Overview

Dataset statistics

Number of variables9
Number of observations1064
Missing cells1285
Missing cells (%)13.4%
Duplicate rows9
Duplicate rows (%)0.8%
Total size in memory77.0 KiB
Average record size in memory74.1 B

Variable types

Categorical2
Text5
Numeric2

Alerts

Dataset has 9 (0.8%) duplicate rowsDuplicates
WGS84위도 is highly overall correlated with 시군명High correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
시장명 has 162 (15.2%) missing valuesMissing
전화번호 has 889 (83.6%) missing valuesMissing
소재지우편번호 has 48 (4.5%) missing valuesMissing
소재지도로명주소 has 79 (7.4%) missing valuesMissing
WGS84위도 has 51 (4.8%) missing valuesMissing
WGS84경도 has 51 (4.8%) missing valuesMissing

Reproduction

Analysis started2024-04-11 01:57:32.984362
Analysis finished2024-04-11 01:57:35.585380
Duration2.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
<NA>
167 
수원시
113 
성남시
110 
고양시
86 
부천시
73 
Other values (27)
515 

Length

Max length4
Median length3
Mean length3.1983083
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광명시
2nd row<NA>
3rd row<NA>
4th row고양시
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 167
15.7%
수원시 113
 
10.6%
성남시 110
 
10.3%
고양시 86
 
8.1%
부천시 73
 
6.9%
용인시 54
 
5.1%
안산시 44
 
4.1%
안양시 44
 
4.1%
광명시 31
 
2.9%
화성시 31
 
2.9%
Other values (22) 311
29.2%

Length

2024-04-11T10:57:35.646691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 167
15.7%
수원시 113
 
10.6%
성남시 110
 
10.3%
고양시 86
 
8.1%
부천시 73
 
6.9%
용인시 54
 
5.1%
안산시 44
 
4.1%
안양시 44
 
4.1%
광명시 31
 
2.9%
화성시 31
 
2.9%
Other values (22) 311
29.2%

시설구분명
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
대규모점포
815 
전통시장
162 
로컬푸드직매장
87 

Length

Max length7
Median length5
Mean length5.0112782
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row로컬푸드직매장
2nd row전통시장
3rd row전통시장
4th row로컬푸드직매장
5th row전통시장

Common Values

ValueCountFrequency (%)
대규모점포 815
76.6%
전통시장 162
 
15.2%
로컬푸드직매장 87
 
8.2%

Length

2024-04-11T10:57:35.751664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T10:57:35.835817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대규모점포 815
76.6%
전통시장 162
 
15.2%
로컬푸드직매장 87
 
8.2%

시장명
Text

MISSING 

Distinct843
Distinct (%)93.5%
Missing162
Missing (%)15.2%
Memory size8.4 KiB
2024-04-11T10:57:36.053439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length20
Mean length10.716186
Min length2

Characters and Unicode

Total characters9666
Distinct characters394
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique791 ?
Unique (%)87.7%

Sample

1st row광명농협 로컬푸드 직매장
2nd row신도농협 로컬푸드직매장
3rd row태안농협 로컬푸드직매장
4th row수원로컬푸드직매장
5th row수지농협 로컬푸드직매장
ValueCountFrequency (%)
롯데쇼핑(주 51
 
3.2%
로컬푸드직매장 47
 
2.9%
홈플러스(주 38
 
2.4%
롯데슈퍼 31
 
1.9%
주)이마트 25
 
1.6%
롯데마트 24
 
1.5%
익스프레스 24
 
1.5%
주)지에스리테일 18
 
1.1%
이마트 18
 
1.1%
the 18
 
1.1%
Other values (873) 1307
81.6%
2024-04-11T10:57:36.432849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
700
 
7.2%
점 505
 
5.2%
주 331
 
3.4%
) 318
 
3.3%
( 317
 
3.3%
스 311
 
3.2%
데 227
 
2.3%
롯 200
 
2.1%
마 190
 
2.0%
이 189
 
2.0%
Other values (384) 6378
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7839
81.1%
Space Separator 700
 
7.2%
Uppercase Letter 361
 
3.7%
Close Punctuation 318
 
3.3%
Open Punctuation 317
 
3.3%
Decimal Number 74
 
0.8%
Lowercase Letter 49
 
0.5%
Dash Punctuation 4
 
< 0.1%
Other Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 505
 
6.4%
주 331
 
4.2%
스 311
 
4.0%
데 227
 
2.9%
롯 200
 
2.6%
마 190
 
2.4%
이 189
 
2.4%
트 186
 
2.4%
장 166
 
2.1%
시 126
 
1.6%
Other values (329) 5408
69.0%
Uppercase Letter
ValueCountFrequency (%)
S 64
17.7%
E 43
11.9%
G 42
11.6%
H 31
8.6%
A 26
7.2%
T 26
7.2%
R 20
 
5.5%
F 19
 
5.3%
C 14
 
3.9%
L 12
 
3.3%
Other values (14) 64
17.7%
Lowercase Letter
ValueCountFrequency (%)
e 12
24.5%
t 4
 
8.2%
a 4
 
8.2%
i 3
 
6.1%
r 3
 
6.1%
n 3
 
6.1%
u 3
 
6.1%
s 3
 
6.1%
l 3
 
6.1%
h 3
 
6.1%
Other values (7) 8
16.3%
Decimal Number
ValueCountFrequency (%)
2 29
39.2%
0 14
18.9%
9 12
16.2%
1 11
 
14.9%
3 6
 
8.1%
4 1
 
1.4%
8 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
& 1
33.3%
Space Separator
ValueCountFrequency (%)
700
100.0%
Close Punctuation
ValueCountFrequency (%)
) 318
100.0%
Open Punctuation
ValueCountFrequency (%)
( 317
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7839
81.1%
Common 1417
 
14.7%
Latin 410
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 505
 
6.4%
주 331
 
4.2%
스 311
 
4.0%
데 227
 
2.9%
롯 200
 
2.6%
마 190
 
2.4%
이 189
 
2.4%
트 186
 
2.4%
장 166
 
2.1%
시 126
 
1.6%
Other values (329) 5408
69.0%
Latin
ValueCountFrequency (%)
S 64
15.6%
E 43
 
10.5%
G 42
 
10.2%
H 31
 
7.6%
A 26
 
6.3%
T 26
 
6.3%
R 20
 
4.9%
F 19
 
4.6%
C 14
 
3.4%
e 12
 
2.9%
Other values (31) 113
27.6%
Common
ValueCountFrequency (%)
700
49.4%
) 318
22.4%
( 317
22.4%
2 29
 
2.0%
0 14
 
1.0%
9 12
 
0.8%
1 11
 
0.8%
3 6
 
0.4%
- 4
 
0.3%
, 2
 
0.1%
Other values (4) 4
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7839
81.1%
ASCII 1827
 
18.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
700
38.3%
) 318
17.4%
( 317
17.4%
S 64
 
3.5%
E 43
 
2.4%
G 42
 
2.3%
H 31
 
1.7%
2 29
 
1.6%
A 26
 
1.4%
T 26
 
1.4%
Other values (45) 231
 
12.6%
Hangul
ValueCountFrequency (%)
점 505
 
6.4%
주 331
 
4.2%
스 311
 
4.0%
데 227
 
2.9%
롯 200
 
2.6%
마 190
 
2.4%
이 189
 
2.4%
트 186
 
2.4%
장 166
 
2.1%
시 126
 
1.6%
Other values (329) 5408
69.0%

전화번호
Text

MISSING 

Distinct164
Distinct (%)93.7%
Missing889
Missing (%)83.6%
Memory size8.4 KiB
2024-04-11T10:57:36.653552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.045714
Min length11

Characters and Unicode

Total characters2108
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique156 ?
Unique (%)89.1%

Sample

1st row02-2169-8092
2nd row02-2614-0006
3rd row02-2614-5292
4th row02-381-0100
5th row02-754-7389
ValueCountFrequency (%)
031-980-2769 4
 
2.3%
031-656-0747 3
 
1.7%
031-952-3233 2
 
1.1%
031-336-1110 2
 
1.1%
031-975-8322 2
 
1.1%
031-946-0013 2
 
1.1%
031-942-5656 2
 
1.1%
031-568-8700 2
 
1.1%
031-797-1133 1
 
0.6%
031-701-7007 1
 
0.6%
Other values (154) 154
88.0%
2024-04-11T10:57:36.982608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 350
16.6%
0 293
13.9%
3 287
13.6%
1 275
13.0%
2 148
7.0%
6 145
6.9%
7 134
 
6.4%
5 134
 
6.4%
8 132
 
6.3%
9 106
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1758
83.4%
Dash Punctuation 350
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 293
16.7%
3 287
16.3%
1 275
15.6%
2 148
8.4%
6 145
8.2%
7 134
7.6%
5 134
7.6%
8 132
7.5%
9 106
 
6.0%
4 104
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 350
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2108
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 350
16.6%
0 293
13.9%
3 287
13.6%
1 275
13.0%
2 148
7.0%
6 145
6.9%
7 134
 
6.4%
5 134
 
6.4%
8 132
 
6.3%
9 106
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 350
16.6%
0 293
13.9%
3 287
13.6%
1 275
13.0%
2 148
7.0%
6 145
6.9%
7 134
 
6.4%
5 134
 
6.4%
8 132
 
6.3%
9 106
 
5.0%

소재지우편번호
Text

MISSING 

Distinct724
Distinct (%)71.3%
Missing48
Missing (%)4.5%
Memory size8.4 KiB
2024-04-11T10:57:37.281897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.3700787
Min length5

Characters and Unicode

Total characters5456
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique533 ?
Unique (%)52.5%

Sample

1st row14316
2nd row14220
3rd row14291
4th row10584
5th row14495
ValueCountFrequency (%)
13497 9
 
0.9%
463050 8
 
0.8%
11915 7
 
0.7%
10929 7
 
0.7%
13599 7
 
0.7%
13837 6
 
0.6%
14637 6
 
0.6%
13597 5
 
0.5%
13587 5
 
0.5%
14548 5
 
0.5%
Other values (714) 951
93.6%
2024-04-11T10:57:37.700668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1190
21.8%
4 710
13.0%
0 614
11.3%
3 500
9.2%
6 463
 
8.5%
5 449
 
8.2%
2 438
 
8.0%
8 373
 
6.8%
7 321
 
5.9%
9 299
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5357
98.2%
Dash Punctuation 99
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1190
22.2%
4 710
13.3%
0 614
11.5%
3 500
9.3%
6 463
 
8.6%
5 449
 
8.4%
2 438
 
8.2%
8 373
 
7.0%
7 321
 
6.0%
9 299
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5456
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1190
21.8%
4 710
13.0%
0 614
11.3%
3 500
9.2%
6 463
 
8.5%
5 449
 
8.2%
2 438
 
8.0%
8 373
 
6.8%
7 321
 
5.9%
9 299
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1190
21.8%
4 710
13.0%
0 614
11.3%
3 500
9.2%
6 463
 
8.5%
5 449
 
8.2%
2 438
 
8.0%
8 373
 
6.8%
7 321
 
5.9%
9 299
 
5.5%

소재지도로명주소
Text

MISSING 

Distinct867
Distinct (%)88.0%
Missing79
Missing (%)7.4%
Memory size8.4 KiB
2024-04-11T10:57:37.965972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length45
Mean length25.158376
Min length8

Characters and Unicode

Total characters24781
Distinct characters386
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique783 ?
Unique (%)79.5%

Sample

1st row경기도 광명시 금하로 450
2nd row경기도 광명시 광이로13번길 17-5
3rd row경기도 광명시 광명로 831번지 4의1
4th row경기도 고양시 덕양구 백운길 22
5th row경기도 부천시 평천로 719
ValueCountFrequency (%)
경기도 982
 
17.7%
성남시 123
 
2.2%
수원시 120
 
2.2%
분당구 88
 
1.6%
부천시 87
 
1.6%
고양시 84
 
1.5%
용인시 54
 
1.0%
안산시 50
 
0.9%
안양시 47
 
0.8%
원미구 42
 
0.8%
Other values (1536) 3862
69.7%
2024-04-11T10:57:38.358796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4563
 
18.4%
경 1040
 
4.2%
시 1039
 
4.2%
기 1029
 
4.2%
도 1014
 
4.1%
로 953
 
3.8%
동 845
 
3.4%
1 755
 
3.0%
) 683
 
2.8%
( 683
 
2.8%
Other values (376) 12177
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15028
60.6%
Space Separator 4563
 
18.4%
Decimal Number 3491
 
14.1%
Close Punctuation 685
 
2.8%
Open Punctuation 685
 
2.8%
Other Punctuation 165
 
0.7%
Dash Punctuation 94
 
0.4%
Uppercase Letter 41
 
0.2%
Lowercase Letter 19
 
0.1%
Math Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 1040
 
6.9%
시 1039
 
6.9%
기 1029
 
6.8%
도 1014
 
6.7%
로 953
 
6.3%
동 845
 
5.6%
구 614
 
4.1%
길 322
 
2.1%
원 297
 
2.0%
안 278
 
1.8%
Other values (326) 7597
50.6%
Uppercase Letter
ValueCountFrequency (%)
B 9
22.0%
A 4
9.8%
K 3
 
7.3%
C 3
 
7.3%
E 3
 
7.3%
S 3
 
7.3%
U 2
 
4.9%
L 2
 
4.9%
P 2
 
4.9%
D 1
 
2.4%
Other values (9) 9
22.0%
Lowercase Letter
ValueCountFrequency (%)
o 3
15.8%
c 3
15.8%
e 2
10.5%
a 2
10.5%
m 2
10.5%
t 2
10.5%
l 1
 
5.3%
u 1
 
5.3%
i 1
 
5.3%
s 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 755
21.6%
2 460
13.2%
3 377
10.8%
0 338
9.7%
4 335
9.6%
7 274
 
7.8%
6 263
 
7.5%
5 261
 
7.5%
8 221
 
6.3%
9 207
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 158
95.8%
. 5
 
3.0%
* 2
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 683
99.7%
] 2
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 683
99.7%
[ 2
 
0.3%
Space Separator
ValueCountFrequency (%)
4563
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15028
60.6%
Common 9693
39.1%
Latin 60
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 1040
 
6.9%
시 1039
 
6.9%
기 1029
 
6.8%
도 1014
 
6.7%
로 953
 
6.3%
동 845
 
5.6%
구 614
 
4.1%
길 322
 
2.1%
원 297
 
2.0%
안 278
 
1.8%
Other values (326) 7597
50.6%
Latin
ValueCountFrequency (%)
B 9
 
15.0%
A 4
 
6.7%
o 3
 
5.0%
K 3
 
5.0%
C 3
 
5.0%
E 3
 
5.0%
S 3
 
5.0%
c 3
 
5.0%
e 2
 
3.3%
a 2
 
3.3%
Other values (20) 25
41.7%
Common
ValueCountFrequency (%)
4563
47.1%
1 755
 
7.8%
) 683
 
7.0%
( 683
 
7.0%
2 460
 
4.7%
3 377
 
3.9%
0 338
 
3.5%
4 335
 
3.5%
7 274
 
2.8%
6 263
 
2.7%
Other values (10) 962
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15028
60.6%
ASCII 9753
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4563
46.8%
1 755
 
7.7%
) 683
 
7.0%
( 683
 
7.0%
2 460
 
4.7%
3 377
 
3.9%
0 338
 
3.5%
4 335
 
3.4%
7 274
 
2.8%
6 263
 
2.7%
Other values (40) 1022
 
10.5%
Hangul
ValueCountFrequency (%)
경 1040
 
6.9%
시 1039
 
6.9%
기 1029
 
6.8%
도 1014
 
6.7%
로 953
 
6.3%
동 845
 
5.6%
구 614
 
4.1%
길 322
 
2.1%
원 297
 
2.0%
안 278
 
1.8%
Other values (326) 7597
50.6%

소재지지번주소
Text

Distinct1005
Distinct (%)94.9%
Missing5
Missing (%)0.5%
Memory size8.4 KiB
2024-04-11T10:57:38.564646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length43
Mean length22.508026
Min length7

Characters and Unicode

Total characters23836
Distinct characters338
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique961 ?
Unique (%)90.7%

Sample

1st row경기도 광명시 소하동 1340-3번지
2nd row경기도 광명시 광명동 158-44
3rd row경기도 광명시 광명동 342-12
4th row경기도 고양시 덕양구 지축동 300번지
5th row경기도 부천시 삼정동 314-13
ValueCountFrequency (%)
경기도 1055
 
19.9%
부천시 91
 
1.7%
1호 87
 
1.6%
성남시 81
 
1.5%
수원시 74
 
1.4%
고양시 58
 
1.1%
분당구 52
 
1.0%
성남시분당구 42
 
0.8%
파주시 42
 
0.8%
용인시 42
 
0.8%
Other values (1590) 3688
69.4%
2024-04-11T10:57:38.910996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4760
20.0%
기 1093
 
4.6%
시 1087
 
4.6%
도 1073
 
4.5%
경 1062
 
4.5%
동 1015
 
4.3%
1 923
 
3.9%
지 715
 
3.0%
구 656
 
2.8%
번 620
 
2.6%
Other values (328) 10832
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14514
60.9%
Space Separator 4760
 
20.0%
Decimal Number 4187
 
17.6%
Dash Punctuation 281
 
1.2%
Other Punctuation 29
 
0.1%
Uppercase Letter 26
 
0.1%
Lowercase Letter 14
 
0.1%
Open Punctuation 9
 
< 0.1%
Close Punctuation 9
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1093
 
7.5%
시 1087
 
7.5%
도 1073
 
7.4%
경 1062
 
7.3%
동 1015
 
7.0%
지 715
 
4.9%
구 656
 
4.5%
번 620
 
4.3%
호 565
 
3.9%
원 282
 
1.9%
Other values (286) 6346
43.7%
Uppercase Letter
ValueCountFrequency (%)
B 6
23.1%
E 2
 
7.7%
P 2
 
7.7%
S 2
 
7.7%
L 2
 
7.7%
K 2
 
7.7%
C 2
 
7.7%
I 1
 
3.8%
A 1
 
3.8%
F 1
 
3.8%
Other values (5) 5
19.2%
Decimal Number
ValueCountFrequency (%)
1 923
22.0%
3 508
12.1%
2 476
11.4%
4 383
9.1%
5 370
8.8%
0 347
 
8.3%
6 342
 
8.2%
7 300
 
7.2%
8 270
 
6.4%
9 268
 
6.4%
Lowercase Letter
ValueCountFrequency (%)
e 3
21.4%
a 2
14.3%
m 2
14.3%
c 1
 
7.1%
l 1
 
7.1%
t 1
 
7.1%
u 1
 
7.1%
i 1
 
7.1%
r 1
 
7.1%
o 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 22
75.9%
. 7
 
24.1%
Space Separator
ValueCountFrequency (%)
4760
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 281
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14514
60.9%
Common 9282
38.9%
Latin 40
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1093
 
7.5%
시 1087
 
7.5%
도 1073
 
7.4%
경 1062
 
7.3%
동 1015
 
7.0%
지 715
 
4.9%
구 656
 
4.5%
번 620
 
4.3%
호 565
 
3.9%
원 282
 
1.9%
Other values (286) 6346
43.7%
Latin
ValueCountFrequency (%)
B 6
 
15.0%
e 3
 
7.5%
E 2
 
5.0%
P 2
 
5.0%
S 2
 
5.0%
L 2
 
5.0%
K 2
 
5.0%
a 2
 
5.0%
m 2
 
5.0%
C 2
 
5.0%
Other values (15) 15
37.5%
Common
ValueCountFrequency (%)
4760
51.3%
1 923
 
9.9%
3 508
 
5.5%
2 476
 
5.1%
4 383
 
4.1%
5 370
 
4.0%
0 347
 
3.7%
6 342
 
3.7%
7 300
 
3.2%
- 281
 
3.0%
Other values (7) 592
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14514
60.9%
ASCII 9322
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4760
51.1%
1 923
 
9.9%
3 508
 
5.4%
2 476
 
5.1%
4 383
 
4.1%
5 370
 
4.0%
0 347
 
3.7%
6 342
 
3.7%
7 300
 
3.2%
- 281
 
3.0%
Other values (32) 632
 
6.8%
Hangul
ValueCountFrequency (%)
기 1093
 
7.5%
시 1087
 
7.5%
도 1073
 
7.4%
경 1062
 
7.3%
동 1015
 
7.0%
지 715
 
4.9%
구 656
 
4.5%
번 620
 
4.3%
호 565
 
3.9%
원 282
 
1.9%
Other values (286) 6346
43.7%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct898
Distinct (%)88.6%
Missing51
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean37.433557
Minimum36.976333
Maximum38.090166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.5 KiB
2024-04-11T10:57:39.035168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.976333
5-th percentile37.127812
Q137.293979
median37.397528
Q337.591933
95-th percentile37.763409
Maximum38.090166
Range1.1138325
Interquartile range (IQR)0.29795387

Descriptive statistics

Standard deviation0.20061931
Coefficient of variation (CV)0.0053593441
Kurtosis0.09339847
Mean37.433557
Median Absolute Deviation (MAD)0.11668149
Skewness0.37628654
Sum37920.193
Variance0.040248108
MonotonicityNot monotonic
2024-04-11T10:57:39.154469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4130257 5
 
0.5%
37.5025517408 5
 
0.5%
37.280846809 4
 
0.4%
37.6131390076 4
 
0.4%
37.4751822 4
 
0.4%
37.5040675095 4
 
0.4%
37.2700608855 3
 
0.3%
37.6126971 3
 
0.3%
37.4095555385 3
 
0.3%
37.5041752477 3
 
0.3%
Other values (888) 975
91.6%
(Missing) 51
 
4.8%
ValueCountFrequency (%)
36.9763331411 1
0.1%
36.9852830383 1
0.1%
36.98766163 1
0.1%
36.9883462779 1
0.1%
36.9886134 1
0.1%
36.9902412081 1
0.1%
36.9919006082 1
0.1%
36.9942489 1
0.1%
36.9945235041 2
0.2%
36.9949133 1
0.1%
ValueCountFrequency (%)
38.0901656506 1
0.1%
38.08994227 1
0.1%
38.0282034881 1
0.1%
38.02715987 1
0.1%
38.0270658075 1
0.1%
38.0205662112 1
0.1%
37.9604678893 1
0.1%
37.95977517 1
0.1%
37.9596084172 1
0.1%
37.9587528035 1
0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct898
Distinct (%)88.6%
Missing51
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean126.99286
Minimum126.59743
Maximum127.7532
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.5 KiB
2024-04-11T10:57:39.295188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.59743
5-th percentile126.73682
Q1126.81432
median127.0075
Q3127.12271
95-th percentile127.31922
Maximum127.7532
Range1.1557677
Interquartile range (IQR)0.30838855

Descriptive statistics

Standard deviation0.19638655
Coefficient of variation (CV)0.0015464377
Kurtosis0.64262899
Mean126.99286
Median Absolute Deviation (MAD)0.13378729
Skewness0.63194432
Sum128643.77
Variance0.038567676
MonotonicityNot monotonic
2024-04-11T10:57:39.424641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1272138 5
 
0.5%
126.7753741701 5
 
0.5%
126.976018037 4
 
0.4%
127.1409110928 4
 
0.4%
126.8670629 4
 
0.4%
126.7639551478 4
 
0.4%
127.0636056648 3
 
0.3%
127.1408759 3
 
0.3%
127.2612452109 3
 
0.3%
126.7566905848 3
 
0.3%
Other values (888) 975
91.6%
(Missing) 51
 
4.8%
ValueCountFrequency (%)
126.597429208 1
0.1%
126.5984311406 1
0.1%
126.5993151 1
0.1%
126.5997011 1
0.1%
126.6195226475 1
0.1%
126.6199103324 1
0.1%
126.6235251 1
0.1%
126.623703 1
0.1%
126.6237054005 1
0.1%
126.6238085 1
0.1%
ValueCountFrequency (%)
127.7531969 1
0.1%
127.7363222241 1
0.1%
127.6539289238 1
0.1%
127.6374429 1
0.1%
127.635666647 1
0.1%
127.6350809464 1
0.1%
127.6342892 1
0.1%
127.6312509 1
0.1%
127.6298805484 1
0.1%
127.6122725791 1
0.1%

Interactions

2024-04-11T10:57:35.040613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T10:57:34.817642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T10:57:35.132236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T10:57:34.948085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-11T10:57:39.509000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명시설구분명WGS84위도WGS84경도
시군명1.0000.4700.9780.952
시설구분명0.4701.0000.2730.258
WGS84위도0.9780.2731.0000.690
WGS84경도0.9520.2580.6901.000
2024-04-11T10:57:39.601704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명시설구분명
시군명1.0000.395
시설구분명0.3951.000
2024-04-11T10:57:39.671290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WGS84위도WGS84경도시군명시설구분명
WGS84위도1.000-0.3090.8400.169
WGS84경도-0.3091.0000.7310.159
시군명0.8400.7311.0000.395
시설구분명0.1690.1590.3951.000

Missing values

2024-04-11T10:57:35.260494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-11T10:57:35.375658image/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.
2024-04-11T10:57:35.494189image/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

시군명시설구분명시장명전화번호소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도
0광명시로컬푸드직매장광명농협 로컬푸드 직매장02-2169-809214316경기도 광명시 금하로 450경기도 광명시 소하동 1340-3번지37.448321126.882294
1<NA>전통시장<NA>02-2614-000614220경기도 광명시 광이로13번길 17-5경기도 광명시 광명동 158-4437.479948126.856165
2<NA>전통시장<NA>02-2614-529214291경기도 광명시 광명로 831번지 4의1경기도 광명시 광명동 342-1237.473654126.8514
3고양시로컬푸드직매장신도농협 로컬푸드직매장02-381-010010584경기도 고양시 덕양구 백운길 22경기도 고양시 덕양구 지축동 300번지37.652333126.934864
4<NA>전통시장<NA>02-754-738914495경기도 부천시 평천로 719경기도 부천시 삼정동 314-1337.515338126.770583
5<NA>전통시장<NA>031-1566-549116285경기도 수원시 장안구 조원로89번길 8 조원동경기도 수원시 장안구 조원동 743-737.300784127.015338
6<NA>전통시장<NA>031-211-393616531경기도 수원시 영통구 매여울로53번길 50-1 매탄동경기도 수원시 영통구 매탄동 172-7237.272603127.041922
7화성시로컬푸드직매장태안농협 로컬푸드직매장031-221-021118341경기도 화성시 기안남로 70경기도 화성시 기안동 457-22번지37.224086126.9842
8<NA>전통시장<NA>031-224-789316461경기도 수원시 팔달구 권선로 477 매산로2가경기도 수원시 팔달구 매산로2가 9037.264571127.003354
9<NA>전통시장<NA>031-237-090316566경기도 수원시 권선구 세권로 185 권선동경기도 수원시 권선동 105137.256099127.02458
시군명시설구분명시장명전화번호소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도
1054연천군대규모점포전곡재래시장<NA>11033경기도 연천군 전곡읍 전곡로172번길 4-19, 경기도상인연합회연천군전곡지부경기도 연천군 전곡읍 전곡리 479-31 경기도상인연합회연천군전곡지부38.027066127.068178
1055남양주시대규모점포다산역 데시앙 상업시설<NA><NA><NA>경기도 남양주시 다산동 605637.625368127.153281
1056수원시대규모점포롯데쇼핑(주) 롯데슈퍼 정자점<NA>16334경기도 수원시 장안구 정자천로 187 (정자동)경기도 수원시 장안구 정자동 874-2번지37.296561126.995462
1057수원시대규모점포홈플러스 익스프레스 수원이의점<NA>16512경기도 수원시 영통구 광교중앙로266번길 20 (하동)경기도 수원시 영통구 하동 983-437.292831127.068653
1058부천시대규모점포GS THE FRESH 부천범박점<NA>14783경기도 부천시 소사구 양지로 88, 보광빌딩 1층 (범박동)경기도 부천시 소사구 범박동 210-1 보광빌딩37.473093126.812685
1059수원시대규모점포스타필드 수원<NA>16318경기도 수원시 장안구 수성로 175경기도 수원시 장안구 정자동 111-10 외 3필지37.287441126.991563
1060성남시대규모점포GS THE FRESH 분당이매역점<NA>13567경기도 성남시 분당구 이매로 45, 이수프라자 (이매동)경기도 성남시 분당구 이매동 115-2 이수프라자37.394981127.125889
1061수원시대규모점포노브랜드 스타필드수원점<NA>16318경기도 수원시 장안구 수성로 175경기도 수원시 장안구 정자동 111-10 외 3필지, 지하2층37.287441126.991563
1062평택시대규모점포GS THE FRESH 평택고덕점<NA>18014경기도 평택시 고덕국제3길 143, 101호 (고덕동)경기도 평택시 고덕동 1956-137.050399127.047637
1063의정부시대규모점포홈플러스의정부점<NA>11757경기도 의정부시 청사로 38 (금오동)경기도 의정부시 금오동 475번지 1호37.75217127.071018

Duplicate rows

Most frequently occurring

시군명시설구분명시장명전화번호소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도# duplicates
3부천시대규모점포(주)GS리테일GS스퀘어부천점<NA>14548경기도 부천시 원미구 길주로 300 (중동)경기도 부천시 원미구중동 1140호37.502552126.7753744
0광명시대규모점포철산중앙시장<NA>14239<NA>경기도 광명시 철산동 440호37.474789126.8703192
1광명시대규모점포파보레쇼핑몰<NA>14237경기도 광명시 철산로 4 (철산동)경기도 광명시 철산동 261호37.475182126.8670632
2동두천시대규모점포롯데쇼핑(주)롯데슈퍼동두천점<NA>483030경기도 동두천시 평화로 2375 (생연동)경기도 동두천시 생연동 722번지37.899638127.0567292
4부천시대규모점포투나<NA>420-713경기도 부천시 원미구 부일로 223 (상동,투나)경기도 부천시 원미구상동 461번지 투나37.48888126.7552922
5수원시대규모점포세파월드<NA>16491경기도 수원시 팔달구 권광로 138 (인계동)경기도 수원시팔달구 인계동 1131호37.259888127.0316252
6수원시대규모점포수원축산농협 하나로마트<NA>16670경기도 수원시 권선구 곡반정로 121 (곡반정동)[*미고시]경기도 수원시 권선구 곡반정동 555번지37.238981127.0307172
7시흥시대규모점포시화유통상가사업협동조합<NA><NA><NA>경기도 시흥시 정왕동 호 시화공단 3다 3다<NA><NA>2
8의왕시대규모점포롯데쇼핑(주)롯데마트 의왕점<NA>16036경기도 의왕시 계원대학로 7 (내손동)경기도 의왕시 내손동 743호37.380165126.9736162