Overview

Dataset statistics

Number of variables11
Number of observations192
Missing cells44
Missing cells (%)2.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.2 KiB
Average record size in memory91.7 B

Variable types

Numeric3
Categorical4
Text4

Dataset

Description대전광역시 서구 제과점 현황(업종명, 업소명, 지번주소, 도로명주소, 행정동코드, 행정동명, 법정동코드, 법정동명, 전화번호) 데이터입니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15108196/fileData.do

Alerts

업종명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
법정동명 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
행정동명 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
전화번호 has 44 (22.9%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:40:05.755486
Analysis finished2023-12-12 04:40:07.879313
Duration2.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct192
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.5
Minimum1
Maximum192
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T13:40:07.972199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.55
Q148.75
median96.5
Q3144.25
95-th percentile182.45
Maximum192
Range191
Interquartile range (IQR)95.5

Descriptive statistics

Standard deviation55.569776
Coefficient of variation (CV)0.5758526
Kurtosis-1.2
Mean96.5
Median Absolute Deviation (MAD)48
Skewness0
Sum18528
Variance3088
MonotonicityStrictly increasing
2023-12-12T13:40:08.127693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
98 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
Other values (182) 182
94.8%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%
185 1
0.5%
184 1
0.5%
183 1
0.5%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
제과점영업
192 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 192
100.0%

Length

2023-12-12T13:40:08.277614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:40:08.378436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 192
100.0%

업소명
Text

Distinct188
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T13:40:08.646810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length16
Mean length7.9791667
Min length2

Characters and Unicode

Total characters1532
Distinct characters294
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique184 ?
Unique (%)95.8%

Sample

1st row하레하레
2nd row새로나제과
3rd row동원제과
4th row파리바게뜨 도마점
5th row파리바게뜨갈마점
ValueCountFrequency (%)
파리바게뜨 15
 
6.0%
뚜레쥬르 6
 
2.4%
성심당 4
 
1.6%
주주케이크 2
 
0.8%
하레하레 2
 
0.8%
대전 2
 
0.8%
파리바게트 2
 
0.8%
주식회사 2
 
0.8%
싶빵공장 2
 
0.8%
관저원앙점 2
 
0.8%
Other values (208) 211
84.4%
2023-12-12T13:40:09.224219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 83
 
5.4%
리 71
 
4.6%
58
 
3.8%
이 52
 
3.4%
바 43
 
2.8%
파 39
 
2.5%
게 38
 
2.5%
레 36
 
2.3%
뜨 35
 
2.3%
대 28
 
1.8%
Other values (284) 1049
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1325
86.5%
Lowercase Letter 62
 
4.0%
Space Separator 58
 
3.8%
Uppercase Letter 30
 
2.0%
Open Punctuation 20
 
1.3%
Close Punctuation 20
 
1.3%
Decimal Number 15
 
1.0%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 83
 
6.3%
리 71
 
5.4%
이 52
 
3.9%
바 43
 
3.2%
파 39
 
2.9%
게 38
 
2.9%
레 36
 
2.7%
뜨 35
 
2.6%
대 28
 
2.1%
전 24
 
1.8%
Other values (240) 876
66.1%
Lowercase Letter
ValueCountFrequency (%)
a 8
12.9%
e 8
12.9%
t 6
9.7%
n 6
9.7%
o 6
9.7%
u 4
 
6.5%
r 3
 
4.8%
i 3
 
4.8%
c 3
 
4.8%
m 2
 
3.2%
Other values (9) 13
21.0%
Uppercase Letter
ValueCountFrequency (%)
N 4
13.3%
C 4
13.3%
I 3
10.0%
T 2
 
6.7%
E 2
 
6.7%
O 2
 
6.7%
D 2
 
6.7%
K 2
 
6.7%
S 2
 
6.7%
P 1
 
3.3%
Other values (6) 6
20.0%
Decimal Number
ValueCountFrequency (%)
2 9
60.0%
3 3
 
20.0%
1 2
 
13.3%
4 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
58
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1324
86.4%
Common 115
 
7.5%
Latin 92
 
6.0%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 83
 
6.3%
리 71
 
5.4%
이 52
 
3.9%
바 43
 
3.2%
파 39
 
2.9%
게 38
 
2.9%
레 36
 
2.7%
뜨 35
 
2.6%
대 28
 
2.1%
전 24
 
1.8%
Other values (239) 875
66.1%
Latin
ValueCountFrequency (%)
a 8
 
8.7%
e 8
 
8.7%
t 6
 
6.5%
n 6
 
6.5%
o 6
 
6.5%
N 4
 
4.3%
u 4
 
4.3%
C 4
 
4.3%
r 3
 
3.3%
i 3
 
3.3%
Other values (25) 40
43.5%
Common
ValueCountFrequency (%)
58
50.4%
( 20
 
17.4%
) 20
 
17.4%
2 9
 
7.8%
3 3
 
2.6%
1 2
 
1.7%
& 1
 
0.9%
, 1
 
0.9%
4 1
 
0.9%
Han
ValueCountFrequency (%)
樣 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1324
86.4%
ASCII 207
 
13.5%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 83
 
6.3%
리 71
 
5.4%
이 52
 
3.9%
바 43
 
3.2%
파 39
 
2.9%
게 38
 
2.9%
레 36
 
2.7%
뜨 35
 
2.6%
대 28
 
2.1%
전 24
 
1.8%
Other values (239) 875
66.1%
ASCII
ValueCountFrequency (%)
58
28.0%
( 20
 
9.7%
) 20
 
9.7%
2 9
 
4.3%
a 8
 
3.9%
e 8
 
3.9%
t 6
 
2.9%
n 6
 
2.9%
o 6
 
2.9%
N 4
 
1.9%
Other values (34) 62
30.0%
CJK
ValueCountFrequency (%)
樣 1
100.0%

지번주소
Text

Distinct174
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T13:40:09.871922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length28
Mean length17.348958
Min length13

Characters and Unicode

Total characters3331
Distinct characters73
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)85.4%

Sample

1st row대전광역시 서구 둔산동 1509
2nd row대전광역시 서구 변동 47-1
3rd row대전광역시 서구 도마동 134-1
4th row대전광역시 서구 도마동 211
5th row대전광역시 서구 갈마동 386-11
ValueCountFrequency (%)
대전광역시 192
24.8%
서구 192
24.8%
둔산동 45
 
5.8%
도안동 26
 
3.4%
월평동 19
 
2.5%
탄방동 19
 
2.5%
관저동 19
 
2.5%
갈마동 17
 
2.2%
괴정동 13
 
1.7%
도마동 8
 
1.0%
Other values (184) 225
29.0%
2023-12-12T13:40:10.727853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
606
18.2%
대 193
 
5.8%
동 192
 
5.8%
광 192
 
5.8%
역 192
 
5.8%
시 192
 
5.8%
서 192
 
5.8%
구 192
 
5.8%
전 192
 
5.8%
1 168
 
5.0%
Other values (63) 1020
30.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1955
58.7%
Decimal Number 713
 
21.4%
Space Separator 606
 
18.2%
Dash Punctuation 57
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 193
9.9%
동 192
9.8%
광 192
9.8%
역 192
9.8%
시 192
9.8%
서 192
9.8%
구 192
9.8%
전 192
9.8%
산 45
 
2.3%
둔 45
 
2.3%
Other values (51) 328
16.8%
Decimal Number
ValueCountFrequency (%)
1 168
23.6%
2 83
11.6%
3 71
10.0%
0 67
 
9.4%
4 67
 
9.4%
8 67
 
9.4%
5 53
 
7.4%
9 51
 
7.2%
6 49
 
6.9%
7 37
 
5.2%
Space Separator
ValueCountFrequency (%)
606
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1954
58.7%
Common 1376
41.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 193
9.9%
동 192
9.8%
광 192
9.8%
역 192
9.8%
시 192
9.8%
서 192
9.8%
구 192
9.8%
전 192
9.8%
산 45
 
2.3%
둔 45
 
2.3%
Other values (50) 327
16.7%
Common
ValueCountFrequency (%)
606
44.0%
1 168
 
12.2%
2 83
 
6.0%
3 71
 
5.2%
0 67
 
4.9%
4 67
 
4.9%
8 67
 
4.9%
- 57
 
4.1%
5 53
 
3.9%
9 51
 
3.7%
Other values (2) 86
 
6.2%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1954
58.7%
ASCII 1376
41.3%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
606
44.0%
1 168
 
12.2%
2 83
 
6.0%
3 71
 
5.2%
0 67
 
4.9%
4 67
 
4.9%
8 67
 
4.9%
- 57
 
4.1%
5 53
 
3.9%
9 51
 
3.7%
Other values (2) 86
 
6.2%
Hangul
ValueCountFrequency (%)
대 193
9.9%
동 192
9.8%
광 192
9.8%
역 192
9.8%
시 192
9.8%
서 192
9.8%
구 192
9.8%
전 192
9.8%
산 45
 
2.3%
둔 45
 
2.3%
Other values (50) 327
16.7%
CJK
ValueCountFrequency (%)
家 1
100.0%

도로명주소
Text

Distinct185
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T13:40:11.230742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length36.5
Mean length26.4375
Min length15

Characters and Unicode

Total characters5076
Distinct characters172
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique180 ?
Unique (%)93.8%

Sample

1st row대전광역시 서구 둔산로 155, 1,2층
2nd row대전광역시 서구 변동로 66
3rd row대전광역시 서구 도화공원길 28
4th row대전광역시 서구 배재로 155-7
5th row대전광역시 서구 신갈마로127번길 2, 1층
ValueCountFrequency (%)
대전광역시 192
 
17.6%
서구 192
 
17.6%
1층 117
 
10.7%
일부호 42
 
3.8%
일부 15
 
1.4%
계룡로 13
 
1.2%
대덕대로 13
 
1.2%
지하1층 9
 
0.8%
청사로 9
 
0.8%
둔산동 8
 
0.7%
Other values (315) 484
44.2%
2023-12-12T13:40:11.911285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
902
17.8%
1 369
 
7.3%
대 229
 
4.5%
서 199
 
3.9%
역 196
 
3.9%
구 196
 
3.9%
시 193
 
3.8%
전 193
 
3.8%
로 193
 
3.8%
광 192
 
3.8%
Other values (162) 2214
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2879
56.7%
Decimal Number 1025
 
20.2%
Space Separator 902
 
17.8%
Other Punctuation 170
 
3.3%
Dash Punctuation 30
 
0.6%
Open Punctuation 28
 
0.6%
Close Punctuation 28
 
0.6%
Uppercase Letter 10
 
0.2%
Math Symbol 3
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 229
 
8.0%
서 199
 
6.9%
역 196
 
6.8%
구 196
 
6.8%
시 193
 
6.7%
전 193
 
6.7%
로 193
 
6.7%
광 192
 
6.7%
층 140
 
4.9%
호 100
 
3.5%
Other values (137) 1048
36.4%
Decimal Number
ValueCountFrequency (%)
1 369
36.0%
2 112
 
10.9%
0 108
 
10.5%
3 84
 
8.2%
5 79
 
7.7%
6 65
 
6.3%
4 64
 
6.2%
7 60
 
5.9%
8 44
 
4.3%
9 40
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
O 2
20.0%
B 2
20.0%
T 1
10.0%
S 1
10.0%
A 1
10.0%
E 1
10.0%
P 1
10.0%
C 1
10.0%
Space Separator
ValueCountFrequency (%)
902
100.0%
Other Punctuation
ValueCountFrequency (%)
, 170
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2878
56.7%
Common 2186
43.1%
Latin 11
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 229
 
8.0%
서 199
 
6.9%
역 196
 
6.8%
구 196
 
6.8%
시 193
 
6.7%
전 193
 
6.7%
로 193
 
6.7%
광 192
 
6.7%
층 140
 
4.9%
호 100
 
3.5%
Other values (136) 1047
36.4%
Common
ValueCountFrequency (%)
902
41.3%
1 369
16.9%
, 170
 
7.8%
2 112
 
5.1%
0 108
 
4.9%
3 84
 
3.8%
5 79
 
3.6%
6 65
 
3.0%
4 64
 
2.9%
7 60
 
2.7%
Other values (6) 173
 
7.9%
Latin
ValueCountFrequency (%)
O 2
18.2%
B 2
18.2%
T 1
9.1%
S 1
9.1%
A 1
9.1%
E 1
9.1%
P 1
9.1%
C 1
9.1%
Ⅰ 1
9.1%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2878
56.7%
ASCII 2196
43.3%
CJK 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
902
41.1%
1 369
16.8%
, 170
 
7.7%
2 112
 
5.1%
0 108
 
4.9%
3 84
 
3.8%
5 79
 
3.6%
6 65
 
3.0%
4 64
 
2.9%
7 60
 
2.7%
Other values (14) 183
 
8.3%
Hangul
ValueCountFrequency (%)
대 229
 
8.0%
서 199
 
6.9%
역 196
 
6.8%
구 196
 
6.8%
시 193
 
6.7%
전 193
 
6.7%
로 193
 
6.7%
광 192
 
6.7%
층 140
 
4.9%
호 100
 
3.5%
Other values (136) 1047
36.4%
CJK
ValueCountFrequency (%)
家 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.017059 × 109
Minimum3.017051 × 109
Maximum3.017066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T13:40:12.122940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017051 × 109
5-th percentile3.017052 × 109
Q13.017056 × 109
median3.017059 × 109
Q33.0170608 × 109
95-th percentile3.017065 × 109
Maximum3.017066 × 109
Range15000
Interquartile range (IQR)4750

Descriptive statistics

Standard deviation3714.6964
Coefficient of variation (CV)1.2312309 × 10-6
Kurtosis-0.52040325
Mean3.017059 × 109
Median Absolute Deviation (MAD)3000
Skewness0.01704328
Sum5.7927533 × 1011
Variance13798969
MonotonicityNot monotonic
2023-12-12T13:40:12.301343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3017064000 28
14.6%
3017059300 26
13.5%
3017055500 19
9.9%
3017059700 18
9.4%
3017056000 13
 
6.8%
3017058100 12
 
6.2%
3017058700 9
 
4.7%
3017063000 8
 
4.2%
3017052000 8
 
4.2%
3017066000 7
 
3.6%
Other values (14) 44
22.9%
ValueCountFrequency (%)
3017051000 4
 
2.1%
3017052000 8
4.2%
3017053000 2
 
1.0%
3017053500 2
 
1.0%
3017054000 2
 
1.0%
3017055000 4
 
2.1%
3017055500 19
9.9%
3017056000 13
6.8%
3017057000 1
 
0.5%
3017057500 4
 
2.1%
ValueCountFrequency (%)
3017066000 7
 
3.6%
3017065000 5
 
2.6%
3017064000 28
14.6%
3017063000 8
 
4.2%
3017060000 1
 
0.5%
3017059700 18
9.4%
3017059600 1
 
0.5%
3017059300 26
13.5%
3017059000 3
 
1.6%
3017058800 4
 
2.1%

행정동명
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
둔산2동
28 
도안동
26 
탄방동
19 
관저2동
18 
괴정동
13 
Other values (19)
88 

Length

Max length4
Median length4
Mean length3.546875
Min length2

Unique

Unique3 ?
Unique (%)1.6%

Sample

1st row둔산1동
2nd row변동
3rd row도마1동
4th row도마2동
5th row갈마1동

Common Values

ValueCountFrequency (%)
둔산2동 28
14.6%
도안동 26
13.5%
탄방동 19
9.9%
관저2동 18
9.4%
괴정동 13
 
6.8%
갈마1동 12
 
6.2%
월평2동 9
 
4.7%
둔산1동 8
 
4.2%
도마1동 8
 
4.2%
둔산3동 7
 
3.6%
Other values (14) 44
22.9%

Length

2023-12-12T13:40:12.520789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
둔산2동 28
14.6%
도안동 26
13.5%
탄방동 19
9.9%
관저2동 18
9.4%
괴정동 13
 
6.8%
갈마1동 12
 
6.2%
월평2동 9
 
4.7%
둔산1동 8
 
4.2%
도마1동 8
 
4.2%
둔산3동 7
 
3.6%
Other values (14) 44
22.9%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)8.9%
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 size1.8 KiB
2023-12-12T13:40:12.683144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0170101 × 109
5-th percentile3.0170103 × 109
Q13.0170108 × 109
median3.0170112 × 109
Q33.0170115 × 109
95-th percentile3.0170116 × 109
Maximum3.0170128 × 109
Range2700
Interquartile range (IQR)700

Descriptive statistics

Standard deviation489.87763
Coefficient of variation (CV)1.6237183 × 10-7
Kurtosis2.0470665
Mean3.0170111 × 109
Median Absolute Deviation (MAD)300
Skewness0.44717646
Sum5.7926614 × 1011
Variance239980.09
MonotonicityNot monotonic
2023-12-12T13:40:12.875116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
3017011200 43
22.4%
3017011500 26
13.5%
3017011600 19
9.9%
3017011300 19
9.9%
3017010600 19
9.9%
3017011100 17
 
8.9%
3017010800 13
 
6.8%
3017010300 10
 
5.2%
3017012800 5
 
2.6%
3017011000 4
 
2.1%
Other values (7) 17
 
8.9%
ValueCountFrequency (%)
3017010100 4
 
2.1%
3017010200 2
 
1.0%
3017010300 10
5.2%
3017010400 2
 
1.0%
3017010500 4
 
2.1%
3017010600 19
9.9%
3017010800 13
6.8%
3017010900 1
 
0.5%
3017011000 4
 
2.1%
3017011100 17
8.9%
ValueCountFrequency (%)
3017012800 5
 
2.6%
3017012000 1
 
0.5%
3017011600 19
9.9%
3017011500 26
13.5%
3017011400 3
 
1.6%
3017011300 19
9.9%
3017011200 43
22.4%
3017011100 17
 
8.9%
3017011000 4
 
2.1%
3017010900 1
 
0.5%

법정동명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
둔산동
45 
도안동
26 
관저동
19 
월평동
19 
탄방동
19 
Other values (12)
64 

Length

Max length4
Median length3
Mean length2.984375
Min length2

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
둔산동 45
23.4%
도안동 26
13.5%
관저동 19
9.9%
월평동 19
9.9%
탄방동 19
9.9%
갈마동 17
 
8.9%
괴정동 13
 
6.8%
도마동 8
 
4.2%
만년동 5
 
2.6%
복수동 4
 
2.1%
Other values (7) 17
 
8.9%

Length

2023-12-12T13:40:13.031766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
둔산동 45
23.4%
도안동 26
13.5%
관저동 19
9.9%
월평동 19
9.9%
탄방동 19
9.9%
갈마동 17
 
8.9%
괴정동 13
 
6.8%
도마동 8
 
4.2%
만년동 5
 
2.6%
복수동 4
 
2.1%
Other values (7) 17
 
8.9%

전화번호
Text

MISSING 

Distinct137
Distinct (%)92.6%
Missing44
Missing (%)22.9%
Memory size1.6 KiB
2023-12-12T13:40:13.310504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.547297
Min length9

Characters and Unicode

Total characters1857
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique129 ?
Unique (%)87.2%

Sample

1st row0507-1424-1595
2nd row042-524-6786
3rd row042-523-0730
4th row042-532-0077
5th row042-523-0806
ValueCountFrequency (%)
1588-8069 4
 
2.6%
042-489-2766 3
 
1.9%
042 3
 
1.9%
042-486-9516 2
 
1.3%
0507-1409-1596 2
 
1.3%
042-489-6879 2
 
1.3%
042-528-0035 2
 
1.3%
042-718-1234 2
 
1.3%
488 2
 
1.3%
0507-1423-6787 2
 
1.3%
Other values (130) 130
84.4%
2023-12-12T13:40:13.798976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 292
15.7%
0 286
15.4%
4 256
13.8%
2 208
11.2%
5 158
8.5%
8 146
7.9%
7 130
7.0%
1 120
6.5%
3 112
 
6.0%
6 72
 
3.9%
Other values (2) 77
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1559
84.0%
Dash Punctuation 292
 
15.7%
Space Separator 6
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 286
18.3%
4 256
16.4%
2 208
13.3%
5 158
10.1%
8 146
9.4%
7 130
8.3%
1 120
7.7%
3 112
 
7.2%
6 72
 
4.6%
9 71
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 292
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1857
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 292
15.7%
0 286
15.4%
4 256
13.8%
2 208
11.2%
5 158
8.5%
8 146
7.9%
7 130
7.0%
1 120
6.5%
3 112
 
6.0%
6 72
 
3.9%
Other values (2) 77
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1857
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 292
15.7%
0 286
15.4%
4 256
13.8%
2 208
11.2%
5 158
8.5%
8 146
7.9%
7 130
7.0%
1 120
6.5%
3 112
 
6.0%
6 72
 
3.9%
Other values (2) 77
 
4.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-10-27
192 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-27
2nd row2023-10-27
3rd row2023-10-27
4th row2023-10-27
5th row2023-10-27

Common Values

ValueCountFrequency (%)
2023-10-27 192
100.0%

Length

2023-12-12T13:40:13.964803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:40:14.070997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-27 192
100.0%

Interactions

2023-12-12T13:40:07.074568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:06.337485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:06.745631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:07.463609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:06.471553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:06.865871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:07.551657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:06.649655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:06.987839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:40:14.137475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동코드행정동명법정동코드법정동명
순번1.0000.1650.1740.2480.258
행정동코드0.1651.0001.0000.9340.956
행정동명0.1741.0001.0001.0000.999
법정동코드0.2480.9341.0001.0001.000
법정동명0.2580.9560.9991.0001.000
2023-12-12T13:40:14.242038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명행정동명
법정동명1.0000.972
행정동명0.9721.000
2023-12-12T13:40:14.329713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동코드법정동코드행정동명법정동명
순번1.0000.0240.0460.0560.099
행정동코드0.0241.0000.7110.9580.816
법정동코드0.0460.7111.0000.9560.964
행정동명0.0560.9580.9561.0000.972
법정동명0.0990.8160.9640.9721.000

Missing values

2023-12-12T13:40:07.681307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:40:07.819625image/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

순번업종명업소명지번주소도로명주소행정동코드행정동명법정동코드법정동명전화번호데이터기준일자
01제과점영업하레하레대전광역시 서구 둔산동 1509대전광역시 서구 둔산로 155, 1,2층3017063000둔산1동3017011200둔산동0507-1424-15952023-10-27
12제과점영업새로나제과대전광역시 서구 변동 47-1대전광역시 서구 변동로 663017054000변동3017010200변동042-524-67862023-10-27
23제과점영업동원제과대전광역시 서구 도마동 134-1대전광역시 서구 도화공원길 283017052000도마1동3017010300도마동042-523-07302023-10-27
34제과점영업파리바게뜨 도마점대전광역시 서구 도마동 211대전광역시 서구 배재로 155-73017053000도마2동3017010300도마동042-532-00772023-10-27
45제과점영업파리바게뜨갈마점대전광역시 서구 갈마동 386-11대전광역시 서구 신갈마로127번길 2, 1층3017058100갈마1동3017011100갈마동042-523-08062023-10-27
56제과점영업내가잘가는빵집대전광역시 서구 갈마동 377-5대전광역시 서구 신갈마로 1533017058100갈마1동3017011100갈마동042-525-28162023-10-27
67제과점영업파리바게뜨둔산점대전광역시 서구 둔산동 1388대전광역시 서구 둔산북로 1603017064000둔산2동3017011200둔산동042-483-04042023-10-27
78제과점영업당신을위한빵집대전광역시 서구 월평동 218대전광역시 서구 월평북로 11, 1층 주공1단지상가 104호3017058700월평2동3017011300월평동<NA>2023-10-27
89제과점영업뚜레쥬르대전내동롯데점대전광역시 서구 내동 220대전광역시 서구 신갈마로 463017057500내동3017011000내동042-531-53852023-10-27
910제과점영업파리바게뜨황실점대전광역시 서구 월평동 302대전광역시 서구 청사로 653017058800월평3동3017011300월평동042-489-27662023-10-27
순번업종명업소명지번주소도로명주소행정동코드행정동명법정동코드법정동명전화번호데이터기준일자
182183제과점영업앤크(anc)대전광역시 서구 월평동 294대전광역시 서구 청사서로 14, 1층 일부호 (월평동)3017058700월평2동3017011300월평동<NA>2023-10-27
183184제과점영업피브완대전광역시 서구 둔산동 1453 대덕프라자대전광역시 서구 둔산로 130, 대덕프라자 1층 110호 (둔산동)3017052000도마1동3017010300둔산동<NA>2023-10-27
184185제과점영업소올투베이커리대전광역시 서구 둔산동 983대전광역시 서구 둔지로 32, 1,2층 (둔산동)3017064000둔산2동3017011200둔산동<NA>2023-10-27
185186제과점영업다람당대전광역시 서구 둔산동 1358대전광역시 서구 둔산로51번길 30, 1층 108호 (둔산동)3017064000둔산2동3017011200둔산동<NA>2023-10-27
186187제과점영업몽글베이커리대전광역시 서구 도안동 1783 좋은빌딩대전광역시 서구 계백로 1145, 좋은빌딩 1층 107호 (도안동)3017059300도안동3017011500도안동<NA>2023-10-27
187188제과점영업라블랑제대전광역시 서구 도안동 1123대전광역시 서구 원도안로224번안길 3, 1층 일부호 (도안동)3017059300도안동3017011500도안동<NA>2023-10-27
188189제과점영업브라보베이커리대전광역시 서구 용문동 280-19대전광역시 서구 괴정로181번길 22, 1층 일부호 (용문동)3017055000용문동3017010500용문동<NA>2023-10-27
189190제과점영업모구모구과자점 인 대전대전광역시 서구 도안동 845 에프엠프라임4차빌딩대전광역시 서구 도안북로93번길 11, 에프엠프라임4차빌딩 1층 108호 (도안동)3017059300도안동3017011500도안동<NA>2023-10-27
190191제과점영업잇츠바닐라대전광역시 서구 둔산동 1509 크로바아파트대전광역시 서구 둔산로 155, 1층 116호 (둔산동, 크로바아파트)3017052000도마1동3017010300둔산동<NA>2023-10-27
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