4.7%
번 11
 
4.7%
성 9
 
3.9%
서 9
 
3.9%
유 8
 
3.4%
업 7
 
3.0%
Other values (55) 101
43.3%
Decimal Number
ValueCountFrequency (%)
1 19
16.4%
6 18
15.5%
2 16
13.8%
5 14
12.1%
3 10
8.6%
8 9
7.8%
9 8
6.9%
7 8
6.9%
4 7
 
6.0%
0 7
 
6.0%
Space Separator
ValueCountFrequency (%)
75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 233
52.7%
Common 209
47.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 26
 
11.2%
구 26
 
11.2%
동 14
 
6.0%
대 11
 
4.7%
길 11
 
4.7%
번 11
 
4.7%
성 9
 
3.9%
서 9
 
3.9%
유 8
 
3.4%
업 7
 
3.0%
Other values (55) 101
43.3%
Common
ValueCountFrequency (%)
75
35.9%
1 19
 
9.1%
6 18
 
8.6%
2 16
 
7.7%
5 14
 
6.7%
3 10
 
4.8%
- 9
 
4.3%
8 9
 
4.3%
9 8
 
3.8%
7 8
 
3.8%
Other values (5) 23
 
11.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 233
52.7%
ASCII 209
47.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
35.9%
1 19
 
9.1%
6 18
 
8.6%
2 16
 
7.7%
5 14
 
6.7%
3 10
 
4.8%
- 9
 
4.3%
8 9
 
4.3%
9 8
 
3.8%
7 8
 
3.8%
Other values (5) 23
 
11.0%
Hangul
ValueCountFrequency (%)
로 26
 
11.2%
구 26
 
11.2%
동 14
 
6.0%
대 11
 
4.7%
길 11
 
4.7%
번 11
 
4.7%
성 9
 
3.9%
서 9
 
3.9%
유 8
 
3.4%
업 7
 
3.0%
Other values (55) 101
43.3%

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)2.8%
Memory size420.0 B

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)2.8%
Memory size420.0 B

Unnamed: 6
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing35
Missing (%)97.2%
Memory size420.0 B
2023-12-12T20:31:14.161609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row비고
ValueCountFrequency (%)
비고 1
100.0%
2023-12-12T20:31:14.760376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Correlations

2023-12-12T20:31:14.920526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년가 계약정보 (공무과, 지역사업소)Unnamed: 1Unnamed: 2Unnamed: 3
년가 계약정보 (공무과, 지역사업소)1.0001.000NaN1.000
Unnamed: 11.0001.0001.0000.986
Unnamed: 2NaN1.0001.0001.000
Unnamed: 31.0000.9861.0001.000

Missing values

2023-12-12T20:31:09.850363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:31:10.134753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T20:31:10.379818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

년가 계약정보 (공무과, 지역사업소)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
0<NA><NA><NA><NA>NaNNaN<NA>
1구별업체명대표자소재지수주건수\n(건)수주액\n(천원)비고
2합계<NA><NA>25개 업체61579605726<NA>
3수도 시설소계<NA>2개 업체160655876<NA>
4<NA>㈜삼복김우섭충청남도 아산시 온천대로 1515, 2층(온천동)56395330<NA>
5<NA>㈜명지공영김효철서구 벌곡로 1349번길 45-0(가수원동)971699<NA>
6<NA>㈜물꼬건설박은남대전광역시 동구 백룡로6번길 76 한빛주택95188847<NA>
7동구소계<NA>5개 업체11342258313<NA>
8<NA>신우건설이엔지㈜신현옥유성구 원계산로 77번길 9251414634<NA>
9<NA>제이건설㈜최정숙서구 괴정로 200-6137405247<NA>
년가 계약정보 (공무과, 지역사업소)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
26유성소계<NA>4개 업체16222533<NA>
27<NA>(유)태안건설송상현대덕구 신탄진로 162번길 56(연축동)449586<NA>
28<NA>㈜삼현건설한경원서구 월평동로 83290637<NA>
29<NA>경훈건설㈜이광희중구 산성로 37-1(산성동)336719<NA>
30<NA>㈜명지건설김석진동구 가양동 352-10547591<NA>
31대덕소계<NA>4개 업체10112062124<NA>
32<NA>㈜범창건설윤수영대덕구 덕암로 215229515713<NA>
33<NA>㈜덕성건설두병록서구 도산로185 3층278518553<NA>
34<NA>㈜주안건설성시천유성구 학하동로63번길 88-12225509203<NA>
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