Overview

Dataset statistics

Number of variables13
Number of observations49
Missing cells46
Missing cells (%)7.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory110.7 B

Variable types

Numeric4
Text3
Categorical6

Dataset

Description인천광역시 관내 고가교(시설물명, 시설물 규모, 위치, 준공년도, 형식, 설계하중, 관리주체 등)에 관한 현황 자료입니다.
Author인천광역시
URLhttps://www.data.go.kr/data/15045185/fileData.do

Alerts

준공년도 is highly overall correlated with 설계하중High correlation
상부 형식 is highly overall correlated with 설계하중High correlation
하부 형식 is highly overall correlated with 관리주체 and 1 other fieldsHigh correlation
설계하중 is highly overall correlated with 준공년도 and 1 other fieldsHigh correlation
관리주체 is highly overall correlated with 하부 형식 and 1 other fieldsHigh correlation
시설물 종류 is highly overall correlated with 하부 형식 and 1 other fieldsHigh correlation
설계하중 is highly imbalanced (59.2%)Imbalance
관리주체 is highly imbalanced (55.8%)Imbalance
비고 has 46 (93.9%) missing valuesMissing
구분 has unique valuesUnique
시설물명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:04:40.400340
Analysis finished2023-12-12 06:04:42.909304
Duration2.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25
Minimum1
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T15:04:42.996623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.4
Q113
median25
Q337
95-th percentile46.6
Maximum49
Range48
Interquartile range (IQR)24

Descriptive statistics

Standard deviation14.28869
Coefficient of variation (CV)0.57154761
Kurtosis-1.2
Mean25
Median Absolute Deviation (MAD)12
Skewness0
Sum1225
Variance204.16667
MonotonicityStrictly increasing
2023-12-12T15:04:43.164826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1 1
 
2.0%
38 1
 
2.0%
28 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%
40 1
2.0%

시설물명
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T15:04:43.441588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length5.5306122
Min length3

Characters and Unicode

Total characters271
Distinct characters83
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

Unique49 ?
Unique (%)100.0%

Sample

1st row주안차도육교
2nd row선학육교
3rd row서창(보차도)육교
4th row논현(보차도)육교
5th row도림1(보차도)육교
ValueCountFrequency (%)
주안차도육교 1
 
2.0%
도림고가교 1
 
2.0%
신북항고가교 1
 
2.0%
바이오산업교 1
 
2.0%
계양대교 1
 
2.0%
시천교 1
 
2.0%
소래대교 1
 
2.0%
만석고가교 1
 
2.0%
숙골고가교 1
 
2.0%
부개고가교 1
 
2.0%
Other values (39) 39
79.6%
2023-12-12T15:04:43.896405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 49
18.1%
가 34
 
12.5%
고 33
 
12.2%
도 10
 
3.7%
석 7
 
2.6%
육 6
 
2.2%
남 5
 
1.8%
차 5
 
1.8%
대 4
 
1.5%
( 4
 
1.5%
Other values (73) 114
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 251
92.6%
Uppercase Letter 8
 
3.0%
Open Punctuation 4
 
1.5%
Close Punctuation 4
 
1.5%
Decimal Number 4
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 49
19.5%
가 34
 
13.5%
고 33
 
13.1%
도 10
 
4.0%
석 7
 
2.8%
육 6
 
2.4%
남 5
 
2.0%
차 5
 
2.0%
대 4
 
1.6%
보 4
 
1.6%
Other values (67) 94
37.5%
Uppercase Letter
ValueCountFrequency (%)
C 4
50.0%
I 4
50.0%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 2
50.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 251
92.6%
Common 12
 
4.4%
Latin 8
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 49
19.5%
가 34
 
13.5%
고 33
 
13.1%
도 10
 
4.0%
석 7
 
2.8%
육 6
 
2.4%
남 5
 
2.0%
차 5
 
2.0%
대 4
 
1.6%
보 4
 
1.6%
Other values (67) 94
37.5%
Common
ValueCountFrequency (%)
( 4
33.3%
) 4
33.3%
2 2
16.7%
1 2
16.7%
Latin
ValueCountFrequency (%)
C 4
50.0%
I 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 251
92.6%
ASCII 20
 
7.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 49
19.5%
가 34
 
13.5%
고 33
 
13.1%
도 10
 
4.0%
석 7
 
2.8%
육 6
 
2.4%
남 5
 
2.0%
차 5
 
2.0%
대 4
 
1.6%
보 4
 
1.6%
Other values (67) 94
37.5%
ASCII
ValueCountFrequency (%)
( 4
20.0%
) 4
20.0%
C 4
20.0%
I 4
20.0%
2 2
10.0%
1 2
10.0%

위 치(군·구)
Categorical

Distinct9
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Memory size524.0 B
남동구
11 
서구
10 
미추홀구
7 
연수구
6 
부평구
5 
Other values (4)
10 

Length

Max length4
Median length3
Mean length2.8367347
Min length2

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row미추홀구
2nd row미추홀구
3rd row남동구
4th row남동구
5th row남동구

Common Values

ValueCountFrequency (%)
남동구 11
22.4%
서구 10
20.4%
미추홀구 7
14.3%
연수구 6
12.2%
부평구 5
10.2%
계양구 4
 
8.2%
동구 3
 
6.1%
중구 2
 
4.1%
강화군 1
 
2.0%

Length

2023-12-12T15:04:44.061982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:04:44.209685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남동구 11
22.4%
서구 10
20.4%
미추홀구 7
14.3%
연수구 6
12.2%
부평구 5
10.2%
계양구 4
 
8.2%
동구 3
 
6.1%
중구 2
 
4.1%
강화군 1
 
2.0%

도로명주소 또는 지번주소
Text

Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T15:04:44.535180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length12.77551
Min length7

Characters and Unicode

Total characters626
Distinct characters109
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)95.9%

Sample

1st row경인북길(주안동 614번지)
2nd row문학길(문학동 143번지)
3rd row장아산로 216
4th row은봉로 419번길 103
5th row도림동 75번지
ValueCountFrequency (%)
중봉대로(석남동648 2
 
3.2%
염전로(도화동743 1
 
1.6%
143번지 1
 
1.6%
봉수대로(백석동51-123 1
 
1.6%
남동대로(남촌동642 1
 
1.6%
건지로(가좌동103 1
 
1.6%
비류대로(도림동75-3 1
 
1.6%
송도바이오대로(송도동242 1
 
1.6%
장제로(귤현동357-7 1
 
1.6%
서곶로(검암동218-5 1
 
1.6%
Other values (52) 52
82.5%
2023-12-12T15:04:44.993048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 50
 
8.0%
로 45
 
7.2%
) 44
 
7.0%
( 44
 
7.0%
1 38
 
6.1%
2 30
 
4.8%
- 23
 
3.7%
5 22
 
3.5%
대 21
 
3.4%
3 20
 
3.2%
Other values (99) 289
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 323
51.6%
Decimal Number 178
28.4%
Close Punctuation 44
 
7.0%
Open Punctuation 44
 
7.0%
Dash Punctuation 23
 
3.7%
Space Separator 14
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 50
 
15.5%
로 45
 
13.9%
대 21
 
6.5%
지 8
 
2.5%
봉 8
 
2.5%
도 7
 
2.2%
석 7
 
2.2%
남 7
 
2.2%
수 6
 
1.9%
송 6
 
1.9%
Other values (85) 158
48.9%
Decimal Number
ValueCountFrequency (%)
1 38
21.3%
2 30
16.9%
5 22
12.4%
3 20
11.2%
4 18
10.1%
6 12
 
6.7%
8 11
 
6.2%
9 11
 
6.2%
7 10
 
5.6%
0 6
 
3.4%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 323
51.6%
Common 303
48.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 50
 
15.5%
로 45
 
13.9%
대 21
 
6.5%
지 8
 
2.5%
봉 8
 
2.5%
도 7
 
2.2%
석 7
 
2.2%
남 7
 
2.2%
수 6
 
1.9%
송 6
 
1.9%
Other values (85) 158
48.9%
Common
ValueCountFrequency (%)
) 44
14.5%
( 44
14.5%
1 38
12.5%
2 30
9.9%
- 23
7.6%
5 22
7.3%
3 20
6.6%
4 18
5.9%
14
 
4.6%
6 12
 
4.0%
Other values (4) 38
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 323
51.6%
ASCII 303
48.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 50
 
15.5%
로 45
 
13.9%
대 21
 
6.5%
지 8
 
2.5%
봉 8
 
2.5%
도 7
 
2.2%
석 7
 
2.2%
남 7
 
2.2%
수 6
 
1.9%
송 6
 
1.9%
Other values (85) 158
48.9%
ASCII
ValueCountFrequency (%)
) 44
14.5%
( 44
14.5%
1 38
12.5%
2 30
9.9%
- 23
7.6%
5 22
7.3%
3 20
6.6%
4 18
5.9%
14
 
4.6%
6 12
 
4.0%
Other values (4) 38
12.5%

길이(m)
Real number (ℝ)

Distinct44
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean341.33306
Minimum38.72
Maximum1276
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T15:04:45.140476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38.72
5-th percentile40
Q1178
median240
Q3495
95-th percentile1002
Maximum1276
Range1237.28
Interquartile range (IQR)317

Descriptive statistics

Standard deviation303.68021
Coefficient of variation (CV)0.88968881
Kurtosis1.9715243
Mean341.33306
Median Absolute Deviation (MAD)158
Skewness1.5187778
Sum16725.32
Variance92221.668
MonotonicityNot monotonic
2023-12-12T15:04:45.291763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
40.0 3
 
6.1%
240.0 2
 
4.1%
50.0 2
 
4.1%
180.0 2
 
4.1%
245.0 1
 
2.0%
1010.0 1
 
2.0%
990.0 1
 
2.0%
593.0 1
 
2.0%
469.3 1
 
2.0%
219.5 1
 
2.0%
Other values (34) 34
69.4%
ValueCountFrequency (%)
38.72 1
 
2.0%
40.0 3
6.1%
49.0 1
 
2.0%
50.0 2
4.1%
51.0 1
 
2.0%
61.2 1
 
2.0%
99.9 1
 
2.0%
113.0 1
 
2.0%
115.0 1
 
2.0%
178.0 1
 
2.0%
ValueCountFrequency (%)
1276.0 1
2.0%
1200.0 1
2.0%
1010.0 1
2.0%
990.0 1
2.0%
825.2 1
2.0%
749.0 1
2.0%
593.0 1
2.0%
579.0 1
2.0%
569.0 1
2.0%
523.0 1
2.0%

폭(m)
Real number (ℝ)

Distinct40
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.179592
Minimum5
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T15:04:45.444916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile6.36
Q111
median19
Q324.5
95-th percentile32.7
Maximum50
Range45
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation9.1851778
Coefficient of variation (CV)0.47890372
Kurtosis1.1989941
Mean19.179592
Median Absolute Deviation (MAD)5.9
Skewness0.72383439
Sum939.8
Variance84.367491
MonotonicityNot monotonic
2023-12-12T15:04:45.578021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
20.0 3
 
6.1%
24.5 3
 
6.1%
15.5 3
 
6.1%
16.5 2
 
4.1%
5.0 2
 
4.1%
11.0 2
 
4.1%
27.4 1
 
2.0%
33.5 1
 
2.0%
9.2 1
 
2.0%
13.0 1
 
2.0%
Other values (30) 30
61.2%
ValueCountFrequency (%)
5.0 2
4.1%
6.0 1
2.0%
6.9 1
2.0%
8.0 1
2.0%
8.1 1
2.0%
8.6 1
2.0%
9.0 1
2.0%
9.2 1
2.0%
10.0 1
2.0%
10.2 1
2.0%
ValueCountFrequency (%)
50.0 1
2.0%
36.0 1
2.0%
33.5 1
2.0%
31.5 1
2.0%
31.0 1
2.0%
30.0 1
2.0%
28.0 1
2.0%
27.4 1
2.0%
27.1 1
2.0%
25.8 1
2.0%

준공년도
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1999.4082
Minimum1975
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T15:04:45.729894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1975
5-th percentile1982.6
Q11992
median1997
Q32009
95-th percentile2014
Maximum2020
Range45
Interquartile range (IQR)17

Descriptive statistics

Standard deviation10.622143
Coefficient of variation (CV)0.0053126438
Kurtosis-0.57802252
Mean1999.4082
Median Absolute Deviation (MAD)6
Skewness-0.13619077
Sum97971
Variance112.82993
MonotonicityNot monotonic
2023-12-12T15:04:45.872466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1992 7
14.3%
2003 4
 
8.2%
2012 4
 
8.2%
1994 4
 
8.2%
1993 4
 
8.2%
2009 2
 
4.1%
2001 2
 
4.1%
2005 2
 
4.1%
2014 2
 
4.1%
1995 2
 
4.1%
Other values (14) 16
32.7%
ValueCountFrequency (%)
1975 1
 
2.0%
1977 1
 
2.0%
1981 1
 
2.0%
1985 1
 
2.0%
1986 2
 
4.1%
1992 7
14.3%
1993 4
8.2%
1994 4
8.2%
1995 2
 
4.1%
1996 1
 
2.0%
ValueCountFrequency (%)
2020 1
 
2.0%
2015 1
 
2.0%
2014 2
4.1%
2013 2
4.1%
2012 4
8.2%
2011 1
 
2.0%
2010 1
 
2.0%
2009 2
4.1%
2006 1
 
2.0%
2005 2
4.1%

상부 형식
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)44.9%
Missing0
Missing (%)0.0%
Memory size524.0 B
STB
15 
강박스
4 
STB+S
3 
STB+PSCI빔
3 
강박스거더
3 
Other values (17)
21 

Length

Max length20
Median length15
Mean length5.5306122
Min length3

Unique

Unique13 ?
Unique (%)26.5%

Sample

1st row강박스
2nd row강박스
3rd row강박스거더
4th row강박스거더
5th row강박스

Common Values

ValueCountFrequency (%)
STB 15
30.6%
강박스 4
 
8.2%
STB+S 3
 
6.1%
STB+PSCI빔 3
 
6.1%
강박스거더 3
 
6.1%
PSC-I 2
 
4.1%
스틸박스 2
 
4.1%
PSCB 2
 
4.1%
P.F 2
 
4.1%
개구제형 PUS 거더 1
 
2.0%
Other values (12) 12
24.5%

Length

2023-12-12T15:04:46.034383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
stb 15
29.4%
강박스 4
 
7.8%
stb+s 3
 
5.9%
stb+psci빔 3
 
5.9%
강박스거더 3
 
5.9%
p.f 3
 
5.9%
psc-i 2
 
3.9%
스틸박스 2
 
3.9%
pscb 2
 
3.9%
extradosed(pscb)+stb 1
 
2.0%
Other values (13) 13
25.5%

하부 형식
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)40.8%
Missing0
Missing (%)0.0%
Memory size524.0 B
T형교각식(T)
10 
T형교각식(T)
9 
라멘식(Ra)
6 
반중력식
5 
라멘식(Ra)
2 
Other values (15)
17 

Length

Max length13
Median length9
Mean length6.8163265
Min length2

Unique

Unique13 ?
Unique (%)26.5%

Sample

1st row반중력식
2nd row역T형
3rd row반중력식
4th row반중력식
5th row반중력식

Common Values

ValueCountFrequency (%)
T형교각식(T) 10
20.4%
T형교각식(T) 9
18.4%
라멘식(Ra) 6
12.2%
반중력식 5
10.2%
라멘식(Ra) 2
 
4.1%
교대(역T형 ) 2
 
4.1%
T형 2
 
4.1%
T형교각식(T) 1
 
2.0%
H형 1
 
2.0%
라멘 1
 
2.0%
Other values (10) 10
20.4%

Length

2023-12-12T15:04:46.178456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
t형교각식(t 20
37.7%
라멘식(ra 8
 
15.1%
반중력식 5
 
9.4%
3
 
5.7%
문형교각 2
 
3.8%
구주식 2
 
3.8%
t형 2
 
3.8%
교대(역t형 2
 
3.8%
h형 1
 
1.9%
라멘 1
 
1.9%
Other values (7) 7
 
13.2%

설계하중
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size524.0 B
DB-24
45 
DB-18
 
4

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDB-24
2nd rowDB-18
3rd rowDB-24
4th rowDB-24
5th rowDB-24

Common Values

ValueCountFrequency (%)
DB-24 45
91.8%
DB-18 4
 
8.2%

Length

2023-12-12T15:04:46.299253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:04:46.419746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
db-24 45
91.8%
db-18 4
 
8.2%

관리주체
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size524.0 B
종합건설본부
40 
남동구
 
4
미추홀구 건설과
 
2
부평구 도로과
 
2
인천시설공단
 
1

Length

Max length8
Median length6
Mean length5.877551
Min length3

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row미추홀구 건설과
2nd row미추홀구 건설과
3rd row남동구
4th row남동구
5th row남동구

Common Values

ValueCountFrequency (%)
종합건설본부 40
81.6%
남동구 4
 
8.2%
미추홀구 건설과 2
 
4.1%
부평구 도로과 2
 
4.1%
인천시설공단 1
 
2.0%

Length

2023-12-12T15:04:46.535147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:04:46.644702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종합건설본부 40
75.5%
남동구 4
 
7.5%
미추홀구 2
 
3.8%
건설과 2
 
3.8%
부평구 2
 
3.8%
도로과 2
 
3.8%
인천시설공단 1
 
1.9%

시설물 종류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size524.0 B
1종
25 
2종
15 
3종
6 
일반
 
1
3종
 
1

Length

Max length3
Median length2
Mean length2.0204082
Min length2

Unique

Unique3 ?
Unique (%)6.1%

Sample

1st row일반
2nd row3종
3rd row3종
4th row3종
5th row3종

Common Values

ValueCountFrequency (%)
1종 25
51.0%
2종 15
30.6%
3종 6
 
12.2%
일반 1
 
2.0%
3종 1
 
2.0%
3동 1
 
2.0%

Length

2023-12-12T15:04:46.767682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:04:46.888955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1종 25
51.0%
2종 15
30.6%
3종 7
 
14.3%
일반 1
 
2.0%
3동 1
 
2.0%

비고
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing46
Missing (%)93.9%
Memory size524.0 B
2023-12-12T15:04:47.043795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.666667
Min length10

Characters and Unicode

Total characters32
Distinct characters12
Distinct categories4 ?
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 (%)100.0%

Sample

1st row폭:6.9~10.4
2nd row폭:15.4~21.9
3rd row폭:33.5~35.5
ValueCountFrequency (%)
폭:6.9~10.4 1
33.3%
폭:15.4~21.9 1
33.3%
폭:33.5~35.5 1
33.3%
2023-12-12T15:04:47.547308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6
18.8%
5 4
12.5%
폭 3
9.4%
: 3
9.4%
~ 3
9.4%
1 3
9.4%
3 3
9.4%
9 2
 
6.2%
4 2
 
6.2%
6 1
 
3.1%
Other values (2) 2
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
53.1%
Other Punctuation 9
28.1%
Other Letter 3
 
9.4%
Math Symbol 3
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4
23.5%
1 3
17.6%
3 3
17.6%
9 2
11.8%
4 2
11.8%
6 1
 
5.9%
0 1
 
5.9%
2 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 6
66.7%
: 3
33.3%
Other Letter
ValueCountFrequency (%)
폭 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29
90.6%
Hangul 3
 
9.4%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6
20.7%
5 4
13.8%
: 3
10.3%
~ 3
10.3%
1 3
10.3%
3 3
10.3%
9 2
 
6.9%
4 2
 
6.9%
6 1
 
3.4%
0 1
 
3.4%
Hangul
ValueCountFrequency (%)
폭 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29
90.6%
Hangul 3
 
9.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6
20.7%
5 4
13.8%
: 3
10.3%
~ 3
10.3%
1 3
10.3%
3 3
10.3%
9 2
 
6.9%
4 2
 
6.9%
6 1
 
3.4%
0 1
 
3.4%
Hangul
ValueCountFrequency (%)
폭 3
100.0%

Interactions

2023-12-12T15:04:42.184304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:41.089583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:41.466240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:41.865479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:42.283538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:41.196892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:41.573465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:41.944205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:42.382741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:41.295829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:41.698184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:42.027679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:42.477459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:41.385939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:41.779034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:42.101681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:04:47.673038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시설물명위 치(군·구)도로명주소 또는 지번주소길이(m)폭(m)준공년도상부 형식하부 형식설계하중관리주체시설물 종류비고
구분1.0001.0000.0000.9360.4890.3110.9030.7040.8790.3360.8110.6811.000
시설물명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위 치(군·구)0.0001.0001.0001.0000.7570.3640.0000.4420.6980.2410.5040.2961.000
도로명주소 또는 지번주소0.9361.0001.0001.0001.0001.0000.9760.9590.9961.0001.0001.0001.000
길이(m)0.4891.0000.7571.0001.0000.4650.0000.7330.8350.0000.0000.4281.000
폭(m)0.3111.0000.3641.0000.4651.0000.2770.7720.8390.0000.2470.3311.000
준공년도0.9031.0000.0000.9760.0000.2771.0000.8810.0000.9350.0000.0001.000
상부 형식0.7041.0000.4420.9590.7330.7720.8811.0000.8100.9280.6770.6291.000
하부 형식0.8791.0000.6980.9960.8350.8390.0000.8101.0000.3260.9910.9261.000
설계하중0.3361.0000.2411.0000.0000.0000.9350.9280.3261.0000.1400.708NaN
관리주체0.8111.0000.5041.0000.0000.2470.0000.6770.9910.1401.0000.807NaN
시설물 종류0.6811.0000.2961.0000.4280.3310.0000.6290.9260.7080.8071.000NaN
비고1.0001.0001.0001.0001.0001.0001.0001.0001.000NaNNaNNaN1.000
2023-12-12T15:04:47.873112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설계하중상부 형식하부 형식위 치(군·구)관리주체시설물 종류
설계하중1.0000.6050.1820.2150.1600.498
상부 형식0.6051.0000.3380.1170.3130.260
하부 형식0.1820.3381.0000.2960.7040.619
위 치(군·구)0.2150.1170.2961.0000.3000.133
관리주체0.1600.3130.7040.3001.0000.689
시설물 종류0.4980.2600.6190.1330.6891.000
2023-12-12T15:04:48.060475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분길이(m)폭(m)준공년도위 치(군·구)상부 형식하부 형식설계하중관리주체시설물 종류
구분1.0000.0620.316-0.0820.0000.2840.4050.2270.4370.419
길이(m)0.0621.0000.5000.3240.3300.3080.4410.0000.0000.212
폭(m)0.3160.5001.0000.1750.1870.3550.4360.0000.1180.188
준공년도-0.0820.3240.1751.0000.0000.3620.0000.7660.0000.000
위 치(군·구)0.0000.3300.1870.0001.0000.1170.2960.2150.3000.133
상부 형식0.2840.3080.3550.3620.1171.0000.3380.6050.3130.260
하부 형식0.4050.4410.4360.0000.2960.3381.0000.1820.7040.619
설계하중0.2270.0000.0000.7660.2150.6050.1821.0000.1600.498
관리주체0.4370.0000.1180.0000.3000.3130.7040.1601.0000.689
시설물 종류0.4190.2120.1880.0000.1330.2600.6190.4980.6891.000

Missing values

2023-12-12T15:04:42.614974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:04:42.832739image/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

구분시설물명위 치(군·구)도로명주소 또는 지번주소길이(m)폭(m)준공년도상부 형식하부 형식설계하중관리주체시설물 종류비고
01주안차도육교미추홀구경인북길(주안동 614번지)38.729.01996강박스반중력식DB-24미추홀구 건설과일반<NA>
12선학육교미추홀구문학길(문학동 143번지)49.06.01994강박스역T형DB-18미추홀구 건설과3종<NA>
23서창(보차도)육교남동구장아산로 21650.010.21994강박스거더반중력식DB-24남동구3종<NA>
34논현(보차도)육교남동구은봉로 419번길 10340.010.02003강박스거더반중력식DB-24남동구3종<NA>
45도림1(보차도)육교남동구도림동 75번지40.05.02003강박스반중력식DB-24남동구3종<NA>
56도림2(보차도)육교남동구논현동 3번지40.05.02003강박스반중력식DB-24남동구3종<NA>
67남부고가교부평구부영로(부평동 738-21)113.015.02006스틸박스H형DB-24부평구 도로과2종<NA>
78작전고가교부평구주부토로(갈산동 419)61.28.61992스틸박스라멘DB-24부평구 도로과3동<NA>
89가좌IC고가교서구백범로(가좌동589-1)500.021.11986STB+ST형교각식(T)DB-24종합건설본부1종<NA>
910장제고가교부평구장제로(삼산동211-6)523.022.71993STB라멘식(Ra)DB-24종합건설본부1종<NA>
구분시설물명위 치(군·구)도로명주소 또는 지번주소길이(m)폭(m)준공년도상부 형식하부 형식설계하중관리주체시설물 종류비고
3940관선고가교미추홀구경원대로(선학동29-21)180.023.51992P.FT형교각식(T)DB-24종합건설본부2종<NA>
4041석남제2고가교서구건지로(석남동609)280.017.81992STB+S라멘식(Ra)DB-24종합건설본부2종<NA>
4142효성고가교계양구청안로(청천동375)51.011.01993STB교대(역T형 )DB-24종합건설본부2종<NA>
4243연수고가교연수구먼우금로(연수동651)252.024.51993PSCB라멘식(Ra)DB-24종합건설본부2종<NA>
4344송림고가교동구봉수대로(송림동4-194)115.022.01995P.F+S라멘식(Ra)DB-24종합건설본부2종<NA>
4445동춘고가교연수구미추홀대로(동춘동259-8)225.028.02009IPC-I문형교각DB-24종합건설본부2종<NA>
4546백운고가교부평구마장로(십정동181-233)178.015.52013P.F교대(역T형 )DB-24종합건설본부2종<NA>
4647부평IC고가교계양구계양대로(갈산동 451-2)50.050.01992강박스거더구주식DB-24종합건설본부3종<NA>
4748백석고가교서구드림로(백석동 산34)99.911.01992P.F.T형DB-24종합건설본부3종<NA>
4849원창고가교서구중봉대로(청라동 1-1115)240.019.02013STBRTADB-24인천시설공단1종<NA>