Overview

Dataset statistics

Number of variables11
Number of observations263
Missing cells207
Missing cells (%)7.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.0 KiB
Average record size in memory93.5 B

Variable types

Numeric5
Text2
Categorical1
DateTime3

Dataset

Description도로시설물관리시스템 공사정보 입니다. 번호, 공사명, 폭, 연장, 덧씌우기, 절삭보수, 절삭, 계약일, 착공일, 준공일, 비고로 구성되어있습니다.
URLhttps://www.data.go.kr/data/15120468/fileData.do

Alerts

번호 is highly overall correlated with 연장High correlation
연장 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
덧씌우기 is highly overall correlated with 절삭High correlation
절삭 is highly overall correlated with 덧씌우기High correlation
폭 is highly overall correlated with 연장High correlation
폭 is highly imbalanced (65.6%)Imbalance
비고 has 205 (77.9%) missing valuesMissing
번호 has unique valuesUnique
연장 has 192 (73.0%) zerosZeros
덧씌우기 has 84 (31.9%) zerosZeros
절삭보수 has 45 (17.1%) zerosZeros
절삭 has 133 (50.6%) zerosZeros

Reproduction

Analysis started2023-12-12 04:22:49.185938
Analysis finished2023-12-12 04:22:52.924524
Duration3.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct263
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean133.95817
Minimum1
Maximum270
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T13:22:53.025014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.1
Q166.5
median134
Q3202.5
95-th percentile254.9
Maximum270
Range269
Interquartile range (IQR)136

Descriptive statistics

Standard deviation77.992232
Coefficient of variation (CV)0.58221331
Kurtosis-1.2074363
Mean133.95817
Median Absolute Deviation (MAD)68
Skewness0.018606346
Sum35231
Variance6082.7883
MonotonicityStrictly increasing
2023-12-12T13:22:53.197256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
184 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
172 1
 
0.4%
173 1
 
0.4%
174 1
 
0.4%
175 1
 
0.4%
176 1
 
0.4%
177 1
 
0.4%
Other values (253) 253
96.2%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
270 1
0.4%
269 1
0.4%
268 1
0.4%
267 1
0.4%
264 1
0.4%
263 1
0.4%
262 1
0.4%
261 1
0.4%
260 1
0.4%
259 1
0.4%

공사명
Text

Distinct261
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T13:22:53.545578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length31
Mean length21.908745
Min length10

Characters and Unicode

Total characters5762
Distinct characters275
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique260 ?
Unique (%)98.9%

Sample

1st row시민운동장 앞외1개소 아스팔트포장 보수공사
2nd rowAID아파트주변 도로포장 보수공사
3rd row현충로~달성군청 아스팔트포장덧씌우기공사
4th row복현오거리 주변도로포장보수공사
5th row달구벌대로(수성교동편)외 1개소 아스팔트포장보수공사
ValueCountFrequency (%)
포장보수공사 111
 
14.9%
외 52
 
7.0%
포장 28
 
3.8%
1개소 25
 
3.4%
포장덧씌우기공사 24
 
3.2%
덧씌우기공사 20
 
2.7%
공사 20
 
2.7%
보수공사 18
 
2.4%
연간단가 14
 
1.9%
2개소 12
 
1.6%
Other values (336) 419
56.4%
2023-12-12T13:22:53.983525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
481
 
8.3%
공 294
 
5.1%
장 281
 
4.9%
사 272
 
4.7%
포 259
 
4.5%
리 232
 
4.0%
거 209
 
3.6%
수 189
 
3.3%
보 174
 
3.0%
~ 164
 
2.8%
Other values (265) 3207
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4700
81.6%
Space Separator 481
 
8.3%
Decimal Number 171
 
3.0%
Math Symbol 164
 
2.8%
Open Punctuation 94
 
1.6%
Close Punctuation 94
 
1.6%
Uppercase Letter 33
 
0.6%
Dash Punctuation 16
 
0.3%
Other Punctuation 9
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 294
 
6.3%
장 281
 
6.0%
사 272
 
5.8%
포 259
 
5.5%
리 232
 
4.9%
거 209
 
4.4%
수 189
 
4.0%
보 174
 
3.7%
네 158
 
3.4%
로 97
 
2.1%
Other values (236) 2535
53.9%
Uppercase Letter
ValueCountFrequency (%)
C 12
36.4%
I 8
24.2%
M 3
 
9.1%
B 2
 
6.1%
L 1
 
3.0%
O 1
 
3.0%
X 1
 
3.0%
E 1
 
3.0%
D 1
 
3.0%
A 1
 
3.0%
Other values (2) 2
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 52
30.4%
2 44
25.7%
0 27
15.8%
3 12
 
7.0%
9 11
 
6.4%
4 9
 
5.3%
5 7
 
4.1%
6 5
 
2.9%
8 3
 
1.8%
7 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 7
77.8%
, 2
 
22.2%
Space Separator
ValueCountFrequency (%)
481
100.0%
Math Symbol
ValueCountFrequency (%)
~ 164
100.0%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%
Close Punctuation
ValueCountFrequency (%)
) 94
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4700
81.6%
Common 1029
 
17.9%
Latin 33
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 294
 
6.3%
장 281
 
6.0%
사 272
 
5.8%
포 259
 
5.5%
리 232
 
4.9%
거 209
 
4.4%
수 189
 
4.0%
보 174
 
3.7%
네 158
 
3.4%
로 97
 
2.1%
Other values (236) 2535
53.9%
Common
ValueCountFrequency (%)
481
46.7%
~ 164
 
15.9%
( 94
 
9.1%
) 94
 
9.1%
1 52
 
5.1%
2 44
 
4.3%
0 27
 
2.6%
- 16
 
1.6%
3 12
 
1.2%
9 11
 
1.1%
Other values (7) 34
 
3.3%
Latin
ValueCountFrequency (%)
C 12
36.4%
I 8
24.2%
M 3
 
9.1%
B 2
 
6.1%
L 1
 
3.0%
O 1
 
3.0%
X 1
 
3.0%
E 1
 
3.0%
D 1
 
3.0%
A 1
 
3.0%
Other values (2) 2
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4700
81.6%
ASCII 1062
 
18.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
481
45.3%
~ 164
 
15.4%
( 94
 
8.9%
) 94
 
8.9%
1 52
 
4.9%
2 44
 
4.1%
0 27
 
2.5%
- 16
 
1.5%
C 12
 
1.1%
3 12
 
1.1%
Other values (19) 66
 
6.2%
Hangul
ValueCountFrequency (%)
공 294
 
6.3%
장 281
 
6.0%
사 272
 
5.8%
포 259
 
5.5%
리 232
 
4.9%
거 209
 
4.4%
수 189
 
4.0%
보 174
 
3.7%
네 158
 
3.4%
로 97
 
2.1%
Other values (236) 2535
53.9%

폭
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct48
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
205 
20
 
9
11.7
 
2
3.5
 
2
35
 
2
Other values (43)
43 

Length

Max length8
Median length1
Mean length1.5855513
Min length1

Unique

Unique43 ?
Unique (%)16.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 205
77.9%
20 9
 
3.4%
11.7 2
 
0.8%
3.5 2
 
0.8%
35 2
 
0.8%
12.6 1
 
0.4%
23.8 1
 
0.4%
21 1
 
0.4%
15 1
 
0.4%
15.7 1
 
0.4%
Other values (38) 38
 
14.4%

Length

2023-12-12T13:22:54.137734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 205
77.9%
20 9
 
3.4%
11.7 2
 
0.8%
3.5 2
 
0.8%
35 2
 
0.8%
3.2~14.4 1
 
0.4%
3.2~6.6 1
 
0.4%
24 1
 
0.4%
20~30 1
 
0.4%
3~13 1
 
0.4%
Other values (38) 38
 
14.4%

연장
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct69
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean383.73004
Minimum0
Maximum5800
Zeros192
Zeros (%)73.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T13:22:54.269374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3183
95-th percentile2091.4
Maximum5800
Range5800
Interquartile range (IQR)183

Descriptive statistics

Standard deviation810.78761
Coefficient of variation (CV)2.1129115
Kurtosis10.318329
Mean383.73004
Median Absolute Deviation (MAD)0
Skewness2.7746596
Sum100921
Variance657376.56
MonotonicityNot monotonic
2023-12-12T13:22:54.404995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 192
73.0%
183 2
 
0.8%
766 2
 
0.8%
1500 2
 
0.8%
1877 1
 
0.4%
115 1
 
0.4%
977 1
 
0.4%
2272 1
 
0.4%
1241 1
 
0.4%
253 1
 
0.4%
Other values (59) 59
 
22.4%
ValueCountFrequency (%)
0 192
73.0%
23 1
 
0.4%
99 1
 
0.4%
115 1
 
0.4%
118 1
 
0.4%
183 2
 
0.8%
230 1
 
0.4%
250 1
 
0.4%
253 1
 
0.4%
265 1
 
0.4%
ValueCountFrequency (%)
5800 1
0.4%
4600 1
0.4%
2982 1
0.4%
2783 1
0.4%
2511 1
0.4%
2438 1
0.4%
2418 1
0.4%
2367 1
0.4%
2356 1
0.4%
2272 1
0.4%

덧씌우기
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct176
Distinct (%)66.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean960565.3
Minimum0
Maximum2.491137 × 108
Zeros84
Zeros (%)31.9%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T13:22:54.540132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5608
Q321215
95-th percentile51554.5
Maximum2.491137 × 108
Range2.491137 × 108
Interquartile range (IQR)21215

Descriptive statistics

Standard deviation15360193
Coefficient of variation (CV)15.990785
Kurtosis262.99922
Mean960565.3
Median Absolute Deviation (MAD)5608
Skewness16.217239
Sum2.5262867 × 108
Variance2.3593553 × 1014
MonotonicityNot monotonic
2023-12-12T13:22:54.679009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 84
31.9%
8 2
 
0.8%
3405 2
 
0.8%
104221 2
 
0.8%
37802 2
 
0.8%
66 1
 
0.4%
6 1
 
0.4%
23000 1
 
0.4%
12 1
 
0.4%
3 1
 
0.4%
Other values (166) 166
63.1%
ValueCountFrequency (%)
0 84
31.9%
1 1
 
0.4%
3 1
 
0.4%
6 1
 
0.4%
8 2
 
0.8%
12 1
 
0.4%
66 1
 
0.4%
609 1
 
0.4%
748 1
 
0.4%
960 1
 
0.4%
ValueCountFrequency (%)
249113702 1
0.4%
104221 2
0.8%
83925 1
0.4%
82402 1
0.4%
70626 1
0.4%
69421 1
0.4%
64153 1
0.4%
63446 1
0.4%
61726 1
0.4%
61725 1
0.4%

절삭보수
Real number (ℝ)

ZEROS 

Distinct209
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5358.8099
Minimum0
Maximum38254
Zeros45
Zeros (%)17.1%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T13:22:54.825966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1200
median3875
Q37773.5
95-th percentile15826.4
Maximum38254
Range38254
Interquartile range (IQR)7573.5

Descriptive statistics

Standard deviation6031.9763
Coefficient of variation (CV)1.1256186
Kurtosis4.9352174
Mean5358.8099
Median Absolute Deviation (MAD)3718
Skewness1.8086364
Sum1409367
Variance36384738
MonotonicityNot monotonic
2023-12-12T13:22:54.972766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 45
 
17.1%
14 2
 
0.8%
9 2
 
0.8%
506 2
 
0.8%
2930 2
 
0.8%
12204 2
 
0.8%
7 2
 
0.8%
5 2
 
0.8%
200 2
 
0.8%
6436 2
 
0.8%
Other values (199) 200
76.0%
ValueCountFrequency (%)
0 45
17.1%
5 2
 
0.8%
6 1
 
0.4%
7 2
 
0.8%
9 2
 
0.8%
10 1
 
0.4%
11 1
 
0.4%
13 1
 
0.4%
14 2
 
0.8%
15 1
 
0.4%
ValueCountFrequency (%)
38254 1
0.4%
32614 1
0.4%
27491 1
0.4%
25679 1
0.4%
21450 1
0.4%
21060 1
0.4%
20838 1
0.4%
19710 1
0.4%
19476 1
0.4%
18600 1
0.4%

절삭
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct126
Distinct (%)47.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2420.0608
Minimum0
Maximum33049
Zeros133
Zeros (%)50.6%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T13:22:55.113348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32515
95-th percentile11635.5
Maximum33049
Range33049
Interquartile range (IQR)2515

Descriptive statistics

Standard deviation4877.3547
Coefficient of variation (CV)2.0153852
Kurtosis11.981855
Mean2420.0608
Median Absolute Deviation (MAD)0
Skewness3.0917722
Sum636476
Variance23788589
MonotonicityNot monotonic
2023-12-12T13:22:55.265266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 133
50.6%
5240 2
 
0.8%
8290 2
 
0.8%
23 2
 
0.8%
2 2
 
0.8%
560 2
 
0.8%
100 1
 
0.4%
247 1
 
0.4%
366 1
 
0.4%
356 1
 
0.4%
Other values (116) 116
44.1%
ValueCountFrequency (%)
0 133
50.6%
2 2
 
0.8%
3 1
 
0.4%
23 2
 
0.8%
26 1
 
0.4%
52 1
 
0.4%
53 1
 
0.4%
80 1
 
0.4%
100 1
 
0.4%
132 1
 
0.4%
ValueCountFrequency (%)
33049 1
0.4%
30773 1
0.4%
23000 1
0.4%
19169 1
0.4%
19167 1
0.4%
18726 1
0.4%
18050 1
0.4%
17960 1
0.4%
13377 1
0.4%
12591 1
0.4%

계약일
Date

Distinct192
Distinct (%)73.6%
Missing2
Missing (%)0.8%
Memory size2.2 KiB
Minimum2000-02-24 00:00:00
Maximum2014-11-19 00:00:00
2023-12-12T13:22:55.477884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:55.932691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공일
Date

Distinct205
Distinct (%)77.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum2000-02-24 00:00:00
Maximum2014-11-20 00:00:00
2023-12-12T13:22:56.107606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:56.279822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

준공일
Date

Distinct229
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum2000-03-01 00:00:00
Maximum2014-12-26 00:00:00
2023-12-12T13:22:56.438004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:56.596241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

비고
Text

MISSING 

Distinct41
Distinct (%)70.7%
Missing205
Missing (%)77.9%
Memory size2.2 KiB
2023-12-12T13:22:56.809779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length6.2413793
Min length2

Characters and Unicode

Total characters362
Distinct characters39
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)63.8%

Sample

1st row수의
2nd row수의
3rd row수의
4th row수의
5th row수의
ValueCountFrequency (%)
수의 14
 
19.7%
조달가격변동 3
 
4.2%
장비운반 3
 
4.2%
l=150m 2
 
2.8%
l=1700m 2
 
2.8%
아스콘 2
 
2.8%
조달가격 2
 
2.8%
1식 2
 
2.8%
b=22m 2
 
2.8%
l=1090m 1
 
1.4%
Other values (38) 38
53.5%
2023-12-12T13:22:57.233072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
= 39
 
10.8%
m 35
 
9.7%
L 34
 
9.4%
1 34
 
9.4%
0 31
 
8.6%
2 25
 
6.9%
수 14
 
3.9%
의 14
 
3.9%
13
 
3.6%
6 11
 
3.0%
Other values (29) 112
30.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 149
41.2%
Other Letter 83
22.9%
Math Symbol 39
 
10.8%
Uppercase Letter 39
 
10.8%
Lowercase Letter 35
 
9.7%
Space Separator 13
 
3.6%
Other Punctuation 2
 
0.6%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 14
16.9%
의 14
16.9%
동 5
 
6.0%
변 5
 
6.0%
격 5
 
6.0%
가 5
 
6.0%
달 5
 
6.0%
조 5
 
6.0%
장 3
 
3.6%
비 3
 
3.6%
Other values (9) 19
22.9%
Decimal Number
ValueCountFrequency (%)
1 34
22.8%
0 31
20.8%
2 25
16.8%
6 11
 
7.4%
3 10
 
6.7%
5 10
 
6.7%
8 9
 
6.0%
7 9
 
6.0%
9 8
 
5.4%
4 2
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
L 34
87.2%
B 3
 
7.7%
A 2
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
: 1
50.0%
Math Symbol
ValueCountFrequency (%)
= 39
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 35
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 205
56.6%
Hangul 83
22.9%
Latin 74
 
20.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 14
16.9%
의 14
16.9%
동 5
 
6.0%
변 5
 
6.0%
격 5
 
6.0%
가 5
 
6.0%
달 5
 
6.0%
조 5
 
6.0%
장 3
 
3.6%
비 3
 
3.6%
Other values (9) 19
22.9%
Common
ValueCountFrequency (%)
= 39
19.0%
1 34
16.6%
0 31
15.1%
2 25
12.2%
13
 
6.3%
6 11
 
5.4%
3 10
 
4.9%
5 10
 
4.9%
8 9
 
4.4%
7 9
 
4.4%
Other values (6) 14
 
6.8%
Latin
ValueCountFrequency (%)
m 35
47.3%
L 34
45.9%
B 3
 
4.1%
A 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 279
77.1%
Hangul 83
 
22.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
= 39
14.0%
m 35
12.5%
L 34
12.2%
1 34
12.2%
0 31
11.1%
2 25
9.0%
13
 
4.7%
6 11
 
3.9%
3 10
 
3.6%
5 10
 
3.6%
Other values (10) 37
13.3%
Hangul
ValueCountFrequency (%)
수 14
16.9%
의 14
16.9%
동 5
 
6.0%
변 5
 
6.0%
격 5
 
6.0%
가 5
 
6.0%
달 5
 
6.0%
조 5
 
6.0%
장 3
 
3.6%
비 3
 
3.6%
Other values (9) 19
22.9%

Interactions

2023-12-12T13:22:52.038306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:49.988650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:50.522608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:51.036166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:51.498955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:52.127138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:50.090743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:50.629178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:51.119834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:51.612748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:52.258668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:50.181397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:50.740739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:51.206590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:51.716426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:52.361992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:50.312428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:50.830637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:51.293491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:51.823697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:52.462706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:50.425965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:50.937425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:51.409700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:51.925109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:22:57.369698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호폭연장덧씌우기절삭보수절삭비고
번호1.0000.5280.4690.0000.4990.2980.972
폭0.5281.0000.9910.0000.8160.000NaN
연장0.4690.9911.0000.0000.4800.4031.000
덧씌우기0.0000.0000.0001.0000.0000.0000.000
절삭보수0.4990.8160.4800.0001.0000.0860.000
절삭0.2980.0000.4030.0000.0861.0000.753
비고0.972NaN1.0000.0000.0000.7531.000
2023-12-12T13:22:57.509604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호연장덧씌우기절삭보수절삭폭
번호1.0000.541-0.4390.448-0.4260.191
연장0.5411.000-0.2170.318-0.1600.797
덧씌우기-0.439-0.2171.000-0.1060.5460.000
절삭보수0.4480.318-0.1061.000-0.1790.406
절삭-0.426-0.1600.546-0.1791.0000.000
폭0.1910.7970.0000.4060.0001.000

Missing values

2023-12-12T13:22:52.594812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:22:52.756507image/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.
2023-12-12T13:22:52.864316image/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

번호공사명폭연장덧씌우기절삭보수절삭계약일착공일준공일비고
01시민운동장 앞외1개소 아스팔트포장 보수공사003625230002000-06-122000-06-132000-06-19수의
12AID아파트주변 도로포장 보수공사000322702000-07-032000-07-052000-07-11수의
23현충로~달성군청 아스팔트포장덧씌우기공사00249113702002000-07-032000-07-062000-09-20수의
34복현오거리 주변도로포장보수공사003860386002000-07-032000-07-052000-07-11수의
45달구벌대로(수성교동편)외 1개소 아스팔트포장보수공사004989498902000-07-032000-07-072000-07-15수의
56칠곡로(태전삼거리~강북네거리)외 1개소 포장보수공사000610302000-07-192000-07-202000-07-26수의
67앞산네거리~삼각지네거리 아스팔트포장덧씌우기공사0023486349002000-07-312000-08-012000-08-12수의
78평리지하차도 램프포장 덧씌우기공사001026640902000-07-312000-08-032000-08-12수의
89장기공원서편(이곡네거리~미주네거리)아스팔트포장보수공사0018592480002000-08-182000-08-222000-09-05수의
910지하철2호선구간 도로포장 보수공사00013045133772000-08-302000-08-312000-09-14수의
번호공사명폭연장덧씌우기절삭보수절삭계약일착공일준공일비고
253259이현자동차검사소~평현치안센터 포장보수공사3~1220152956693902014-04-172014-04-222014-05-20<NA>
254260칠곡동아백화점~동천교 외 1개소 포장보수공사3~16214009214522014-02-272014-03-052014-04-01<NA>
255261각산네거리~송정삼거리 외 1개소 포장보수공사3.1~352783700493433562014-04-072014-04-092014-05-02<NA>
256262국도5호선~공단5교 외 1개소 포장보수공사3.2~7.81918087318162014-02-252014-02-272014-03-26<NA>
257263신당네거리~성서네거리 포장보수공사3.1~11.816650998902014-02-252014-02-272014-03-26<NA>
258264조암남로(월성1동주민센터~송일초교네거리) 외 2개소 포장보수공사3.1~15.118072212648002013-08-302013-09-042014-05-07<NA>
259267신천교 포장보수공사 (초속경LMC)3.48118040802014-11-192014-11-202014-12-18<NA>
260268경동초교 서편 외 2개소 포장보수공사10.910080628202014-09-012014-09-012014-11-10<NA>
261269아양로(아양네거리) 외 3개소 포장보수공사3.561624523636802014-09-012014-09-012014-12-09<NA>
262270호국로(국우터널남편) 포장보수공사3.517700757602014-09-012014-09-012014-12-26<NA>