Overview

Dataset statistics

Number of variables11
Number of observations32
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory97.1 B

Variable types

Numeric4
Text6
Categorical1

Dataset

Description대전광역시 서구 공공기관 장애인 전용주차 면수 현황입니다.(순번, 시설, 주소, 지번주소, 도로명주소, 행정동명, 행정동코드, 법정동명, 법정동코드, 장애인주차구역수, 전체주차장대수)
URLhttps://www.data.go.kr/data/15104510/fileData.do

Alerts

순번 is highly overall correlated with 법정동코드High correlation
행정동코드 is highly overall correlated with 법정동코드High correlation
법정동코드 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
전체주차장대수 is highly overall correlated with 장애인주차구역수High correlation
장애인주차구역수 is highly overall correlated with 전체주차장대수High correlation
순번 has unique valuesUnique
시설 has unique valuesUnique
주소 has unique valuesUnique
지번주소 has unique valuesUnique
도로명주소 has unique valuesUnique
전체주차장대수 has 1 (3.1%) zerosZeros

Reproduction

Analysis started2023-12-12 01:04:13.314003
Analysis finished2023-12-12 01:04:16.063023
Duration2.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.5
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T10:04:16.142761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.55
Q18.75
median16.5
Q324.25
95-th percentile30.45
Maximum32
Range31
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation9.3808315
Coefficient of variation (CV)0.56853524
Kurtosis-1.2
Mean16.5
Median Absolute Deviation (MAD)8
Skewness0
Sum528
Variance88
MonotonicityStrictly increasing
2023-12-12T10:04:16.311382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 1
 
3.1%
18 1
 
3.1%
32 1
 
3.1%
31 1
 
3.1%
30 1
 
3.1%
29 1
 
3.1%
28 1
 
3.1%
27 1
 
3.1%
26 1
 
3.1%
25 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
1 1
3.1%
2 1
3.1%
3 1
3.1%
4 1
3.1%
5 1
3.1%
6 1
3.1%
7 1
3.1%
8 1
3.1%
9 1
3.1%
10 1
3.1%
ValueCountFrequency (%)
32 1
3.1%
31 1
3.1%
30 1
3.1%
29 1
3.1%
28 1
3.1%
27 1
3.1%
26 1
3.1%
25 1
3.1%
24 1
3.1%
23 1
3.1%

시설
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-12T10:04:16.549921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length3.90625
Min length2

Characters and Unicode

Total characters125
Distinct characters45
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

Unique32 ?
Unique (%)100.0%

Sample

1st row서구청
2nd row복수동
3rd row도마1동
4th row도마2동
5th row정림동
ValueCountFrequency (%)
정림동 2
 
6.1%
서구청 1
 
3.0%
월평2동 1
 
3.0%
어린이도서관 1
 
3.0%
갈마도서관 1
 
3.0%
가수원도서관 1
 
3.0%
둔산도서관 1
 
3.0%
평생학습원 1
 
3.0%
보건소 1
 
3.0%
도안동 1
 
3.0%
Other values (22) 22
66.7%
2023-12-12T10:04:16.942970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 25
20.0%
도 8
 
6.4%
관 7
 
5.6%
서 6
 
4.8%
마 5
 
4.0%
1 5
 
4.0%
2 5
 
4.0%
평 5
 
4.0%
둔 4
 
3.2%
산 4
 
3.2%
Other values (35) 51
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 112
89.6%
Decimal Number 12
 
9.6%
Space Separator 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 25
22.3%
도 8
 
7.1%
관 7
 
6.2%
서 6
 
5.4%
마 5
 
4.5%
평 5
 
4.5%
둔 4
 
3.6%
산 4
 
3.6%
월 4
 
3.6%
원 3
 
2.7%
Other values (31) 41
36.6%
Decimal Number
ValueCountFrequency (%)
1 5
41.7%
2 5
41.7%
3 2
 
16.7%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 112
89.6%
Common 13
 
10.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 25
22.3%
도 8
 
7.1%
관 7
 
6.2%
서 6
 
5.4%
마 5
 
4.5%
평 5
 
4.5%
둔 4
 
3.6%
산 4
 
3.6%
월 4
 
3.6%
원 3
 
2.7%
Other values (31) 41
36.6%
Common
ValueCountFrequency (%)
1 5
38.5%
2 5
38.5%
3 2
 
15.4%
1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 112
89.6%
ASCII 13
 
10.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 25
22.3%
도 8
 
7.1%
관 7
 
6.2%
서 6
 
5.4%
마 5
 
4.5%
평 5
 
4.5%
둔 4
 
3.6%
산 4
 
3.6%
월 4
 
3.6%
원 3
 
2.7%
Other values (31) 41
36.6%
ASCII
ValueCountFrequency (%)
1 5
38.5%
2 5
38.5%
3 2
 
15.4%
1
 
7.7%

주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-12T10:04:17.227376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.90625
Min length6

Characters and Unicode

Total characters253
Distinct characters52
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

Unique32 ?
Unique (%)100.0%

Sample

1st row둔산서로 100
2nd row복수동로 49
3rd row도마3길 46
4th row도림1길 14
5th row정림동로 10
ValueCountFrequency (%)
둔산서로 2
 
3.1%
갈마역로 2
 
3.1%
청사로 2
 
3.1%
만년로 2
 
3.1%
정림동로 2
 
3.1%
가수원로 2
 
3.1%
82 1
 
1.6%
13 1
 
1.6%
145 1
 
1.6%
27-9 1
 
1.6%
Other values (48) 48
75.0%
2023-12-12T10:04:17.684937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
 
12.6%
로 27
 
10.7%
1 20
 
7.9%
2 14
 
5.5%
5 12
 
4.7%
3 11
 
4.3%
4 9
 
3.6%
길 8
 
3.2%
7 8
 
3.2%
9 6
 
2.4%
Other values (42) 106
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 122
48.2%
Decimal Number 95
37.5%
Space Separator 32
 
12.6%
Dash Punctuation 4
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 27
22.1%
길 8
 
6.6%
마 5
 
4.1%
가 4
 
3.3%
산 4
 
3.3%
갈 4
 
3.3%
번 4
 
3.3%
둔 4
 
3.3%
도 4
 
3.3%
동 4
 
3.3%
Other values (30) 54
44.3%
Decimal Number
ValueCountFrequency (%)
1 20
21.1%
2 14
14.7%
5 12
12.6%
3 11
11.6%
4 9
9.5%
7 8
 
8.4%
9 6
 
6.3%
0 6
 
6.3%
6 6
 
6.3%
8 3
 
3.2%
Space Separator
ValueCountFrequency (%)
32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 131
51.8%
Hangul 122
48.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 27
22.1%
길 8
 
6.6%
마 5
 
4.1%
가 4
 
3.3%
산 4
 
3.3%
갈 4
 
3.3%
번 4
 
3.3%
둔 4
 
3.3%
도 4
 
3.3%
동 4
 
3.3%
Other values (30) 54
44.3%
Common
ValueCountFrequency (%)
32
24.4%
1 20
15.3%
2 14
10.7%
5 12
 
9.2%
3 11
 
8.4%
4 9
 
6.9%
7 8
 
6.1%
9 6
 
4.6%
0 6
 
4.6%
6 6
 
4.6%
Other values (2) 7
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 131
51.8%
Hangul 122
48.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
24.4%
1 20
15.3%
2 14
10.7%
5 12
 
9.2%
3 11
 
8.4%
4 9
 
6.9%
7 8
 
6.1%
9 6
 
4.6%
0 6
 
4.6%
6 6
 
4.6%
Other values (2) 7
 
5.3%
Hangul
ValueCountFrequency (%)
로 27
22.1%
길 8
 
6.6%
마 5
 
4.1%
가 4
 
3.3%
산 4
 
3.3%
갈 4
 
3.3%
번 4
 
3.3%
둔 4
 
3.3%
도 4
 
3.3%
동 4
 
3.3%
Other values (30) 54
44.3%

지번주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-12T10:04:17.937755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18.5
Mean length17.15625
Min length13

Characters and Unicode

Total characters549
Distinct characters50
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

Unique32 ?
Unique (%)100.0%

Sample

1st row대전광역시 서구 둔산동 1300
2nd row대전광역시 서구 복수동 614
3rd row대전광역시 서구 도마동 132-5
4th row대전광역시 서구 도마동 155-16
5th row대전광역시 서구 정림동 636
ValueCountFrequency (%)
서구 32
25.0%
대전광역시 31
24.2%
둔산동 5
 
3.9%
갈마동 4
 
3.1%
월평동 3
 
2.3%
도마동 2
 
1.6%
정림동 2
 
1.6%
만년동 2
 
1.6%
가수원동 2
 
1.6%
관저동 2
 
1.6%
Other values (42) 43
33.6%
2023-12-12T10:04:18.335077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
17.5%
대 32
 
5.8%
서 32
 
5.8%
구 32
 
5.8%
전 32
 
5.8%
광 31
 
5.6%
역 31
 
5.6%
시 31
 
5.6%
동 31
 
5.6%
1 27
 
4.9%
Other values (40) 174
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 317
57.7%
Decimal Number 120
 
21.9%
Space Separator 96
 
17.5%
Dash Punctuation 16
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 32
10.1%
서 32
10.1%
구 32
10.1%
전 32
10.1%
광 31
9.8%
역 31
9.8%
시 31
9.8%
동 31
9.8%
마 6
 
1.9%
산 5
 
1.6%
Other values (28) 54
17.0%
Decimal Number
ValueCountFrequency (%)
1 27
22.5%
3 14
11.7%
6 13
10.8%
2 13
10.8%
0 13
10.8%
4 10
 
8.3%
8 8
 
6.7%
9 8
 
6.7%
5 8
 
6.7%
7 6
 
5.0%
Space Separator
ValueCountFrequency (%)
96
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 317
57.7%
Common 232
42.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 32
10.1%
서 32
10.1%
구 32
10.1%
전 32
10.1%
광 31
9.8%
역 31
9.8%
시 31
9.8%
동 31
9.8%
마 6
 
1.9%
산 5
 
1.6%
Other values (28) 54
17.0%
Common
ValueCountFrequency (%)
96
41.4%
1 27
 
11.6%
- 16
 
6.9%
3 14
 
6.0%
6 13
 
5.6%
2 13
 
5.6%
0 13
 
5.6%
4 10
 
4.3%
8 8
 
3.4%
9 8
 
3.4%
Other values (2) 14
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 317
57.7%
ASCII 232
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
41.4%
1 27
 
11.6%
- 16
 
6.9%
3 14
 
6.0%
6 13
 
5.6%
2 13
 
5.6%
0 13
 
5.6%
4 10
 
4.3%
8 8
 
3.4%
9 8
 
3.4%
Other values (2) 14
 
6.0%
Hangul
ValueCountFrequency (%)
대 32
10.1%
서 32
10.1%
구 32
10.1%
전 32
10.1%
광 31
9.8%
역 31
9.8%
시 31
9.8%
동 31
9.8%
마 6
 
1.9%
산 5
 
1.6%
Other values (28) 54
17.0%

도로명주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-12T10:04:18.618772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length16.84375
Min length14

Characters and Unicode

Total characters539
Distinct characters58
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

Unique32 ?
Unique (%)100.0%

Sample

1st row대전광역시 서구 둔산서로 100
2nd row대전광역시 서구 복수동로 49
3rd row대전광역시 서구 도마3길 46
4th row대전광역시 서구 도림1길 14
5th row대전광역시 서구 정림동로 10
ValueCountFrequency (%)
서구 32
25.0%
대전광역시 31
24.2%
둔산서로 2
 
1.6%
청사로 2
 
1.6%
만년로 2
 
1.6%
정림동로 2
 
1.6%
가수원로 2
 
1.6%
82 1
 
0.8%
13 1
 
0.8%
갈마역로 1
 
0.8%
Other values (52) 52
40.6%
2023-12-12T10:04:19.099299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
17.8%
대 35
 
6.5%
서 35
 
6.5%
역 32
 
5.9%
구 32
 
5.9%
전 32
 
5.9%
광 31
 
5.8%
시 31
 
5.8%
로 27
 
5.0%
1 20
 
3.7%
Other values (48) 168
31.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 343
63.6%
Space Separator 96
 
17.8%
Decimal Number 96
 
17.8%
Dash Punctuation 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 35
10.2%
서 35
10.2%
역 32
9.3%
구 32
9.3%
전 32
9.3%
광 31
9.0%
시 31
9.0%
로 27
 
7.9%
길 8
 
2.3%
산 4
 
1.2%
Other values (36) 76
22.2%
Decimal Number
ValueCountFrequency (%)
1 20
20.8%
2 13
13.5%
3 11
11.5%
4 10
10.4%
5 10
10.4%
6 8
 
8.3%
7 8
 
8.3%
0 7
 
7.3%
9 6
 
6.2%
8 3
 
3.1%
Space Separator
ValueCountFrequency (%)
96
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 343
63.6%
Common 196
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 35
10.2%
서 35
10.2%
역 32
9.3%
구 32
9.3%
전 32
9.3%
광 31
9.0%
시 31
9.0%
로 27
 
7.9%
길 8
 
2.3%
산 4
 
1.2%
Other values (36) 76
22.2%
Common
ValueCountFrequency (%)
96
49.0%
1 20
 
10.2%
2 13
 
6.6%
3 11
 
5.6%
4 10
 
5.1%
5 10
 
5.1%
6 8
 
4.1%
7 8
 
4.1%
0 7
 
3.6%
9 6
 
3.1%
Other values (2) 7
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 343
63.6%
ASCII 196
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
49.0%
1 20
 
10.2%
2 13
 
6.6%
3 11
 
5.6%
4 10
 
5.1%
5 10
 
5.1%
6 8
 
4.1%
7 8
 
4.1%
0 7
 
3.6%
9 6
 
3.1%
Other values (2) 7
 
3.6%
Hangul
ValueCountFrequency (%)
대 35
10.2%
서 35
10.2%
역 32
9.3%
구 32
9.3%
전 32
9.3%
광 31
9.0%
시 31
9.0%
로 27
 
7.9%
길 8
 
2.3%
산 4
 
1.2%
Other values (36) 76
22.2%

행정동명
Text

Distinct24
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-12T10:04:19.340458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.5
Min length2

Characters and Unicode

Total characters112
Distinct characters32
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

Unique18 ?
Unique (%)56.2%

Sample

1st row둔산2동
2nd row복수동
3rd row도마1동
4th row도마2동
5th row정림동
ValueCountFrequency (%)
둔산2동 3
 
9.4%
갈마1동 3
 
9.4%
정림동 2
 
6.2%
가수원동 2
 
6.2%
탄방동 2
 
6.2%
만년동 2
 
6.2%
복수동 1
 
3.1%
기성동 1
 
3.1%
관저2동 1
 
3.1%
관저1동 1
 
3.1%
Other values (14) 14
43.8%
2023-12-12T10:04:19.710501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 32
28.6%
2 7
 
6.2%
1 7
 
6.2%
마 6
 
5.4%
둔 5
 
4.5%
산 5
 
4.5%
갈 4
 
3.6%
수 3
 
2.7%
도 3
 
2.7%
월 3
 
2.7%
Other values (22) 37
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96
85.7%
Decimal Number 16
 
14.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 32
33.3%
마 6
 
6.2%
둔 5
 
5.2%
산 5
 
5.2%
갈 4
 
4.2%
수 3
 
3.1%
도 3
 
3.1%
월 3
 
3.1%
평 3
 
3.1%
가 3
 
3.1%
Other values (19) 29
30.2%
Decimal Number
ValueCountFrequency (%)
2 7
43.8%
1 7
43.8%
3 2
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96
85.7%
Common 16
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 32
33.3%
마 6
 
6.2%
둔 5
 
5.2%
산 5
 
5.2%
갈 4
 
4.2%
수 3
 
3.1%
도 3
 
3.1%
월 3
 
3.1%
평 3
 
3.1%
가 3
 
3.1%
Other values (19) 29
30.2%
Common
ValueCountFrequency (%)
2 7
43.8%
1 7
43.8%
3 2
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96
85.7%
ASCII 16
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 32
33.3%
마 6
 
6.2%
둔 5
 
5.2%
산 5
 
5.2%
갈 4
 
4.2%
수 3
 
3.1%
도 3
 
3.1%
월 3
 
3.1%
평 3
 
3.1%
가 3
 
3.1%
Other values (19) 29
30.2%
ASCII
ValueCountFrequency (%)
2 7
43.8%
1 7
43.8%
3 2
 
12.5%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170584 × 109
Minimum3.017051 × 109
Maximum3.017066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T10:04:19.871544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017051 × 109
5-th percentile3.0170526 × 109
Q13.0170555 × 109
median3.0170584 × 109
Q33.0170598 × 109
95-th percentile3.017065 × 109
Maximum3.017066 × 109
Range15000
Interquartile range (IQR)4275

Descriptive statistics

Standard deviation4002.6151
Coefficient of variation (CV)1.3266614 × 10-6
Kurtosis-0.58626587
Mean3.0170584 × 109
Median Absolute Deviation (MAD)2650
Skewness0.19756994
Sum9.6545869 × 1010
Variance16020927
MonotonicityNot monotonic
2023-12-12T10:04:20.025177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3017064000 3
 
9.4%
3017058100 3
 
9.4%
3017059000 3
 
9.4%
3017053500 2
 
6.2%
3017055500 2
 
6.2%
3017065000 2
 
6.2%
3017060000 1
 
3.1%
3017059700 1
 
3.1%
3017059600 1
 
3.1%
3017058800 1
 
3.1%
Other values (13) 13
40.6%
ValueCountFrequency (%)
3017051000 1
3.1%
3017052000 1
3.1%
3017053000 1
3.1%
3017053500 2
6.2%
3017054000 1
3.1%
3017055000 1
3.1%
3017055500 2
6.2%
3017056000 1
3.1%
3017057000 1
3.1%
3017057500 1
3.1%
ValueCountFrequency (%)
3017066000 1
 
3.1%
3017065000 2
6.2%
3017064000 3
9.4%
3017063000 1
 
3.1%
3017060000 1
 
3.1%
3017059700 1
 
3.1%
3017059600 1
 
3.1%
3017059000 3
9.4%
3017058800 1
 
3.1%
3017058700 1
 
3.1%

법정동명
Text

Distinct17
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-12T10:04:20.213571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters96
Distinct characters29
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

Unique8 ?
Unique (%)25.0%

Sample

1st row둔산동
2nd row복수동
3rd row도마동
4th row도마동
5th row정림동
ValueCountFrequency (%)
둔산동 5
15.6%
갈마동 4
12.5%
월평동 3
9.4%
관저동 2
 
6.2%
정림동 2
 
6.2%
도마동 2
 
6.2%
만년동 2
 
6.2%
가수원동 2
 
6.2%
탄방동 2
 
6.2%
흑석동 1
 
3.1%
Other values (7) 7
21.9%
2023-12-12T10:04:20.533821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 32
33.3%
마 6
 
6.2%
둔 5
 
5.2%
산 5
 
5.2%
갈 4
 
4.2%
월 3
 
3.1%
평 3
 
3.1%
도 3
 
3.1%
가 3
 
3.1%
수 3
 
3.1%
Other values (19) 29
30.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 32
33.3%
마 6
 
6.2%
둔 5
 
5.2%
산 5
 
5.2%
갈 4
 
4.2%
월 3
 
3.1%
평 3
 
3.1%
도 3
 
3.1%
가 3
 
3.1%
수 3
 
3.1%
Other values (19) 29
30.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 32
33.3%
마 6
 
6.2%
둔 5
 
5.2%
산 5
 
5.2%
갈 4
 
4.2%
월 3
 
3.1%
평 3
 
3.1%
도 3
 
3.1%
가 3
 
3.1%
수 3
 
3.1%
Other values (19) 29
30.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 32
33.3%
마 6
 
6.2%
둔 5
 
5.2%
산 5
 
5.2%
갈 4
 
4.2%
월 3
 
3.1%
평 3
 
3.1%
도 3
 
3.1%
가 3
 
3.1%
수 3
 
3.1%
Other values (19) 29
30.2%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170111 × 109
Minimum3.0170101 × 109
Maximum3.0170128 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T10:04:20.705299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0170101 × 109
5-th percentile3.0170103 × 109
Q13.0170106 × 109
median3.0170112 × 109
Q33.0170113 × 109
95-th percentile3.0170122 × 109
Maximum3.0170128 × 109
Range2700
Interquartile range (IQR)725

Descriptive statistics

Standard deviation627.84835
Coefficient of variation (CV)2.0810276 × 10-7
Kurtosis1.7826791
Mean3.0170111 × 109
Median Absolute Deviation (MAD)300
Skewness0.90340496
Sum9.6544355 × 1010
Variance394193.55
MonotonicityNot monotonic
2023-12-12T10:04:20.896283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
3017011200 5
15.6%
3017011100 4
12.5%
3017011300 3
9.4%
3017010300 2
 
6.2%
3017010400 2
 
6.2%
3017010600 2
 
6.2%
3017011600 2
 
6.2%
3017011400 2
 
6.2%
3017012800 2
 
6.2%
3017011500 1
 
3.1%
Other values (7) 7
21.9%
ValueCountFrequency (%)
3017010100 1
 
3.1%
3017010200 1
 
3.1%
3017010300 2
6.2%
3017010400 2
6.2%
3017010500 1
 
3.1%
3017010600 2
6.2%
3017010800 1
 
3.1%
3017010900 1
 
3.1%
3017011000 1
 
3.1%
3017011100 4
12.5%
ValueCountFrequency (%)
3017012800 2
 
6.2%
3017011700 1
 
3.1%
3017011600 2
 
6.2%
3017011500 1
 
3.1%
3017011400 2
 
6.2%
3017011300 3
9.4%
3017011200 5
15.6%
3017011100 4
12.5%
3017011000 1
 
3.1%
3017010900 1
 
3.1%

장애인주차구역수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size388.0 B
1
17 
0
7 
2
6 
9
 
1
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)6.2%

Sample

1st row9
2nd row2
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 17
53.1%
0 7
21.9%
2 6
 
18.8%
9 1
 
3.1%
5 1
 
3.1%

Length

2023-12-12T10:04:21.046341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:04:21.165918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 17
53.1%
0 7
21.9%
2 6
 
18.8%
9 1
 
3.1%
5 1
 
3.1%

전체주차장대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)59.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.6875
Minimum0
Maximum314
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T10:04:21.271738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.55
Q14
median10.5
Q323
95-th percentile97.75
Maximum314
Range314
Interquartile range (IQR)19

Descriptive statistics

Standard deviation59.399923
Coefficient of variation (CV)2.1453697
Kurtosis18.829606
Mean27.6875
Median Absolute Deviation (MAD)7.5
Skewness4.209901
Sum886
Variance3528.3508
MonotonicityNot monotonic
2023-12-12T10:04:21.384419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
4 4
12.5%
8 3
 
9.4%
3 3
 
9.4%
19 3
 
9.4%
10 2
 
6.2%
23 2
 
6.2%
26 2
 
6.2%
11 2
 
6.2%
5 1
 
3.1%
2 1
 
3.1%
Other values (9) 9
28.1%
ValueCountFrequency (%)
0 1
 
3.1%
2 1
 
3.1%
3 3
9.4%
4 4
12.5%
5 1
 
3.1%
7 1
 
3.1%
8 3
9.4%
10 2
6.2%
11 2
6.2%
18 1
 
3.1%
ValueCountFrequency (%)
314 1
 
3.1%
161 1
 
3.1%
46 1
 
3.1%
36 1
 
3.1%
31 1
 
3.1%
26 2
6.2%
23 2
6.2%
20 1
 
3.1%
19 3
9.4%
18 1
 
3.1%

Interactions

2023-12-12T10:04:15.320675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:13.747632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:14.424044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:14.874527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:15.411722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:13.865239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:14.534315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:14.969452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:15.535503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:13.953971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:14.645668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:15.079315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:15.639303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:14.317544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:14.754640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:04:15.189605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:04:21.486514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시설주소지번주소도로명주소행정동명행정동코드법정동명법정동코드장애인주차구역수전체주차장대수
순번1.0001.0001.0001.0001.0000.6890.7330.8320.8110.5890.000
시설1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
행정동명0.6891.0001.0001.0001.0001.0001.0001.0001.0000.0000.000
행정동코드0.7331.0001.0001.0001.0001.0001.0000.9150.9070.0000.092
법정동명0.8321.0001.0001.0001.0001.0000.9151.0001.0000.0000.000
법정동코드0.8111.0001.0001.0001.0001.0000.9071.0001.0000.0000.000
장애인주차구역수0.5891.0001.0001.0001.0000.0000.0000.0000.0001.0000.867
전체주차장대수0.0001.0001.0001.0001.0000.0000.0920.0000.0000.8671.000
2023-12-12T10:04:21.622486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동코드법정동코드전체주차장대수장애인주차구역수
순번1.0000.3320.521-0.0630.237
행정동코드0.3321.0000.8680.3280.097
법정동코드0.5210.8681.0000.3030.000
전체주차장대수-0.0630.3280.3031.0000.837
장애인주차구역수0.2370.0970.0000.8371.000

Missing values

2023-12-12T10:04:15.793284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:04:15.983736image/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

순번시설주소지번주소도로명주소행정동명행정동코드법정동명법정동코드장애인주차구역수전체주차장대수
01서구청둔산서로 100대전광역시 서구 둔산동 1300대전광역시 서구 둔산서로 100둔산2동3017064000둔산동30170112009314
12복수동복수동로 49대전광역시 서구 복수동 614대전광역시 서구 복수동로 49복수동3017051000복수동3017010100231
23도마1동도마3길 46대전광역시 서구 도마동 132-5대전광역시 서구 도마3길 46도마1동3017052000도마동3017010300223
34도마2동도림1길 14대전광역시 서구 도마동 155-16대전광역시 서구 도림1길 14도마2동3017053000도마동301701030017
45정림동정림동로 10대전광역시 서구 정림동 636대전광역시 서구 정림동로 10정림동3017053500정림동301701040018
56변동중반5길 133대전광역시 서구 변동 1-23대전광역시 서구 중반5길 133변동3017054000변동301701020014
67용문동계룡로662번길 6대전광역시 서구 용문동 256-29대전광역시 서구 계룡로662번길 6용문동3017055000용문동301701050000
78탄방동탄방로7번길 97대전광역시 서구 탄방동 1041-1대전광역시 서구 탄방로7번길 97탄방동3017055500탄방동301701060013
89둔산1동둔산중로 65대전광역시 서구 둔산동 1402대전광역시 서구 둔산중로 65둔산1동3017063000둔산동3017011200126
910둔산2동둔산서로 80대전광역시 서구 둔산동 1301대전광역시 서구 둔산서로 80둔산2동3017064000둔산동3017011200123
순번시설주소지번주소도로명주소행정동명행정동코드법정동명법정동코드장애인주차구역수전체주차장대수
2223관저2동관저중로 82대전광역시 서구 관저동 1104대전광역시 서구 관저중로 82관저2동3017059700관저동3017011600236
2324기성동흑석1길 16대전광역시 서구 흑석동 892대전광역시 서구 흑석1길 16기성동3017060000흑석동301701170015
2425도안동원도안로242번길 33대전광역시 서구 도안동 1097대전광역시 서구 원도안로242번길 33도안동3017059000도안동3017011500226
2526보건소만년로 72대전광역시 서구 만년동 340대전광역시 서구 만년로 70만년동3017065000만년동3017012800246
2627평생학습원계룡로 553대전광역시 서구 탄방동 667대전광역시 서구 계룡로 553탄방동3017055500탄방동30170106005161
2728둔산도서관청사로 253대전광역시 서구 둔산동 908-1대전광역시 서구 청사로 253둔산2동3017064000둔산동3017011200118
2829가수원도서관가수원로 91-11대전광역시 서구 가수원동 656-48대전광역시 서구 가수원로 91-11가수원동3017059000가수원동3017011400119
2930갈마도서관신갈마로127번길 138대전광역시 서구 갈마동 427-45대전광역시 서구 신갈마로127번길 138갈마1동3017058100갈마동301701110022
3031정림동 어린이도서관정림동로 25대전광역시 서구 정림동 127-5대전광역시 서구 정림동로 25정림동3017053500정림동301701040003
3132월평도서관갈마역로 55대전 서구 갈마동 820대전 서구 한밭대로 664갈마1동3017058100갈마동301701110003