Overview

Dataset statistics

Number of variables9
Number of observations2176
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory159.5 KiB
Average record size in memory75.1 B

Variable types

Numeric3
Text3
Categorical2
DateTime1

Dataset

Description부산광역시 음식적 위생등급 지정 현황에 대한 데이터로 업소명, 소재지, 지정등급, 지정번호, 지역, 지정일자 등 항목 정보를 제공합니다
Author부산광역시
URLhttps://www.data.go.kr/data/15077429/fileData.do

Alerts

연번 is highly overall correlated with 관할기관High correlation
경도 is highly overall correlated with 관할기관High correlation
위도 is highly overall correlated with 관할기관High correlation
관할기관 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
위생등급 is highly imbalanced (63.1%)Imbalance
연번 has unique valuesUnique
지정번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:24:30.657698
Analysis finished2023-12-12 13:24:33.060352
Duration2.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2176
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1088.5
Minimum1
Maximum2176
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2023-12-12T22:24:33.175099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile109.75
Q1544.75
median1088.5
Q31632.25
95-th percentile2067.25
Maximum2176
Range2175
Interquartile range (IQR)1087.5

Descriptive statistics

Standard deviation628.30141
Coefficient of variation (CV)0.57721765
Kurtosis-1.2
Mean1088.5
Median Absolute Deviation (MAD)544
Skewness0
Sum2368576
Variance394762.67
MonotonicityStrictly increasing
2023-12-12T22:24:33.333926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1455 1
 
< 0.1%
1449 1
 
< 0.1%
1450 1
 
< 0.1%
1451 1
 
< 0.1%
1452 1
 
< 0.1%
1453 1
 
< 0.1%
1454 1
 
< 0.1%
1456 1
 
< 0.1%
1090 1
 
< 0.1%
Other values (2166) 2166
99.5%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2176 1
< 0.1%
2175 1
< 0.1%
2174 1
< 0.1%
2173 1
< 0.1%
2172 1
< 0.1%
2171 1
< 0.1%
2170 1
< 0.1%
2169 1
< 0.1%
2168 1
< 0.1%
2167 1
< 0.1%

업소명(상호)
Text

Distinct2059
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2023-12-12T22:24:33.720005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length10.120864
Min length2

Characters and Unicode

Total characters22023
Distinct characters668
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

Unique2010 ?
Unique (%)92.4%

Sample

1st rowBHC 보수부민점
2nd row푸라닭
3rd row떡볶이참잘하는집 떡참 부산중구점
4th row부평동 커피공장
5th row배스킨라빈스부산부평
ValueCountFrequency (%)
스타벅스 95
 
2.6%
배스킨라빈스 47
 
1.3%
투썸플레이스 45
 
1.2%
이디야 43
 
1.2%
교촌치킨 43
 
1.2%
카페051 38
 
1.0%
뚜레쥬르 36
 
1.0%
맘스터치 31
 
0.8%
하이오커피 27
 
0.7%
푸라닭 26
 
0.7%
Other values (2135) 3230
88.2%
2023-12-12T22:24:34.302646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 1557
 
7.1%
1486
 
6.7%
스 878
 
4.0%
산 667
 
3.0%
부 640
 
2.9%
이 481
 
2.2%
킨 321
 
1.5%
( 296
 
1.3%
) 296
 
1.3%
치 280
 
1.3%
Other values (658) 15121
68.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18610
84.5%
Space Separator 1486
 
6.7%
Uppercase Letter 535
 
2.4%
Decimal Number 408
 
1.9%
Lowercase Letter 335
 
1.5%
Open Punctuation 296
 
1.3%
Close Punctuation 296
 
1.3%
Other Punctuation 54
 
0.2%
Connector Punctuation 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1557
 
8.4%
스 878
 
4.7%
산 667
 
3.6%
부 640
 
3.4%
이 481
 
2.6%
킨 321
 
1.7%
치 280
 
1.5%
리 270
 
1.5%
피 254
 
1.4%
대 252
 
1.4%
Other values (586) 13010
69.9%
Uppercase Letter
ValueCountFrequency (%)
C 70
13.1%
T 58
10.8%
B 52
 
9.7%
D 50
 
9.3%
H 37
 
6.9%
S 31
 
5.8%
F 30
 
5.6%
K 23
 
4.3%
E 22
 
4.1%
G 19
 
3.6%
Other values (15) 143
26.7%
Lowercase Letter
ValueCountFrequency (%)
e 48
14.3%
a 36
 
10.7%
i 31
 
9.3%
o 25
 
7.5%
s 22
 
6.6%
c 21
 
6.3%
n 18
 
5.4%
u 15
 
4.5%
f 14
 
4.2%
r 14
 
4.2%
Other values (13) 91
27.2%
Decimal Number
ValueCountFrequency (%)
1 105
25.7%
0 96
23.5%
5 69
16.9%
2 47
11.5%
6 35
 
8.6%
3 23
 
5.6%
7 12
 
2.9%
9 10
 
2.5%
4 7
 
1.7%
8 4
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 14
25.9%
& 13
24.1%
. 12
22.2%
' 8
14.8%
？ 3
 
5.6%
% 1
 
1.9%
/ 1
 
1.9%
· 1
 
1.9%
: 1
 
1.9%
Space Separator
ValueCountFrequency (%)
1486
100.0%
Open Punctuation
ValueCountFrequency (%)
( 296
100.0%
Close Punctuation
ValueCountFrequency (%)
) 296
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18610
84.5%
Common 2543
 
11.5%
Latin 870
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1557
 
8.4%
스 878
 
4.7%
산 667
 
3.6%
부 640
 
3.4%
이 481
 
2.6%
킨 321
 
1.7%
치 280
 
1.5%
리 270
 
1.5%
피 254
 
1.4%
대 252
 
1.4%
Other values (586) 13010
69.9%
Latin
ValueCountFrequency (%)
C 70
 
8.0%
T 58
 
6.7%
B 52
 
6.0%
D 50
 
5.7%
e 48
 
5.5%
H 37
 
4.3%
a 36
 
4.1%
S 31
 
3.6%
i 31
 
3.6%
F 30
 
3.4%
Other values (38) 427
49.1%
Common
ValueCountFrequency (%)
1486
58.4%
( 296
 
11.6%
) 296
 
11.6%
1 105
 
4.1%
0 96
 
3.8%
5 69
 
2.7%
2 47
 
1.8%
6 35
 
1.4%
3 23
 
0.9%
, 14
 
0.6%
Other values (14) 76
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18610
84.5%
ASCII 3409
 
15.5%
None 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 1557
 
8.4%
스 878
 
4.7%
산 667
 
3.6%
부 640
 
3.4%
이 481
 
2.6%
킨 321
 
1.7%
치 280
 
1.5%
리 270
 
1.5%
피 254
 
1.4%
대 252
 
1.4%
Other values (586) 13010
69.9%
ASCII
ValueCountFrequency (%)
1486
43.6%
( 296
 
8.7%
) 296
 
8.7%
1 105
 
3.1%
0 96
 
2.8%
C 70
 
2.1%
5 69
 
2.0%
T 58
 
1.7%
B 52
 
1.5%
D 50
 
1.5%
Other values (60) 831
24.4%
None
ValueCountFrequency (%)
？ 3
75.0%
· 1
 
25.0%

영업장소재지
Text

Distinct1973
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2023-12-12T22:24:34.676765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length55
Mean length32.434743
Min length15

Characters and Unicode

Total characters70578
Distinct characters459
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

Unique1889 ?
Unique (%)86.8%

Sample

1st row부산광역시 중구 보수대로106번길 14(1층 보수동3가, 22-2번지)
2nd row부산광역시 중구 흑교로35번길 6(1층 부평동3가)
3rd row부산광역시 중구 법수길 4(1층 보수동1가)
4th row부산광역시 중구 부평2길 28(1층 부평동1가)
5th row부산광역시 중구 비프광장로 21(1,2층 부평동1가)
ValueCountFrequency (%)
부산광역시 2174
 
17.6%
해운대구 324
 
2.6%
부산진구 276
 
2.2%
1층 209
 
1.7%
동래구 177
 
1.4%
중앙대로 165
 
1.3%
사하구 161
 
1.3%
기장군 150
 
1.2%
연제구 145
 
1.2%
금정구 138
 
1.1%
Other values (3107) 8413
68.2%
2023-12-12T22:24:35.171415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10168
 
14.4%
1 3547
 
5.0%
부 2963
 
4.2%
동 2943
 
4.2%
산 2764
 
3.9%
시 2411
 
3.4%
광 2372
 
3.4%
역 2207
 
3.1%
) 2158
 
3.1%
( 2158
 
3.1%
Other values (449) 36887
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43403
61.5%
Decimal Number 11303
 
16.0%
Space Separator 10168
 
14.4%
Close Punctuation 2165
 
3.1%
Open Punctuation 2165
 
3.1%
Other Punctuation 812
 
1.2%
Dash Punctuation 261
 
0.4%
Uppercase Letter 222
 
0.3%
Math Symbol 61
 
0.1%
Lowercase Letter 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 2963
 
6.8%
동 2943
 
6.8%
산 2764
 
6.4%
시 2411
 
5.6%
광 2372
 
5.5%
역 2207
 
5.1%
로 2143
 
4.9%
구 2142
 
4.9%
층 1499
 
3.5%
대 1280
 
2.9%
Other values (399) 20679
47.6%
Uppercase Letter
ValueCountFrequency (%)
B 42
18.9%
A 41
18.5%
S 20
9.0%
W 18
8.1%
K 15
 
6.8%
E 13
 
5.9%
C 11
 
5.0%
I 9
 
4.1%
D 8
 
3.6%
H 7
 
3.2%
Other values (11) 38
17.1%
Decimal Number
ValueCountFrequency (%)
1 3547
31.4%
2 1755
15.5%
3 1105
 
9.8%
0 1104
 
9.8%
4 774
 
6.8%
7 741
 
6.6%
5 722
 
6.4%
6 619
 
5.5%
9 479
 
4.2%
8 457
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 793
97.7%
. 8
 
1.0%
* 7
 
0.9%
@ 2
 
0.2%
· 1
 
0.1%
/ 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 8
44.4%
l 4
22.2%
i 2
 
11.1%
s 2
 
11.1%
g 1
 
5.6%
f 1
 
5.6%
Close Punctuation
ValueCountFrequency (%)
) 2158
99.7%
] 7
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 2158
99.7%
[ 7
 
0.3%
Space Separator
ValueCountFrequency (%)
10168
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 261
100.0%
Math Symbol
ValueCountFrequency (%)
~ 61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43403
61.5%
Common 26935
38.2%
Latin 240
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 2963
 
6.8%
동 2943
 
6.8%
산 2764
 
6.4%
시 2411
 
5.6%
광 2372
 
5.5%
역 2207
 
5.1%
로 2143
 
4.9%
구 2142
 
4.9%
층 1499
 
3.5%
대 1280
 
2.9%
Other values (399) 20679
47.6%
Latin
ValueCountFrequency (%)
B 42
17.5%
A 41
17.1%
S 20
 
8.3%
W 18
 
7.5%
K 15
 
6.2%
E 13
 
5.4%
C 11
 
4.6%
I 9
 
3.8%
e 8
 
3.3%
D 8
 
3.3%
Other values (17) 55
22.9%
Common
ValueCountFrequency (%)
10168
37.8%
1 3547
 
13.2%
) 2158
 
8.0%
( 2158
 
8.0%
2 1755
 
6.5%
3 1105
 
4.1%
0 1104
 
4.1%
, 793
 
2.9%
4 774
 
2.9%
7 741
 
2.8%
Other values (13) 2632
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43403
61.5%
ASCII 27174
38.5%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10168
37.4%
1 3547
 
13.1%
) 2158
 
7.9%
( 2158
 
7.9%
2 1755
 
6.5%
3 1105
 
4.1%
0 1104
 
4.1%
, 793
 
2.9%
4 774
 
2.8%
7 741
 
2.7%
Other values (39) 2871
 
10.6%
Hangul
ValueCountFrequency (%)
부 2963
 
6.8%
동 2943
 
6.8%
산 2764
 
6.4%
시 2411
 
5.6%
광 2372
 
5.5%
역 2207
 
5.1%
로 2143
 
4.9%
구 2142
 
4.9%
층 1499
 
3.5%
대 1280
 
2.9%
Other values (399) 20679
47.6%
None
ValueCountFrequency (%)
· 1
100.0%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1585
Distinct (%)72.9%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean129.06933
Minimum128.81107
Maximum129.27873
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2023-12-12T22:24:35.334254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.81107
5-th percentile128.96209
Q1129.02521
median129.06876
Q3129.11195
95-th percentile129.21278
Maximum129.27873
Range0.4676571
Interquartile range (IQR)0.0867311

Descriptive statistics

Standard deviation0.07207087
Coefficient of variation (CV)0.00055838883
Kurtosis0.26939148
Mean129.06933
Median Absolute Deviation (MAD)0.0431915
Skewness-0.040000024
Sum280725.79
Variance0.0051942103
MonotonicityNot monotonic
2023-12-12T22:24:35.778988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.1290849 63
 
2.9%
129.0564133 57
 
2.6%
129.0367048 49
 
2.3%
129.0774768 30
 
1.4%
129.2127825 25
 
1.1%
128.966874 22
 
1.0%
129.0450567 17
 
0.8%
128.9809875 17
 
0.8%
129.0620097 16
 
0.7%
129.0630128 15
 
0.7%
Other values (1575) 1864
85.7%
ValueCountFrequency (%)
128.8110705 1
< 0.1%
128.8150536 1
< 0.1%
128.8309552 1
< 0.1%
128.8313223 1
< 0.1%
128.8339461 1
< 0.1%
128.8342313 1
< 0.1%
128.8352848 1
< 0.1%
128.8359182 1
< 0.1%
128.8367129 1
< 0.1%
128.877691 1
< 0.1%
ValueCountFrequency (%)
129.2787276 1
 
< 0.1%
129.2483977 5
0.2%
129.2464003 1
 
< 0.1%
129.2453451 1
 
< 0.1%
129.2395335 1
 
< 0.1%
129.2349503 8
0.4%
129.2340326 1
 
< 0.1%
129.2301 1
 
< 0.1%
129.2295052 1
 
< 0.1%
129.2289006 3
 
0.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1585
Distinct (%)72.9%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean35.167577
Minimum35.041835
Maximum35.382872
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2023-12-12T22:24:35.953837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.041835
5-th percentile35.086385
Q135.136558
median35.166421
Q335.197316
95-th percentile35.249337
Maximum35.382872
Range0.34103731
Interquartile range (IQR)0.060757765

Descriptive statistics

Standard deviation0.052372997
Coefficient of variation (CV)0.001489241
Kurtosis0.97739929
Mean35.167577
Median Absolute Deviation (MAD)0.03033786
Skewness0.48299128
Sum76489.479
Variance0.0027429309
MonotonicityNot monotonic
2023-12-12T22:24:36.130845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.16881869 63
 
2.9%
35.15679253 57
 
2.6%
35.09830894 49
 
2.3%
35.21170859 30
 
1.4%
35.19221051 25
 
1.1%
35.10681916 22
 
1.0%
35.11760826 17
 
0.8%
35.1631425 17
 
0.8%
35.19126678 16
 
0.7%
35.15703218 15
 
0.7%
Other values (1575) 1864
85.7%
ValueCountFrequency (%)
35.04183483 1
< 0.1%
35.0481839 1
< 0.1%
35.04876808 1
< 0.1%
35.04892488 1
< 0.1%
35.04913699 1
< 0.1%
35.04978906 2
0.1%
35.05102069 1
< 0.1%
35.05189767 1
< 0.1%
35.05295812 2
0.1%
35.05428767 1
< 0.1%
ValueCountFrequency (%)
35.38287214 5
0.2%
35.37752079 1
 
< 0.1%
35.37044306 1
 
< 0.1%
35.337363 1
 
< 0.1%
35.33512773 1
 
< 0.1%
35.33475709 1
 
< 0.1%
35.33449336 1
 
< 0.1%
35.33328752 2
 
0.1%
35.32813813 1
 
< 0.1%
35.32763586 1
 
< 0.1%

위생등급
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
매우우수
1940 
우수
 
174
좋음
 
62

Length

Max length4
Median length4
Mean length3.7830882
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row매우우수
2nd row매우우수
3rd row우수
4th row매우우수
5th row매우우수

Common Values

ValueCountFrequency (%)
매우우수 1940
89.2%
우수 174
 
8.0%
좋음 62
 
2.8%

Length

2023-12-12T22:24:36.285852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:24:36.409120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
매우우수 1940
89.2%
우수 174
 
8.0%
좋음 62
 
2.8%

지정번호
Text

UNIQUE 

Distinct2176
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2023-12-12T22:24:36.645779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters23936
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2176 ?
Unique (%)100.0%

Sample

1st rowHG230003847
2nd rowHG220006326
3rd rowHG220005674
4th rowHG220008762
5th rowHG210003215
ValueCountFrequency (%)
hg230003847 1
 
< 0.1%
hg220006326 1
 
< 0.1%
hg220005663 1
 
< 0.1%
hg210003242 1
 
< 0.1%
hg230002500 1
 
< 0.1%
hg230008555 1
 
< 0.1%
hg230000115 1
 
< 0.1%
hg230002394 1
 
< 0.1%
hg210011552 1
 
< 0.1%
hg220008664 1
 
< 0.1%
Other values (2166) 2166
99.5%
2023-12-12T22:24:37.043409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7543
31.5%
2 3955
16.5%
H 2176
 
9.1%
G 2176
 
9.1%
1 1614
 
6.7%
3 1475
 
6.2%
8 878
 
3.7%
7 839
 
3.5%
6 827
 
3.5%
9 826
 
3.5%
Other values (2) 1627
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19584
81.8%
Uppercase Letter 4352
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7543
38.5%
2 3955
20.2%
1 1614
 
8.2%
3 1475
 
7.5%
8 878
 
4.5%
7 839
 
4.3%
6 827
 
4.2%
9 826
 
4.2%
5 817
 
4.2%
4 810
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
H 2176
50.0%
G 2176
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19584
81.8%
Latin 4352
 
18.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7543
38.5%
2 3955
20.2%
1 1614
 
8.2%
3 1475
 
7.5%
8 878
 
4.5%
7 839
 
4.3%
6 827
 
4.2%
9 826
 
4.2%
5 817
 
4.2%
4 810
 
4.1%
Latin
ValueCountFrequency (%)
H 2176
50.0%
G 2176
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23936
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7543
31.5%
2 3955
16.5%
H 2176
 
9.1%
G 2176
 
9.1%
1 1614
 
6.7%
3 1475
 
6.2%
8 878
 
3.7%
7 839
 
3.5%
6 827
 
3.5%
9 826
 
3.5%
Other values (2) 1627
 
6.8%

관할기관
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
부산광역시 해운대구
324 
부산광역시 부산진구
276 
부산광역시 동래구
178 
부산광역시 사하구
161 
부산광역시 기장군
151 
Other values (11)
1086 

Length

Max length10
Median length9
Mean length9.0611213
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 중구
2nd row부산광역시 중구
3rd row부산광역시 중구
4th row부산광역시 중구
5th row부산광역시 중구

Common Values

ValueCountFrequency (%)
부산광역시 해운대구 324
14.9%
부산광역시 부산진구 276
12.7%
부산광역시 동래구 178
8.2%
부산광역시 사하구 161
 
7.4%
부산광역시 기장군 151
 
6.9%
부산광역시 연제구 145
 
6.7%
부산광역시 금정구 138
 
6.3%
부산광역시 북구 132
 
6.1%
부산광역시 사상구 120
 
5.5%
부산광역시 남구 112
 
5.1%
Other values (6) 439
20.2%

Length

2023-12-12T22:24:37.230093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산광역시 2176
50.0%
해운대구 324
 
7.4%
부산진구 276
 
6.3%
동래구 178
 
4.1%
사하구 161
 
3.7%
기장군 151
 
3.5%
연제구 145
 
3.3%
금정구 138
 
3.2%
북구 132
 
3.0%
사상구 120
 
2.8%
Other values (7) 551
 
12.7%

지정일자
Date

Distinct428
Distinct (%)19.7%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
Minimum2021-11-17 00:00:00
Maximum2023-11-15 00:00:00
2023-12-12T22:24:37.383780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:24:37.575447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T22:24:32.338071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:24:31.673937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:24:31.998313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:24:32.442794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:24:31.778426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:24:32.097785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:24:32.547425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:24:31.899568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:24:32.217228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:24:37.678794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번경도위도위생등급관할기관
연번1.0000.7770.6230.2330.861
경도0.7771.0000.8000.0000.911
위도0.6230.8001.0000.0560.874
위생등급0.2330.0000.0561.0000.039
관할기관0.8610.9110.8740.0391.000
2023-12-12T22:24:37.791719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관할기관위생등급
관할기관1.0000.021
위생등급0.0211.000
2023-12-12T22:24:37.898275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번경도위도위생등급관할기관
연번1.0000.0580.1610.1420.567
경도0.0581.0000.4710.0000.671
위도0.1610.4711.0000.0330.591
위생등급0.1420.0000.0331.0000.021
관할기관0.5670.6710.5910.0211.000

Missing values

2023-12-12T22:24:32.688057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:24:32.860084image/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.
2023-12-12T22:24:32.999041image/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

연번업소명(상호)영업장소재지경도위도위생등급지정번호관할기관지정일자
01BHC 보수부민점부산광역시 중구 보수대로106번길 14(1층 보수동3가, 22-2번지)129.02168335.104774매우우수HG230003847부산광역시 중구2023-06-16
12푸라닭부산광역시 중구 흑교로35번길 6(1층 부평동3가)129.02476135.102719매우우수HG220006326부산광역시 중구2022-08-04
23떡볶이참잘하는집 떡참 부산중구점부산광역시 중구 법수길 4(1층 보수동1가)129.02575635.104207우수HG220005674부산광역시 중구2022-07-14
34부평동 커피공장부산광역시 중구 부평2길 28(1층 부평동1가)129.02653435.100676매우우수HG220008762부산광역시 중구2022-10-13
45배스킨라빈스부산부평부산광역시 중구 비프광장로 21(1,2층 부평동1가)129.02753135.098802매우우수HG210003215부산광역시 중구2023-04-23
56(유)아웃백스테이크하우스코리아 남포점부산광역시 중구 구덕로 54-1(3층 남포동5가, 피닉스호텔)129.02970835.098378매우우수HG230001405부산광역시 중구2023-03-23
67아비꼬 남포점부산광역시 중구 남포길 14(1~2층 남포동3가)129.03022935.098833매우우수HG220008686부산광역시 중구2022-10-12
78롤링파스타(부산남포점)부산광역시 중구 광복로 64-1(2층 광복동2가)129.0319335.098909매우우수HG230005762부산광역시 중구2023-08-11
89인생아구찜부산광역시 중구 복병산길 6(대청동1가)129.03197435.103217매우우수HG230009021부산광역시 중구2023-11-15
910남포설렁탕부산광역시 중구 구덕로34번길 5(1층 남포동2가)129.03204535.098466매우우수HG220008664부산광역시 중구2022-10-12
연번업소명(상호)영업장소재지경도위도위생등급지정번호관할기관지정일자
21662167부산엄궁 뚜레쥬르부산광역시 사상구 엄궁로203번길 40(1층 엄궁동)128.97184235.128873매우우수HG230006944부산광역시 사상구2023-09-18
21672168뚜레쥬르 부산 학장본점부산광역시 사상구 학감대로 111(학장동)128.98765535.140896매우우수HG230008370부산광역시 사상구2023-11-01
21682169파리바게뜨 정관중앙점부산광역시 기장군 정관읍 정관로 581(성원프라자 102호,103호)129.17748135.321247매우우수HG210007300부산광역시 기장군2023-07-30
21692170뚜레쥬르 정관홈플러스점부산광역시 기장군 정관읍 정관5로 50(정관 홈플러스 1층)129.17638635.323052매우우수HG220009135부산광역시 기장군2022-10-25
21702171뚜레쥬르부산기장교리점부산광역시 기장군 기장읍 차성로 436(1층)129.21778735.254454매우우수HG220004359부산광역시 기장군2022-06-13
21712172앤티앤스 첼시기장점부산광역시 기장군 장안읍 정관로 1133(1400동 177호 부산프리미엄아울렛)129.2349535.32381매우우수HG210001770부산광역시 기장군2023-03-19
21722173이케아 베이커리부산광역시 기장군 기장읍 동부산관광3로 17(2층)129.21027235.190289매우우수HG230004599부산광역시 기장군2023-07-10
21732174뚜레쥬르부산일광신도시부산광역시 기장군 일광읍 해빛2로 21(상가동 105호 e편한세상 일광)129.22606235.269062매우우수HG230005897부산광역시 기장군2023-08-17
21742175파리바게뜨 일광신도시점부산광역시 기장군 일광면 해빛로 17(1층 106~107호)129.2260235.266304매우우수HG210005793부산광역시 기장군2023-06-28
21752176파리바게뜨 일광해빛로점부산광역시 기장군 일광면 해빛1로 74(107호)129.22280935.260325매우우수HG230005921부산광역시 기장군2023-08-17