Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells4926
Missing cells (%)6.2%
Duplicate rows3
Duplicate rows (%)< 0.1%
Total size in memory722.7 KiB
Average record size in memory74.0 B

Variable types

Text4
Categorical1
Numeric2
DateTime1

Dataset

Description지역경제 활성화를 위하여 포항시장이 발행하는 포항사랑 상품권 가맹정 현황 자료
Author경상북도 포항시
URLhttps://www.data.go.kr/data/15030170/fileData.do

Alerts

데이터 기준일자 has constant value ""Constant
Dataset has 3 (< 0.1%) duplicate rowsDuplicates
위도 is highly overall correlated with 행정동High correlation
경도 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
연락처 has 4155 (41.5%) missing valuesMissing
업태 has 771 (7.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 10:24:41.601712
Analysis finished2023-12-12 10:24:44.251746
Duration2.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

Distinct9694
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T19:24:44.570599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length6.3914
Min length1

Characters and Unicode

Total characters63914
Distinct characters1040
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9433 ?
Unique (%)94.3%

Sample

1st row도움터 어린이집
2nd row치키치키통닭집
3rd row강변마트
4th row아임파인
5th row물빛
ValueCountFrequency (%)
노점 68
 
0.6%
주식회사 63
 
0.5%
포항점 48
 
0.4%
포항 39
 
0.3%
씨유 28
 
0.2%
죽도농산물시장 27
 
0.2%
㈜ 26
 
0.2%
죽도시장 25
 
0.2%
gs25 22
 
0.2%
세븐일레븐 20
 
0.2%
Other values (10464) 11913
97.0%
2023-12-12T19:24:45.178664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2282
 
3.6%
점 1497
 
2.3%
이 1138
 
1.8%
포 1136
 
1.8%
스 932
 
1.5%
항 872
 
1.4%
리 829
 
1.3%
원 749
 
1.2%
식 724
 
1.1%
장 702
 
1.1%
Other values (1030) 53053
83.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57021
89.2%
Space Separator 2282
 
3.6%
Uppercase Letter 1303
 
2.0%
Decimal Number 863
 
1.4%
Lowercase Letter 859
 
1.3%
Close Punctuation 621
 
1.0%
Open Punctuation 617
 
1.0%
Other Punctuation 172
 
0.3%
Other Symbol 140
 
0.2%
Dash Punctuation 31
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1497
 
2.6%
이 1138
 
2.0%
포 1136
 
2.0%
스 932
 
1.6%
항 872
 
1.5%
리 829
 
1.5%
원 749
 
1.3%
식 724
 
1.3%
장 702
 
1.2%
사 697
 
1.2%
Other values (952) 47745
83.7%
Uppercase Letter
ValueCountFrequency (%)
S 139
 
10.7%
C 108
 
8.3%
G 101
 
7.8%
O 85
 
6.5%
E 79
 
6.1%
A 70
 
5.4%
T 66
 
5.1%
N 58
 
4.5%
B 57
 
4.4%
M 54
 
4.1%
Other values (16) 486
37.3%
Lowercase Letter
ValueCountFrequency (%)
e 131
15.3%
a 85
 
9.9%
o 80
 
9.3%
n 61
 
7.1%
i 60
 
7.0%
l 59
 
6.9%
r 41
 
4.8%
c 35
 
4.1%
t 35
 
4.1%
s 35
 
4.1%
Other values (15) 237
27.6%
Decimal Number
ValueCountFrequency (%)
2 184
21.3%
1 141
16.3%
5 131
15.2%
4 77
8.9%
3 76
8.8%
0 66
 
7.6%
8 60
 
7.0%
9 49
 
5.7%
7 49
 
5.7%
6 30
 
3.5%
Other Punctuation
ValueCountFrequency (%)
. 54
31.4%
, 50
29.1%
& 47
27.3%
# 8
 
4.7%
! 4
 
2.3%
· 3
 
1.7%
＆ 2
 
1.2%
: 2
 
1.2%
/ 1
 
0.6%
* 1
 
0.6%
Math Symbol
ValueCountFrequency (%)
+ 3
60.0%
= 2
40.0%
Space Separator
ValueCountFrequency (%)
2282
100.0%
Close Punctuation
ValueCountFrequency (%)
) 621
100.0%
Open Punctuation
ValueCountFrequency (%)
( 617
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 140
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57154
89.4%
Common 4591
 
7.2%
Latin 2162
 
3.4%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1497
 
2.6%
이 1138
 
2.0%
포 1136
 
2.0%
스 932
 
1.6%
항 872
 
1.5%
리 829
 
1.5%
원 749
 
1.3%
식 724
 
1.3%
장 702
 
1.2%
사 697
 
1.2%
Other values (947) 47878
83.8%
Latin
ValueCountFrequency (%)
S 139
 
6.4%
e 131
 
6.1%
C 108
 
5.0%
G 101
 
4.7%
a 85
 
3.9%
O 85
 
3.9%
o 80
 
3.7%
E 79
 
3.7%
A 70
 
3.2%
T 66
 
3.1%
Other values (41) 1218
56.3%
Common
ValueCountFrequency (%)
2282
49.7%
) 621
 
13.5%
( 617
 
13.4%
2 184
 
4.0%
1 141
 
3.1%
5 131
 
2.9%
4 77
 
1.7%
3 76
 
1.7%
0 66
 
1.4%
8 60
 
1.3%
Other values (16) 336
 
7.3%
Han
ValueCountFrequency (%)
美 2
28.6%
花 1
14.3%
家 1
14.3%
海 1
14.3%
串 1
14.3%
乳 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57013
89.2%
ASCII 6748
 
10.6%
None 145
 
0.2%
CJK 7
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2282
33.8%
) 621
 
9.2%
( 617
 
9.1%
2 184
 
2.7%
1 141
 
2.1%
S 139
 
2.1%
e 131
 
1.9%
5 131
 
1.9%
C 108
 
1.6%
G 101
 
1.5%
Other values (65) 2293
34.0%
Hangul
ValueCountFrequency (%)
점 1497
 
2.6%
이 1138
 
2.0%
포 1136
 
2.0%
스 932
 
1.6%
항 872
 
1.5%
리 829
 
1.5%
원 749
 
1.3%
식 724
 
1.3%
장 702
 
1.2%
사 697
 
1.2%
Other values (945) 47737
83.7%
None
ValueCountFrequency (%)
㈜ 140
96.6%
· 3
 
2.1%
＆ 2
 
1.4%
CJK
ValueCountFrequency (%)
美 2
28.6%
花 1
14.3%
家 1
14.3%
海 1
14.3%
串 1
14.3%
乳 1
14.3%
Compat Jamo
ValueCountFrequency (%)
ㅋ 1
100.0%

연락처
Text

MISSING 

Distinct5723
Distinct (%)97.9%
Missing4155
Missing (%)41.5%
Memory size156.2 KiB
2023-12-12T19:24:45.469427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.005988
Min length9

Characters and Unicode

Total characters70175
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

Unique5606 ?
Unique (%)95.9%

Sample

1st row054-231-7743
2nd row054-285-3765
3rd row054-281-5344
4th row054-273-2929
5th row054-256-8598
ValueCountFrequency (%)
054-285-2030 3
 
0.1%
054-244-0292 3
 
0.1%
054-255-2229 3
 
0.1%
054-285-9989 3
 
0.1%
054-282-0500 3
 
0.1%
054-278-7575 2
 
< 0.1%
054-252-8180 2
 
< 0.1%
054-243-1583 2
 
< 0.1%
054-262-2438 2
 
< 0.1%
054-261-0947 2
 
< 0.1%
Other values (5713) 5820
99.6%
2023-12-12T19:24:45.887647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 11684
16.6%
4 9588
13.7%
5 9531
13.6%
2 9504
13.5%
0 9281
13.2%
7 4179
 
6.0%
8 3670
 
5.2%
1 3425
 
4.9%
3 3317
 
4.7%
6 3037
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58491
83.4%
Dash Punctuation 11684
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 9588
16.4%
5 9531
16.3%
2 9504
16.2%
0 9281
15.9%
7 4179
7.1%
8 3670
 
6.3%
1 3425
 
5.9%
3 3317
 
5.7%
6 3037
 
5.2%
9 2959
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 11684
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70175
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 11684
16.6%
4 9588
13.7%
5 9531
13.6%
2 9504
13.5%
0 9281
13.2%
7 4179
 
6.0%
8 3670
 
5.2%
1 3425
 
4.9%
3 3317
 
4.7%
6 3037
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 11684
16.6%
4 9588
13.7%
5 9531
13.6%
2 9504
13.5%
0 9281
13.2%
7 4179
 
6.0%
8 3670
 
5.2%
1 3425
 
4.9%
3 3317
 
4.7%
6 3037
 
4.3%

업태
Text

MISSING 

Distinct1580
Distinct (%)17.1%
Missing771
Missing (%)7.7%
Memory size156.2 KiB
2023-12-12T19:24:46.233415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length2
Mean length3.0456171
Min length1

Characters and Unicode

Total characters28108
Distinct characters478
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1101 ?
Unique (%)11.9%

Sample

1st row기타
2nd row슈퍼
3rd row비알콜 음료점
4th row호프주점업
5th row건어물
ValueCountFrequency (%)
한식 1065
 
11.3%
음식 520
 
5.5%
도소매 451
 
4.8%
소매 446
 
4.7%
서비스 401
 
4.2%
의류 236
 
2.5%
음숙 206
 
2.2%
슈퍼 187
 
2.0%
미용 168
 
1.8%
편의점 113
 
1.2%
Other values (1516) 5664
59.9%
2023-12-12T19:24:46.774573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 2706
 
9.6%
음 1297
 
4.6%
매 1234
 
4.4%
소 1233
 
4.4%
한 1187
 
4.2%
도 641
 
2.3%
점 631
 
2.2%
업 611
 
2.2%
비 584
 
2.1%
스 573
 
2.0%
Other values (468) 17411
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27229
96.9%
Other Punctuation 534
 
1.9%
Space Separator 242
 
0.9%
Uppercase Letter 51
 
0.2%
Close Punctuation 30
 
0.1%
Open Punctuation 16
 
0.1%
Lowercase Letter 3
 
< 0.1%
Decimal Number 2
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 2706
 
9.9%
음 1297
 
4.8%
매 1234
 
4.5%
소 1233
 
4.5%
한 1187
 
4.4%
도 641
 
2.4%
점 631
 
2.3%
업 611
 
2.2%
비 584
 
2.1%
스 573
 
2.1%
Other values (446) 16532
60.7%
Uppercase Letter
ValueCountFrequency (%)
P 15
29.4%
L 12
23.5%
G 10
19.6%
C 7
13.7%
A 2
 
3.9%
E 1
 
2.0%
D 1
 
2.0%
S 1
 
2.0%
V 1
 
2.0%
T 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 523
97.9%
. 8
 
1.5%
/ 3
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
g 1
33.3%
p 1
33.3%
l 1
33.3%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
242
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27228
96.9%
Common 825
 
2.9%
Latin 54
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 2706
 
9.9%
음 1297
 
4.8%
매 1234
 
4.5%
소 1233
 
4.5%
한 1187
 
4.4%
도 641
 
2.4%
점 631
 
2.3%
업 611
 
2.2%
비 584
 
2.1%
스 573
 
2.1%
Other values (445) 16531
60.7%
Latin
ValueCountFrequency (%)
P 15
27.8%
L 12
22.2%
G 10
18.5%
C 7
13.0%
A 2
 
3.7%
E 1
 
1.9%
D 1
 
1.9%
g 1
 
1.9%
p 1
 
1.9%
l 1
 
1.9%
Other values (3) 3
 
5.6%
Common
ValueCountFrequency (%)
, 523
63.4%
242
29.3%
) 30
 
3.6%
( 16
 
1.9%
. 8
 
1.0%
/ 3
 
0.4%
` 1
 
0.1%
3 1
 
0.1%
2 1
 
0.1%
Han
ValueCountFrequency (%)
外 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27228
96.9%
ASCII 879
 
3.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 2706
 
9.9%
음 1297
 
4.8%
매 1234
 
4.5%
소 1233
 
4.5%
한 1187
 
4.4%
도 641
 
2.4%
점 631
 
2.3%
업 611
 
2.2%
비 584
 
2.1%
스 573
 
2.1%
Other values (445) 16531
60.7%
ASCII
ValueCountFrequency (%)
, 523
59.5%
242
27.5%
) 30
 
3.4%
( 16
 
1.8%
P 15
 
1.7%
L 12
 
1.4%
G 10
 
1.1%
. 8
 
0.9%
C 7
 
0.8%
/ 3
 
0.3%
Other values (12) 13
 
1.5%
CJK
ValueCountFrequency (%)
外 1
100.0%

행정동
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
죽도동
1177 
장량동
1051 
오천읍
874 
중앙동
855 
상대동
732 
Other values (24)
5311 

Length

Max length4
Median length3
Mean length3.0336
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row장량동
2nd row연일읍
3rd row해도동
4th row송도동
5th row해도동

Common Values

ValueCountFrequency (%)
죽도동 1177
11.8%
장량동 1051
 
10.5%
오천읍 874
 
8.7%
중앙동 855
 
8.6%
상대동 732
 
7.3%
흥해읍 629
 
6.3%
대이동 587
 
5.9%
연일읍 473
 
4.7%
해도동 466
 
4.7%
두호동 420
 
4.2%
Other values (19) 2736
27.4%

Length

2023-12-12T19:24:46.907080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
죽도동 1177
11.8%
장량동 1051
 
10.5%
오천읍 874
 
8.7%
중앙동 855
 
8.6%
상대동 732
 
7.3%
흥해읍 629
 
6.3%
대이동 587
 
5.9%
연일읍 473
 
4.7%
해도동 466
 
4.7%
두호동 420
 
4.2%
Other values (19) 2736
27.4%

도로명 주소
Text

Distinct9319
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T19:24:47.222944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length53
Mean length27.464
Min length16

Characters and Unicode

Total characters274640
Distinct characters403
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8795 ?
Unique (%)87.9%

Sample

1st row경상북도 포항시 북구 장량로31번길 53-6 (장성동)
2nd row경상북도 포항시 남구 연일읍 연일로 130, 107호(형산강변상가)
3rd row경상북도 포항시 남구 희망대로 1003 (해도동)
4th row경상북도 포항시 남구 송도해안길112번길 2
5th row경상북도 포항시 남구 해동로 26-1(해도동)
ValueCountFrequency (%)
포항시 10011
17.3%
경상북도 10000
17.3%
북구 5367
 
9.3%
남구 4623
 
8.0%
오천읍 865
 
1.5%
흥해읍 629
 
1.1%
연일읍 470
 
0.8%
1층 466
 
0.8%
중앙로 431
 
0.7%
죽도동 338
 
0.6%
Other values (7305) 24720
42.7%
2023-12-12T19:24:47.681632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48659
 
17.7%
북 15429
 
5.6%
도 13104
 
4.8%
상 11485
 
4.2%
포 10814
 
3.9%
1 10653
 
3.9%
시 10564
 
3.8%
구 10541
 
3.8%
항 10226
 
3.7%
경 10054
 
3.7%
Other values (393) 123111
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 167108
60.8%
Space Separator 48659
 
17.7%
Decimal Number 40589
 
14.8%
Open Punctuation 6069
 
2.2%
Close Punctuation 6068
 
2.2%
Other Punctuation 3202
 
1.2%
Dash Punctuation 2749
 
1.0%
Uppercase Letter 152
 
0.1%
Math Symbol 29
 
< 0.1%
Lowercase Letter 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 15429
 
9.2%
도 13104
 
7.8%
상 11485
 
6.9%
포 10814
 
6.5%
시 10564
 
6.3%
구 10541
 
6.3%
항 10226
 
6.1%
경 10054
 
6.0%
로 8259
 
4.9%
동 7659
 
4.6%
Other values (347) 58973
35.3%
Uppercase Letter
ValueCountFrequency (%)
B 47
30.9%
A 39
25.7%
K 12
 
7.9%
C 11
 
7.2%
D 8
 
5.3%
S 7
 
4.6%
L 6
 
3.9%
T 5
 
3.3%
P 2
 
1.3%
M 2
 
1.3%
Other values (9) 13
 
8.6%
Decimal Number
ValueCountFrequency (%)
1 10653
26.2%
2 5606
13.8%
3 4402
10.8%
4 3482
 
8.6%
0 3395
 
8.4%
5 3212
 
7.9%
6 2781
 
6.9%
7 2641
 
6.5%
8 2272
 
5.6%
9 2145
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
e 4
28.6%
c 2
14.3%
b 2
14.3%
w 2
14.3%
r 1
 
7.1%
o 1
 
7.1%
k 1
 
7.1%
s 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 3133
97.8%
. 65
 
2.0%
/ 4
 
0.1%
Space Separator
ValueCountFrequency (%)
48659
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6069
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6068
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2749
100.0%
Math Symbol
ValueCountFrequency (%)
~ 29
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 167108
60.8%
Common 107366
39.1%
Latin 166
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 15429
 
9.2%
도 13104
 
7.8%
상 11485
 
6.9%
포 10814
 
6.5%
시 10564
 
6.3%
구 10541
 
6.3%
항 10226
 
6.1%
경 10054
 
6.0%
로 8259
 
4.9%
동 7659
 
4.6%
Other values (347) 58973
35.3%
Latin
ValueCountFrequency (%)
B 47
28.3%
A 39
23.5%
K 12
 
7.2%
C 11
 
6.6%
D 8
 
4.8%
S 7
 
4.2%
L 6
 
3.6%
T 5
 
3.0%
e 4
 
2.4%
c 2
 
1.2%
Other values (17) 25
15.1%
Common
ValueCountFrequency (%)
48659
45.3%
1 10653
 
9.9%
( 6069
 
5.7%
) 6068
 
5.7%
2 5606
 
5.2%
3 4402
 
4.1%
4 3482
 
3.2%
0 3395
 
3.2%
5 3212
 
3.0%
, 3133
 
2.9%
Other values (9) 12687
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 167108
60.8%
ASCII 107532
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48659
45.3%
1 10653
 
9.9%
( 6069
 
5.6%
) 6068
 
5.6%
2 5606
 
5.2%
3 4402
 
4.1%
4 3482
 
3.2%
0 3395
 
3.2%
5 3212
 
3.0%
, 3133
 
2.9%
Other values (36) 12853
 
12.0%
Hangul
ValueCountFrequency (%)
북 15429
 
9.2%
도 13104
 
7.8%
상 11485
 
6.9%
포 10814
 
6.5%
시 10564
 
6.3%
구 10541
 
6.3%
항 10226
 
6.1%
경 10054
 
6.0%
로 8259
 
4.9%
동 7659
 
4.6%
Other values (347) 58973
35.3%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct7984
Distinct (%)79.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.035717
Minimum35.842741
Maximum36.320909
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:24:47.839646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.842741
5-th percentile35.966852
Q136.010038
median36.031526
Q336.062163
95-th percentile36.11047
Maximum36.320909
Range0.4781679
Interquartile range (IQR)0.052124275

Descriptive statistics

Standard deviation0.047626781
Coefficient of variation (CV)0.0013216549
Kurtosis3.4956688
Mean36.035717
Median Absolute Deviation (MAD)0.02516695
Skewness0.964368
Sum360357.17
Variance0.0022683103
MonotonicityNot monotonic
2023-12-12T19:24:48.001496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.0818247 27
 
0.3%
36.0362603 21
 
0.2%
36.01274069 17
 
0.2%
36.03958347 16
 
0.2%
36.0358905 16
 
0.2%
36.0364191 13
 
0.1%
36.0840359 13
 
0.1%
36.0289336 13
 
0.1%
36.0085672 12
 
0.1%
36.0126269 11
 
0.1%
Other values (7974) 9841
98.4%
ValueCountFrequency (%)
35.842741 1
< 0.1%
35.84456244 1
< 0.1%
35.8601128 1
< 0.1%
35.8622986 1
< 0.1%
35.8625479 1
< 0.1%
35.8768807 1
< 0.1%
35.8773422 1
< 0.1%
35.8774267 1
< 0.1%
35.8775609 1
< 0.1%
35.8775833 1
< 0.1%
ValueCountFrequency (%)
36.3209089 1
< 0.1%
36.3037448 1
< 0.1%
36.2666216 1
< 0.1%
36.2650112 1
< 0.1%
36.2643759 1
< 0.1%
36.2624625 1
< 0.1%
36.2623273 1
< 0.1%
36.2588453 1
< 0.1%
36.25563 1
< 0.1%
36.2542736 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct7905
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.3727
Minimum129.02403
Maximum129.57995
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:24:48.142946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.02403
5-th percentile129.33013
Q1129.35093
median129.36674
Q3129.38489
95-th percentile129.4481
Maximum129.57995
Range0.5559234
Interquartile range (IQR)0.0339624

Descriptive statistics

Standard deviation0.051433031
Coefficient of variation (CV)0.00039755708
Kurtosis9.2740302
Mean129.3727
Median Absolute Deviation (MAD)0.01667805
Skewness0.5135356
Sum1293727
Variance0.0026453567
MonotonicityNot monotonic
2023-12-12T19:24:48.293507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.3366261 27
 
0.3%
129.3688268 21
 
0.2%
129.3489248 18
 
0.2%
129.369506 16
 
0.2%
129.3654382 16
 
0.2%
129.4004716 13
 
0.1%
129.3681417 13
 
0.1%
129.3240324 13
 
0.1%
129.3304543 12
 
0.1%
129.3561426 11
 
0.1%
Other values (7895) 9840
98.4%
ValueCountFrequency (%)
129.024027 1
< 0.1%
129.0250927 1
< 0.1%
129.0276045 1
< 0.1%
129.0412552 1
< 0.1%
129.0552065 1
< 0.1%
129.0698173 1
< 0.1%
129.0777274 1
< 0.1%
129.0781712 1
< 0.1%
129.0790732 1
< 0.1%
129.0868058 2
< 0.1%
ValueCountFrequency (%)
129.5799504 1
< 0.1%
129.5795216 1
< 0.1%
129.5795101 1
< 0.1%
129.579456 2
< 0.1%
129.5794309 1
< 0.1%
129.5793959 1
< 0.1%
129.5790273 2
< 0.1%
129.5785594 1
< 0.1%
129.5783918 1
< 0.1%
129.578361 1
< 0.1%

데이터 기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-11-29 00:00:00
Maximum2020-11-29 00:00:00
2023-12-12T19:24:48.421019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:48.544324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T19:24:43.631849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:43.425405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:43.747730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:43.537150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:24:48.611921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동위도경도
행정동1.0000.9470.960
위도0.9471.0000.800
경도0.9600.8001.000
2023-12-12T19:24:48.699805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도행정동
위도1.000-0.1180.727
경도-0.1181.0000.776
행정동0.7270.7761.000

Missing values

2023-12-12T19:24:43.898527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:24:44.062079image/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.
2023-12-12T19:24:44.186186image/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

업체명연락처업태행정동도로명 주소위도경도데이터 기준일자
10866도움터 어린이집054-231-7743기타장량동경상북도 포항시 북구 장량로31번길 53-6 (장성동)36.087617129.3845362020-11-29
5628치키치키통닭집054-285-3765<NA>연일읍경상북도 포항시 남구 연일읍 연일로 130, 107호(형산강변상가)35.99992129.3426692020-11-29
1546강변마트<NA>슈퍼해도동경상북도 포항시 남구 희망대로 1003 (해도동)36.020989129.3751032020-11-29
15456아임파인<NA>비알콜 음료점송도동경상북도 포항시 남구 송도해안길112번길 236.040305129.3766222020-11-29
8289물빛<NA>호프주점업해도동경상북도 포항시 남구 해동로 26-1(해도동)36.021768129.3739182020-11-29
7678신안상회<NA>건어물죽도동경상북도 포항시 북구 죽도시장11길 8 (죽도동)36.035761129.3681452020-11-29
13168롯데아이스크림 흥해대리점<NA>슈퍼흥해읍경상북도 포항시 북구 흥해읍 흥해로 45-836.10957129.3463992020-11-29
14577르네상스여관054-281-5344여관죽도동경상북도 포항시 북구 죽도로20번길 5(죽도동)36.033928129.3630212020-11-29
13111포항재래식손두부054-273-2929한식오천읍경상북도 포항시 남구 오천읍 문덕로53번길20-24,1층35.957306129.4058292020-11-29
14277다윈커머스054-256-8598도소매상대동경상북도 포항시 남구 중흥로 77,그랜드애비뉴 5층36.012741129.3489252020-11-29
업체명연락처업태행정동도로명 주소위도경도데이터 기준일자
10886더 나이스 플라이데이<NA>음식장량동경상북도 포항시 북구 새천년대로 1220 (장성동)36.072464129.380972020-11-29
4773화진펜션매점054-262-0243식잡송라면경상북도 포항시 북구 송라면 동해대로 332036.258845129.3738182020-11-29
11614경빈석유054-261-1818소매흥해읍경상북도 포항시 북구 흥해읍 용금길11번길 136.14116129.3508352020-11-29
15831원테크<NA>소매대이동경상북도 포항시 남구 새천년대로460번길 13-4(대잠동,1층)36.016166129.3479062020-11-29
13845JDX(제이디엑스골프)<NA>그랜드애비뉴)상대동경상북도 포항시 남구 중흥로 77, 5층(상도동,그랜드애비뉴)36.012741129.3489252020-11-29
11054진아농산물상회<NA>도소매죽도동경상북도 포항시 북구 중흥로321번길 21 (죽도동)36.03182129.3621732020-11-29
1882온누리피아노교습소054-281-7349예능상대동경상북도 포항시 남구 포스코대로353번길 18 (대도동)36.018461129.3632682020-11-29
10785태백이054-274-9288음식점상대동경상북도 포항시 남구 상도로 62-1(상도동)36.014232129.3551012020-11-29
4646환여종합건재철물054-252-4981철물, 건재환여동경상북도 포항시 북구 삼호로 486-1(환호동)36.071483129.3992952020-11-29
14109까망뷰티<NA>이용실장량동경상북도 포항시 북구 학전로 152(장성동)36.064264129.3787292020-11-29

Duplicate rows

Most frequently occurring

업체명연락처업태행정동도로명 주소위도경도데이터 기준일자# duplicates
0동남카프라자054-249-3140<NA>중앙동경상북도 포항시 북구 동빈로 84 (동빈1가)36.044501129.3699112020-11-292
1솔마루맛가054-255-0679한식용흥동경상북도 포항시 북구 새마을로 42(용흥동)36.038914129.3553882020-11-292
2해동유통<NA>도소매환여동경상북도 포항시 북구 여남포길 27, 2동 (여남동)36.074032129.4083422020-11-292