Overview

Dataset statistics

Number of variables14
Number of observations357
Missing cells608
Missing cells (%)12.2%
Duplicate rows1
Duplicate rows (%)0.3%
Total size in memory41.3 KiB
Average record size in memory118.4 B

Variable types

Categorical4
Text4
DateTime2
Numeric4

Dataset

Description반려동물 판매업체 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=99L24Y065OQ36TTGVENX502240&infSeq=1

Alerts

총종업원수 has constant value ""Constant
Dataset has 1 (0.3%) duplicate rowsDuplicates
소재지면적정보 is highly overall correlated with 도로명우편번호 and 5 other fieldsHigh correlation
영업상태명 is highly overall correlated with 소재지면적정보High correlation
시군명 is highly overall correlated with 도로명우편번호 and 4 other fieldsHigh correlation
도로명우편번호 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with 도로명우편번호 and 3 other fieldsHigh correlation
X좌표값 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
Y좌표값 is highly overall correlated with 도로명우편번호 and 3 other fieldsHigh correlation
영업상태명 is highly imbalanced (53.4%)Imbalance
소재지면적정보 is highly imbalanced (97.2%)Imbalance
소재지시설전화번호 has 348 (97.5%) missing valuesMissing
도로명우편번호 has 18 (5.0%) missing valuesMissing
소재지도로명주소 has 14 (3.9%) missing valuesMissing
소재지지번주소 has 5 (1.4%) missing valuesMissing
소재지우편번호 has 217 (60.8%) missing valuesMissing

Reproduction

Analysis started2023-12-10 22:26:44.727029
Analysis finished2023-12-10 22:26:47.743273
Duration3.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
여주시
43 
파주시
42 
양평군
40 
화성시
35 
용인시
29 
Other values (20)
168 

Length

Max length4
Median length3
Mean length3.0392157
Min length3

Unique

Unique5 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
여주시 43
12.0%
파주시 42
11.8%
양평군 40
11.2%
화성시 35
9.8%
용인시 29
8.1%
양주시 29
8.1%
안성시 25
 
7.0%
김포시 20
 
5.6%
평택시 16
 
4.5%
연천군 14
 
3.9%
Other values (15) 64
17.9%

Length

2023-12-11T07:26:47.816692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여주시 43
12.0%
파주시 42
11.8%
양평군 40
11.2%
화성시 35
9.8%
용인시 29
8.1%
양주시 29
8.1%
안성시 25
 
7.0%
김포시 20
 
5.6%
평택시 16
 
4.5%
연천군 14
 
3.9%
Other values (15) 64
17.9%

사업장명
Text

Distinct348
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-12-11T07:26:48.155258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length20
Mean length5.5322129
Min length1

Characters and Unicode

Total characters1975
Distinct characters378
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

Unique340 ?
Unique (%)95.2%

Sample

1st row시바견 전문 가도켄넬
2nd row설악펫
3rd row월드애견
4th row예분
5th row라임
ValueCountFrequency (%)
켄넬 8
 
1.8%
kennel 5
 
1.1%
puppy 4
 
0.9%
농장 4
 
0.9%
캐터리 4
 
0.9%
피닉스 3
 
0.7%
퍼피 3
 
0.7%
dog 3
 
0.7%
흑석미미 2
 
0.4%
하우스 2
 
0.4%
Other values (406) 416
91.6%
2023-12-11T07:26:48.671685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
 
4.9%
스 52
 
2.6%
넬 46
 
2.3%
켄 43
 
2.2%
리 42
 
2.1%
이 41
 
2.1%
견 41
 
2.1%
애 39
 
2.0%
우 29
 
1.5%
e 29
 
1.5%
Other values (368) 1516
76.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1401
70.9%
Lowercase Letter 232
 
11.7%
Uppercase Letter 194
 
9.8%
Space Separator 97
 
4.9%
Open Punctuation 16
 
0.8%
Close Punctuation 16
 
0.8%
Other Punctuation 10
 
0.5%
Decimal Number 7
 
0.4%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 52
 
3.7%
넬 46
 
3.3%
켄 43
 
3.1%
리 42
 
3.0%
이 41
 
2.9%
견 41
 
2.9%
애 39
 
2.8%
우 29
 
2.1%
하 27
 
1.9%
장 24
 
1.7%
Other values (309) 1017
72.6%
Uppercase Letter
ValueCountFrequency (%)
E 15
 
7.7%
L 14
 
7.2%
O 14
 
7.2%
S 13
 
6.7%
A 13
 
6.7%
D 12
 
6.2%
C 11
 
5.7%
G 10
 
5.2%
B 10
 
5.2%
H 9
 
4.6%
Other values (14) 73
37.6%
Lowercase Letter
ValueCountFrequency (%)
e 29
12.5%
o 23
 
9.9%
n 22
 
9.5%
l 19
 
8.2%
a 16
 
6.9%
i 15
 
6.5%
t 14
 
6.0%
y 12
 
5.2%
d 10
 
4.3%
u 10
 
4.3%
Other values (12) 62
26.7%
Decimal Number
ValueCountFrequency (%)
3 2
28.6%
2 2
28.6%
5 1
14.3%
8 1
14.3%
1 1
14.3%
Other Punctuation
ValueCountFrequency (%)
& 5
50.0%
. 3
30.0%
· 1
 
10.0%
' 1
 
10.0%
Space Separator
ValueCountFrequency (%)
97
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1401
70.9%
Latin 426
 
21.6%
Common 148
 
7.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 52
 
3.7%
넬 46
 
3.3%
켄 43
 
3.1%
리 42
 
3.0%
이 41
 
2.9%
견 41
 
2.9%
애 39
 
2.8%
우 29
 
2.1%
하 27
 
1.9%
장 24
 
1.7%
Other values (309) 1017
72.6%
Latin
ValueCountFrequency (%)
e 29
 
6.8%
o 23
 
5.4%
n 22
 
5.2%
l 19
 
4.5%
a 16
 
3.8%
i 15
 
3.5%
E 15
 
3.5%
L 14
 
3.3%
t 14
 
3.3%
O 14
 
3.3%
Other values (36) 245
57.5%
Common
ValueCountFrequency (%)
97
65.5%
( 16
 
10.8%
) 16
 
10.8%
& 5
 
3.4%
. 3
 
2.0%
- 2
 
1.4%
3 2
 
1.4%
2 2
 
1.4%
5 1
 
0.7%
8 1
 
0.7%
Other values (3) 3
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1401
70.9%
ASCII 573
29.0%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
97
 
16.9%
e 29
 
5.1%
o 23
 
4.0%
n 22
 
3.8%
l 19
 
3.3%
( 16
 
2.8%
) 16
 
2.8%
a 16
 
2.8%
i 15
 
2.6%
E 15
 
2.6%
Other values (48) 305
53.2%
Hangul
ValueCountFrequency (%)
스 52
 
3.7%
넬 46
 
3.3%
켄 43
 
3.1%
리 42
 
3.0%
이 41
 
2.9%
견 41
 
2.9%
애 39
 
2.8%
우 29
 
2.1%
하 27
 
1.9%
장 24
 
1.7%
Other values (309) 1017
72.6%
None
ValueCountFrequency (%)
· 1
100.0%

인허가일자
Date

Distinct301
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum2008-06-09 00:00:00
Maximum2023-12-04 00:00:00
2023-12-11T07:26:48.811587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:48.947379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
정상
279 
폐업
62 
휴업
 
15
말소
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
정상 279
78.2%
폐업 62
 
17.4%
휴업 15
 
4.2%
말소 1
 
0.3%

Length

2023-12-11T07:26:49.059671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:26:49.152703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 279
78.2%
폐업 62
 
17.4%
휴업 15
 
4.2%
말소 1
 
0.3%

소재지시설전화번호
Text

MISSING 

Distinct8
Distinct (%)88.9%
Missing348
Missing (%)97.5%
Memory size2.9 KiB
2023-12-11T07:26:49.286790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.888889
Min length11

Characters and Unicode

Total characters107
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

Unique7 ?
Unique (%)77.8%

Sample

1st row031-555-5920
2nd row031-759-9141
3rd row03176751419
4th row031-844-2045
5th row031-884-7708
ValueCountFrequency (%)
031-334-4812 2
22.2%
031-555-5920 1
11.1%
031-759-9141 1
11.1%
03176751419 1
11.1%
031-844-2045 1
11.1%
031-884-7708 1
11.1%
031-881-1535 1
11.1%
031-322-6536 1
11.1%
2023-12-11T07:26:49.546619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
15.9%
3 16
15.0%
- 16
15.0%
0 12
11.2%
4 10
9.3%
5 10
9.3%
8 8
7.5%
2 6
 
5.6%
7 5
 
4.7%
9 4
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 91
85.0%
Dash Punctuation 16
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
18.7%
3 16
17.6%
0 12
13.2%
4 10
11.0%
5 10
11.0%
8 8
8.8%
2 6
 
6.6%
7 5
 
5.5%
9 4
 
4.4%
6 3
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 107
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
15.9%
3 16
15.0%
- 16
15.0%
0 12
11.2%
4 10
9.3%
5 10
9.3%
8 8
7.5%
2 6
 
5.6%
7 5
 
4.7%
9 4
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
15.9%
3 16
15.0%
- 16
15.0%
0 12
11.2%
4 10
9.3%
5 10
9.3%
8 8
7.5%
2 6
 
5.6%
7 5
 
4.7%
9 4
 
3.7%

소재지면적정보
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
356 
<NA>
 
1

Length

Max length4
Median length1
Mean length1.0084034
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 356
99.7%
<NA> 1
 
0.3%

Length

2023-12-11T07:26:49.655130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:26:49.744003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 356
99.7%
na 1
 
0.3%

도로명우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct246
Distinct (%)72.6%
Missing18
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean13718.027
Minimum10011
Maximum18586
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-11T07:26:49.834518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10011
5-th percentile10093.6
Q111134
median12581
Q317164.5
95-th percentile18545.4
Maximum18586
Range8575
Interquartile range (IQR)6030.5

Descriptive statistics

Standard deviation2942.3489
Coefficient of variation (CV)0.21448776
Kurtosis-1.3926594
Mean13718.027
Median Absolute Deviation (MAD)1648
Skewness0.52298496
Sum4650411
Variance8657416.8
MonotonicityNot monotonic
2023-12-11T07:26:49.944190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10025 6
 
1.7%
11423 5
 
1.4%
12570 5
 
1.4%
12544 5
 
1.4%
11047 5
 
1.4%
10804 5
 
1.4%
12611 4
 
1.1%
12667 4
 
1.1%
17406 4
 
1.1%
17039 4
 
1.1%
Other values (236) 292
81.8%
(Missing) 18
 
5.0%
ValueCountFrequency (%)
10011 1
 
0.3%
10012 1
 
0.3%
10014 1
 
0.3%
10015 1
 
0.3%
10017 1
 
0.3%
10022 1
 
0.3%
10024 1
 
0.3%
10025 6
1.7%
10036 1
 
0.3%
10039 1
 
0.3%
ValueCountFrequency (%)
18586 4
1.1%
18584 1
 
0.3%
18583 1
 
0.3%
18582 1
 
0.3%
18577 1
 
0.3%
18569 1
 
0.3%
18561 1
 
0.3%
18556 4
1.1%
18555 1
 
0.3%
18549 2
0.6%

소재지도로명주소
Text

MISSING 

Distinct316
Distinct (%)92.1%
Missing14
Missing (%)3.9%
Memory size2.9 KiB
2023-12-11T07:26:50.138613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length33
Mean length24.014577
Min length17

Characters and Unicode

Total characters8237
Distinct characters251
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique295 ?
Unique (%)86.0%

Sample

1st row경기도 가평군 가평읍 분자골로**번길 **-*
2nd row경기도 가평군 설악면 신천중앙로**번길 ***-**
3rd row경기도 가평군 설악면 신천중앙로**번길 ***-**
4th row경기도 가평군 가평읍 석봉로*번길 ***-**
5th row경기도 가평군 북면 백둔로 ***-**
ValueCountFrequency (%)
경기도 343
 
18.8%
336
 
18.5%
여주시 43
 
2.4%
파주시 39
 
2.1%
화성시 35
 
1.9%
양평군 31
 
1.7%
양주시 29
 
1.6%
용인시 29
 
1.6%
층 28
 
1.5%
처인구 26
 
1.4%
Other values (470) 882
48.4%
2023-12-11T07:26:50.446232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 1653
20.1%
1478
17.9%
도 357
 
4.3%
경 350
 
4.2%
기 349
 
4.2%
시 295
 
3.6%
길 250
 
3.0%
면 225
 
2.7%
로 214
 
2.6%
- 194
 
2.4%
Other values (241) 2872
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4735
57.5%
Other Punctuation 1720
 
20.9%
Space Separator 1478
 
17.9%
Dash Punctuation 194
 
2.4%
Open Punctuation 53
 
0.6%
Close Punctuation 53
 
0.6%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 357
 
7.5%
경 350
 
7.4%
기 349
 
7.4%
시 295
 
6.2%
길 250
 
5.3%
면 225
 
4.8%
로 214
 
4.5%
동 138
 
2.9%
주 134
 
2.8%
양 121
 
2.6%
Other values (232) 2302
48.6%
Uppercase Letter
ValueCountFrequency (%)
D 2
50.0%
A 1
25.0%
B 1
25.0%
Other Punctuation
ValueCountFrequency (%)
* 1653
96.1%
, 67
 
3.9%
Space Separator
ValueCountFrequency (%)
1478
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 194
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4735
57.5%
Common 3498
42.5%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 357
 
7.5%
경 350
 
7.4%
기 349
 
7.4%
시 295
 
6.2%
길 250
 
5.3%
면 225
 
4.8%
로 214
 
4.5%
동 138
 
2.9%
주 134
 
2.8%
양 121
 
2.6%
Other values (232) 2302
48.6%
Common
ValueCountFrequency (%)
* 1653
47.3%
1478
42.3%
- 194
 
5.5%
, 67
 
1.9%
( 53
 
1.5%
) 53
 
1.5%
Latin
ValueCountFrequency (%)
D 2
50.0%
A 1
25.0%
B 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4735
57.5%
ASCII 3502
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 1653
47.2%
1478
42.2%
- 194
 
5.5%
, 67
 
1.9%
( 53
 
1.5%
) 53
 
1.5%
D 2
 
0.1%
A 1
 
< 0.1%
B 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
도 357
 
7.5%
경 350
 
7.4%
기 349
 
7.4%
시 295
 
6.2%
길 250
 
5.3%
면 225
 
4.8%
로 214
 
4.5%
동 138
 
2.9%
주 134
 
2.8%
양 121
 
2.6%
Other values (232) 2302
48.6%

소재지지번주소
Text

MISSING 

Distinct302
Distinct (%)85.8%
Missing5
Missing (%)1.4%
Memory size2.9 KiB
2023-12-11T07:26:50.715841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length30
Mean length21.764205
Min length16

Characters and Unicode

Total characters7661
Distinct characters202
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique269 ?
Unique (%)76.4%

Sample

1st row경기도 가평군 가평읍 산유리 ***-*
2nd row경기도 가평군 설악면 신천리 ***-*
3rd row경기도 가평군 설악면 신천리 ***-*
4th row경기도 가평군 가평읍 대곡리 ***-*
5th row경기도 가평군 설악면 신천리 ***-*
ValueCountFrequency (%)
경기도 352
19.8%
352
19.8%
여주시 43
 
2.4%
양평군 40
 
2.2%
파주시 38
 
2.1%
화성시 35
 
2.0%
용인시 29
 
1.6%
양주시 29
 
1.6%
처인구 26
 
1.5%
안성시 25
 
1.4%
Other values (399) 811
45.6%
2023-12-11T07:26:51.300355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1777
23.2%
* 1384
18.1%
도 369
 
4.8%
기 357
 
4.7%
경 352
 
4.6%
리 304
 
4.0%
시 293
 
3.8%
- 257
 
3.4%
면 234
 
3.1%
주 130
 
1.7%
Other values (192) 2204
28.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4240
55.3%
Space Separator 1777
23.2%
Other Punctuation 1384
 
18.1%
Dash Punctuation 257
 
3.4%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 369
 
8.7%
기 357
 
8.4%
경 352
 
8.3%
리 304
 
7.2%
시 293
 
6.9%
면 234
 
5.5%
주 130
 
3.1%
양 114
 
2.7%
동 110
 
2.6%
평 89
 
2.1%
Other values (187) 1888
44.5%
Uppercase Letter
ValueCountFrequency (%)
D 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
1777
100.0%
Other Punctuation
ValueCountFrequency (%)
* 1384
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 257
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4240
55.3%
Common 3418
44.6%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 369
 
8.7%
기 357
 
8.4%
경 352
 
8.3%
리 304
 
7.2%
시 293
 
6.9%
면 234
 
5.5%
주 130
 
3.1%
양 114
 
2.7%
동 110
 
2.6%
평 89
 
2.1%
Other values (187) 1888
44.5%
Common
ValueCountFrequency (%)
1777
52.0%
* 1384
40.5%
- 257
 
7.5%
Latin
ValueCountFrequency (%)
D 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4240
55.3%
ASCII 3421
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1777
51.9%
* 1384
40.5%
- 257
 
7.5%
D 2
 
0.1%
B 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
도 369
 
8.7%
기 357
 
8.4%
경 352
 
8.3%
리 304
 
7.2%
시 293
 
6.9%
면 234
 
5.5%
주 130
 
3.1%
양 114
 
2.7%
동 110
 
2.6%
평 89
 
2.1%
Other values (187) 1888
44.5%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct96
Distinct (%)68.6%
Missing217
Missing (%)60.8%
Infinite0
Infinite (%)0.0%
Mean13675.75
Minimum10099
Maximum18586
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-11T07:26:51.433967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10099
5-th percentile10804
Q111128.75
median12570
Q317402.25
95-th percentile18556
Maximum18586
Range8487
Interquartile range (IQR)6273.5

Descriptive statistics

Standard deviation2869.0959
Coefficient of variation (CV)0.20979441
Kurtosis-1.2212197
Mean13675.75
Median Absolute Deviation (MAD)1524
Skewness0.69487812
Sum1914605
Variance8231711.3
MonotonicityNot monotonic
2023-12-11T07:26:51.541367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12544 6
 
1.7%
10804 5
 
1.4%
11047 5
 
1.4%
18586 4
 
1.1%
17406 4
 
1.1%
18556 4
 
1.1%
10801 3
 
0.8%
11045 3
 
0.8%
17608 3
 
0.8%
12665 3
 
0.8%
Other values (86) 100
28.0%
(Missing) 217
60.8%
ValueCountFrequency (%)
10099 2
 
0.6%
10577 1
 
0.3%
10801 3
0.8%
10804 5
1.4%
10809 1
 
0.3%
10830 1
 
0.3%
10839 1
 
0.3%
10857 1
 
0.3%
10858 1
 
0.3%
10860 1
 
0.3%
ValueCountFrequency (%)
18586 4
1.1%
18577 1
 
0.3%
18556 4
1.1%
18545 1
 
0.3%
18544 1
 
0.3%
18540 1
 
0.3%
18514 1
 
0.3%
18355 1
 
0.3%
17963 1
 
0.3%
17927 1
 
0.3%

데이터갱신시각
Date

Distinct154
Distinct (%)43.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum2023-04-01 02:40:00
Maximum2023-12-08 02:40:00
2023-12-11T07:26:51.644158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:51.748652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

X좌표값
Real number (ℝ)

HIGH CORRELATION 

Distinct327
Distinct (%)92.4%
Missing3
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean214012.6
Minimum159712.44
Maximum268723.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-11T07:26:51.857183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum159712.44
5-th percentile171707.51
Q1189859.56
median214226.7
Q3241518.73
95-th percentile258217.32
Maximum268723.16
Range109010.71
Interquartile range (IQR)51659.176

Descriptive statistics

Standard deviation28813.687
Coefficient of variation (CV)0.13463547
Kurtosis-1.1556698
Mean214012.6
Median Absolute Deviation (MAD)25701.084
Skewness0.048677269
Sum75760459
Variance8.3022859 × 108
MonotonicityNot monotonic
2023-12-11T07:26:51.976615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
251670.885904551 5
 
1.4%
159712.805419118 4
 
1.1%
239028.846842397 4
 
1.1%
193880.180476123 3
 
0.8%
200822.269293154 3
 
0.8%
200138.657871181 3
 
0.8%
175777.045591953 2
 
0.6%
251673.804140614 2
 
0.6%
228035.93414103 2
 
0.6%
196055.771259137 2
 
0.6%
Other values (317) 324
90.8%
(Missing) 3
 
0.8%
ValueCountFrequency (%)
159712.443415208 1
 
0.3%
159712.805419118 4
1.1%
159843.680122721 1
 
0.3%
160522.500562898 1
 
0.3%
160979.884735116 1
 
0.3%
162628.085046042 1
 
0.3%
163080.796223046 1
 
0.3%
164546.44666091 1
 
0.3%
166107.718114664 1
 
0.3%
166795.00930874 1
 
0.3%
ValueCountFrequency (%)
268723.158012174 1
0.3%
268102.122092259 1
0.3%
266111.777045975 1
0.3%
264484.193560158 1
0.3%
262083.535991123 1
0.3%
262024.810866276 1
0.3%
261883.038951851 1
0.3%
261803.706830516 1
0.3%
261126.262833931 1
0.3%
260818.695151134 1
0.3%

Y좌표값
Real number (ℝ)

HIGH CORRELATION 

Distinct327
Distinct (%)92.4%
Missing3
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean441539.87
Minimum379598.25
Maximum521639.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-11T07:26:52.085541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum379598.25
5-th percentile388715.85
Q1411034.4
median436604.35
Q3472834.23
95-th percentile499768.96
Maximum521639.77
Range142041.52
Interquartile range (IQR)61799.833

Descriptive statistics

Standard deviation35464.948
Coefficient of variation (CV)0.080321054
Kurtosis-1.1976879
Mean441539.87
Median Absolute Deviation (MAD)29939.479
Skewness0.1218102
Sum1.5630511 × 108
Variance1.2577625 × 109
MonotonicityNot monotonic
2023-12-11T07:26:52.212686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
435443.562902921 5
 
1.4%
465327.230265845 4
 
1.1%
405575.014904152 4
 
1.1%
480245.946424279 3
 
0.8%
497050.812637971 3
 
0.8%
502378.395174842 3
 
0.8%
458830.878392679 2
 
0.6%
435411.340879456 2
 
0.6%
411034.401578762 2
 
0.6%
383497.401056246 2
 
0.6%
Other values (317) 324
90.8%
(Missing) 3
 
0.8%
ValueCountFrequency (%)
379598.251156353 1
0.3%
381526.965032199 1
0.3%
381787.427887327 1
0.3%
381943.420167773 2
0.6%
383118.804840559 1
0.3%
383497.401056246 2
0.6%
384141.385575977 1
0.3%
385141.828071119 1
0.3%
385439.909033845 1
0.3%
385838.097334672 1
0.3%
ValueCountFrequency (%)
521639.77044525 1
 
0.3%
510109.879646913 1
 
0.3%
506283.067942985 1
 
0.3%
506234.998211045 1
 
0.3%
506219.585315101 1
 
0.3%
503708.1198991 1
 
0.3%
502378.395174842 3
0.8%
502327.971951421 2
0.6%
501968.901119515 2
0.6%
501016.505007957 1
 
0.3%

총종업원수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
357 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 357
100.0%

Length

2023-12-11T07:26:52.322481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:26:52.402643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 357
100.0%

Interactions

2023-12-11T07:26:46.713783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:45.556862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:45.963361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:46.341175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:46.811317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:45.636173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:46.061531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:46.426080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:46.916551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:45.725897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:46.146233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:46.514536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:47.024127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:45.859298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:46.243799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:26:46.609730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:26:52.455351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명소재지시설전화번호도로명우편번호소재지우편번호X좌표값Y좌표값
시군명1.0000.3931.0000.9980.9690.9080.901
영업상태명0.3931.0001.0000.0000.0000.2380.126
소재지시설전화번호1.0001.0001.0001.0001.0001.0001.000
도로명우편번호0.9980.0001.0001.0000.9970.7550.752
소재지우편번호0.9690.0001.0000.9971.0000.8040.812
X좌표값0.9080.2381.0000.7550.8041.0000.738
Y좌표값0.9010.1261.0000.7520.8120.7381.000
2023-12-11T07:26:52.588370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지면적정보영업상태명시군명
소재지면적정보1.0001.0001.000
영업상태명1.0001.0000.210
시군명1.0000.2101.000
2023-12-11T07:26:52.670606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로명우편번호소재지우편번호X좌표값Y좌표값시군명영업상태명소재지면적정보
도로명우편번호1.0001.0000.271-0.8890.9370.0001.000
소재지우편번호1.0001.0000.179-0.9210.8590.0001.000
X좌표값0.2710.1791.000-0.2370.6230.1381.000
Y좌표값-0.889-0.921-0.2371.0000.6060.0721.000
시군명0.9370.8590.6230.6061.0000.2101.000
영업상태명0.0000.0000.1380.0720.2101.0001.000
소재지면적정보1.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-11T07:26:47.188133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:26:47.436027image/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.
2023-12-11T07:26:47.619267image/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

시군명사업장명인허가일자영업상태명소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호데이터갱신시각X좌표값Y좌표값총종업원수
0가평군시바견 전문 가도켄넬2023-09-13정상<NA>012429경기도 가평군 가평읍 분자골로**번길 **-*경기도 가평군 가평읍 산유리 ***-*124292023-09-15 00:18:04243919.743289473539.4915230
1가평군설악펫2022-07-14정상<NA>012467경기도 가평군 설악면 신천중앙로**번길 ***-**경기도 가평군 설악면 신천리 ***-*<NA>2023-07-01 02:40:00243139.074224462062.8562280
2가평군월드애견2022-07-14정상<NA>012467경기도 가평군 설악면 신천중앙로**번길 ***-**경기도 가평군 설악면 신천리 ***-*<NA>2023-12-01 02:40:00243145.739535462032.2543590
3가평군예분2022-10-18정상<NA>012416경기도 가평군 가평읍 석봉로*번길 ***-**경기도 가평군 가평읍 대곡리 ***-*<NA>2023-05-14 02:40:00243247.30137480064.5138520
4가평군라임2020-12-31정상<NA>0<NA><NA>경기도 가평군 설악면 신천리 ***-*<NA>2023-04-08 02:40:00243132.930714462099.8060020
5가평군A HAPPY DOG WORLD2019-09-03정상<NA>012406경기도 가평군 북면 백둔로 ***-**경기도 가평군 북면 백둔리 **-*124062023-11-02 02:40:00243058.525141488517.4455610
6가평군S.S.G2023-05-09정상<NA>012467경기도 가평군 설악면 신천중앙로**번길 ***-**경기도 가평군 설악면 신천리 ***-*<NA>2023-05-11 00:19:54243162.092933462078.672320
7가평군러브캣2018-11-06폐업<NA>012440경기도 가평군 상면 물골길 ***경기도 가평군 상면 봉수리 **-*124402023-04-01 02:40:00227316.457262481512.6762570
8고양시냥냥하우스2023-03-28정상<NA>010254경기도 고양시 일산동구 문원길***번길 ***-**(설문동)경기도 고양시 일산동구 설문동 **-**<NA>2023-06-25 02:40:00184093.827524468900.1045760
9고양시디자인독2018-11-07정상<NA>010260경기도 고양시 일산동구 공릉천로***번길 **-* (사리현동)경기도 고양시 일산동구 사리현동 ***-**<NA>2023-05-13 02:40:00186065.297021466846.7521480
시군명사업장명인허가일자영업상태명소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호데이터갱신시각X좌표값Y좌표값총종업원수
347화성시루나캣2022-03-11폐업<NA>018278경기도 화성시 남양읍 고향의봄길 ***-**경기도 화성시 남양읍 활초리 ***-**<NA>2023-10-25 02:40:00185060.936826408967.3994310
348화성시서신농원2023-04-03폐업<NA>018556경기도 화성시 서신면 홍법사길 **-*경기도 화성시 서신면 홍법리 **185562023-11-11 02:40:00175910.200227407713.1462130
349화성시에덴축산2009-03-09폐업<NA>0<NA>경기도 화성시 매송면 송숙로 **경기도 화성시 매송면 송라리 ***-*<NA>2023-04-23 02:40:00190379.229474418773.780570
350화성시라임캣2023-11-27폐업<NA><NA>18582경기도 화성시 향남읍 상신로 ***-*경기도 화성시 향남읍 상신리 ***-*<NA>2023-11-29 00:17:01189906.472605399684.794670
351화성시우리데코2018-06-19폐업<NA>018283경기도 화성시 비봉면 삼화길***번길 **-*경기도 화성시 비봉면 삼화리 ***-*<NA>2023-04-01 02:40:00186960.59211415862.9528630
352화성시그녀의고양이2020-06-30폐업<NA>018583경기도 화성시 장안면 고해길 **경기도 화성시 장안면 독정리 **-*<NA>2023-11-25 02:40:00188315.695153395838.4460970
353화성시코코로캔넬2021-03-16휴업<NA>018569경기도 화성시 우정읍 석천길 *경기도 화성시 우정읍 화산리 ****-**<NA>2023-11-25 02:40:00<NA><NA>0
354화성시데비아스2008-06-09휴업<NA>0<NA>경기도 화성시 봉담읍 분천길***번길 **경기도 화성시 봉담읍 분천리 ***-*<NA>2023-11-24 02:40:00195807.42232411393.762660
355화성시어워크2013-02-08휴업<NA>018577경기도 화성시 팔탄면 온천로***번길 **-**경기도 화성시 팔탄면 덕우리 ***-*185772023-12-02 02:40:00187834.500886404481.6446450
356화성시하나켄넬2017-12-27휴업<NA>018269경기도 화성시 남양읍 남양로***번길 **경기도 화성시 남양읍 신남리 ***<NA>2023-11-22 02:40:00183620.839411408975.1754060

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시군명사업장명인허가일자영업상태명소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호데이터갱신시각X좌표값Y좌표값총종업원수# duplicates
0용인시오산농장2019-09-03정상031-334-4812017136경기도 용인시 처인구 이동읍 경기동로 ***경기도 용인시 처인구 이동읍 송전리 ***-**<NA>2023-06-10 02:40:00217479.432767404231.26488502