Overview

Dataset statistics

Number of variables10
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory88.3 B

Variable types

Text5
Categorical3
Numeric2

Dataset

Description부산 동래구 자전거도로 현황에 대한 데이터로 노선번호, 노선명, 자전거도로 종류, 도로관리청, 도로구간, 총길이, 너비, 주요경유지 등의 항목을 제공합니다.
Author부산광역시 동래구
URLhttps://www.data.go.kr/data/15028029/fileData.do

Alerts

도로관리청 has constant value ""Constant
너비(m) is highly overall correlated with 자전거도로의 종류High correlation
자전거도로의 종류 is highly overall correlated with 너비(m)High correlation
지정사유(변경, 폐지) is highly imbalanced (72.4%)Imbalance
노선번호 has unique valuesUnique
도로구간(기점) has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:46:49.824409
Analysis finished2023-12-12 20:46:51.085488
Duration1.26 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선번호
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T05:46:51.224035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.5714286
Min length4

Characters and Unicode

Total characters96
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row동래-1
2nd row동래-2
3rd row동래-3
4th row동래-4
5th row동래-5
ValueCountFrequency (%)
동래-1 1
 
4.8%
동래-12 1
 
4.8%
동래-20 1
 
4.8%
동래-19 1
 
4.8%
동래-18 1
 
4.8%
동래-17 1
 
4.8%
동래-16 1
 
4.8%
동래-15 1
 
4.8%
동래-14 1
 
4.8%
동래-13 1
 
4.8%
Other values (11) 11
52.4%
2023-12-13T05:46:51.656424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 21
21.9%
래 21
21.9%
- 21
21.9%
1 13
13.5%
2 4
 
4.2%
3 2
 
2.1%
4 2
 
2.1%
5 2
 
2.1%
6 2
 
2.1%
7 2
 
2.1%
Other values (3) 6
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42
43.8%
Decimal Number 33
34.4%
Dash Punctuation 21
21.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
39.4%
2 4
 
12.1%
3 2
 
6.1%
4 2
 
6.1%
5 2
 
6.1%
6 2
 
6.1%
7 2
 
6.1%
8 2
 
6.1%
9 2
 
6.1%
0 2
 
6.1%
Other Letter
ValueCountFrequency (%)
동 21
50.0%
래 21
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54
56.2%
Hangul 42
43.8%

Most frequent character per script

Common
ValueCountFrequency (%)
- 21
38.9%
1 13
24.1%
2 4
 
7.4%
3 2
 
3.7%
4 2
 
3.7%
5 2
 
3.7%
6 2
 
3.7%
7 2
 
3.7%
8 2
 
3.7%
9 2
 
3.7%
Hangul
ValueCountFrequency (%)
동 21
50.0%
래 21
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54
56.2%
Hangul 42
43.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 21
50.0%
래 21
50.0%
ASCII
ValueCountFrequency (%)
- 21
38.9%
1 13
24.1%
2 4
 
7.4%
3 2
 
3.7%
4 2
 
3.7%
5 2
 
3.7%
6 2
 
3.7%
7 2
 
3.7%
8 2
 
3.7%
9 2
 
3.7%

노선명
Text

Distinct14
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T05:46:51.905926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.6190476
Min length3

Characters and Unicode

Total characters76
Distinct characters37
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

Unique7 ?
Unique (%)33.3%

Sample

1st row중앙대로
2nd row중앙대로
3rd row온천천로
4th row읍내길
5th row만덕로
ValueCountFrequency (%)
중앙대로 2
9.5%
온천천로 2
9.5%
만덕로 2
9.5%
여고로 2
9.5%
미남로 2
9.5%
충렬로 2
9.5%
수영강변로 2
9.5%
읍내길 1
 
4.8%
아시아드로 1
 
4.8%
석사로 1
 
4.8%
Other values (4) 4
19.0%
2023-12-13T05:46:52.446438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 20
26.3%
천 4
 
5.3%
중 2
 
2.6%
남 2
 
2.6%
아 2
 
2.6%
앙 2
 
2.6%
변 2
 
2.6%
강 2
 
2.6%
영 2
 
2.6%
수 2
 
2.6%
Other values (27) 36
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 20
26.3%
천 4
 
5.3%
중 2
 
2.6%
남 2
 
2.6%
아 2
 
2.6%
앙 2
 
2.6%
변 2
 
2.6%
강 2
 
2.6%
영 2
 
2.6%
수 2
 
2.6%
Other values (27) 36
47.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 20
26.3%
천 4
 
5.3%
중 2
 
2.6%
남 2
 
2.6%
아 2
 
2.6%
앙 2
 
2.6%
변 2
 
2.6%
강 2
 
2.6%
영 2
 
2.6%
수 2
 
2.6%
Other values (27) 36
47.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 20
26.3%
천 4
 
5.3%
중 2
 
2.6%
남 2
 
2.6%
아 2
 
2.6%
앙 2
 
2.6%
변 2
 
2.6%
강 2
 
2.6%
영 2
 
2.6%
수 2
 
2.6%
Other values (27) 36
47.4%

자전거도로의 종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
자전거보행자겸용도로
13 
자전거전용도로
6 
자전거전용도로(자전거연결통로)
 
1
자전거보행자 겸용도로
 
1

Length

Max length16
Median length10
Mean length9.4761905
Min length7

Unique

Unique2 ?
Unique (%)9.5%

Sample

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

Common Values

ValueCountFrequency (%)
자전거보행자겸용도로 13
61.9%
자전거전용도로 6
28.6%
자전거전용도로(자전거연결통로) 1
 
4.8%
자전거보행자 겸용도로 1
 
4.8%

Length

2023-12-13T05:46:52.664376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:46:52.830884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자전거보행자겸용도로 13
59.1%
자전거전용도로 6
27.3%
자전거전용도로(자전거연결통로 1
 
4.5%
자전거보행자 1
 
4.5%
겸용도로 1
 
4.5%

도로관리청
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
부산광역시 동래구청
21 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 동래구청
2nd row부산광역시 동래구청
3rd row부산광역시 동래구청
4th row부산광역시 동래구청
5th row부산광역시 동래구청

Common Values

ValueCountFrequency (%)
부산광역시 동래구청 21
100.0%

Length

2023-12-13T05:46:53.024015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:46:53.185092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 21
50.0%
동래구청 21
50.0%

도로구간(기점)
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T05:46:53.440367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length31
Mean length27.285714
Min length6

Characters and Unicode

Total characters573
Distinct characters68
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

Unique21 ?
Unique (%)100.0%

Sample

1st row부산광역시 동래구 중앙대로1523 (홈플러스 온천점, 온천동 1829-1)
2nd row부산광역시 동래구 충렬대로1324 (온천동 527)
3rd row부산광역시 동래구 중앙대로1520 (온천동 1750-1)
4th row부산광역시 동래구 온천장로1 (온천동 473-13)
5th row부산광역시 동래구 충렬대로157 (온천동1439-6)
ValueCountFrequency (%)
부산광역시 19
19.2%
동래구 19
19.2%
온천동 6
 
6.1%
사직동 5
 
5.1%
경계 2
 
2.0%
안락동 2
 
2.0%
533-217 1
 
1.0%
미남로141 1
 
1.0%
1422-10 1
 
1.0%
미남로28-1 1
 
1.0%
Other values (42) 42
42.4%
2023-12-13T05:46:53.813573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
78
 
13.6%
동 40
 
7.0%
1 30
 
5.2%
구 21
 
3.7%
산 20
 
3.5%
시 20
 
3.5%
부 19
 
3.3%
- 19
 
3.3%
( 19
 
3.3%
) 19
 
3.3%
Other values (58) 288
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 307
53.6%
Decimal Number 130
22.7%
Space Separator 78
 
13.6%
Dash Punctuation 19
 
3.3%
Open Punctuation 19
 
3.3%
Close Punctuation 19
 
3.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 40
 
13.0%
구 21
 
6.8%
산 20
 
6.5%
시 20
 
6.5%
부 19
 
6.2%
래 19
 
6.2%
역 19
 
6.2%
광 19
 
6.2%
로 16
 
5.2%
온 10
 
3.3%
Other values (43) 104
33.9%
Decimal Number
ValueCountFrequency (%)
1 30
23.1%
5 17
13.1%
2 17
13.1%
3 16
12.3%
4 15
11.5%
7 14
10.8%
0 6
 
4.6%
8 5
 
3.8%
6 5
 
3.8%
9 5
 
3.8%
Space Separator
ValueCountFrequency (%)
78
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 307
53.6%
Common 266
46.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 40
 
13.0%
구 21
 
6.8%
산 20
 
6.5%
시 20
 
6.5%
부 19
 
6.2%
래 19
 
6.2%
역 19
 
6.2%
광 19
 
6.2%
로 16
 
5.2%
온 10
 
3.3%
Other values (43) 104
33.9%
Common
ValueCountFrequency (%)
78
29.3%
1 30
 
11.3%
- 19
 
7.1%
( 19
 
7.1%
) 19
 
7.1%
5 17
 
6.4%
2 17
 
6.4%
3 16
 
6.0%
4 15
 
5.6%
7 14
 
5.3%
Other values (5) 22
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 307
53.6%
ASCII 266
46.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
78
29.3%
1 30
 
11.3%
- 19
 
7.1%
( 19
 
7.1%
) 19
 
7.1%
5 17
 
6.4%
2 17
 
6.4%
3 16
 
6.0%
4 15
 
5.6%
7 14
 
5.3%
Other values (5) 22
 
8.3%
Hangul
ValueCountFrequency (%)
동 40
 
13.0%
구 21
 
6.8%
산 20
 
6.5%
시 20
 
6.5%
부 19
 
6.2%
래 19
 
6.2%
역 19
 
6.2%
광 19
 
6.2%
로 16
 
5.2%
온 10
 
3.3%
Other values (43) 104
33.9%

도로구간(종점)
Text

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T05:46:54.031207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length26.285714
Min length3

Characters and Unicode

Total characters552
Distinct characters56
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

Unique17 ?
Unique (%)81.0%

Sample

1st row부산광역시 동래구 충렬대로157-1 (온천동 1439-7)
2nd row부산광역시 동래구 중앙대로1520 (온천동 1750-1)
3rd row부산광역시 동래구 안락교 (안락동 134-2)
4th row부산광역시 동래구 금강로54 (온천동425-24)
5th row부산광역시 동래구 충렬대로85 (온천동1427-3)
ValueCountFrequency (%)
동래구 19
19.8%
부산광역시 19
19.8%
사직동 6
 
6.2%
안락동 4
 
4.2%
온천동 4
 
4.2%
온천천 2
 
2.1%
180-5 2
 
2.1%
수영강 2
 
2.1%
53-4 1
 
1.0%
미남로148 1
 
1.0%
Other values (36) 36
37.5%
2023-12-13T05:46:54.376926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
13.6%
동 38
 
6.9%
1 27
 
4.9%
- 21
 
3.8%
시 21
 
3.8%
구 19
 
3.4%
부 19
 
3.4%
산 19
 
3.4%
광 19
 
3.4%
역 19
 
3.4%
Other values (46) 275
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 292
52.9%
Decimal Number 126
22.8%
Space Separator 75
 
13.6%
Dash Punctuation 21
 
3.8%
Open Punctuation 19
 
3.4%
Close Punctuation 19
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 38
13.0%
시 21
 
7.2%
구 19
 
6.5%
부 19
 
6.5%
산 19
 
6.5%
광 19
 
6.5%
역 19
 
6.5%
래 19
 
6.5%
로 14
 
4.8%
천 12
 
4.1%
Other values (32) 93
31.8%
Decimal Number
ValueCountFrequency (%)
1 27
21.4%
3 19
15.1%
5 14
11.1%
4 14
11.1%
0 12
9.5%
2 12
9.5%
7 10
 
7.9%
8 8
 
6.3%
9 6
 
4.8%
6 4
 
3.2%
Space Separator
ValueCountFrequency (%)
75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 292
52.9%
Common 260
47.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 38
13.0%
시 21
 
7.2%
구 19
 
6.5%
부 19
 
6.5%
산 19
 
6.5%
광 19
 
6.5%
역 19
 
6.5%
래 19
 
6.5%
로 14
 
4.8%
천 12
 
4.1%
Other values (32) 93
31.8%
Common
ValueCountFrequency (%)
75
28.8%
1 27
 
10.4%
- 21
 
8.1%
( 19
 
7.3%
) 19
 
7.3%
3 19
 
7.3%
5 14
 
5.4%
4 14
 
5.4%
0 12
 
4.6%
2 12
 
4.6%
Other values (4) 28
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 292
52.9%
ASCII 260
47.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
28.8%
1 27
 
10.4%
- 21
 
8.1%
( 19
 
7.3%
) 19
 
7.3%
3 19
 
7.3%
5 14
 
5.4%
4 14
 
5.4%
0 12
 
4.6%
2 12
 
4.6%
Other values (4) 28
 
10.8%
Hangul
ValueCountFrequency (%)
동 38
13.0%
시 21
 
7.2%
구 19
 
6.5%
부 19
 
6.5%
산 19
 
6.5%
광 19
 
6.5%
역 19
 
6.5%
래 19
 
6.5%
로 14
 
4.8%
천 12
 
4.1%
Other values (32) 93
31.8%

총길이(㎞)
Real number (ℝ)

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3609524
Minimum0.15
Maximum5.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T05:46:54.486925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.15
5-th percentile0.24
Q10.48
median1.1
Q31.65
95-th percentile3.52
Maximum5.6
Range5.45
Interquartile range (IQR)1.17

Descriptive statistics

Standard deviation1.3237368
Coefficient of variation (CV)0.97265473
Kurtosis4.4218302
Mean1.3609524
Median Absolute Deviation (MAD)0.55
Skewness1.9703272
Sum28.58
Variance1.752279
MonotonicityNot monotonic
2023-12-13T05:46:54.583286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1.65 2
 
9.5%
1.1 2
 
9.5%
0.7 2
 
9.5%
1.28 1
 
4.8%
0.24 1
 
4.8%
0.73 1
 
4.8%
2.35 1
 
4.8%
0.57 1
 
4.8%
3.52 1
 
4.8%
2.94 1
 
4.8%
Other values (8) 8
38.1%
ValueCountFrequency (%)
0.15 1
4.8%
0.24 1
4.8%
0.25 1
4.8%
0.3 1
4.8%
0.47 1
4.8%
0.48 1
4.8%
0.57 1
4.8%
0.7 2
9.5%
0.73 1
4.8%
1.1 2
9.5%
ValueCountFrequency (%)
5.6 1
4.8%
3.52 1
4.8%
2.94 1
4.8%
2.35 1
4.8%
1.65 2
9.5%
1.6 1
4.8%
1.28 1
4.8%
1.2 1
4.8%
1.1 2
9.5%
0.73 1
4.8%

너비(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8809524
Minimum1
Maximum4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T05:46:54.670595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.2
Q11.2
median1.2
Q32.5
95-th percentile3
Maximum4
Range3
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation0.87613871
Coefficient of variation (CV)0.46579527
Kurtosis-0.27290967
Mean1.8809524
Median Absolute Deviation (MAD)0.2
Skewness0.88525999
Sum39.5
Variance0.76761905
MonotonicityNot monotonic
2023-12-13T05:46:54.764369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1.2 10
47.6%
2.5 4
 
19.0%
3.0 3
 
14.3%
1.5 1
 
4.8%
1.0 1
 
4.8%
2.0 1
 
4.8%
4.0 1
 
4.8%
ValueCountFrequency (%)
1.0 1
 
4.8%
1.2 10
47.6%
1.5 1
 
4.8%
2.0 1
 
4.8%
2.5 4
 
19.0%
3.0 3
 
14.3%
4.0 1
 
4.8%
ValueCountFrequency (%)
4.0 1
 
4.8%
3.0 3
 
14.3%
2.5 4
 
19.0%
2.0 1
 
4.8%
1.5 1
 
4.8%
1.2 10
47.6%
1.0 1
 
4.8%

주요경유지
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T05:46:54.913301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.5714286
Min length3

Characters and Unicode

Total characters117
Distinct characters80
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)90.5%

Sample

1st row동래롯데백화점
2nd row도시철도명륜역
3rd row세병교
4th row세븐일레븐
5th row한국건강관리협회
ValueCountFrequency (%)
충렬사 2
 
9.5%
동래롯데백화점 1
 
4.8%
도시철도명륜역 1
 
4.8%
원동ic 1
 
4.8%
수영강 1
 
4.8%
수영환경공원 1
 
4.8%
동래소방서 1
 
4.8%
안락교차로 1
 
4.8%
시내버스57번종점 1
 
4.8%
온천반도보라아파트 1
 
4.8%
Other values (10) 10
47.6%
2023-12-13T05:46:55.219352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 5
 
4.3%
동 4
 
3.4%
원 4
 
3.4%
교 4
 
3.4%
도 3
 
2.6%
세 3
 
2.6%
수 3
 
2.6%
직 3
 
2.6%
병 3
 
2.6%
영 3
 
2.6%
Other values (70) 82
70.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111
94.9%
Decimal Number 4
 
3.4%
Uppercase Letter 2
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 5
 
4.5%
동 4
 
3.6%
원 4
 
3.6%
교 4
 
3.6%
도 3
 
2.7%
세 3
 
2.7%
수 3
 
2.7%
직 3
 
2.7%
병 3
 
2.7%
영 3
 
2.7%
Other values (64) 76
68.5%
Decimal Number
ValueCountFrequency (%)
4 1
25.0%
5 1
25.0%
7 1
25.0%
1 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
I 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111
94.9%
Common 4
 
3.4%
Latin 2
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 5
 
4.5%
동 4
 
3.6%
원 4
 
3.6%
교 4
 
3.6%
도 3
 
2.7%
세 3
 
2.7%
수 3
 
2.7%
직 3
 
2.7%
병 3
 
2.7%
영 3
 
2.7%
Other values (64) 76
68.5%
Common
ValueCountFrequency (%)
4 1
25.0%
5 1
25.0%
7 1
25.0%
1 1
25.0%
Latin
ValueCountFrequency (%)
C 1
50.0%
I 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111
94.9%
ASCII 6
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 5
 
4.5%
동 4
 
3.6%
원 4
 
3.6%
교 4
 
3.6%
도 3
 
2.7%
세 3
 
2.7%
수 3
 
2.7%
직 3
 
2.7%
병 3
 
2.7%
영 3
 
2.7%
Other values (64) 76
68.5%
ASCII
ValueCountFrequency (%)
4 1
16.7%
5 1
16.7%
7 1
16.7%
C 1
16.7%
I 1
16.7%
1 1
16.7%

지정사유(변경, 폐지)
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
지정
20 
폐지
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
지정 20
95.2%
폐지 1
 
4.8%

Length

2023-12-13T05:46:55.326307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:46:55.410480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지정 20
95.2%
폐지 1
 
4.8%

Interactions

2023-12-13T05:46:50.536330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:46:50.322210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:46:50.647166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:46:50.422526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:46:55.477671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선명자전거도로의 종류도로구간(기점)도로구간(종점)총길이(㎞)너비(m)주요경유지지정사유(변경, 폐지)
노선번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
노선명1.0001.0000.8151.0000.9620.8290.9750.9221.000
자전거도로의 종류1.0000.8151.0001.0000.0000.0000.8661.0000.000
도로구간(기점)1.0001.0001.0001.0001.0001.0001.0001.0001.000
도로구간(종점)1.0000.9620.0001.0001.0000.9290.0000.9441.000
총길이(㎞)1.0000.8290.0001.0000.9291.0000.5260.0000.000
너비(m)1.0000.9750.8661.0000.0000.5261.0000.0000.000
주요경유지1.0000.9221.0001.0000.9440.0000.0001.0001.000
지정사유(변경, 폐지)1.0001.0000.0001.0001.0000.0000.0001.0001.000
2023-12-13T05:46:55.828811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정사유(변경, 폐지)자전거도로의 종류
지정사유(변경, 폐지)1.0000.000
자전거도로의 종류0.0001.000
2023-12-13T05:46:55.899095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총길이(㎞)너비(m)자전거도로의 종류지정사유(변경, 폐지)
총길이(㎞)1.000-0.0800.0000.000
너비(m)-0.0801.0000.6860.000
자전거도로의 종류0.0000.6861.0000.000
지정사유(변경, 폐지)0.0000.0000.0001.000

Missing values

2023-12-13T05:46:50.801596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:46:51.004572image/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

노선번호노선명자전거도로의 종류도로관리청도로구간(기점)도로구간(종점)총길이(㎞)너비(m)주요경유지지정사유(변경, 폐지)
0동래-1중앙대로자전거보행자겸용도로부산광역시 동래구청부산광역시 동래구 중앙대로1523 (홈플러스 온천점, 온천동 1829-1)부산광역시 동래구 충렬대로157-1 (온천동 1439-7)1.651.2동래롯데백화점지정
1동래-2중앙대로자전거보행자겸용도로부산광역시 동래구청부산광역시 동래구 충렬대로1324 (온천동 527)부산광역시 동래구 중앙대로1520 (온천동 1750-1)1.651.2도시철도명륜역지정
2동래-3온천천로자전거보행자겸용도로부산광역시 동래구청부산광역시 동래구 중앙대로1520 (온천동 1750-1)부산광역시 동래구 안락교 (안락동 134-2)5.63.0세병교지정
3동래-4읍내길자전거보행자겸용도로부산광역시 동래구청부산광역시 동래구 온천장로1 (온천동 473-13)부산광역시 동래구 금강로54 (온천동425-24)0.31.2세븐일레븐지정
4동래-5만덕로자전거보행자겸용도로부산광역시 동래구청부산광역시 동래구 충렬대로157 (온천동1439-6)부산광역시 동래구 충렬대로85 (온천동1427-3)0.71.2한국건강관리협회지정
5동래-6만덕로자전거보행자겸용도로부산광역시 동래구청부산광역시 동래구 충렬대로96(온천동 1423-10)부산광역시 동래구 중앙대로1307번길 6 (온천동 1440-13)0.71.2으뜸요양병원지정
6동래-7아시아드로자전거보행자겸용도로부산광역시 동래구청부산광역시 동래구 아시아드대로255번길 3 (온천동 1273-17)부산광역시 동래구 아시아드대로10 (사직동 104-13)1.61.5사직1치안센터지정
7동래-8석사로자전거전용도로부산광역시 동래구청부산광역시 동래구 사직로77 (사직동 749-6)부산광역시 동래구 사직사거리 (사직동 788-3)0.472.5사직야구장지정
8동래-9종합운동장로자전거전용도로부산광역시 동래구청부산광역시 동래구 사직사거리 (사직동 788-3)부산광역시 동래구 사직로55-32 (사직동 930-2)0.151.2사직종합운동장지정
9동래-10여고로자전거전용도로부산광역시 동래구청부산광역시 동래구 종합운동장로42 (사직동 102-7)부산광역시 동래구 아시아드대로113 (사직동 104-6)0.252.5세계로병원지정
노선번호노선명자전거도로의 종류도로관리청도로구간(기점)도로구간(종점)총길이(㎞)너비(m)주요경유지지정사유(변경, 폐지)
11동래-12미남로자전거보행자겸용도로부산광역시 동래구청부산광역시 동래구 미남로141 (온천동 1422-10)부산광역시 동래구 미남로27 (사직동 133-9)1.21.2온천반도보라아파트지정
12동래-13미남로자전거보행자겸용도로부산광역시 동래구청부산광역시 동래구 미남로28-1 (사직동 153-7)부산광역시 동래구 미남로148 (온천동 1423-1)1.11.2시내버스57번종점지정
13동래-14충렬로자전거보행자겸용도로부산광역시 동래구청부산광역시 동래구 충렬대로455 (안락동 461-9)부산광역시 동래구 충렬대로171 (명륜동 533-230)2.941.2충렬사지정
14동래-15충렬로자전거보행자겸용도로부산광역시 동래구청부산광역시 동래구 충렬대로174 (명륜동 533-217)부산광역시 동래구 충렬대로506 (안락동 53-4)3.521.2안락교차로지정
15동래-16명륜로자전거보행자겸용도로부산광역시 동래구청부산광역시 동래구 명륜로81 (수안동 3-5)부산광역시 동래구 명륜로29 (수안동 11-37)0.571.0동래소방서폐지
16동래-17반송로자전거보행자겸용도로부산광역시 동래구청부산광역시 동래구 반송로353 (명장동 산65-14)부산광역시 동래구 온천천로345 (낙민동 79-8)2.352.0충렬사지정
17동래-18온천천로자전거전용도로부산광역시 동래구청부산광역시 동래구 안락교 (안락동134-2)부산광역시 동래구 안락동 180-5 (수영강)0.733.0수영환경공원지정
18동래-19삼어로자전거전용도로(자전거연결통로)부산광역시 동래구청부산광역시 동래구 안락동15-45 (안락동 클린센터)부산광역시 동래구 안락동 180-5 (수영강)0.244.0수영강지정
19동래-20수영강변로자전거전용도로부산광역시 동래구청해운대구 경계온천천1.12.5원동IC지정
20동래-21수영강변로자전거보행자 겸용도로부산광역시 동래구청수영구 경계온천천1.283.0수영4호교지정