Overview

Dataset statistics

Number of variables10
Number of observations195
Missing cells27
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.9 KiB
Average record size in memory83.7 B

Variable types

Categorical1
Text5
DateTime1
Numeric3

Alerts

데이터기준일자 has constant value ""Constant
정제우편번호 is highly overall correlated with 정제WGS84위도High correlation
정제WGS84위도 is highly overall correlated with 정제우편번호High correlation
정제지번주소 has 5 (2.6%) missing valuesMissing
정제우편번호 has 3 (1.5%) missing valuesMissing
정제WGS84위도 has 9 (4.6%) missing valuesMissing
정제WGS84경도 has 9 (4.6%) missing valuesMissing
정제도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:59:12.689496
Analysis finished2023-12-10 21:59:14.176272
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
음식점업
112 
도소매업
61 
서비스업
16 
제조업
 
6

Length

Max length4
Median length4
Mean length3.9692308
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row음식점업
2nd row도소매업
3rd row도소매업
4th row음식점업
5th row음식점업

Common Values

ValueCountFrequency (%)
음식점업 112
57.4%
도소매업 61
31.3%
서비스업 16
 
8.2%
제조업 6
 
3.1%

Length

2023-12-11T06:59:14.241560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:59:14.339694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음식점업 112
57.4%
도소매업 61
31.3%
서비스업 16
 
8.2%
제조업 6
 
3.1%

업체명
Text

Distinct194
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T06:59:14.532654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length5.3897436
Min length2

Characters and Unicode

Total characters1051
Distinct characters312
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)99.0%

Sample

1st row무진장
2nd row대왕기름집
3rd row서울기름집
4th row문산순대국
5th row제일황소
ValueCountFrequency (%)
두꺼비집 2
 
1.0%
김치관 1
 
0.5%
마루솥뚜껑와인삼겹살 1
 
0.5%
대훈생고기 1
 
0.5%
한주토피스 1
 
0.5%
천안기름집 1
 
0.5%
통나무집 1
 
0.5%
성진카정비 1
 
0.5%
고기돌담집 1
 
0.5%
수도전기모터 1
 
0.5%
Other values (190) 190
94.5%
2023-12-11T06:59:14.855123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
집 29
 
2.8%
대 20
 
1.9%
이 19
 
1.8%
기 17
 
1.6%
안 16
 
1.5%
당 15
 
1.4%
성 15
 
1.4%
식 15
 
1.4%
정 14
 
1.3%
장 14
 
1.3%
Other values (302) 877
83.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 998
95.0%
Uppercase Letter 11
 
1.0%
Open Punctuation 10
 
1.0%
Close Punctuation 10
 
1.0%
Space Separator 6
 
0.6%
Other Symbol 4
 
0.4%
Other Punctuation 4
 
0.4%
Decimal Number 4
 
0.4%
Lowercase Letter 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
집 29
 
2.9%
대 20
 
2.0%
이 19
 
1.9%
기 17
 
1.7%
안 16
 
1.6%
당 15
 
1.5%
성 15
 
1.5%
식 15
 
1.5%
정 14
 
1.4%
장 14
 
1.4%
Other values (282) 824
82.6%
Uppercase Letter
ValueCountFrequency (%)
S 2
18.2%
L 2
18.2%
G 2
18.2%
O 2
18.2%
W 1
9.1%
N 1
9.1%
B 1
9.1%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
? 1
25.0%
& 1
25.0%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
8 1
25.0%
9 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
o 2
50.0%
b 1
25.0%
m 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1002
95.3%
Common 34
 
3.2%
Latin 15
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
집 29
 
2.9%
대 20
 
2.0%
이 19
 
1.9%
기 17
 
1.7%
안 16
 
1.6%
당 15
 
1.5%
성 15
 
1.5%
식 15
 
1.5%
정 14
 
1.4%
장 14
 
1.4%
Other values (283) 828
82.6%
Latin
ValueCountFrequency (%)
S 2
13.3%
L 2
13.3%
o 2
13.3%
G 2
13.3%
O 2
13.3%
W 1
6.7%
N 1
6.7%
b 1
6.7%
m 1
6.7%
B 1
6.7%
Common
ValueCountFrequency (%)
( 10
29.4%
) 10
29.4%
6
17.6%
. 2
 
5.9%
1 2
 
5.9%
8 1
 
2.9%
9 1
 
2.9%
? 1
 
2.9%
& 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 998
95.0%
ASCII 49
 
4.7%
None 4
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
집 29
 
2.9%
대 20
 
2.0%
이 19
 
1.9%
기 17
 
1.7%
안 16
 
1.6%
당 15
 
1.5%
성 15
 
1.5%
식 15
 
1.5%
정 14
 
1.4%
장 14
 
1.4%
Other values (282) 824
82.6%
ASCII
ValueCountFrequency (%)
( 10
20.4%
) 10
20.4%
6
12.2%
S 2
 
4.1%
L 2
 
4.1%
. 2
 
4.1%
1 2
 
4.1%
o 2
 
4.1%
G 2
 
4.1%
O 2
 
4.1%
Other values (9) 9
18.4%
None
ValueCountFrequency (%)
㈜ 4
100.0%

업력(창업년도)
Text

Distinct112
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T06:59:15.097676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters1755
Distinct characters13
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

Unique70 ?
Unique (%)35.9%

Sample

1st row27(1993년)
2nd row23(1998년)
3rd row22(1986년)
4th row44(1976년)
5th row30(1987년)
ValueCountFrequency (%)
34(1986년 7
 
3.6%
30(1990년 5
 
2.6%
23(1997년 5
 
2.6%
30(1989년 5
 
2.6%
22(1999년 5
 
2.6%
20(2000년 5
 
2.6%
21(1999년 5
 
2.6%
28(1991년 4
 
2.1%
31(1989년 4
 
2.1%
33(1987년 4
 
2.1%
Other values (102) 146
74.9%
2023-12-11T06:59:15.446293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 285
16.2%
1 225
12.8%
( 195
11.1%
년 195
11.1%
) 195
11.1%
2 125
7.1%
3 117
6.7%
8 106
 
6.0%
0 94
 
5.4%
4 65
 
3.7%
Other values (3) 153
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1170
66.7%
Open Punctuation 195
 
11.1%
Other Letter 195
 
11.1%
Close Punctuation 195
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 285
24.4%
1 225
19.2%
2 125
10.7%
3 117
10.0%
8 106
 
9.1%
0 94
 
8.0%
4 65
 
5.6%
5 53
 
4.5%
7 52
 
4.4%
6 48
 
4.1%
Open Punctuation
ValueCountFrequency (%)
( 195
100.0%
Other Letter
ValueCountFrequency (%)
년 195
100.0%
Close Punctuation
ValueCountFrequency (%)
) 195
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1560
88.9%
Hangul 195
 
11.1%

Most frequent character per script

Common
ValueCountFrequency (%)
9 285
18.3%
1 225
14.4%
( 195
12.5%
) 195
12.5%
2 125
8.0%
3 117
7.5%
8 106
 
6.8%
0 94
 
6.0%
4 65
 
4.2%
5 53
 
3.4%
Other values (2) 100
 
6.4%
Hangul
ValueCountFrequency (%)
년 195
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1560
88.9%
Hangul 195
 
11.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 285
18.3%
1 225
14.4%
( 195
12.5%
) 195
12.5%
2 125
8.0%
3 117
7.5%
8 106
 
6.8%
0 94
 
6.0%
4 65
 
4.2%
5 53
 
3.4%
Other values (2) 100
 
6.4%
Hangul
ValueCountFrequency (%)
년 195
100.0%

전화번호
Text

Distinct194
Distinct (%)100.0%
Missing1
Missing (%)0.5%
Memory size1.7 KiB
2023-12-11T06:59:15.718096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.020619
Min length11

Characters and Unicode

Total characters2332
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

Unique194 ?
Unique (%)100.0%

Sample

1st row031-375-0772
2nd row031-758-1245
3rd row031-754-1610
4th row031-975-4791
5th row031-451-3006
ValueCountFrequency (%)
031-375-0772 1
 
0.5%
031-318-3822 1
 
0.5%
031-212-2354 1
 
0.5%
031-223-0300 1
 
0.5%
031-214-9181 1
 
0.5%
031-435-9600 1
 
0.5%
031-756-0706 1
 
0.5%
02-503-9555 1
 
0.5%
031-408-0989 1
 
0.5%
031-261-5292 1
 
0.5%
Other values (184) 184
94.8%
2023-12-11T06:59:16.056296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 388
16.6%
3 331
14.2%
0 320
13.7%
1 296
12.7%
2 163
7.0%
6 161
6.9%
5 159
6.8%
4 142
 
6.1%
8 135
 
5.8%
7 130
 
5.6%
Other values (2) 107
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1943
83.3%
Dash Punctuation 388
 
16.6%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 331
17.0%
0 320
16.5%
1 296
15.2%
2 163
8.4%
6 161
8.3%
5 159
8.2%
4 142
7.3%
8 135
6.9%
7 130
 
6.7%
9 106
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 388
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2332
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 388
16.6%
3 331
14.2%
0 320
13.7%
1 296
12.7%
2 163
7.0%
6 161
6.9%
5 159
6.8%
4 142
 
6.1%
8 135
 
5.8%
7 130
 
5.6%
Other values (2) 107
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2332
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 388
16.6%
3 331
14.2%
0 320
13.7%
1 296
12.7%
2 163
7.0%
6 161
6.9%
5 159
6.8%
4 142
 
6.1%
8 135
 
5.8%
7 130
 
5.6%
Other values (2) 107
 
4.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2022-11-24 00:00:00
Maximum2022-11-24 00:00:00
2023-12-11T06:59:16.156714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:16.231252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

정제도로명주소
Text

UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T06:59:16.438337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length38
Mean length26.723077
Min length14

Characters and Unicode

Total characters5211
Distinct characters241
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique195 ?
Unique (%)100.0%

Sample

1st row경기도 오산시 경기도대로658번길 19(내삼미동)
2nd row경기도 성남시 중원구 둔촌대로 83번길 9-1(성남동)
3rd row경기도 성남시 중원구 둔촌대로83번길 5(성남동)
4th row경기도 고양시 일산서구 고양대로 667-5(일산동, 1층 일부)
5th row경기도 군포시 군포로534번길 16, 1층(당동)
ValueCountFrequency (%)
경기도 195
 
18.2%
1층 28
 
2.6%
수원시 20
 
1.9%
성남시 16
 
1.5%
안산시 13
 
1.2%
안성시 12
 
1.1%
화성시 12
 
1.1%
고양시 12
 
1.1%
부천시 11
 
1.0%
중원구 10
 
0.9%
Other values (542) 740
69.2%
2023-12-11T06:59:16.801484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
876
 
16.8%
1 250
 
4.8%
시 208
 
4.0%
경 206
 
4.0%
기 205
 
3.9%
도 204
 
3.9%
로 173
 
3.3%
동 146
 
2.8%
) 123
 
2.4%
( 123
 
2.4%
Other values (231) 2697
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3021
58.0%
Decimal Number 920
 
17.7%
Space Separator 876
 
16.8%
Close Punctuation 123
 
2.4%
Open Punctuation 123
 
2.4%
Other Punctuation 90
 
1.7%
Dash Punctuation 52
 
1.0%
Math Symbol 3
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 208
 
6.9%
경 206
 
6.8%
기 205
 
6.8%
도 204
 
6.8%
로 173
 
5.7%
동 146
 
4.8%
길 91
 
3.0%
번 78
 
2.6%
구 76
 
2.5%
성 66
 
2.2%
Other values (212) 1568
51.9%
Decimal Number
ValueCountFrequency (%)
1 250
27.2%
3 112
12.2%
2 101
11.0%
0 92
 
10.0%
6 71
 
7.7%
4 67
 
7.3%
5 66
 
7.2%
7 60
 
6.5%
8 53
 
5.8%
9 48
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
H 1
33.3%
C 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
876
100.0%
Close Punctuation
ValueCountFrequency (%)
) 123
100.0%
Open Punctuation
ValueCountFrequency (%)
( 123
100.0%
Other Punctuation
ValueCountFrequency (%)
, 90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3021
58.0%
Common 2187
42.0%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 208
 
6.9%
경 206
 
6.8%
기 205
 
6.8%
도 204
 
6.8%
로 173
 
5.7%
동 146
 
4.8%
길 91
 
3.0%
번 78
 
2.6%
구 76
 
2.5%
성 66
 
2.2%
Other values (212) 1568
51.9%
Common
ValueCountFrequency (%)
876
40.1%
1 250
 
11.4%
) 123
 
5.6%
( 123
 
5.6%
3 112
 
5.1%
2 101
 
4.6%
0 92
 
4.2%
, 90
 
4.1%
6 71
 
3.2%
4 67
 
3.1%
Other values (6) 282
 
12.9%
Latin
ValueCountFrequency (%)
H 1
33.3%
C 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3021
58.0%
ASCII 2190
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
876
40.0%
1 250
 
11.4%
) 123
 
5.6%
( 123
 
5.6%
3 112
 
5.1%
2 101
 
4.6%
0 92
 
4.2%
, 90
 
4.1%
6 71
 
3.2%
4 67
 
3.1%
Other values (9) 285
 
13.0%
Hangul
ValueCountFrequency (%)
시 208
 
6.9%
경 206
 
6.8%
기 205
 
6.8%
도 204
 
6.8%
로 173
 
5.7%
동 146
 
4.8%
길 91
 
3.0%
번 78
 
2.6%
구 76
 
2.5%
성 66
 
2.2%
Other values (212) 1568
51.9%

정제지번주소
Text

MISSING 

Distinct188
Distinct (%)98.9%
Missing5
Missing (%)2.6%
Memory size1.7 KiB
2023-12-11T06:59:17.053459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length40
Mean length24.773684
Min length14

Characters and Unicode

Total characters4707
Distinct characters214
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)97.9%

Sample

1st row경기도 성남시 중원구 성남동 4244번지
2nd row경기도 성남시 중원구 성남동 4220번지
3rd row경기도 고양시 일산서구 일산동 627-2번지 1층 일부
4th row경기도 군포시 당동 750-18번지 1층
5th row경기도 안양시 만안구 석수동 267-11번지
ValueCountFrequency (%)
경기도 190
 
18.7%
1층 41
 
4.0%
수원시 20
 
2.0%
성남시 16
 
1.6%
고양시 12
 
1.2%
안성시 12
 
1.2%
안산시 12
 
1.2%
화성시 11
 
1.1%
성남동 10
 
1.0%
부천시 10
 
1.0%
Other values (466) 680
67.1%
2023-12-11T06:59:17.415823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
824
 
17.5%
1 236
 
5.0%
시 198
 
4.2%
기 195
 
4.1%
도 194
 
4.1%
경 190
 
4.0%
지 188
 
4.0%
번 177
 
3.8%
동 169
 
3.6%
- 147
 
3.1%
Other values (204) 2189
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2743
58.3%
Decimal Number 967
 
20.5%
Space Separator 824
 
17.5%
Dash Punctuation 147
 
3.1%
Other Punctuation 16
 
0.3%
Math Symbol 3
 
0.1%
Uppercase Letter 3
 
0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 198
 
7.2%
기 195
 
7.1%
도 194
 
7.1%
경 190
 
6.9%
지 188
 
6.9%
번 177
 
6.5%
동 169
 
6.2%
구 76
 
2.8%
성 58
 
2.1%
양 57
 
2.1%
Other values (185) 1241
45.2%
Decimal Number
ValueCountFrequency (%)
1 236
24.4%
2 126
13.0%
4 103
10.7%
0 84
 
8.7%
5 81
 
8.4%
3 76
 
7.9%
6 74
 
7.7%
8 73
 
7.5%
7 63
 
6.5%
9 51
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
H 1
33.3%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
824
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 147
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2743
58.3%
Common 1961
41.7%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 198
 
7.2%
기 195
 
7.1%
도 194
 
7.1%
경 190
 
6.9%
지 188
 
6.9%
번 177
 
6.5%
동 169
 
6.2%
구 76
 
2.8%
성 58
 
2.1%
양 57
 
2.1%
Other values (185) 1241
45.2%
Common
ValueCountFrequency (%)
824
42.0%
1 236
 
12.0%
- 147
 
7.5%
2 126
 
6.4%
4 103
 
5.3%
0 84
 
4.3%
5 81
 
4.1%
3 76
 
3.9%
6 74
 
3.8%
8 73
 
3.7%
Other values (6) 137
 
7.0%
Latin
ValueCountFrequency (%)
A 1
33.3%
H 1
33.3%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2743
58.3%
ASCII 1964
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
824
42.0%
1 236
 
12.0%
- 147
 
7.5%
2 126
 
6.4%
4 103
 
5.2%
0 84
 
4.3%
5 81
 
4.1%
3 76
 
3.9%
6 74
 
3.8%
8 73
 
3.7%
Other values (9) 140
 
7.1%
Hangul
ValueCountFrequency (%)
시 198
 
7.2%
기 195
 
7.1%
도 194
 
7.1%
경 190
 
6.9%
지 188
 
6.9%
번 177
 
6.5%
동 169
 
6.2%
구 76
 
2.8%
성 58
 
2.1%
양 57
 
2.1%
Other values (185) 1241
45.2%

정제우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct154
Distinct (%)80.2%
Missing3
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean14397.719
Minimum10016
Maximum18593
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T06:59:17.556643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10016
5-th percentile10342
Q112218.75
median14598
Q316491.75
95-th percentile18342.1
Maximum18593
Range8577
Interquartile range (IQR)4273

Descriptive statistics

Standard deviation2572.1198
Coefficient of variation (CV)0.17864773
Kurtosis-1.2006354
Mean14397.719
Median Absolute Deviation (MAD)2099
Skewness-0.09764512
Sum2764362
Variance6615800.2
MonotonicityNot monotonic
2023-12-11T06:59:17.889863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13377 9
 
4.6%
10059 4
 
2.1%
16257 4
 
2.1%
12700 3
 
1.5%
10342 3
 
1.5%
11695 3
 
1.5%
16800 3
 
1.5%
17757 2
 
1.0%
16269 2
 
1.0%
15220 2
 
1.0%
Other values (144) 157
80.5%
(Missing) 3
 
1.5%
ValueCountFrequency (%)
10016 1
 
0.5%
10020 1
 
0.5%
10059 4
2.1%
10111 1
 
0.5%
10115 1
 
0.5%
10222 1
 
0.5%
10342 3
1.5%
10416 2
1.0%
10439 1
 
0.5%
10508 1
 
0.5%
ValueCountFrequency (%)
18593 2
1.0%
18573 1
0.5%
18567 1
0.5%
18527 1
0.5%
18516 1
0.5%
18465 2
1.0%
18399 1
0.5%
18374 1
0.5%
18316 1
0.5%
18136 2
1.0%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct180
Distinct (%)96.8%
Missing9
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean37.419191
Minimum36.983808
Maximum37.917296
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T06:59:18.022021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.983808
5-th percentile37.007286
Q137.279327
median37.400298
Q337.601255
95-th percentile37.858227
Maximum37.917296
Range0.93348806
Interquartile range (IQR)0.32192893

Descriptive statistics

Standard deviation0.23466255
Coefficient of variation (CV)0.006271182
Kurtosis-0.48141982
Mean37.419191
Median Absolute Deviation (MAD)0.12660433
Skewness0.19043568
Sum6959.9695
Variance0.055066514
MonotonicityNot monotonic
2023-12-11T06:59:18.148916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4309074665 4
 
2.1%
37.3423606229 2
 
1.0%
37.6539744065 2
 
1.0%
37.4306354573 2
 
1.0%
36.9931934581 1
 
0.5%
37.3991555099 1
 
0.5%
37.4289927411 1
 
0.5%
37.2991766581 1
 
0.5%
37.3573669592 1
 
0.5%
37.0009583109 1
 
0.5%
Other values (170) 170
87.2%
(Missing) 9
 
4.6%
ValueCountFrequency (%)
36.9838079972 1
0.5%
36.9896855222 1
0.5%
36.9931934581 1
0.5%
36.9973120837 1
0.5%
37.0009583109 1
0.5%
37.0051378937 1
0.5%
37.0053832121 1
0.5%
37.005988296 1
0.5%
37.006171638 1
0.5%
37.0071561035 1
0.5%
ValueCountFrequency (%)
37.9172960562 1
0.5%
37.9129321976 1
0.5%
37.9091647403 1
0.5%
37.9090571948 1
0.5%
37.9010075784 1
0.5%
37.8967525623 1
0.5%
37.8924344506 1
0.5%
37.8863322735 1
0.5%
37.8783747348 1
0.5%
37.8606023824 1
0.5%

정제WGS84경도
Real number (ℝ)

MISSING 

Distinct180
Distinct (%)96.8%
Missing9
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean127.01381
Minimum126.52603
Maximum127.57316
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T06:59:18.277159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.52603
5-th percentile126.7652
Q1126.85196
median127.02143
Q3127.12806
95-th percentile127.36347
Maximum127.57316
Range1.0471257
Interquartile range (IQR)0.27609681

Descriptive statistics

Standard deviation0.19907826
Coefficient of variation (CV)0.0015673749
Kurtosis0.13276997
Mean127.01381
Median Absolute Deviation (MAD)0.12387047
Skewness0.38631239
Sum23624.569
Variance0.039632152
MonotonicityNot monotonic
2023-12-11T06:59:18.399903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1280050188 4
 
2.1%
126.803638668 2
 
1.0%
126.7899010911 2
 
1.0%
127.1274977308 2
 
1.0%
127.0895564212 1
 
0.5%
126.9354258673 1
 
0.5%
126.9914552184 1
 
0.5%
126.8731462177 1
 
0.5%
127.0509279665 1
 
0.5%
127.2671481534 1
 
0.5%
Other values (170) 170
87.2%
(Missing) 9
 
4.6%
ValueCountFrequency (%)
126.5260317627 1
0.5%
126.5855625261 1
0.5%
126.6236655324 1
0.5%
126.6240280479 1
0.5%
126.6242177841 1
0.5%
126.721186914 1
0.5%
126.7284736768 1
0.5%
126.729522443 1
0.5%
126.7347854162 1
0.5%
126.7637247459 1
0.5%
ValueCountFrequency (%)
127.5731574854 1
0.5%
127.5489582384 1
0.5%
127.5319351334 1
0.5%
127.4932241503 1
0.5%
127.4806834787 1
0.5%
127.4785971989 1
0.5%
127.4555046796 1
0.5%
127.439197742 1
0.5%
127.4388709628 1
0.5%
127.368332227 1
0.5%

Interactions

2023-12-11T06:59:13.596682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:13.166392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:13.386320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:13.665765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:13.241070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:13.457552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:13.734643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:13.309301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:13.522578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:59:18.493977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분정제우편번호정제WGS84위도정제WGS84경도
구분1.0000.2840.2960.023
정제우편번호0.2841.0000.9420.870
정제WGS84위도0.2960.9421.0000.756
정제WGS84경도0.0230.8700.7561.000
2023-12-11T06:59:18.596899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정제우편번호정제WGS84위도정제WGS84경도구분
정제우편번호1.000-0.9330.1990.167
정제WGS84위도-0.9331.000-0.2340.177
정제WGS84경도0.199-0.2341.0000.000
구분0.1670.1770.0001.000

Missing values

2023-12-11T06:59:13.836447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:59:13.989246image/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.
2023-12-11T06:59:14.116823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

구분업체명업력(창업년도)전화번호데이터기준일자정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
0음식점업무진장27(1993년)031-375-07722022-11-24경기도 오산시 경기도대로658번길 19(내삼미동)<NA><NA><NA><NA>
1도소매업대왕기름집23(1998년)031-758-12452022-11-24경기도 성남시 중원구 둔촌대로 83번길 9-1(성남동)경기도 성남시 중원구 성남동 4244번지1337737.431097127.128072
2도소매업서울기름집22(1986년)031-754-16102022-11-24경기도 성남시 중원구 둔촌대로83번길 5(성남동)경기도 성남시 중원구 성남동 4220번지1337737.430701127.128187
3음식점업문산순대국44(1976년)031-975-47912022-11-24경기도 고양시 일산서구 고양대로 667-5(일산동, 1층 일부)경기도 고양시 일산서구 일산동 627-2번지 1층 일부1034237.684653126.770238
4음식점업제일황소30(1987년)031-451-30062022-11-24경기도 군포시 군포로534번길 16, 1층(당동)경기도 군포시 당동 750-18번지 1층1585537.353539126.947375
5서비스업장머리방33(1988년)031-471-20042022-11-24경기도 안양시 만안구 안양로548번길 36(석수동)경기도 안양시 만안구 석수동 267-11번지1396237.418414126.908871
6서비스업정흥교 헤어샵45(1976년)031-594-00262022-11-24경기도 남양주시 화도읍 마석로61번길 18-25경기도 남양주시 화도읍 마석우리 379-3번지1217537.657427127.304102
7음식점업왈츠와닥터만34(1986년)031-576-00202022-11-24경기도 남양주시 조안면 북한강로 856-37경기도 남양주시 조안면 삼봉리 272-6번지1227837.591969127.33846
8음식점업귀래정23(1996년)031-263-82662022-11-24경기도 용인시 수지구 동천로 635(고기동)경기도 용인시 수지구 고기동 755-11번지1680037.358896127.054792
9도소매업제일농약사35(1986년)031-672-51012022-11-24경기도 안성시 일죽면 주래본죽로 35-1경기도 안성시 일죽면 송천리 28-9번지1752937.093717127.478597
구분업체명업력(창업년도)전화번호데이터기준일자정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
185도소매업이안경박사42(1978년)031-492-00852022-11-24경기도 안산시 단원구 원곡로 36, 1층동 (원곡동)경기도 안산시 단원구 원곡동 801번지 1층 동1539237.330201126.792982
186도소매업안성땅콩상회35(1984년)031-674-80892022-11-24경기도 안성시 아양동 286-4경기도 안성시 아양동 286-41758237.005988127.267122
187음식점업단골집47(1973년)031-882-76072022-11-24경기도 여주시 대신면 율촌리 379-4경기도 여주시 대신면 율촌리 379-412610<NA><NA>
188음식점업경원식당39(1980년)031-878-54642022-11-24경기도 의정부시 둔야로 49번길 21경기도 의정부시 의정부동 483번지1167337.740276127.038285
189도소매업해성장식31(1989년)031-633-78872022-11-24경기도 이천시 중리천로 11경기도 이천시 관고동 12-5번지1736837.280657127.439198
190제조업청아원㈜27(1987년)031-554-07752022-11-24경기도 포천시 군내면 용정경제로 1길 48-39경기도 포천시 군내면 용정리 484번지1115437.878375127.199917
191음식점업털보회관28(1991년)031-376-24792022-11-24경기도 화성시 풀무골로 106번길 19경기도 화성시 중동 243번지1846537.203486127.139514
192음식점업쉐프부랑제30(1989년)031-998-13132022-11-24경기도 김포시 사우중로 82 (사우프라자 108,109호)경기도 김포시 사우동 875번지 사우프라자 108,109호1011137.621715126.721187
193제조업에이큐양복점38(1981년)031-666-47862022-11-24경기도 평택시 쇼핑로 6-2(신장동, 1층)경기도 평택시 신장동 302-190번지 1층1775837.080319127.050385
194도소매업정금주한복연구실25(1994년)02-503-08452022-11-24경기도 과천시 별양상가2로 20(별양동, 새서울프라자2층 14호, 62호)경기도 과천시 별양동 1-18번지 새서울프라자 2층 14호, 62호1383737.426825126.992555