Overview

Dataset statistics

Number of variables14
Number of observations251
Missing cells407
Missing cells (%)11.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.6 KiB
Average record size in memory116.5 B

Variable types

Categorical3
Text4
DateTime2
Boolean1
Numeric3
Unsupported1

Dataset

Description휴게음식점(키즈카페) 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=7CGU0B5LDQGDQL4CS1CV14632307&infSeq=1

Alerts

시군명 is highly overall correlated with WGS84위도 and 2 other fieldsHigh correlation
위생업태명 is highly overall correlated with 총시설규모(㎡) and 5 other fieldsHigh correlation
다중이용업소여부 is highly overall correlated with 총시설규모(㎡) and 1 other fieldsHigh correlation
영업상태명 is highly overall correlated with 위생업태명High correlation
총시설규모(㎡) is highly overall correlated with 다중이용업소여부 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
위생업태명 is highly imbalanced (81.6%)Imbalance
폐업일자 has 140 (55.8%) missing valuesMissing
다중이용업소여부 has 7 (2.8%) missing valuesMissing
총시설규모(㎡) has 7 (2.8%) missing valuesMissing
위생업종명 has 251 (100.0%) missing valuesMissing
소재지도로명주소 has unique valuesUnique
위생업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총시설규모(㎡) has 10 (4.0%) zerosZeros

Reproduction

Analysis started2024-05-10 20:29:47.341357
Analysis finished2024-05-10 20:29:53.348717
Duration6.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
부천시
42 
화성시
21 
용인시
18 
수원시
17 
성남시
 
12
Other values (24)
141 

Length

Max length4
Median length3
Mean length3.0956175
Min length3

Unique

Unique3 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
부천시 42
16.7%
화성시 21
 
8.4%
용인시 18
 
7.2%
수원시 17
 
6.8%
성남시 12
 
4.8%
김포시 11
 
4.4%
남양주시 11
 
4.4%
시흥시 11
 
4.4%
파주시 11
 
4.4%
의정부시 11
 
4.4%
Other values (19) 86
34.3%

Length

2024-05-10T20:29:53.869585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부천시 42
16.7%
화성시 21
 
8.4%
용인시 18
 
7.2%
수원시 17
 
6.8%
성남시 12
 
4.8%
김포시 11
 
4.4%
남양주시 11
 
4.4%
시흥시 11
 
4.4%
파주시 11
 
4.4%
의정부시 11
 
4.4%
Other values (19) 86
34.3%

사업장명
Text

Distinct231
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-10T20:29:54.540704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length17
Mean length8.2908367
Min length2

Characters and Unicode

Total characters2081
Distinct characters344
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

Unique213 ?
Unique (%)84.9%

Sample

1st row점프노리
2nd row노리파크 가평점
3rd row노리파크 가평점
4th row키즈스테이
5th row키윙키즈카페
ValueCountFrequency (%)
키즈카페 13
 
3.7%
노리파크 11
 
3.1%
맘스카페 6
 
1.7%
타요키즈카페 6
 
1.7%
옥길점 5
 
1.4%
동탄점 5
 
1.4%
키즈인러브 4
 
1.1%
헬로방방 3
 
0.8%
챔피언 3
 
0.8%
키즈더웨이브 2
 
0.6%
Other values (274) 298
83.7%
2024-05-10T20:29:56.146964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
키 113
 
5.4%
105
 
5.0%
즈 99
 
4.8%
점 97
 
4.7%
카 86
 
4.1%
페 84
 
4.0%
리 58
 
2.8%
이 54
 
2.6%
스 34
 
1.6%
아 33
 
1.6%
Other values (334) 1318
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1850
88.9%
Space Separator 105
 
5.0%
Uppercase Letter 37
 
1.8%
Close Punctuation 27
 
1.3%
Open Punctuation 27
 
1.3%
Lowercase Letter 20
 
1.0%
Decimal Number 7
 
0.3%
Other Punctuation 7
 
0.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
키 113
 
6.1%
즈 99
 
5.4%
점 97
 
5.2%
카 86
 
4.6%
페 84
 
4.5%
리 58
 
3.1%
이 54
 
2.9%
스 34
 
1.8%
아 33
 
1.8%
방 26
 
1.4%
Other values (290) 1166
63.0%
Uppercase Letter
ValueCountFrequency (%)
A 5
13.5%
S 4
10.8%
K 4
10.8%
M 3
 
8.1%
T 2
 
5.4%
C 2
 
5.4%
D 2
 
5.4%
I 2
 
5.4%
E 2
 
5.4%
L 2
 
5.4%
Other values (9) 9
24.3%
Lowercase Letter
ValueCountFrequency (%)
i 5
25.0%
o 4
20.0%
l 1
 
5.0%
n 1
 
5.0%
r 1
 
5.0%
e 1
 
5.0%
h 1
 
5.0%
p 1
 
5.0%
u 1
 
5.0%
z 1
 
5.0%
Other values (3) 3
15.0%
Decimal Number
ValueCountFrequency (%)
2 4
57.1%
1 1
 
14.3%
5 1
 
14.3%
0 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
& 4
57.1%
, 1
 
14.3%
! 1
 
14.3%
/ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1850
88.9%
Common 174
 
8.4%
Latin 57
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
키 113
 
6.1%
즈 99
 
5.4%
점 97
 
5.2%
카 86
 
4.6%
페 84
 
4.5%
리 58
 
3.1%
이 54
 
2.9%
스 34
 
1.8%
아 33
 
1.8%
방 26
 
1.4%
Other values (290) 1166
63.0%
Latin
ValueCountFrequency (%)
A 5
 
8.8%
i 5
 
8.8%
o 4
 
7.0%
S 4
 
7.0%
K 4
 
7.0%
M 3
 
5.3%
T 2
 
3.5%
C 2
 
3.5%
D 2
 
3.5%
I 2
 
3.5%
Other values (22) 24
42.1%
Common
ValueCountFrequency (%)
105
60.3%
) 27
 
15.5%
( 27
 
15.5%
2 4
 
2.3%
& 4
 
2.3%
, 1
 
0.6%
! 1
 
0.6%
- 1
 
0.6%
/ 1
 
0.6%
1 1
 
0.6%
Other values (2) 2
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1850
88.9%
ASCII 231
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
키 113
 
6.1%
즈 99
 
5.4%
점 97
 
5.2%
카 86
 
4.6%
페 84
 
4.5%
리 58
 
3.1%
이 54
 
2.9%
스 34
 
1.8%
아 33
 
1.8%
방 26
 
1.4%
Other values (290) 1166
63.0%
ASCII
ValueCountFrequency (%)
105
45.5%
) 27
 
11.7%
( 27
 
11.7%
A 5
 
2.2%
i 5
 
2.2%
o 4
 
1.7%
S 4
 
1.7%
2 4
 
1.7%
& 4
 
1.7%
K 4
 
1.7%
Other values (34) 42
 
18.2%

인허가일자
Date

Distinct220
Distinct (%)87.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2007-03-27 00:00:00
Maximum2024-04-25 00:00:00
2024-05-10T20:29:56.566033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:29:57.003638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
영업
140 
폐업
111 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업
2nd row영업
3rd row폐업
4th row폐업
5th row영업

Common Values

ValueCountFrequency (%)
영업 140
55.8%
폐업 111
44.2%

Length

2024-05-10T20:29:57.431107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T20:29:57.711497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 140
55.8%
폐업 111
44.2%

폐업일자
Date

MISSING 

Distinct98
Distinct (%)88.3%
Missing140
Missing (%)55.8%
Memory size2.1 KiB
Minimum2019-09-24 00:00:00
Maximum2024-04-30 00:00:00
2024-05-10T20:29:58.062746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:29:58.504381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

다중이용업소여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.8%
Missing7
Missing (%)2.8%
Memory size634.0 B
False
195 
True
49 
(Missing)
 
7
ValueCountFrequency (%)
False 195
77.7%
True 49
 
19.5%
(Missing) 7
 
2.8%
2024-05-10T20:29:58.858209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

총시설규모(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct211
Distinct (%)86.5%
Missing7
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean78.241025
Minimum0
Maximum660.1
Zeros10
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-10T20:29:59.162787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.795
Q131.46
median59.405
Q390.03
95-th percentile252.988
Maximum660.1
Range660.1
Interquartile range (IQR)58.57

Descriptive statistics

Standard deviation85.254797
Coefficient of variation (CV)1.0896432
Kurtosis13.33036
Mean78.241025
Median Absolute Deviation (MAD)29.33
Skewness3.1383257
Sum19090.81
Variance7268.3803
MonotonicityNot monotonic
2024-05-10T20:29:59.525251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 10
 
4.0%
66.0 4
 
1.6%
3.3 3
 
1.2%
20.0 3
 
1.2%
18.37 2
 
0.8%
92.4 2
 
0.8%
47.26 2
 
0.8%
66.1 2
 
0.8%
64.0 2
 
0.8%
33.0 2
 
0.8%
Other values (201) 212
84.5%
(Missing) 7
 
2.8%
ValueCountFrequency (%)
0.0 10
4.0%
3.3 3
 
1.2%
6.6 1
 
0.4%
7.98 1
 
0.4%
8.25 1
 
0.4%
10.0 1
 
0.4%
11.0 1
 
0.4%
11.2 1
 
0.4%
11.5 1
 
0.4%
12.09 1
 
0.4%
ValueCountFrequency (%)
660.1 1
0.4%
499.3 1
0.4%
412.54 1
0.4%
410.0 1
0.4%
390.79 1
0.4%
352.0 1
0.4%
348.01 1
0.4%
310.23 1
0.4%
302.26 1
0.4%
264.74 1
0.4%

위생업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

위생업태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
키즈카페
244 
<NA>
 
7

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
키즈카페 244
97.2%
<NA> 7
 
2.8%

Length

2024-05-10T20:29:59.949296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T20:30:00.277747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
키즈카페 244
97.2%
na 7
 
2.8%

소재지도로명주소
Text

UNIQUE 

Distinct251
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-10T20:30:00.756372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length50
Mean length38.768924
Min length19

Characters and Unicode

Total characters9731
Distinct characters345
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique251 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 가평읍 오리나무길 20 (제1동 1층)
2nd row경기도 가평군 조종면 조종희망로 26, 2층
3rd row경기도 가평군 조종면 현창로 28-8, 2층
4th row경기도 가평군 청평면 상지로 123, 1층
5th row경기도 고양시 덕양구 서오릉로 474, 2층 일부호 (용두동)
ValueCountFrequency (%)
경기도 251
 
12.4%
2층 51
 
2.5%
일부호 44
 
2.2%
부천시 42
 
2.1%
4층 32
 
1.6%
일부 29
 
1.4%
3층 27
 
1.3%
화성시 21
 
1.0%
5층 19
 
0.9%
용인시 18
 
0.9%
Other values (885) 1489
73.6%
2024-05-10T20:30:01.840856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1773
 
18.2%
, 344
 
3.5%
동 311
 
3.2%
2 306
 
3.1%
1 302
 
3.1%
시 282
 
2.9%
기 272
 
2.8%
경 267
 
2.7%
도 267
 
2.7%
0 250
 
2.6%
Other values (335) 5357
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5346
54.9%
Space Separator 1773
 
18.2%
Decimal Number 1683
 
17.3%
Other Punctuation 347
 
3.6%
Close Punctuation 239
 
2.5%
Open Punctuation 239
 
2.5%
Uppercase Letter 49
 
0.5%
Dash Punctuation 44
 
0.5%
Lowercase Letter 5
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 311
 
5.8%
시 282
 
5.3%
기 272
 
5.1%
경 267
 
5.0%
도 267
 
5.0%
로 242
 
4.5%
층 209
 
3.9%
호 203
 
3.8%
부 193
 
3.6%
일 135
 
2.5%
Other values (293) 2965
55.5%
Uppercase Letter
ValueCountFrequency (%)
B 10
20.4%
A 8
16.3%
K 4
 
8.2%
O 3
 
6.1%
T 3
 
6.1%
D 3
 
6.1%
S 3
 
6.1%
L 2
 
4.1%
M 2
 
4.1%
E 2
 
4.1%
Other values (8) 9
18.4%
Decimal Number
ValueCountFrequency (%)
2 306
18.2%
1 302
17.9%
0 250
14.9%
4 185
11.0%
3 160
9.5%
5 130
7.7%
6 104
 
6.2%
7 101
 
6.0%
8 91
 
5.4%
9 54
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
o 2
40.0%
y 1
20.0%
s 1
20.0%
k 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 344
99.1%
. 2
 
0.6%
& 1
 
0.3%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
66.7%
Ⅲ 1
33.3%
Space Separator
ValueCountFrequency (%)
1773
100.0%
Close Punctuation
ValueCountFrequency (%)
) 239
100.0%
Open Punctuation
ValueCountFrequency (%)
( 239
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5346
54.9%
Common 4328
44.5%
Latin 57
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 311
 
5.8%
시 282
 
5.3%
기 272
 
5.1%
경 267
 
5.0%
도 267
 
5.0%
로 242
 
4.5%
층 209
 
3.9%
호 203
 
3.8%
부 193
 
3.6%
일 135
 
2.5%
Other values (293) 2965
55.5%
Latin
ValueCountFrequency (%)
B 10
17.5%
A 8
14.0%
K 4
 
7.0%
O 3
 
5.3%
T 3
 
5.3%
D 3
 
5.3%
S 3
 
5.3%
L 2
 
3.5%
M 2
 
3.5%
E 2
 
3.5%
Other values (14) 17
29.8%
Common
ValueCountFrequency (%)
1773
41.0%
, 344
 
7.9%
2 306
 
7.1%
1 302
 
7.0%
0 250
 
5.8%
) 239
 
5.5%
( 239
 
5.5%
4 185
 
4.3%
3 160
 
3.7%
5 130
 
3.0%
Other values (8) 400
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5346
54.9%
ASCII 4382
45.0%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1773
40.5%
, 344
 
7.9%
2 306
 
7.0%
1 302
 
6.9%
0 250
 
5.7%
) 239
 
5.5%
( 239
 
5.5%
4 185
 
4.2%
3 160
 
3.7%
5 130
 
3.0%
Other values (30) 454
 
10.4%
Hangul
ValueCountFrequency (%)
동 311
 
5.8%
시 282
 
5.3%
기 272
 
5.1%
경 267
 
5.0%
도 267
 
5.0%
로 242
 
4.5%
층 209
 
3.9%
호 203
 
3.8%
부 193
 
3.6%
일 135
 
2.5%
Other values (293) 2965
55.5%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
66.7%
Ⅲ 1
33.3%

소재지지번주소
Text

Distinct248
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-10T20:30:02.436593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length42
Mean length28.613546
Min length16

Characters and Unicode

Total characters7182
Distinct characters299
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique245 ?
Unique (%)97.6%

Sample

1st row경기도 가평군 가평읍 대곡리 240-9 , 238-8 제1동 1층
2nd row경기도 가평군 조종면 현리 259-7 2층
3rd row경기도 가평군 조종면 현리 410-51
4th row경기도 가평군 청평면 상천리 1470-2
5th row경기도 고양시 덕양구 용두동 432-185 202호
ValueCountFrequency (%)
경기도 251
 
16.2%
부천시 42
 
2.7%
일부 35
 
2.3%
2층 21
 
1.4%
화성시 21
 
1.4%
용인시 18
 
1.2%
수원시 17
 
1.1%
원미구 14
 
0.9%
4층 14
 
0.9%
성남시 12
 
0.8%
Other values (694) 1108
71.3%
2024-05-10T20:30:03.479779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1521
21.2%
1 283
 
3.9%
동 279
 
3.9%
시 275
 
3.8%
기 266
 
3.7%
도 264
 
3.7%
경 253
 
3.5%
2 201
 
2.8%
- 178
 
2.5%
0 161
 
2.2%
Other values (289) 3501
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3928
54.7%
Space Separator 1521
 
21.2%
Decimal Number 1461
 
20.3%
Dash Punctuation 178
 
2.5%
Other Punctuation 44
 
0.6%
Uppercase Letter 36
 
0.5%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Math Symbol 3
 
< 0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 279
 
7.1%
시 275
 
7.0%
기 266
 
6.8%
도 264
 
6.7%
경 253
 
6.4%
부 145
 
3.7%
구 105
 
2.7%
호 98
 
2.5%
층 94
 
2.4%
일 91
 
2.3%
Other values (254) 2058
52.4%
Uppercase Letter
ValueCountFrequency (%)
A 8
22.2%
B 7
19.4%
K 3
 
8.3%
M 2
 
5.6%
I 2
 
5.6%
T 2
 
5.6%
E 2
 
5.6%
S 2
 
5.6%
O 2
 
5.6%
N 1
 
2.8%
Other values (5) 5
13.9%
Decimal Number
ValueCountFrequency (%)
1 283
19.4%
2 201
13.8%
0 161
11.0%
3 154
10.5%
4 141
9.7%
5 135
9.2%
6 109
 
7.5%
7 109
 
7.5%
9 88
 
6.0%
8 80
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 41
93.2%
. 2
 
4.5%
& 1
 
2.3%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
66.7%
Ⅲ 1
33.3%
Space Separator
ValueCountFrequency (%)
1521
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 178
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3928
54.7%
Common 3215
44.8%
Latin 39
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 279
 
7.1%
시 275
 
7.0%
기 266
 
6.8%
도 264
 
6.7%
경 253
 
6.4%
부 145
 
3.7%
구 105
 
2.7%
호 98
 
2.5%
층 94
 
2.4%
일 91
 
2.3%
Other values (254) 2058
52.4%
Common
ValueCountFrequency (%)
1521
47.3%
1 283
 
8.8%
2 201
 
6.3%
- 178
 
5.5%
0 161
 
5.0%
3 154
 
4.8%
4 141
 
4.4%
5 135
 
4.2%
6 109
 
3.4%
7 109
 
3.4%
Other values (8) 223
 
6.9%
Latin
ValueCountFrequency (%)
A 8
20.5%
B 7
17.9%
K 3
 
7.7%
M 2
 
5.1%
I 2
 
5.1%
T 2
 
5.1%
E 2
 
5.1%
S 2
 
5.1%
O 2
 
5.1%
Ⅰ 2
 
5.1%
Other values (7) 7
17.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3928
54.7%
ASCII 3251
45.3%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1521
46.8%
1 283
 
8.7%
2 201
 
6.2%
- 178
 
5.5%
0 161
 
5.0%
3 154
 
4.7%
4 141
 
4.3%
5 135
 
4.2%
6 109
 
3.4%
7 109
 
3.4%
Other values (23) 259
 
8.0%
Hangul
ValueCountFrequency (%)
동 279
 
7.1%
시 275
 
7.0%
기 266
 
6.8%
도 264
 
6.7%
경 253
 
6.4%
부 145
 
3.7%
구 105
 
2.7%
호 98
 
2.5%
층 94
 
2.4%
일 91
 
2.3%
Other values (254) 2058
52.4%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
66.7%
Ⅲ 1
33.3%

소재지우편번호
Text

Distinct197
Distinct (%)78.5%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-10T20:30:04.207813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1354582
Min length5

Characters and Unicode

Total characters1540
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

Unique160 ?
Unique (%)63.7%

Sample

1st row477-702
2nd row12437
3rd row12438
4th row477-814
5th row412-110
ValueCountFrequency (%)
14786 7
 
2.8%
445150 4
 
1.6%
14543 4
 
1.6%
14565 4
 
1.6%
413190 3
 
1.2%
445851 3
 
1.2%
441-460 3
 
1.2%
14789 3
 
1.2%
14592 3
 
1.2%
465150 3
 
1.2%
Other values (187) 214
85.3%
2024-05-10T20:30:05.337651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 369
24.0%
1 200
13.0%
0 183
11.9%
8 147
 
9.5%
5 137
 
8.9%
2 103
 
6.7%
6 97
 
6.3%
3 94
 
6.1%
- 88
 
5.7%
7 68
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1452
94.3%
Dash Punctuation 88
 
5.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 369
25.4%
1 200
13.8%
0 183
12.6%
8 147
 
10.1%
5 137
 
9.4%
2 103
 
7.1%
6 97
 
6.7%
3 94
 
6.5%
7 68
 
4.7%
9 54
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1540
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 369
24.0%
1 200
13.0%
0 183
11.9%
8 147
 
9.5%
5 137
 
8.9%
2 103
 
6.7%
6 97
 
6.3%
3 94
 
6.1%
- 88
 
5.7%
7 68
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1540
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 369
24.0%
1 200
13.0%
0 183
11.9%
8 147
 
9.5%
5 137
 
8.9%
2 103
 
6.7%
6 97
 
6.3%
3 94
 
6.1%
- 88
 
5.7%
7 68
 
4.4%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct226
Distinct (%)90.4%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean37.445161
Minimum36.998529
Maximum37.892677
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-10T20:30:05.690320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.998529
5-th percentile37.151137
Q137.296169
median37.439787
Q337.608895
95-th percentile37.777663
Maximum37.892677
Range0.89414758
Interquartile range (IQR)0.31272591

Descriptive statistics

Standard deviation0.20039708
Coefficient of variation (CV)0.0053517483
Kurtosis-0.53119958
Mean37.445161
Median Absolute Deviation (MAD)0.15145161
Skewness0.090888302
Sum9361.2902
Variance0.040158989
MonotonicityNot monotonic
2024-05-10T20:30:06.071063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4929130744 4
 
1.6%
37.4988667424 3
 
1.2%
37.4750385925 2
 
0.8%
37.7228859348 2
 
0.8%
37.4621355051 2
 
0.8%
37.5076050541 2
 
0.8%
37.521938246 2
 
0.8%
37.4987587907 2
 
0.8%
37.645986513 2
 
0.8%
37.5043171668 2
 
0.8%
Other values (216) 227
90.4%
ValueCountFrequency (%)
36.9985290453 1
0.4%
36.9996450075 1
0.4%
37.0001986017 1
0.4%
37.0002582546 1
0.4%
37.0013542162 1
0.4%
37.0015961352 1
0.4%
37.0074078742 1
0.4%
37.0159437697 1
0.4%
37.1146380407 1
0.4%
37.1385111072 1
0.4%
ValueCountFrequency (%)
37.8926766231 1
0.4%
37.8926667488 1
0.4%
37.8417696599 1
0.4%
37.8372227482 1
0.4%
37.8301972412 1
0.4%
37.8257501758 1
0.4%
37.8236159627 1
0.4%
37.8221357217 1
0.4%
37.8210318745 1
0.4%
37.8190769043 1
0.4%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct226
Distinct (%)90.4%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean126.97695
Minimum126.54609
Maximum127.62814
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-10T20:30:06.438892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.54609
5-th percentile126.72746
Q1126.80679
median126.98176
Q3127.1141
95-th percentile127.24004
Maximum127.62814
Range1.0820429
Interquartile range (IQR)0.30731073

Descriptive statistics

Standard deviation0.18798723
Coefficient of variation (CV)0.0014804831
Kurtosis-0.10918344
Mean126.97695
Median Absolute Deviation (MAD)0.15833794
Skewness0.32910062
Sum31744.238
Variance0.0353392
MonotonicityNot monotonic
2024-05-10T20:30:07.077913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.791179932 4
 
1.6%
126.745384894 3
 
1.2%
126.8001362657 2
 
0.8%
126.7600363486 2
 
0.8%
126.813158481 2
 
0.8%
126.7517235046 2
 
0.8%
126.8051303633 2
 
0.8%
126.7786011093 2
 
0.8%
126.6294804128 2
 
0.8%
126.7620745903 2
 
0.8%
Other values (216) 227
90.4%
ValueCountFrequency (%)
126.5460934539 1
0.4%
126.6266409118 1
0.4%
126.6294804128 2
0.8%
126.6331667826 1
0.4%
126.6795904732 1
0.4%
126.682576215 1
0.4%
126.6850635963 1
0.4%
126.7010077217 1
0.4%
126.705533005 1
0.4%
126.7142677606 1
0.4%
ValueCountFrequency (%)
127.628136386 1
0.4%
127.5137265767 1
0.4%
127.5117193102 1
0.4%
127.4652789941 1
0.4%
127.4545638333 1
0.4%
127.4164288568 1
0.4%
127.3508282298 1
0.4%
127.3496614747 1
0.4%
127.3127615495 1
0.4%
127.3045940441 1
0.4%

Interactions

2024-05-10T20:29:50.688686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:29:49.155483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:29:49.945017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:29:50.958560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:29:49.412091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:29:50.199872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:29:51.204190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:29:49.664387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:29:50.435881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T20:30:07.360639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명폐업일자다중이용업소여부총시설규모(㎡)WGS84위도WGS84경도
시군명1.0000.2360.9560.2210.0000.9790.946
영업상태명0.2361.000NaN0.3290.1090.1850.100
폐업일자0.956NaN1.0000.7650.3890.8700.968
다중이용업소여부0.2210.3290.7651.0000.6090.1230.000
총시설규모(㎡)0.0000.1090.3890.6091.0000.1310.000
WGS84위도0.9790.1850.8700.1230.1311.0000.736
WGS84경도0.9460.1000.9680.0000.0000.7361.000
2024-05-10T20:30:07.674972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명위생업태명다중이용업소여부영업상태명
시군명1.0001.0000.1770.189
위생업태명1.0001.0001.0001.000
다중이용업소여부0.1771.0001.0000.214
영업상태명0.1891.0000.2141.000
2024-05-10T20:30:07.937950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총시설규모(㎡)WGS84위도WGS84경도시군명영업상태명다중이용업소여부위생업태명
총시설규모(㎡)1.0000.0540.0430.0000.1070.6051.000
WGS84위도0.0541.000-0.2280.8240.1390.0921.000
WGS84경도0.043-0.2281.0000.6950.0740.0001.000
시군명0.0000.8240.6951.0000.1890.1771.000
영업상태명0.1070.1390.0740.1891.0000.2141.000
다중이용업소여부0.6050.0920.0000.1770.2141.0001.000
위생업태명1.0001.0001.0001.0001.0001.0001.000

Missing values

2024-05-10T20:29:51.593589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T20:29:52.329367image/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.
2024-05-10T20:29:52.916895image/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

시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부총시설규모(㎡)위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0가평군점프노리2015-10-05영업<NA>N71.48<NA>키즈카페경기도 가평군 가평읍 오리나무길 20 (제1동 1층)경기도 가평군 가평읍 대곡리 240-9 , 238-8 제1동 1층477-70237.82575127.513727
1가평군노리파크 가평점2023-06-02영업<NA>Y108.92<NA>키즈카페경기도 가평군 조종면 조종희망로 26, 2층경기도 가평군 조종면 현리 259-7 2층1243737.819077127.350828
2가평군노리파크 가평점2019-10-25폐업2024-01-25N66.0<NA>키즈카페경기도 가평군 조종면 현창로 28-8, 2층경기도 가평군 조종면 현리 410-511243837.817336127.349661
3가평군키즈스테이2020-06-12폐업2024-03-19N200.55<NA>키즈카페경기도 가평군 청평면 상지로 123, 1층경기도 가평군 청평면 상천리 1470-2477-81437.767827127.465279
4고양시키윙키즈카페2024-04-25영업<NA>Y256.34<NA>키즈카페경기도 고양시 덕양구 서오릉로 474, 2층 일부호 (용두동)경기도 고양시 덕양구 용두동 432-185 202호412-11037.628125126.888084
5고양시타요키즈카페 롯데마트 주엽점20190130영업<NA>N78.75<NA>키즈카페경기도 고양시 일산서구 중앙로 1496, 문촌마을 상가동 1층일부호 (주엽동)경기도 고양시 일산서구 주엽동 15 문촌마을상가동 1층일부41183837.673157126.755212
6고양시잭슨와플2018-10-26영업<NA>N15.65<NA>키즈카페경기도 고양시 일산서구 일현로 97-11, B106(일부)호 (탄현동, 일산 위브더제니스)경기도 고양시 일산서구 탄현동 1640 일산 위브더제니스, B106호일부411-32037.693475126.762824
7고양시봉봉키즈 고양원흥점2022-10-11영업<NA>N94.0<NA>키즈카페경기도 고양시 덕양구 원흥1로 33, 2(일부)층 (원흥동)경기도 고양시 덕양구 원흥동 597412-04037.652747126.86547
8고양시리틀비틀원흥20190711영업<NA>N63.0<NA>키즈카페경기도 고양시 덕양구 의장로 140, 원흥연세프라자 제1동 301(일부)호 (도내동)경기도 고양시 덕양구 도내동 961 원흥연세프라자 제1동 301호 일부41206037.63519126.870697
9고양시원마운트 맘스카페2020-09-28영업<NA>N62.87<NA>키즈카페경기도 고양시 일산서구 한류월드로 300, 원마운트1층, S101 (대화동)경기도 고양시 일산서구 대화동 2606 원마운트1층, S101411-41037.664554126.754527
시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부총시설규모(㎡)위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
241화성시상상쿠키&카페20200914폐업20210511N83.6<NA>키즈카페경기도 화성시 동탄영천로 81-5, 골든프라자 2층 211호 (영천동)경기도 화성시 영천동 539-16 골든프라자 2층 211호44513037.209688127.102948
242화성시뮤직방방20160608폐업20210202N59.4<NA>키즈카페경기도 화성시 남양읍 남양시장로42번길 1, 1층경기도 화성시 남양읍 남양리 550 1층44585137.208603126.814178
243화성시샤를롯데키즈카페20170929폐업20211115N26.4<NA>키즈카페경기도 화성시 남양읍 시청로 64 (일영프라자 1동 4층 일부)경기도 화성시 남양읍 남양리 1752 일영프라자 1동 4층 일부44585137.203997126.821984
244화성시더물노리(The Moolnori)20160621폐업20210331N66.0<NA>키즈카페경기도 화성시 동탄대로시범길 148-20, 6층 일부호 (청계동, 마추프라자)경기도 화성시 청계동 510-842 마추프라자 6층일부호44514037.200343127.11449
245화성시유후점핑클럽20190122폐업20211126N3.3<NA>키즈카페경기도 화성시 향남읍 상신하길로298번길 7-27, 7층 일부경기도 화성시 향남읍 하길리 1470-544593837.114638126.912726
246화성시프릴리 키즈카페20171120폐업20211220N92.4<NA>키즈카페경기도 화성시 동탄신리천로 268, 501,502일부호 (오산동)경기도 화성시 오산동 465 베라프라자 501,502일부호44515037.183627127.107782
247화성시시크릿쥬쥬 또봇 키즈카페 동탄점20181114폐업20211125N94.25<NA>키즈카페경기도 화성시 동탄대로 557-9, 우성르보아시티 B동 6층 601의 일부호 (오산동)경기도 화성시 오산동 967-3 우성르보아시티 B동 601호44515037.203199127.097956
248화성시타요키즈카페 동탄2신도시점20170714폐업20210113N65.88<NA>키즈카페경기도 화성시 동탄대로 489, 11층 1104호 (오산동, 우성KTX타워)경기도 화성시 오산동 969-3 1104호44515037.19735127.098268
249화성시타요키즈카페 동탄점20170209폐업20210512N85.0<NA>키즈카페경기도 화성시 동탄지성로 11, 208,209일부호 (반송동, 동탄SR GOLD프라자)경기도 화성시 반송동 93-2 208,209일부호44516037.204518127.072785
250화성시상상샘20210319폐업20221215N38.57<NA>키즈카페경기도 화성시 경기대로 985, 홈플러스 병점점 2층 일부호 (병점동)경기도 화성시 병점동 399-4 홈플러스 병점점 2층 일부호44536037.203724127.036762