Overview

Dataset statistics

Number of variables15
Number of observations886
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory110.0 KiB
Average record size in memory127.1 B

Variable types

Numeric1
Text4
Categorical10

Dataset

Description인천광역시 미추홀구 도로 현황에 대한 데이터로 노선명, 노선번호,동별 포장도로, 미포장도로 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15086894/fileData.do

Alerts

광역시도 has constant value ""Constant
시군구 has constant value ""Constant
5차로 has constant value ""Constant
6차로 has constant value ""Constant
7차로 has constant value ""Constant
8차로 has constant value ""Constant
미포장도 has constant value ""Constant
2차로 is highly overall correlated with 3차로 and 1 other fieldsHigh correlation
3차로 is highly overall correlated with 2차로High correlation
4차로 is highly overall correlated with 2차로High correlation
2차로 is highly imbalanced (88.6%)Imbalance
3차로 is highly imbalanced (97.8%)Imbalance
4차로 is highly imbalanced (95.5%)Imbalance
노선번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:29:14.294152
Analysis finished2023-12-12 19:29:15.311979
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선번호
Real number (ℝ)

UNIQUE 

Distinct886
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3873.6738
Minimum1001
Maximum7072
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-13T04:29:15.410794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1001
5-th percentile1045.25
Q12084.25
median4075.5
Q35182.75
95-th percentile7018.75
Maximum7072
Range6071
Interquartile range (IQR)3098.5

Descriptive statistics

Standard deviation1784.4138
Coefficient of variation (CV)0.46065155
Kurtosis-1.0345298
Mean3873.6738
Median Absolute Deviation (MAD)1134
Skewness-0.16123102
Sum3432075
Variance3184132.7
MonotonicityStrictly increasing
2023-12-13T04:29:15.585369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1001 1
 
0.1%
5115 1
 
0.1%
5104 1
 
0.1%
5105 1
 
0.1%
5106 1
 
0.1%
5107 1
 
0.1%
5108 1
 
0.1%
5109 1
 
0.1%
5110 1
 
0.1%
5111 1
 
0.1%
Other values (876) 876
98.9%
ValueCountFrequency (%)
1001 1
0.1%
1002 1
0.1%
1003 1
0.1%
1004 1
0.1%
1005 1
0.1%
1006 1
0.1%
1007 1
0.1%
1008 1
0.1%
1009 1
0.1%
1010 1
0.1%
ValueCountFrequency (%)
7072 1
0.1%
7070 1
0.1%
7068 1
0.1%
7066 1
0.1%
7064 1
0.1%
7062 1
0.1%
7060 1
0.1%
7058 1
0.1%
7056 1
0.1%
7054 1
0.1%

노선명
Text

Distinct732
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2023-12-13T04:29:15.873446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length12.059819
Min length3

Characters and Unicode

Total characters10685
Distinct characters104
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique626 ?
Unique (%)70.7%

Sample

1st row제물량로4번길 4~제물량로4번길 21
2nd row숭의동 379-17~숭의동 350-10
3rd row인주대로11번길
4th row제물량로4번길 15-13~숭의동 348-25
5th row인주대로23번길
ValueCountFrequency (%)
학익동 19
 
1.4%
주승로 14
 
1.0%
한나루로357번길 9
 
0.7%
소성로 9
 
0.7%
매소홀로 8
 
0.6%
경인로 8
 
0.6%
용현동 8
 
0.6%
염창로 8
 
0.6%
수봉로 8
 
0.6%
주안동 7
 
0.5%
Other values (955) 1253
92.7%
2023-12-13T04:29:16.391645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
길 1051
 
9.8%
로 971
 
9.1%
번 877
 
8.2%
1 583
 
5.5%
468
 
4.4%
3 453
 
4.2%
2 448
 
4.2%
4 444
 
4.2%
5 383
 
3.6%
~ 354
 
3.3%
Other values (94) 4653
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6023
56.4%
Decimal Number 3665
34.3%
Space Separator 468
 
4.4%
Math Symbol 354
 
3.3%
Dash Punctuation 175
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 1051
17.4%
로 971
16.1%
번 877
14.6%
인 244
 
4.1%
주 196
 
3.3%
대 186
 
3.1%
경 164
 
2.7%
소 143
 
2.4%
동 137
 
2.3%
홀 106
 
1.8%
Other values (81) 1948
32.3%
Decimal Number
ValueCountFrequency (%)
1 583
15.9%
3 453
12.4%
2 448
12.2%
4 444
12.1%
5 383
10.5%
6 332
9.1%
7 297
8.1%
8 269
7.3%
9 228
 
6.2%
0 228
 
6.2%
Space Separator
ValueCountFrequency (%)
468
100.0%
Math Symbol
ValueCountFrequency (%)
~ 354
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 175
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6023
56.4%
Common 4662
43.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 1051
17.4%
로 971
16.1%
번 877
14.6%
인 244
 
4.1%
주 196
 
3.3%
대 186
 
3.1%
경 164
 
2.7%
소 143
 
2.4%
동 137
 
2.3%
홀 106
 
1.8%
Other values (81) 1948
32.3%
Common
ValueCountFrequency (%)
1 583
12.5%
468
10.0%
3 453
9.7%
2 448
9.6%
4 444
9.5%
5 383
8.2%
~ 354
7.6%
6 332
7.1%
7 297
6.4%
8 269
5.8%
Other values (3) 631
13.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6023
56.4%
ASCII 4662
43.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
길 1051
17.4%
로 971
16.1%
번 877
14.6%
인 244
 
4.1%
주 196
 
3.3%
대 186
 
3.1%
경 164
 
2.7%
소 143
 
2.4%
동 137
 
2.3%
홀 106
 
1.8%
Other values (81) 1948
32.3%
ASCII
ValueCountFrequency (%)
1 583
12.5%
468
10.0%
3 453
9.7%
2 448
9.6%
4 444
9.5%
5 383
8.2%
~ 354
7.6%
6 332
7.1%
7 297
6.4%
8 269
5.8%
Other values (3) 631
13.5%

광역시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
인천광역시
886 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 886
100.0%

Length

2023-12-13T04:29:16.547334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:29:16.653873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 886
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
미추홀구
886 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미추홀구 886
100.0%

Length

2023-12-13T04:29:16.758693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:29:16.849205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미추홀구 886
100.0%

개통도
Text

Distinct443
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2023-12-13T04:29:17.193280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.7234763
Min length1

Characters and Unicode

Total characters2413
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique254 ?
Unique (%)28.7%

Sample

1st row108
2nd row221
3rd row110
4th row269
5th row97
ValueCountFrequency (%)
0 40
 
4.5%
90 9
 
1.0%
104 8
 
0.9%
107 8
 
0.9%
109 8
 
0.9%
67 7
 
0.8%
81 7
 
0.8%
100 7
 
0.8%
106 7
 
0.8%
119 7
 
0.8%
Other values (433) 778
87.8%
2023-12-13T04:29:17.902195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 453
18.8%
2 317
13.1%
0 255
10.6%
4 235
9.7%
3 211
8.7%
5 207
8.6%
9 188
7.8%
7 176
 
7.3%
6 176
 
7.3%
8 175
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2393
99.2%
Other Punctuation 20
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 453
18.9%
2 317
13.2%
0 255
10.7%
4 235
9.8%
3 211
8.8%
5 207
8.7%
9 188
7.9%
7 176
 
7.4%
6 176
 
7.4%
8 175
 
7.3%
Other Punctuation
ValueCountFrequency (%)
, 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2413
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 453
18.8%
2 317
13.1%
0 255
10.6%
4 235
9.7%
3 211
8.7%
5 207
8.6%
9 188
7.8%
7 176
 
7.3%
6 176
 
7.3%
8 175
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2413
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 453
18.8%
2 317
13.1%
0 255
10.6%
4 235
9.7%
3 211
8.7%
5 207
8.6%
9 188
7.8%
7 176
 
7.3%
6 176
 
7.3%
8 175
 
7.3%

포장도
Text

Distinct443
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2023-12-13T04:29:18.407464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.7234763
Min length1

Characters and Unicode

Total characters2413
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique254 ?
Unique (%)28.7%

Sample

1st row108
2nd row221
3rd row110
4th row269
5th row97
ValueCountFrequency (%)
0 40
 
4.5%
90 9
 
1.0%
104 8
 
0.9%
107 8
 
0.9%
109 8
 
0.9%
67 7
 
0.8%
81 7
 
0.8%
100 7
 
0.8%
106 7
 
0.8%
119 7
 
0.8%
Other values (433) 778
87.8%
2023-12-13T04:29:19.105430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 453
18.8%
2 317
13.1%
0 255
10.6%
4 235
9.7%
3 211
8.7%
5 207
8.6%
9 188
7.8%
7 176
 
7.3%
6 176
 
7.3%
8 175
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2393
99.2%
Other Punctuation 20
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 453
18.9%
2 317
13.2%
0 255
10.7%
4 235
9.8%
3 211
8.8%
5 207
8.7%
9 188
7.9%
7 176
 
7.4%
6 176
 
7.4%
8 175
 
7.3%
Other Punctuation
ValueCountFrequency (%)
, 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2413
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 453
18.8%
2 317
13.1%
0 255
10.6%
4 235
9.7%
3 211
8.7%
5 207
8.6%
9 188
7.8%
7 176
 
7.3%
6 176
 
7.3%
8 175
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2413
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 453
18.8%
2 317
13.1%
0 255
10.6%
4 235
9.7%
3 211
8.7%
5 207
8.6%
9 188
7.8%
7 176
 
7.3%
6 176
 
7.3%
8 175
 
7.3%

1차로
Text

Distinct412
Distinct (%)46.5%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2023-12-13T04:29:19.601671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.6072235
Min length1

Characters and Unicode

Total characters2310
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique229 ?
Unique (%)25.8%

Sample

1st row108
2nd row221
3rd row110
4th row269
5th row97
ValueCountFrequency (%)
0 85
 
9.6%
90 9
 
1.0%
109 8
 
0.9%
107 8
 
0.9%
104 8
 
0.9%
81 7
 
0.8%
67 7
 
0.8%
119 7
 
0.8%
106 7
 
0.8%
120 6
 
0.7%
Other values (402) 734
82.8%
2023-12-13T04:29:20.263242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 432
18.7%
2 303
13.1%
0 286
12.4%
4 221
9.6%
3 200
8.7%
5 190
8.2%
9 176
7.6%
8 164
 
7.1%
6 164
 
7.1%
7 162
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2298
99.5%
Other Punctuation 12
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 432
18.8%
2 303
13.2%
0 286
12.4%
4 221
9.6%
3 200
8.7%
5 190
8.3%
9 176
7.7%
8 164
 
7.1%
6 164
 
7.1%
7 162
 
7.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 432
18.7%
2 303
13.1%
0 286
12.4%
4 221
9.6%
3 200
8.7%
5 190
8.2%
9 176
7.6%
8 164
 
7.1%
6 164
 
7.1%
7 162
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 432
18.7%
2 303
13.1%
0 286
12.4%
4 221
9.6%
3 200
8.7%
5 190
8.2%
9 176
7.6%
8 164
 
7.1%
6 164
 
7.1%
7 162
 
7.0%

2차로
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct48
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
0
835 
255
 
2
590
 
2
183
 
2
196
 
2
Other values (43)
 
43

Length

Max length5
Median length1
Mean length1.1218962
Min length1

Unique

Unique43 ?
Unique (%)4.9%

Sample

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

Common Values

ValueCountFrequency (%)
0 835
94.2%
255 2
 
0.2%
590 2
 
0.2%
183 2
 
0.2%
196 2
 
0.2%
802 1
 
0.1%
285 1
 
0.1%
544 1
 
0.1%
327 1
 
0.1%
419 1
 
0.1%
Other values (38) 38
 
4.3%

Length

2023-12-13T04:29:20.480936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 835
94.2%
590 2
 
0.2%
183 2
 
0.2%
196 2
 
0.2%
255 2
 
0.2%
260 1
 
0.1%
325 1
 
0.1%
339 1
 
0.1%
23 1
 
0.1%
318 1
 
0.1%
Other values (38) 38
 
4.3%

3차로
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
0
882 
313
 
1
797
 
1
64
 
1
68
 
1

Length

Max length3
Median length1
Mean length1.006772
Min length1

Unique

Unique4 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 882
99.5%
313 1
 
0.1%
797 1
 
0.1%
64 1
 
0.1%
68 1
 
0.1%

Length

2023-12-13T04:29:20.682945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:29:20.836586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 882
99.5%
313 1
 
0.1%
797 1
 
0.1%
64 1
 
0.1%
68 1
 
0.1%

4차로
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct15
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
0
872 
160
 
1
1,543
 
1
402
 
1
767
 
1
Other values (10)
 
10

Length

Max length5
Median length1
Mean length1.0327314
Min length1

Unique

Unique14 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 872
98.4%
160 1
 
0.1%
1,543 1
 
0.1%
402 1
 
0.1%
767 1
 
0.1%
487 1
 
0.1%
140 1
 
0.1%
335 1
 
0.1%
251 1
 
0.1%
356 1
 
0.1%
Other values (5) 5
 
0.6%

Length

2023-12-13T04:29:21.005146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 872
98.4%
160 1
 
0.1%
1,543 1
 
0.1%
402 1
 
0.1%
767 1
 
0.1%
487 1
 
0.1%
140 1
 
0.1%
335 1
 
0.1%
251 1
 
0.1%
356 1
 
0.1%
Other values (5) 5
 
0.6%

5차로
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
0
886 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 886
100.0%

Length

2023-12-13T04:29:21.192988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:29:21.334086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 886
100.0%

6차로
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
0
886 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 886
100.0%

Length

2023-12-13T04:29:21.468259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:29:21.584090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 886
100.0%

7차로
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
0
886 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 886
100.0%

Length

2023-12-13T04:29:21.730040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:29:21.869389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 886
100.0%

8차로
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
0
886 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 886
100.0%

Length

2023-12-13T04:29:22.002109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:29:22.135678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 886
100.0%

미포장도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
0
886 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 886
100.0%

Length

2023-12-13T04:29:22.258392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:29:22.389692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 886
100.0%

Interactions

2023-12-13T04:29:14.762534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:29:22.477789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호2차로3차로4차로
노선번호1.0000.0000.0000.133
2차로0.0001.0000.9450.935
3차로0.0000.9451.0000.000
4차로0.1330.9350.0001.000
2023-12-13T04:29:22.624263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2차로3차로4차로
2차로1.0000.7580.588
3차로0.7581.0000.000
4차로0.5880.0001.000
2023-12-13T04:29:22.728338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호2차로3차로4차로
노선번호1.0000.0000.0000.054
2차로0.0001.0000.7580.588
3차로0.0000.7581.0000.000
4차로0.0540.5880.0001.000

Missing values

2023-12-13T04:29:14.980550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:29:15.228583image/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

노선번호노선명광역시도시군구개통도포장도1차로2차로3차로4차로5차로6차로7차로8차로미포장도
01001제물량로4번길 4~제물량로4번길 21인천광역시미추홀구10810810800000000
11002숭의동 379-17~숭의동 350-10인천광역시미추홀구22122122100000000
21003인주대로11번길인천광역시미추홀구11011011000000000
31004제물량로4번길 15-13~숭의동 348-25인천광역시미추홀구26926926900000000
41005인주대로23번길인천광역시미추홀구97979700000000
51006수봉로21번길인천광역시미추홀구17017017000000000
61007인주대로45번길 2~석정로49번길 30인천광역시미추홀구815815334321016000000
71008장천로8번길 39~인주대로45번길 10인천광역시미추홀구43143143100000000
81009장천로인천광역시미추홀구28528502850000000
91010장천로14번길인천광역시미추홀구20820820800000000
노선번호노선명광역시도시군구개통도포장도1차로2차로3차로4차로5차로6차로7차로8차로미포장도
8767054매소홀로535번길인천광역시미추홀구69696900000000
8777056매소홀로541번길인천광역시미추홀구11411411400000000
8787058문학길인천광역시미추홀구17817817800000000
8797060매소홀로541번길인천광역시미추홀구37537537500000000
8807062매소홀로535번길인천광역시미추홀구60606000000000
8817064매소홀로 553~문학동 329-8인천광역시미추홀구51951951900000000
8827066승학길인천광역시미추홀구60606000000000
8837068문학동 397-6~ 소성로332번길 39인천광역시미추홀구00000000000
8847070소성로332번길인천광역시미추홀구55555500000000
8857072소성로인천광역시미추홀구1,1681,16801,1680000000