Overview

Dataset statistics

Number of variables15
Number of observations483
Missing cells494
Missing cells (%)6.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory57.2 KiB
Average record size in memory121.3 B

Variable types

Unsupported9
Text3
Categorical3

Alerts

Unnamed: 11 is highly overall correlated with Unnamed: 12 and 1 other fieldsHigh correlation
Unnamed: 12 is highly overall correlated with Unnamed: 11 and 1 other fieldsHigh correlation
Unnamed: 13 is highly overall correlated with Unnamed: 11 and 1 other fieldsHigh correlation
Unnamed: 13 is highly imbalanced (50.6%)Imbalance
Unnamed: 10 has 483 (100.0%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
교량현황 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
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 01:58:49.965624
Analysis finished2024-03-14 01:58:50.799646
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.2%
Memory size3.9 KiB

Unnamed: 1
Text

Distinct53
Distinct (%)11.0%
Missing1
Missing (%)0.2%
Memory size3.9 KiB
2024-03-14T10:58:50.951390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.7759336
Min length3

Characters and Unicode

Total characters4230
Distinct characters20
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

Unique3 ?
Unique (%)0.6%

Sample

1st row노선명
2nd row국가지원지방도15호선
3rd row국가지원지방도15호선
4th row국가지원지방도15호선
5th row국가지원지방도15호선
ValueCountFrequency (%)
국가지원지방도49호선 71
 
14.7%
지방도743호선 28
 
5.8%
지방도745호선 27
 
5.6%
지방도714호선 21
 
4.4%
지방도740호선 21
 
4.4%
국가지원지방도55호선 18
 
3.7%
국가지원지방도15호선 17
 
3.5%
지방도711호선 17
 
3.5%
지방도721호선 17
 
3.5%
국가지원지방도60호선 16
 
3.3%
Other values (43) 229
47.5%
2024-03-14T10:58:51.315956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 606
14.3%
선 482
11.4%
방 481
11.4%
도 481
11.4%
호 481
11.4%
7 351
8.3%
4 213
 
5.0%
1 144
 
3.4%
9 137
 
3.2%
가 125
 
3.0%
Other values (10) 729
17.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2908
68.7%
Decimal Number 1322
31.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 606
20.8%
선 482
16.6%
방 481
16.5%
도 481
16.5%
호 481
16.5%
가 125
 
4.3%
국 125
 
4.3%
원 125
 
4.3%
노 1
 
< 0.1%
명 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
7 351
26.6%
4 213
16.1%
1 144
10.9%
9 137
 
10.4%
5 122
 
9.2%
3 105
 
7.9%
0 83
 
6.3%
2 82
 
6.2%
6 62
 
4.7%
8 23
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2908
68.7%
Common 1322
31.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 606
20.8%
선 482
16.6%
방 481
16.5%
도 481
16.5%
호 481
16.5%
가 125
 
4.3%
국 125
 
4.3%
원 125
 
4.3%
노 1
 
< 0.1%
명 1
 
< 0.1%
Common
ValueCountFrequency (%)
7 351
26.6%
4 213
16.1%
1 144
10.9%
9 137
 
10.4%
5 122
 
9.2%
3 105
 
7.9%
0 83
 
6.3%
2 82
 
6.2%
6 62
 
4.7%
8 23
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2908
68.7%
ASCII 1322
31.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 606
20.8%
선 482
16.6%
방 481
16.5%
도 481
16.5%
호 481
16.5%
가 125
 
4.3%
국 125
 
4.3%
원 125
 
4.3%
노 1
 
< 0.1%
명 1
 
< 0.1%
ASCII
ValueCountFrequency (%)
7 351
26.6%
4 213
16.1%
1 144
10.9%
9 137
 
10.4%
5 122
 
9.2%
3 105
 
7.9%
0 83
 
6.3%
2 82
 
6.2%
6 62
 
4.7%
8 23
 
1.7%

Unnamed: 2
Text

Distinct458
Distinct (%)95.0%
Missing1
Missing (%)0.2%
Memory size3.9 KiB
2024-03-14T10:58:51.578359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.4854772
Min length2

Characters and Unicode

Total characters1680
Distinct characters207
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique437 ?
Unique (%)90.7%

Sample

1st row교량명
2nd row고수교
3rd row고창IC교
4th row돌담교
5th row석교2교
ValueCountFrequency (%)
신기교 3
 
0.6%
신성교 3
 
0.6%
신월교 3
 
0.6%
신흥교 2
 
0.4%
송현교 2
 
0.4%
대덕교 2
 
0.4%
유천교 2
 
0.4%
대산교 2
 
0.4%
산내교 2
 
0.4%
서산교 2
 
0.4%
Other values (448) 459
95.2%
2024-03-14T10:58:51.955109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 483
28.7%
2 51
 
3.0%
1 48
 
2.9%
산 44
 
2.6%
월 28
 
1.7%
신 27
 
1.6%
대 26
 
1.5%
천 26
 
1.5%
동 24
 
1.4%
상 23
 
1.4%
Other values (197) 900
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1520
90.5%
Decimal Number 116
 
6.9%
Close Punctuation 16
 
1.0%
Open Punctuation 16
 
1.0%
Uppercase Letter 12
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 483
31.8%
산 44
 
2.9%
월 28
 
1.8%
신 27
 
1.8%
대 26
 
1.7%
천 26
 
1.7%
동 24
 
1.6%
상 23
 
1.5%
용 23
 
1.5%
암 21
 
1.4%
Other values (188) 795
52.3%
Decimal Number
ValueCountFrequency (%)
2 51
44.0%
1 48
41.4%
3 11
 
9.5%
4 5
 
4.3%
5 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
I 6
50.0%
C 6
50.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1520
90.5%
Common 148
 
8.8%
Latin 12
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 483
31.8%
산 44
 
2.9%
월 28
 
1.8%
신 27
 
1.8%
대 26
 
1.7%
천 26
 
1.7%
동 24
 
1.6%
상 23
 
1.5%
용 23
 
1.5%
암 21
 
1.4%
Other values (188) 795
52.3%
Common
ValueCountFrequency (%)
2 51
34.5%
1 48
32.4%
) 16
 
10.8%
( 16
 
10.8%
3 11
 
7.4%
4 5
 
3.4%
5 1
 
0.7%
Latin
ValueCountFrequency (%)
I 6
50.0%
C 6
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1520
90.5%
ASCII 160
 
9.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 483
31.8%
산 44
 
2.9%
월 28
 
1.8%
신 27
 
1.8%
대 26
 
1.7%
천 26
 
1.7%
동 24
 
1.6%
상 23
 
1.5%
용 23
 
1.5%
암 21
 
1.4%
Other values (188) 795
52.3%
ASCII
ValueCountFrequency (%)
2 51
31.9%
1 48
30.0%
) 16
 
10.0%
( 16
 
10.0%
3 11
 
6.9%
I 6
 
3.8%
C 6
 
3.8%
4 5
 
3.1%
5 1
 
0.6%

Unnamed: 3
Text

Distinct301
Distinct (%)62.4%
Missing1
Missing (%)0.2%
Memory size3.9 KiB
2024-03-14T10:58:52.266106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length15.952282
Min length2

Characters and Unicode

Total characters7689
Distinct characters179
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

Unique194 ?
Unique (%)40.2%

Sample

1st row위치
2nd row전라북도 고창군 고창읍 도산리
3rd row전라북도 고창군 고창읍 주곡리
4th row전라북도 고창군 고창읍 율계리
5th row전라북도 고창군 고창읍 석교리
ValueCountFrequency (%)
전라북도 481
25.0%
진안군 68
 
3.5%
완주군 66
 
3.4%
정읍시 47
 
2.4%
남원시 45
 
2.3%
장수군 40
 
2.1%
임실군 36
 
1.9%
김제시 35
 
1.8%
고창군 35
 
1.8%
익산시 33
 
1.7%
Other values (403) 1038
54.0%
2024-03-14T10:58:52.684716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1442
18.8%
북 497
 
6.5%
도 491
 
6.4%
전 489
 
6.4%
리 483
 
6.3%
라 483
 
6.3%
면 444
 
5.8%
군 322
 
4.2%
산 200
 
2.6%
시 180
 
2.3%
Other values (169) 2658
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6247
81.2%
Space Separator 1442
 
18.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 497
 
8.0%
도 491
 
7.9%
전 489
 
7.8%
리 483
 
7.7%
라 483
 
7.7%
면 444
 
7.1%
군 322
 
5.2%
산 200
 
3.2%
시 180
 
2.9%
주 122
 
2.0%
Other values (168) 2536
40.6%
Space Separator
ValueCountFrequency (%)
1442
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6247
81.2%
Common 1442
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 497
 
8.0%
도 491
 
7.9%
전 489
 
7.8%
리 483
 
7.7%
라 483
 
7.7%
면 444
 
7.1%
군 322
 
5.2%
산 200
 
3.2%
시 180
 
2.9%
주 122
 
2.0%
Other values (168) 2536
40.6%
Common
ValueCountFrequency (%)
1442
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6247
81.2%
ASCII 1442
 
18.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1442
100.0%
Hangul
ValueCountFrequency (%)
북 497
 
8.0%
도 491
 
7.9%
전 489
 
7.8%
리 483
 
7.7%
라 483
 
7.7%
면 444
 
7.1%
군 322
 
5.2%
산 200
 
3.2%
시 180
 
2.9%
주 122
 
2.0%
Other values (168) 2536
40.6%

교량현황
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.2%
Memory size3.9 KiB

Unnamed: 5
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.2%
Memory size3.9 KiB

Unnamed: 6
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.2%
Memory size3.9 KiB

Unnamed: 7
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.2%
Memory size3.9 KiB

Unnamed: 8
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.2%
Memory size3.9 KiB

Unnamed: 9
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.2%
Memory size3.9 KiB

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing483
Missing (%)100.0%
Memory size4.4 KiB

Unnamed: 11
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
RC슬래브교
206 
라멘교
100 
PSC I형교
85 
강상자형교
44 
RC T형교
22 
Other values (8)
26 

Length

Max length7
Median length6
Mean length5.4761905
Min length2

Unique

Unique5 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row대표 상부
3rd rowPSC I형교
4th row강상자형교
5th row강상자형교

Common Values

ValueCountFrequency (%)
RC슬래브교 206
42.7%
라멘교 100
20.7%
PSC I형교 85
17.6%
강상자형교 44
 
9.1%
RC T형교 22
 
4.6%
PSC슬래브교 10
 
2.1%
프리플렉스형교 9
 
1.9%
기타 2
 
0.4%
<NA> 1
 
0.2%
대표 상부 1
 
0.2%
Other values (3) 3
 
0.6%

Length

2024-03-14T10:58:52.808361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
rc슬래브교 206
34.8%
라멘교 100
16.9%
i형교 86
14.5%
psc 85
14.4%
강상자형교 44
 
7.4%
rc 22
 
3.7%
t형교 22
 
3.7%
psc슬래브교 10
 
1.7%
프리플렉스형교 9
 
1.5%
기타 2
 
0.3%
Other values (6) 6
 
1.0%

Unnamed: 12
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
벽식 교각
103 
기타
95 
T형 교각
86 
라멘식 교각
68 
역T형식 교대
42 
Other values (10)
89 

Length

Max length7
Median length6
Mean length4.9233954
Min length2

Unique

Unique5 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row대표 하부
3rd row라멘식 교각
4th row역T형식 교대
5th row역T형식 교대

Common Values

ValueCountFrequency (%)
벽식 교각 103
21.3%
기타 95
19.7%
T형 교각 86
17.8%
라멘식 교각 68
14.1%
역T형식 교대 42
8.7%
중력식 교각 39
 
8.1%
중력식 교대 17
 
3.5%
구주식 교각 14
 
2.9%
반중력식 교대 10
 
2.1%
라멘식 교대 4
 
0.8%
Other values (5) 5
 
1.0%

Length

2024-03-14T10:58:52.971446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
교각 313
36.0%
벽식 103
 
11.8%
기타 95
 
10.9%
t형 86
 
9.9%
교대 73
 
8.4%
라멘식 72
 
8.3%
중력식 56
 
6.4%
역t형식 42
 
4.8%
구주식 14
 
1.6%
반중력식 11
 
1.3%
Other values (5) 5
 
0.6%

Unnamed: 13
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
DB-24
285 
DB-18
166 
DB-13.5
29 
<NA>
 
1
설계 하중
 
1

Length

Max length7
Median length5
Mean length5.1180124
Min length4

Unique

Unique3 ?
Unique (%)0.6%

Sample

1st row<NA>
2nd row설계 하중
3rd rowDB-24
4th rowDB-24
5th rowDB-24

Common Values

ValueCountFrequency (%)
DB-24 285
59.0%
DB-18 166
34.4%
DB-13.5 29
 
6.0%
<NA> 1
 
0.2%
설계 하중 1
 
0.2%
D9/T9 1
 
0.2%

Length

2024-03-14T10:58:53.102644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:58:53.217778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
db-24 285
58.9%
db-18 166
34.3%
db-13.5 29
 
6.0%
na 1
 
0.2%
설계 1
 
0.2%
하중 1
 
0.2%
d9/t9 1
 
0.2%

Unnamed: 14
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.2%
Memory size3.9 KiB

Correlations

2024-03-14T10:58:53.299967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 11Unnamed: 12Unnamed: 13
Unnamed: 11.0000.7860.8250.843
Unnamed: 110.7861.0000.8580.780
Unnamed: 120.8250.8581.0000.825
Unnamed: 130.8430.7800.8251.000
2024-03-14T10:58:53.384138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 12Unnamed: 13Unnamed: 11
Unnamed: 121.0000.6080.546
Unnamed: 130.6081.0000.575
Unnamed: 110.5460.5751.000
2024-03-14T10:58:53.460205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 11Unnamed: 12Unnamed: 13
Unnamed: 111.0000.5460.575
Unnamed: 120.5461.0000.608
Unnamed: 130.5750.6081.000

Missing values

2024-03-14T10:58:50.311083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:58:50.456932image/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.
2024-03-14T10:58:50.599817image/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

Unnamed: 0Unnamed: 1Unnamed: 2Unnamed: 3교량현황Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14
0NaN<NA><NA><NA>NaNNaNNaNNaNNaNNaN<NA><NA><NA><NA>NaN
1연번노선명교량명위치연장총폭유효폭교고경간수최대\n지간장<NA>대표 상부대표 하부설계 하중준공\n년도
21국가지원지방도15호선고수교전라북도 고창군 고창읍 도산리90.319.418.54.3330.1<NA>PSC I형교라멘식 교각DB-242006
32국가지원지방도15호선고창IC교전라북도 고창군 고창읍 주곡리4019.418.55.1140<NA>강상자형교역T형식 교대DB-242006
43국가지원지방도15호선돌담교전라북도 고창군 고창읍 율계리39.919.418.55139.9<NA>강상자형교역T형식 교대DB-242006
54국가지원지방도15호선석교2교전라북도 고창군 고창읍 석교리11.219.418.58.2111.2<NA>라멘교기타DB-242006
65국가지원지방도15호선성두교전라북도 고창군 고창읍 성두리285.324.9245660<NA>강상자형교라멘식 교각DB-242006
76국가지원지방도15호선아산1교전라북도 고창군 아산면 하갑리7519.418.54325<NA>PSC I형교라멘식 교각DB-242006
87국가지원지방도15호선아산2교전라북도 고창군 아산면 상갑리2519.418.54.8125<NA>PSC I형교역T형식 교대DB-242006
98국가지원지방도15호선아산3교전라북도 고창군 아산면 상갑리8019.418.54240<NA>강상자형교라멘식 교각DB-242006
Unnamed: 0Unnamed: 1Unnamed: 2Unnamed: 3교량현황Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14
473472지방도743호선월현5교전라북도 장수군 계북면 월현리90109.19243.8<NA>강상자형교반중력식 교대DB-242013
474473국가지원지방도15호선송현교전라북도 고창군 무장면 송현리5151816.881051<NA>강상자형교벽식 교각DB-242004
475474국가지원지방도15호선대동교전라북도 고창군 아산면 대동리1519.418.55113.8<NA>라멘교반중력식 교대DB-242013
476475지방도714호선안덕교전라북도 완주군 구이면 안덕리159.58.66.918.6<NA>라멘교역T형식 교대DB-242013
477476지방도714호선원안덕1교전라북도 완주군 구이면 안덕리509.58.67224.2<NA>PSC슬래브교반중력식 교대DB-242013
478477지방도714호선밤티교전라북도 김제시 금산면 화율리259.58.6618.6<NA>PSC슬래브교반중력식 교대DB-242013
479478지방도714호선율치1교전라북도 김제시 금산면 화율리509.58.67248.8<NA>PSC슬래브교반중력식 교대DB-242013
480479지방도714호선율치2교전라북도 김제시 금산면 화율리359.58.67218<NA>PSC슬래브교반중력식 교대DB-242013
481480지방도714호선봉월IC교전라북도 김제시 황산면 봉월리4019.518.67.5117.4<NA>PSC슬래브교역T형식 교대DB-242013
482481지방도714호선두월천교전라북도 김제시 황산동15019.518.611.3437.5<NA>PSC슬래브교역T형식 교대DB-242013