Overview

Dataset statistics

Number of variables10
Number of observations147
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.2 KiB
Average record size in memory84.9 B

Variable types

Numeric3
Text4
Categorical3

Dataset

Description대전광역시 서구 관내에서 운영중인 폐수배출 시설에 대한 현황정보(업소명, 행정동, 법정동, 상세주소, 사업 종 등)를 제공합니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15104108/fileData.do

Alerts

법정동 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
행정동 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
행정동코드 is highly overall correlated with 법정동코드 and 2 other fieldsHigh correlation
법정동코드 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
종별 is highly imbalanced (88.9%)Imbalance
순번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:14:16.685234
Analysis finished2023-12-12 21:14:18.341090
Duration1.66 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct147
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74
Minimum1
Maximum147
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T06:14:18.405124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.3
Q137.5
median74
Q3110.5
95-th percentile139.7
Maximum147
Range146
Interquartile range (IQR)73

Descriptive statistics

Standard deviation42.579338
Coefficient of variation (CV)0.57539646
Kurtosis-1.2
Mean74
Median Absolute Deviation (MAD)37
Skewness0
Sum10878
Variance1813
MonotonicityStrictly increasing
2023-12-13T06:14:18.546356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
94 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
Other values (137) 137
93.2%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%

업소명
Text

UNIQUE 

Distinct147
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T06:14:18.839085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length8.0612245
Min length2

Characters and Unicode

Total characters1185
Distinct characters261
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)100.0%

Sample

1st row학교법인 건양학원 건양대학교대학병원
2nd row학교법인 을지학원 대전을지대학교병원
3rd row계룡병원
4th row상수도사업본부월평정수사업소
5th row배재대학교
ValueCountFrequency (%)
주식회사 5
 
2.6%
세차장 3
 
1.6%
대전대학교 2
 
1.0%
학교법인 2
 
1.0%
믿음카서비스 1
 
0.5%
도로관리소 1
 
0.5%
씨앤에스유통㈜호수공원주유소 1
 
0.5%
영덴트세차 1
 
0.5%
세븐카 1
 
0.5%
주)월드마스터 1
 
0.5%
Other values (173) 173
90.6%
2023-12-13T06:14:19.229879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44
 
3.7%
차 42
 
3.5%
세 37
 
3.1%
대 36
 
3.0%
주 36
 
3.0%
소 29
 
2.4%
유 29
 
2.4%
전 26
 
2.2%
장 25
 
2.1%
스 22
 
1.9%
Other values (251) 859
72.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1075
90.7%
Space Separator 44
 
3.7%
Uppercase Letter 20
 
1.7%
Other Symbol 14
 
1.2%
Close Punctuation 9
 
0.8%
Open Punctuation 9
 
0.8%
Decimal Number 8
 
0.7%
Other Punctuation 6
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
차 42
 
3.9%
세 37
 
3.4%
대 36
 
3.3%
주 36
 
3.3%
소 29
 
2.7%
유 29
 
2.7%
전 26
 
2.4%
장 25
 
2.3%
스 22
 
2.0%
프 21
 
2.0%
Other values (228) 772
71.8%
Uppercase Letter
ValueCountFrequency (%)
K 2
10.0%
G 2
10.0%
O 2
10.0%
C 2
10.0%
A 2
10.0%
R 2
10.0%
P 2
10.0%
L 2
10.0%
Y 1
5.0%
T 1
5.0%
Other values (2) 2
10.0%
Other Punctuation
ValueCountFrequency (%)
. 3
50.0%
& 1
 
16.7%
/ 1
 
16.7%
· 1
 
16.7%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 3
37.5%
4 1
 
12.5%
Space Separator
ValueCountFrequency (%)
44
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1089
91.9%
Common 76
 
6.4%
Latin 20
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
차 42
 
3.9%
세 37
 
3.4%
대 36
 
3.3%
주 36
 
3.3%
소 29
 
2.7%
유 29
 
2.7%
전 26
 
2.4%
장 25
 
2.3%
스 22
 
2.0%
프 21
 
1.9%
Other values (229) 786
72.2%
Latin
ValueCountFrequency (%)
K 2
10.0%
G 2
10.0%
O 2
10.0%
C 2
10.0%
A 2
10.0%
R 2
10.0%
P 2
10.0%
L 2
10.0%
Y 1
5.0%
T 1
5.0%
Other values (2) 2
10.0%
Common
ValueCountFrequency (%)
44
57.9%
) 9
 
11.8%
( 9
 
11.8%
2 4
 
5.3%
1 3
 
3.9%
. 3
 
3.9%
& 1
 
1.3%
4 1
 
1.3%
/ 1
 
1.3%
· 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1075
90.7%
ASCII 95
 
8.0%
None 15
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
46.3%
) 9
 
9.5%
( 9
 
9.5%
2 4
 
4.2%
1 3
 
3.2%
. 3
 
3.2%
K 2
 
2.1%
G 2
 
2.1%
O 2
 
2.1%
C 2
 
2.1%
Other values (11) 15
 
15.8%
Hangul
ValueCountFrequency (%)
차 42
 
3.9%
세 37
 
3.4%
대 36
 
3.3%
주 36
 
3.3%
소 29
 
2.7%
유 29
 
2.7%
전 26
 
2.4%
장 25
 
2.3%
스 22
 
2.0%
프 21
 
2.0%
Other values (228) 772
71.8%
None
ValueCountFrequency (%)
㈜ 14
93.3%
· 1
 
6.7%

행정동
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
변동
15 
탄방동
14 
월평1동
14 
정림동
13 
둔산2동
11 
Other values (18)
80 

Length

Max length4
Median length3
Mean length3.3333333
Min length2

Unique

Unique4 ?
Unique (%)2.7%

Sample

1st row관저1동
2nd row둔산2동
3rd row갈마2동
4th row갈마1동
5th row도마2동

Common Values

ValueCountFrequency (%)
변동 15
 
10.2%
탄방동 14
 
9.5%
월평1동 14
 
9.5%
정림동 13
 
8.8%
둔산2동 11
 
7.5%
괴정동 9
 
6.1%
갈마1동 8
 
5.4%
도마2동 8
 
5.4%
가수원동 8
 
5.4%
용문동 7
 
4.8%
Other values (13) 40
27.2%

Length

2023-12-13T06:14:19.388281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
변동 15
 
10.2%
탄방동 14
 
9.5%
월평1동 14
 
9.5%
정림동 13
 
8.8%
둔산2동 11
 
7.5%
괴정동 9
 
6.1%
갈마1동 8
 
5.4%
도마2동 8
 
5.4%
가수원동 8
 
5.4%
용문동 7
 
4.8%
Other values (13) 40
27.2%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170568 × 109
Minimum3.017051 × 109
Maximum3.017065 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T06:14:19.519000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017051 × 109
5-th percentile3.017052 × 109
Q13.017054 × 109
median3.017056 × 109
Q33.0170586 × 109
95-th percentile3.017064 × 109
Maximum3.017065 × 109
Range14000
Interquartile range (IQR)4600

Descriptive statistics

Standard deviation3438.1682
Coefficient of variation (CV)1.1395769 × 10-6
Kurtosis-0.05624196
Mean3.0170568 × 109
Median Absolute Deviation (MAD)2500
Skewness0.65193104
Sum4.4350734 × 1011
Variance11821001
MonotonicityNot monotonic
2023-12-13T06:14:19.627805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
3017054000 15
 
10.2%
3017055500 14
 
9.5%
3017058600 14
 
9.5%
3017053500 13
 
8.8%
3017064000 11
 
7.5%
3017056000 9
 
6.1%
3017059000 9
 
6.1%
3017058100 8
 
5.4%
3017053000 8
 
5.4%
3017055000 7
 
4.8%
Other values (11) 39
26.5%
ValueCountFrequency (%)
3017051000 4
 
2.7%
3017052000 7
4.8%
3017053000 8
5.4%
3017053500 13
8.8%
3017054000 15
10.2%
3017055000 7
4.8%
3017055500 14
9.5%
3017056000 9
6.1%
3017057000 6
 
4.1%
3017057500 4
 
2.7%
ValueCountFrequency (%)
3017065000 3
 
2.0%
3017064000 11
7.5%
3017063000 1
 
0.7%
3017060000 2
 
1.4%
3017059700 3
 
2.0%
3017059600 4
 
2.7%
3017059000 9
6.1%
3017058700 1
 
0.7%
3017058600 14
9.5%
3017058200 4
 
2.7%

법정동
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
변동
15 
도마동
15 
월평동
15 
탄방동
14 
정림동
13 
Other values (13)
75 

Length

Max length4
Median length3
Mean length2.8911565
Min length2

Unique

Unique2 ?
Unique (%)1.4%

Sample

1st row관저동
2nd row둔산동
3rd row갈마동
4th row갈마동
5th row도마동

Common Values

ValueCountFrequency (%)
변동 15
10.2%
도마동 15
10.2%
월평동 15
10.2%
탄방동 14
9.5%
정림동 13
8.8%
갈마동 12
8.2%
둔산동 12
8.2%
괴정동 9
 
6.1%
용문동 7
 
4.8%
관저동 7
 
4.8%
Other values (8) 28
19.0%

Length

2023-12-13T06:14:19.751808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
변동 15
10.2%
도마동 15
10.2%
월평동 15
10.2%
탄방동 14
9.5%
정림동 13
8.8%
갈마동 12
8.2%
둔산동 12
8.2%
괴정동 9
 
6.1%
관저동 7
 
4.8%
용문동 7
 
4.8%
Other values (8) 28
19.0%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170109 × 109
Minimum3.0170101 × 109
Maximum3.0170128 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T06:14:20.179441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0170101 × 109
5-th percentile3.0170102 × 109
Q13.0170104 × 109
median3.0170108 × 109
Q33.0170112 × 109
95-th percentile3.0170116 × 109
Maximum3.0170128 × 109
Range2700
Interquartile range (IQR)800

Descriptive statistics

Standard deviation558.0136
Coefficient of variation (CV)1.8495578 × 10-7
Kurtosis1.4137374
Mean3.0170109 × 109
Median Absolute Deviation (MAD)400
Skewness0.95672077
Sum4.435006 × 1011
Variance311379.18
MonotonicityNot monotonic
2023-12-13T06:14:20.290969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
3017010200 15
10.2%
3017010300 15
10.2%
3017011300 15
10.2%
3017010600 14
9.5%
3017010400 13
8.8%
3017011100 12
8.2%
3017011200 12
8.2%
3017010800 9
 
6.1%
3017011600 7
 
4.8%
3017010500 7
 
4.8%
Other values (8) 28
19.0%
ValueCountFrequency (%)
3017010100 4
 
2.7%
3017010200 15
10.2%
3017010300 15
10.2%
3017010400 13
8.8%
3017010500 7
4.8%
3017010600 14
9.5%
3017010800 9
6.1%
3017010900 6
 
4.1%
3017011000 4
 
2.7%
3017011100 12
8.2%
ValueCountFrequency (%)
3017012800 3
 
2.0%
3017012300 1
 
0.7%
3017012200 1
 
0.7%
3017011600 7
4.8%
3017011500 5
 
3.4%
3017011400 4
 
2.7%
3017011300 15
10.2%
3017011200 12
8.2%
3017011100 12
8.2%
3017011000 4
 
2.7%

지번주소
Text

Distinct143
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T06:14:20.645693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length17.469388
Min length15

Characters and Unicode

Total characters2568
Distinct characters55
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

Unique140 ?
Unique (%)95.2%

Sample

1st row대전광역시 서구 관저동 1643
2nd row대전광역시 서구 둔산동 1306
3rd row대전광역시 서구 갈마동 362-1
4th row대전광역시 서구 갈마동 425-16
5th row대전광역시 서구 도마동 439-6
ValueCountFrequency (%)
대전광역시 147
25.0%
서구 147
25.0%
월평동 15
 
2.5%
변동 15
 
2.5%
도마동 15
 
2.5%
탄방동 14
 
2.4%
정림동 13
 
2.2%
갈마동 12
 
2.0%
둔산동 12
 
2.0%
괴정동 9
 
1.5%
Other values (153) 190
32.3%
2023-12-13T06:14:21.169249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
442
17.2%
동 148
 
5.8%
대 147
 
5.7%
광 147
 
5.7%
역 147
 
5.7%
시 147
 
5.7%
서 147
 
5.7%
구 147
 
5.7%
전 147
 
5.7%
1 128
 
5.0%
Other values (45) 821
32.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1460
56.9%
Decimal Number 559
 
21.8%
Space Separator 442
 
17.2%
Dash Punctuation 104
 
4.0%
Other Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 148
10.1%
대 147
10.1%
광 147
10.1%
역 147
10.1%
시 147
10.1%
서 147
10.1%
구 147
10.1%
전 147
10.1%
마 27
 
1.8%
정 22
 
1.5%
Other values (30) 234
16.0%
Decimal Number
ValueCountFrequency (%)
1 128
22.9%
2 73
13.1%
4 55
9.8%
3 54
9.7%
6 53
9.5%
5 50
 
8.9%
7 41
 
7.3%
9 37
 
6.6%
8 36
 
6.4%
0 32
 
5.7%
Space Separator
ValueCountFrequency (%)
442
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1460
56.9%
Common 1108
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 148
10.1%
대 147
10.1%
광 147
10.1%
역 147
10.1%
시 147
10.1%
서 147
10.1%
구 147
10.1%
전 147
10.1%
마 27
 
1.8%
정 22
 
1.5%
Other values (30) 234
16.0%
Common
ValueCountFrequency (%)
442
39.9%
1 128
 
11.6%
- 104
 
9.4%
2 73
 
6.6%
4 55
 
5.0%
3 54
 
4.9%
6 53
 
4.8%
5 50
 
4.5%
7 41
 
3.7%
9 37
 
3.3%
Other values (5) 71
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1460
56.9%
ASCII 1108
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
442
39.9%
1 128
 
11.6%
- 104
 
9.4%
2 73
 
6.6%
4 55
 
5.0%
3 54
 
4.9%
6 53
 
4.8%
5 50
 
4.5%
7 41
 
3.7%
9 37
 
3.3%
Other values (5) 71
 
6.4%
Hangul
ValueCountFrequency (%)
동 148
10.1%
대 147
10.1%
광 147
10.1%
역 147
10.1%
시 147
10.1%
서 147
10.1%
구 147
10.1%
전 147
10.1%
마 27
 
1.8%
정 22
 
1.5%
Other values (30) 234
16.0%

도로명주소
Text

Distinct143
Distinct (%)97.9%
Missing1
Missing (%)0.7%
Memory size1.3 KiB
2023-12-13T06:14:21.464897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length21.958904
Min length15

Characters and Unicode

Total characters3206
Distinct characters83
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

Unique141 ?
Unique (%)96.6%

Sample

1st row대전광역시 서구 관저동로 158(관저동)
2nd row대전광역시 서구 둔산서로 95(둔산동)
3rd row대전광역시 서구 갈마로 45(갈마동)
4th row대전광역시 서구 신갈마로141번길 83(갈마동)
5th row대전광역시 서구 배재로 155-40(도마동)
ValueCountFrequency (%)
대전광역시 146
24.9%
서구 146
24.9%
계백로 13
 
2.2%
도산로 12
 
2.0%
갈마로 10
 
1.7%
계룡로232번길 7
 
1.2%
도솔로 7
 
1.2%
괴정로 6
 
1.0%
배재로 6
 
1.0%
동서대로 5
 
0.9%
Other values (194) 228
38.9%
2023-12-13T06:14:21.919644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
441
 
13.8%
대 169
 
5.3%
동 157
 
4.9%
서 153
 
4.8%
구 147
 
4.6%
광 146
 
4.6%
역 146
 
4.6%
시 146
 
4.6%
전 146
 
4.6%
로 141
 
4.4%
Other values (73) 1414
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1973
61.5%
Decimal Number 504
 
15.7%
Space Separator 441
 
13.8%
Open Punctuation 136
 
4.2%
Close Punctuation 136
 
4.2%
Dash Punctuation 14
 
0.4%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 169
 
8.6%
동 157
 
8.0%
서 153
 
7.8%
구 147
 
7.5%
광 146
 
7.4%
역 146
 
7.4%
시 146
 
7.4%
전 146
 
7.4%
로 141
 
7.1%
도 47
 
2.4%
Other values (58) 575
29.1%
Decimal Number
ValueCountFrequency (%)
1 109
21.6%
2 78
15.5%
4 61
12.1%
3 49
9.7%
8 48
9.5%
7 37
 
7.3%
5 36
 
7.1%
0 30
 
6.0%
6 30
 
6.0%
9 26
 
5.2%
Space Separator
ValueCountFrequency (%)
441
100.0%
Open Punctuation
ValueCountFrequency (%)
( 136
100.0%
Close Punctuation
ValueCountFrequency (%)
) 136
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1973
61.5%
Common 1233
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 169
 
8.6%
동 157
 
8.0%
서 153
 
7.8%
구 147
 
7.5%
광 146
 
7.4%
역 146
 
7.4%
시 146
 
7.4%
전 146
 
7.4%
로 141
 
7.1%
도 47
 
2.4%
Other values (58) 575
29.1%
Common
ValueCountFrequency (%)
441
35.8%
( 136
 
11.0%
) 136
 
11.0%
1 109
 
8.8%
2 78
 
6.3%
4 61
 
4.9%
3 49
 
4.0%
8 48
 
3.9%
7 37
 
3.0%
5 36
 
2.9%
Other values (5) 102
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1973
61.5%
ASCII 1233
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
441
35.8%
( 136
 
11.0%
) 136
 
11.0%
1 109
 
8.8%
2 78
 
6.3%
4 61
 
4.9%
3 49
 
4.0%
8 48
 
3.9%
7 37
 
3.0%
5 36
 
2.9%
Other values (5) 102
 
8.3%
Hangul
ValueCountFrequency (%)
대 169
 
8.6%
동 157
 
8.0%
서 153
 
7.8%
구 147
 
7.5%
광 146
 
7.4%
역 146
 
7.4%
시 146
 
7.4%
전 146
 
7.4%
로 141
 
7.1%
도 47
 
2.4%
Other values (58) 575
29.1%

상세주소
Text

Distinct145
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T06:14:22.236369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length25
Mean length13.482993
Min length8

Characters and Unicode

Total characters1982
Distinct characters89
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

Unique144 ?
Unique (%)98.0%

Sample

1st row관저동로 158(관저동)
2nd row둔산서로 95(둔산동)
3rd row갈마로 45(갈마동)
4th row신갈마로141번길 82(월평동)
5th row배재로 155-40(도마동)
ValueCountFrequency (%)
도산로 12
 
4.0%
계백로 12
 
4.0%
갈마로 10
 
3.3%
계룡로232번길 7
 
2.3%
도솔로 7
 
2.3%
계룡로 6
 
2.0%
괴정로 6
 
2.0%
배재로 6
 
2.0%
유등로 4
 
1.3%
동서대로 4
 
1.3%
Other values (201) 229
75.6%
2023-12-13T06:14:22.704029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 166
 
8.4%
158
 
8.0%
) 143
 
7.2%
( 143
 
7.2%
로 139
 
7.0%
1 112
 
5.7%
2 81
 
4.1%
4 62
 
3.1%
3 56
 
2.8%
8 48
 
2.4%
Other values (79) 874
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 994
50.2%
Decimal Number 523
26.4%
Space Separator 158
 
8.0%
Close Punctuation 143
 
7.2%
Open Punctuation 143
 
7.2%
Dash Punctuation 17
 
0.9%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 166
16.7%
로 139
 
14.0%
도 48
 
4.8%
마 43
 
4.3%
길 36
 
3.6%
번 33
 
3.3%
정 32
 
3.2%
산 32
 
3.2%
갈 27
 
2.7%
계 26
 
2.6%
Other values (64) 412
41.4%
Decimal Number
ValueCountFrequency (%)
1 112
21.4%
2 81
15.5%
4 62
11.9%
3 56
10.7%
8 48
9.2%
7 39
 
7.5%
5 37
 
7.1%
0 31
 
5.9%
6 30
 
5.7%
9 27
 
5.2%
Space Separator
ValueCountFrequency (%)
158
100.0%
Close Punctuation
ValueCountFrequency (%)
) 143
100.0%
Open Punctuation
ValueCountFrequency (%)
( 143
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 994
50.2%
Common 988
49.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 166
16.7%
로 139
 
14.0%
도 48
 
4.8%
마 43
 
4.3%
길 36
 
3.6%
번 33
 
3.3%
정 32
 
3.2%
산 32
 
3.2%
갈 27
 
2.7%
계 26
 
2.6%
Other values (64) 412
41.4%
Common
ValueCountFrequency (%)
158
16.0%
) 143
14.5%
( 143
14.5%
1 112
11.3%
2 81
8.2%
4 62
 
6.3%
3 56
 
5.7%
8 48
 
4.9%
7 39
 
3.9%
5 37
 
3.7%
Other values (5) 109
11.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 994
50.2%
ASCII 988
49.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 166
16.7%
로 139
 
14.0%
도 48
 
4.8%
마 43
 
4.3%
길 36
 
3.6%
번 33
 
3.3%
정 32
 
3.2%
산 32
 
3.2%
갈 27
 
2.7%
계 26
 
2.6%
Other values (64) 412
41.4%
ASCII
ValueCountFrequency (%)
158
16.0%
) 143
14.5%
( 143
14.5%
1 112
11.3%
2 81
8.2%
4 62
 
6.3%
3 56
 
5.7%
8 48
 
4.9%
7 39
 
3.9%
5 37
 
3.7%
Other values (5) 109
11.0%

종별
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
5
143 
3
 
2
4
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)1.4%

Sample

1st row3
2nd row4
3rd row5
4th row2
5th row5

Common Values

ValueCountFrequency (%)
5 143
97.3%
3 2
 
1.4%
4 1
 
0.7%
2 1
 
0.7%

Length

2023-12-13T06:14:22.849458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:14:22.975475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 143
97.3%
3 2
 
1.4%
4 1
 
0.7%
2 1
 
0.7%

Interactions

2023-12-13T06:14:17.813800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:17.240669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:17.553064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:17.917071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:17.384964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:17.645013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:18.005364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:17.470945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:17.727156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:14:23.064028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동행정동코드법정동법정동코드종별
순번1.0000.4230.2880.3040.0000.246
행정동0.4231.0001.0000.9940.9820.390
행정동코드0.2881.0001.0000.9740.9130.325
법정동0.3040.9940.9741.0001.0000.603
법정동코드0.0000.9820.9131.0001.0000.564
종별0.2460.3900.3250.6030.5641.000
2023-12-13T06:14:23.182606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종별법정동행정동
종별1.0000.3550.200
법정동0.3551.0000.914
행정동0.2000.9141.000
2023-12-13T06:14:23.318758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동코드법정동코드행정동법정동종별
순번1.000-0.136-0.0540.1690.1250.144
행정동코드-0.1361.0000.9310.9480.8580.213
법정동코드-0.0540.9311.0000.8580.9670.392
행정동0.1690.9480.8581.0000.9140.200
법정동0.1250.8580.9670.9141.0000.355
종별0.1440.2130.3920.2000.3551.000

Missing values

2023-12-13T06:14:18.129949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:14:18.291947image/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

순번업소명행정동행정동코드법정동법정동코드지번주소도로명주소상세주소종별
01학교법인 건양학원 건양대학교대학병원관저1동3017059600관저동3017011600대전광역시 서구 관저동 1643대전광역시 서구 관저동로 158(관저동)관저동로 158(관저동)3
12학교법인 을지학원 대전을지대학교병원둔산2동3017064000둔산동3017011200대전광역시 서구 둔산동 1306대전광역시 서구 둔산서로 95(둔산동)둔산서로 95(둔산동)4
23계룡병원갈마2동3017058200갈마동3017011100대전광역시 서구 갈마동 362-1대전광역시 서구 갈마로 45(갈마동)갈마로 45(갈마동)5
34상수도사업본부월평정수사업소갈마1동3017058100갈마동3017011100대전광역시 서구 갈마동 425-16대전광역시 서구 신갈마로141번길 83(갈마동)신갈마로141번길 82(월평동)2
45배재대학교도마2동3017053000도마동3017010300대전광역시 서구 도마동 439-6대전광역시 서구 배재로 155-40(도마동)배재로 155-40(도마동)5
56대청병원정림동3017053500정림동3017010400대전광역시 서구 정림동 716대전광역시 서구 계백로 1322계백로 13225
67삼성산업사용문동3017055000용문동3017010500대전광역시 서구 용문동 224-14대전광역시 서구 도솔로 530(용문동)도솔로 530(용문동)5
78한국건강관리협회(대전.충남지부)탄방동3017055500탄방동3017010600대전광역시 서구 탄방동 90-8대전광역시 서구 계룡로 611(탄방동)계룡로 611(탄방동)5
89대전대학교 대전한방병원둔산2동3017064000둔산동3017011200대전광역시 서구 둔산동 1136대전광역시 서구 대덕대로176번길 75(둔산동)대덕대로176번길 75(둔산동)5
910㈜맥키스컴퍼니기성동3017060000오동3017012200대전광역시 서구 오동 276대전광역시 서구 영골길 158 (오동)영골길 158 (오동)3
순번업소명행정동행정동코드법정동법정동코드지번주소도로명주소상세주소종별
137138차굿간만년동3017065000만년동3017012800대전광역시 서구 만년동 392대전광역시 서구 둔산대로117번길 88(만년동)둔산대로117번길 88(만년동)5
138139명카워시가장동3017057000가장동3017010900대전광역시 서구 가장동 42-9대전광역시 서구 갈마로 293(가장동)갈마로 293(가장동)5
139140아우토클래스정림동3017053500정림동3017010400대전광역시 서구 정림동 13-7대전광역시 서구 계백로 1294정림동 13-30외1필지(정림동 13-7)5
140141으랏차차센트럴세차장정림동3017053500정림동3017010400대전광역시 서구 정림동 582-1대전광역시 서구 정림서로 208정림서로 208(정림동)5
141142주식회사 제이디워시가장동3017057000가장동3017010900대전광역시 서구 가장동 30-12대전광역시 서구 갈마로 321갈마로 321(가장동)5
142143용문세차장용문동3017055000용문동3017010500대전광역시 서구 용문동 208-16대전광역시 서구 도산로464도산로464(용문동)5
143144서대전서비스 기아오토큐㈜도안동3017059000도안동3017011500대전광역시 서구 도안동 2065대전광역시 서구 도안동로12번길 26도안동로12번길 26(도안동)5
144145자자워쉬&디테일링가이드관저동3017059700관저동3017011600대전광역시 서구 관저동 1749대전광역시 서구 봉우로8번길8관저동 17495
145146세차의 고수(대전 서구점)가장동3017057000가장동3017010900대전광역시 서구 가장동 21-5대전광역시 서구 유등로 445유등로 445(가장동)5
146147디케이워시 내동점내동3017057500내동3017011000대전광역시 서구 내동 218-4대전광역시 서구 내동 218-4번지내동 218-4번지5