Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells39007
Missing cells (%)32.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory111.0 B

Variable types

Numeric6
Text2
Categorical2
Boolean1
Unsupported1

Dataset

Description울산광역시에 위치한 식당의 품질정보를 적어놓은 데이터 입니다. 식당명, 어워드정보설명, RTI지수, 온라인화진행여부, 수용태세지수, 인기도 등 식당품질정보를 포함하고 있습니다.
Author재단법인울산관광재단
URLhttps://www.data.go.kr/data/15109431/fileData.do

Alerts

식당(ID) is highly overall correlated with 어워드정보설명High correlation
(RTI)지수 is highly overall correlated with 수용태세지수 and 1 other fieldsHigh correlation
수용태세지수 is highly overall correlated with (RTI)지수High correlation
인기도 is highly overall correlated with (RTI)지수High correlation
어워드정보설명 is highly overall correlated with 식당(ID)High correlation
어워드정보설명 is highly imbalanced (95.4%)Imbalance
지점명 has 7664 (76.6%) missing valuesMissing
온라인화진행여부 has 2028 (20.3%) missing valuesMissing
수용태세지수 has 702 (7.0%) missing valuesMissing
인기도 has 4957 (49.6%) missing valuesMissing
트립어드바이저평점 has 9934 (99.3%) missing valuesMissing
씨트립평점 has 10000 (100.0%) missing valuesMissing
네이버평점 has 3708 (37.1%) missing valuesMissing
식당(ID) has unique valuesUnique
씨트립평점 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 12:23:23.424715
Analysis finished2023-12-12 12:23:31.188191
Duration7.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

식당(ID)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean346647.01
Minimum11434
Maximum947925
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:23:31.300256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11434
5-th percentile131501.95
Q1140080.75
median149722.5
Q3911601.5
95-th percentile928489.2
Maximum947925
Range936491
Interquartile range (IQR)771520.75

Descriptive statistics

Standard deviation342037.92
Coefficient of variation (CV)0.98670379
Kurtosis-0.81869484
Mean346647.01
Median Absolute Deviation (MAD)10198.5
Skewness1.0814679
Sum3.4664701 × 109
Variance1.1698994 × 1011
MonotonicityNot monotonic
2023-12-12T21:23:31.474379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
144945 1
 
< 0.1%
11434 1
 
< 0.1%
157461 1
 
< 0.1%
141548 1
 
< 0.1%
913036 1
 
< 0.1%
156853 1
 
< 0.1%
151012 1
 
< 0.1%
136156 1
 
< 0.1%
154663 1
 
< 0.1%
922634 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
11434 1
< 0.1%
11437 1
< 0.1%
11439 1
< 0.1%
11440 1
< 0.1%
11442 1
< 0.1%
11443 1
< 0.1%
11445 1
< 0.1%
11450 1
< 0.1%
11451 1
< 0.1%
11453 1
< 0.1%
ValueCountFrequency (%)
947925 1
< 0.1%
930989 1
< 0.1%
930980 1
< 0.1%
930977 1
< 0.1%
930974 1
< 0.1%
930972 1
< 0.1%
930964 1
< 0.1%
930958 1
< 0.1%
930956 1
< 0.1%
930953 1
< 0.1%

식당명
Text

Distinct8455
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T21:23:31.881662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length26
Mean length5.1685
Min length1

Characters and Unicode

Total characters51685
Distinct characters1061
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7753 ?
Unique (%)77.5%

Sample

1st row엘리펀트피자
2nd row참살이 산들바람
3rd row옹심이메밀칼국수
4th row역전의통닭
5th row더엠가든
ValueCountFrequency (%)
카페 52
 
0.5%
파리바게뜨 43
 
0.4%
맘스터치 39
 
0.4%
더벤티 22
 
0.2%
커피 22
 
0.2%
스타벅스 18
 
0.2%
파스쿠찌 18
 
0.2%
옛날통닭 18
 
0.2%
롯데리아 17
 
0.2%
네네치킨 17
 
0.2%
Other values (8814) 10482
97.5%
2023-12-12T21:23:32.546239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 1171
 
2.3%
식 903
 
1.7%
리 850
 
1.6%
스 794
 
1.5%
751
 
1.5%
국 628
 
1.2%
당 621
 
1.2%
밥 596
 
1.2%
가 580
 
1.1%
집 566
 
1.1%
Other values (1051) 44225
85.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49070
94.9%
Space Separator 751
 
1.5%
Decimal Number 611
 
1.2%
Lowercase Letter 446
 
0.9%
Uppercase Letter 329
 
0.6%
Other Punctuation 161
 
0.3%
Open Punctuation 151
 
0.3%
Close Punctuation 151
 
0.3%
Dash Punctuation 5
 
< 0.1%
Control 5
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1171
 
2.4%
식 903
 
1.8%
리 850
 
1.7%
스 794
 
1.6%
국 628
 
1.3%
당 621
 
1.3%
밥 596
 
1.2%
가 580
 
1.2%
집 566
 
1.2%
마 542
 
1.1%
Other values (972) 41819
85.2%
Uppercase Letter
ValueCountFrequency (%)
C 34
 
10.3%
O 26
 
7.9%
B 25
 
7.6%
A 24
 
7.3%
E 24
 
7.3%
S 24
 
7.3%
G 23
 
7.0%
M 16
 
4.9%
L 15
 
4.6%
D 14
 
4.3%
Other values (16) 104
31.6%
Lowercase Letter
ValueCountFrequency (%)
e 62
13.9%
o 51
11.4%
a 46
 
10.3%
n 30
 
6.7%
f 28
 
6.3%
i 23
 
5.2%
c 23
 
5.2%
r 23
 
5.2%
t 21
 
4.7%
u 19
 
4.3%
Other values (14) 120
26.9%
Other Punctuation
ValueCountFrequency (%)
& 93
57.8%
. 25
 
15.5%
, 19
 
11.8%
! 7
 
4.3%
: 6
 
3.7%
/ 2
 
1.2%
? 2
 
1.2%
# 2
 
1.2%
· 2
 
1.2%
@ 2
 
1.2%
Decimal Number
ValueCountFrequency (%)
2 108
17.7%
1 98
16.0%
0 78
12.8%
9 68
11.1%
3 64
10.5%
5 56
9.2%
4 38
 
6.2%
8 36
 
5.9%
7 36
 
5.9%
6 29
 
4.7%
Math Symbol
ValueCountFrequency (%)
+ 3
75.0%
~ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
751
100.0%
Open Punctuation
ValueCountFrequency (%)
( 151
100.0%
Close Punctuation
ValueCountFrequency (%)
) 151
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Control
ValueCountFrequency (%)
5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49067
94.9%
Common 1839
 
3.6%
Latin 776
 
1.5%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1171
 
2.4%
식 903
 
1.8%
리 850
 
1.7%
스 794
 
1.6%
국 628
 
1.3%
당 621
 
1.3%
밥 596
 
1.2%
가 580
 
1.2%
집 566
 
1.2%
마 542
 
1.1%
Other values (969) 41816
85.2%
Latin
ValueCountFrequency (%)
e 62
 
8.0%
o 51
 
6.6%
a 46
 
5.9%
C 34
 
4.4%
n 30
 
3.9%
f 28
 
3.6%
O 26
 
3.4%
B 25
 
3.2%
A 24
 
3.1%
E 24
 
3.1%
Other values (41) 426
54.9%
Common
ValueCountFrequency (%)
751
40.8%
( 151
 
8.2%
) 151
 
8.2%
2 108
 
5.9%
1 98
 
5.3%
& 93
 
5.1%
0 78
 
4.2%
9 68
 
3.7%
3 64
 
3.5%
5 56
 
3.0%
Other values (18) 221
 
12.0%
Han
ValueCountFrequency (%)
一 1
33.3%
香 1
33.3%
味 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49035
94.9%
ASCII 2611
 
5.1%
Compat Jamo 32
 
0.1%
None 3
 
< 0.1%
CJK 3
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 1171
 
2.4%
식 903
 
1.8%
리 850
 
1.7%
스 794
 
1.6%
국 628
 
1.3%
당 621
 
1.3%
밥 596
 
1.2%
가 580
 
1.2%
집 566
 
1.2%
마 542
 
1.1%
Other values (952) 41784
85.2%
ASCII
ValueCountFrequency (%)
751
28.8%
( 151
 
5.8%
) 151
 
5.8%
2 108
 
4.1%
1 98
 
3.8%
& 93
 
3.6%
0 78
 
3.0%
9 68
 
2.6%
3 64
 
2.5%
e 62
 
2.4%
Other values (66) 987
37.8%
Compat Jamo
ValueCountFrequency (%)
ㅤ 8
25.0%
ㅍ 4
12.5%
ㅅ 3
 
9.4%
ㅑ 3
 
9.4%
ㄸ 2
 
6.2%
ㅛ 1
 
3.1%
ㄴ 1
 
3.1%
ㅉ 1
 
3.1%
ㄲ 1
 
3.1%
ㅗ 1
 
3.1%
Other values (7) 7
21.9%
None
ValueCountFrequency (%)
· 2
66.7%
＆ 1
33.3%
CJK
ValueCountFrequency (%)
一 1
33.3%
香 1
33.3%
味 1
33.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

지점명
Text

MISSING 

Distinct631
Distinct (%)27.0%
Missing7664
Missing (%)76.6%
Memory size156.2 KiB
2023-12-12T21:23:33.013080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length4.1806507
Min length2

Characters and Unicode

Total characters9766
Distinct characters289
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique425 ?
Unique (%)18.2%

Sample

1st row울산북구점
2nd row삼산점
3rd row시청점
4th row옥동 농협하나로점
5th row태화강국가정원점
ValueCountFrequency (%)
울산점 99
 
4.1%
본점 82
 
3.4%
삼산점 68
 
2.8%
언양점 58
 
2.4%
무거점 53
 
2.2%
달동점 53
 
2.2%
울산 51
 
2.1%
울산본점 42
 
1.7%
호계점 40
 
1.6%
울산대점 38
 
1.6%
Other values (601) 1845
76.0%
2023-12-12T21:23:33.632918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 2361
24.2%
산 1121
 
11.5%
울 900
 
9.2%
동 254
 
2.6%
구 247
 
2.5%
정 194
 
2.0%
화 159
 
1.6%
호 156
 
1.6%
본 155
 
1.6%
삼 146
 
1.5%
Other values (279) 4073
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9527
97.6%
Space Separator 93
 
1.0%
Decimal Number 81
 
0.8%
Uppercase Letter 36
 
0.4%
Lowercase Letter 23
 
0.2%
Other Punctuation 4
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 2361
24.8%
산 1121
 
11.8%
울 900
 
9.4%
동 254
 
2.7%
구 247
 
2.6%
정 194
 
2.0%
화 159
 
1.7%
호 156
 
1.6%
본 155
 
1.6%
삼 146
 
1.5%
Other values (246) 3834
40.2%
Uppercase Letter
ValueCountFrequency (%)
D 8
22.2%
T 8
22.2%
C 5
13.9%
G 3
 
8.3%
V 3
 
8.3%
S 2
 
5.6%
F 2
 
5.6%
N 2
 
5.6%
K 1
 
2.8%
E 1
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
o 4
17.4%
e 4
17.4%
l 3
13.0%
f 3
13.0%
n 2
8.7%
a 2
8.7%
m 1
 
4.3%
c 1
 
4.3%
i 1
 
4.3%
y 1
 
4.3%
Decimal Number
ValueCountFrequency (%)
2 38
46.9%
1 28
34.6%
3 10
 
12.3%
8 3
 
3.7%
5 1
 
1.2%
4 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
, 2
50.0%
Space Separator
ValueCountFrequency (%)
93
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9527
97.6%
Common 180
 
1.8%
Latin 59
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 2361
24.8%
산 1121
 
11.8%
울 900
 
9.4%
동 254
 
2.7%
구 247
 
2.6%
정 194
 
2.0%
화 159
 
1.7%
호 156
 
1.6%
본 155
 
1.6%
삼 146
 
1.5%
Other values (246) 3834
40.2%
Latin
ValueCountFrequency (%)
D 8
13.6%
T 8
13.6%
C 5
 
8.5%
o 4
 
6.8%
e 4
 
6.8%
G 3
 
5.1%
V 3
 
5.1%
l 3
 
5.1%
f 3
 
5.1%
n 2
 
3.4%
Other values (12) 16
27.1%
Common
ValueCountFrequency (%)
93
51.7%
2 38
21.1%
1 28
 
15.6%
3 10
 
5.6%
8 3
 
1.7%
. 2
 
1.1%
, 2
 
1.1%
5 1
 
0.6%
) 1
 
0.6%
( 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9527
97.6%
ASCII 239
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 2361
24.8%
산 1121
 
11.8%
울 900
 
9.4%
동 254
 
2.7%
구 247
 
2.6%
정 194
 
2.0%
화 159
 
1.7%
호 156
 
1.6%
본 155
 
1.6%
삼 146
 
1.5%
Other values (246) 3834
40.2%
ASCII
ValueCountFrequency (%)
93
38.9%
2 38
15.9%
1 28
 
11.7%
3 10
 
4.2%
D 8
 
3.3%
T 8
 
3.3%
C 5
 
2.1%
o 4
 
1.7%
e 4
 
1.7%
G 3
 
1.3%
Other values (23) 38
15.9%

지역명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남구
3362 
울주군
2072 
중구
1684 
북구
1542 
동구
1340 

Length

Max length3
Median length2
Mean length2.2072
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row북구
2nd row남구
3rd row남구
4th row동구
5th row울주군

Common Values

ValueCountFrequency (%)
남구 3362
33.6%
울주군 2072
20.7%
중구 1684
16.8%
북구 1542
15.4%
동구 1340
 
13.4%

Length

2023-12-12T21:23:33.856870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:23:34.026366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남구 3362
33.6%
울주군 2072
20.7%
중구 1684
16.8%
북구 1542
15.4%
동구 1340
 
13.4%

어워드정보설명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct36
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9759 
안심식당(2020)
 
109
안심식당(2021)
 
48
어린이 우수판매업소(2021)
 
12
모범음식점(2015)
 
6
Other values (31)
 
66

Length

Max length33
Median length4
Mean length4.1925
Min length4

Unique

Unique11 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9759
97.6%
안심식당(2020) 109
 
1.1%
안심식당(2021) 48
 
0.5%
어린이 우수판매업소(2021) 12
 
0.1%
모범음식점(2015) 6
 
0.1%
블루리본(2021) 5
 
0.1%
모범음식점(2014) 4
 
< 0.1%
모범음식점(2018) 4
 
< 0.1%
모범음식점(2013),안심식당(2020) 4
 
< 0.1%
모범음식점(2015),안심식당(2020) 4
 
< 0.1%
Other values (26) 45
 
0.4%

Length

2023-12-12T21:23:34.204567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9759
97.5%
안심식당(2020 109
 
1.1%
안심식당(2021 48
 
0.5%
어린이 12
 
0.1%
우수판매업소(2021 12
 
0.1%
모범음식점(2015 6
 
0.1%
블루리본(2021 5
 
< 0.1%
모범음식점(2013),안심식당(2020 4
 
< 0.1%
모범음식점(2015),안심식당(2020 4
 
< 0.1%
모범음식점(2018 4
 
< 0.1%
Other values (27) 49
 
0.5%

(RTI)지수
Real number (ℝ)

HIGH CORRELATION 

Distinct1897
Distinct (%)19.0%
Missing14
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean2.4833458
Minimum0.0186212
Maximum4.9898276
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:23:34.387388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0186212
5-th percentile0.0186212
Q10.910544
median3.7781069
Q34.2651776
95-th percentile4.447416
Maximum4.9898276
Range4.9712064
Interquartile range (IQR)3.3546336

Descriptive statistics

Standard deviation1.8553813
Coefficient of variation (CV)0.74712964
Kurtosis-1.8134507
Mean2.4833458
Median Absolute Deviation (MAD)0.6868675
Skewness-0.20656339
Sum24798.691
Variance3.4424396
MonotonicityNot monotonic
2023-12-12T21:23:34.564076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.910544 2346
23.5%
0.0186212 2014
20.1%
3.8151542 486
 
4.9%
4.0717341 238
 
2.4%
4.0210963 172
 
1.7%
4.2834283 116
 
1.2%
0.6118575 105
 
1.1%
4.2453604 92
 
0.9%
3.4508113 82
 
0.8%
3.2736601 71
 
0.7%
Other values (1887) 4264
42.6%
ValueCountFrequency (%)
0.0186212 2014
20.1%
0.1577147 13
 
0.1%
0.3580624 1
 
< 0.1%
0.4254137 1
 
< 0.1%
0.4563329 1
 
< 0.1%
0.5516763 2
 
< 0.1%
0.5986256 8
 
0.1%
0.6118575 105
 
1.1%
0.6815285 14
 
0.1%
0.6920943 1
 
< 0.1%
ValueCountFrequency (%)
4.9898276 1
< 0.1%
4.8865116 1
< 0.1%
4.8403388 1
< 0.1%
4.8205794 1
< 0.1%
4.7766542 1
< 0.1%
4.7263887 2
< 0.1%
4.702867 1
< 0.1%
4.6734414 1
< 0.1%
4.6733739 2
< 0.1%
4.6626798 1
< 0.1%

온라인화진행여부
Boolean

MISSING 

Distinct2
Distinct (%)< 0.1%
Missing2028
Missing (%)20.3%
Memory size97.7 KiB
False
6847 
True
1125 
(Missing)
2028 
ValueCountFrequency (%)
False 6847
68.5%
True 1125
 
11.2%
(Missing) 2028
 
20.3%
2023-12-12T21:23:34.708028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

수용태세지수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct168
Distinct (%)1.8%
Missing702
Missing (%)7.0%
Infinite0
Infinite (%)0.0%
Mean0.18126414
Minimum0.029
Maximum0.345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:23:34.862086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.029
5-th percentile0.029
Q10.17
median0.201
Q30.218
95-th percentile0.266
Maximum0.345
Range0.316
Interquartile range (IQR)0.048

Descriptive statistics

Standard deviation0.071438663
Coefficient of variation (CV)0.39411359
Kurtosis0.44111527
Mean0.18126414
Median Absolute Deviation (MAD)0.02
Skewness-1.1982983
Sum1685.394
Variance0.0051034825
MonotonicityNot monotonic
2023-12-12T21:23:35.044659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.201 1481
14.8%
0.029 1350
13.5%
0.17 833
 
8.3%
0.2 803
 
8.0%
0.202 423
 
4.2%
0.189 401
 
4.0%
0.218 369
 
3.7%
0.12 245
 
2.5%
0.217 218
 
2.2%
0.199 197
 
2.0%
Other values (158) 2978
29.8%
(Missing) 702
 
7.0%
ValueCountFrequency (%)
0.029 1350
13.5%
0.044 22
 
0.2%
0.048 11
 
0.1%
0.051 1
 
< 0.1%
0.053 2
 
< 0.1%
0.057 3
 
< 0.1%
0.063 45
 
0.4%
0.066 4
 
< 0.1%
0.072 1
 
< 0.1%
0.075 1
 
< 0.1%
ValueCountFrequency (%)
0.345 1
< 0.1%
0.337 2
< 0.1%
0.336 1
< 0.1%
0.33 1
< 0.1%
0.329 1
< 0.1%
0.322 1
< 0.1%
0.321 1
< 0.1%
0.32 1
< 0.1%
0.318 1
< 0.1%
0.317 1
< 0.1%

인기도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct30
Distinct (%)0.6%
Missing4957
Missing (%)49.6%
Infinite0
Infinite (%)0.0%
Mean0.13361293
Minimum0.01
Maximum0.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:23:35.219675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.01
Q10.02
median0.08
Q30.27
95-th percentile0.33
Maximum0.33
Range0.32
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation0.12512602
Coefficient of variation (CV)0.93648135
Kurtosis-1.264715
Mean0.13361293
Median Absolute Deviation (MAD)0.07
Skewness0.62497656
Sum673.81
Variance0.01565652
MonotonicityNot monotonic
2023-12-12T21:23:35.392584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.33 1099
 
11.0%
0.01 841
 
8.4%
0.02 497
 
5.0%
0.03 389
 
3.9%
0.04 294
 
2.9%
0.06 224
 
2.2%
0.07 199
 
2.0%
0.08 167
 
1.7%
0.09 153
 
1.5%
0.1 119
 
1.2%
Other values (20) 1061
 
10.6%
(Missing) 4957
49.6%
ValueCountFrequency (%)
0.01 841
8.4%
0.02 497
5.0%
0.03 389
3.9%
0.04 294
 
2.9%
0.06 224
 
2.2%
0.07 199
 
2.0%
0.08 167
 
1.7%
0.09 153
 
1.5%
0.1 119
 
1.2%
0.11 86
 
0.9%
ValueCountFrequency (%)
0.33 1099
11.0%
0.32 23
 
0.2%
0.31 25
 
0.2%
0.3 30
 
0.3%
0.29 41
 
0.4%
0.28 30
 
0.3%
0.27 37
 
0.4%
0.26 38
 
0.4%
0.24 42
 
0.4%
0.23 35
 
0.4%

트립어드바이저평점
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)9.1%
Missing9934
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean3.9848485
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:23:35.574953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q14
median4
Q34.375
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)0.375

Descriptive statistics

Standard deviation0.70148029
Coefficient of variation (CV)0.17603688
Kurtosis3.8440723
Mean3.9848485
Median Absolute Deviation (MAD)0.25
Skewness-1.0822304
Sum263
Variance0.49207459
MonotonicityNot monotonic
2023-12-12T21:23:35.742235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
4.0 33
 
0.3%
5.0 11
 
0.1%
3.0 9
 
0.1%
4.5 6
 
0.1%
3.5 6
 
0.1%
1.0 1
 
< 0.1%
(Missing) 9934
99.3%
ValueCountFrequency (%)
1.0 1
 
< 0.1%
3.0 9
 
0.1%
3.5 6
 
0.1%
4.0 33
0.3%
4.5 6
 
0.1%
5.0 11
 
0.1%
ValueCountFrequency (%)
5.0 11
 
0.1%
4.5 6
 
0.1%
4.0 33
0.3%
3.5 6
 
0.1%
3.0 9
 
0.1%
1.0 1
 
< 0.1%

씨트립평점
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

네이버평점
Real number (ℝ)

MISSING 

Distinct160
Distinct (%)2.5%
Missing3708
Missing (%)37.1%
Infinite0
Infinite (%)0.0%
Mean4.4252352
Minimum0.5
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:23:35.945465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile4
Q14.32
median4.44
Q34.57
95-th percentile4.9
Maximum5
Range4.5
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation0.31199859
Coefficient of variation (CV)0.070504407
Kurtosis21.482618
Mean4.4252352
Median Absolute Deviation (MAD)0.12
Skewness-2.7366468
Sum27843.58
Variance0.097343117
MonotonicityNot monotonic
2023-12-12T21:23:36.176502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.0 277
 
2.8%
4.5 277
 
2.8%
4.38 152
 
1.5%
4.33 152
 
1.5%
4.41 150
 
1.5%
4.44 150
 
1.5%
4.42 149
 
1.5%
4.47 143
 
1.4%
4.45 143
 
1.4%
4.43 138
 
1.4%
Other values (150) 4561
45.6%
(Missing) 3708
37.1%
ValueCountFrequency (%)
0.5 3
 
< 0.1%
1.5 2
 
< 0.1%
2.0 4
 
< 0.1%
2.25 1
 
< 0.1%
2.3 1
 
< 0.1%
2.5 7
 
0.1%
2.67 1
 
< 0.1%
2.7 1
 
< 0.1%
2.83 1
 
< 0.1%
3.0 38
0.4%
ValueCountFrequency (%)
5.0 277
2.8%
4.97 1
 
< 0.1%
4.96 1
 
< 0.1%
4.95 4
 
< 0.1%
4.94 5
 
0.1%
4.93 7
 
0.1%
4.92 7
 
0.1%
4.91 1
 
< 0.1%
4.9 15
 
0.1%
4.89 9
 
0.1%

Interactions

2023-12-12T21:23:29.316779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:25.462960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:26.227033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:27.048238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:27.811032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:28.526771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:29.440508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:25.579011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:26.355763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:27.160665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:27.937352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:28.632288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:29.575650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:25.717544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:26.492450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:27.303002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:28.055051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:28.763880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:29.709145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:25.845528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:26.638314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:27.443762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:28.167248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:28.905928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:29.856913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:25.963749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:26.781155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:27.562076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:28.280330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:29.037548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:29.996673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:26.103886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:26.913127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:27.688224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:28.394945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:29.163986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:23:36.308668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
식당(ID)지역명어워드정보설명(RTI)지수온라인화진행여부수용태세지수인기도트립어드바이저평점네이버평점
식당(ID)1.0000.0360.8040.5700.1450.5830.0910.5560.060
지역명0.0361.0000.4650.1050.0410.1140.1530.0000.070
어워드정보설명0.8040.4651.0000.0000.4080.3040.0000.6330.000
(RTI)지수0.5700.1050.0001.0000.3410.7100.4950.3440.328
온라인화진행여부0.1450.0410.4080.3411.0000.3560.1530.2420.090
수용태세지수0.5830.1140.3040.7100.3561.0000.2520.5220.178
인기도0.0910.1530.0000.4950.1530.2521.0000.3850.112
트립어드바이저평점0.5560.0000.6330.3440.2420.5220.3851.0000.000
네이버평점0.0600.0700.0000.3280.0900.1780.1120.0001.000
2023-12-12T21:23:36.474794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온라인화진행여부어워드정보설명지역명
온라인화진행여부1.0000.3200.051
어워드정보설명0.3201.0000.204
지역명0.0510.2041.000
2023-12-12T21:23:36.622738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
식당(ID)(RTI)지수수용태세지수인기도트립어드바이저평점네이버평점지역명어워드정보설명온라인화진행여부
식당(ID)1.000-0.400-0.3450.0320.1540.0780.0200.5500.155
(RTI)지수-0.4001.0000.7920.633-0.3070.0760.0610.0000.340
수용태세지수-0.3450.7921.0000.3710.0920.2620.0470.1000.273
인기도0.0320.6330.3711.000-0.0290.0600.0640.1150.118
트립어드바이저평점0.154-0.3070.092-0.0291.0000.0830.0000.0000.165
네이버평점0.0780.0760.2620.0600.0831.0000.0380.0000.098
지역명0.0200.0610.0470.0640.0000.0381.0000.2040.051
어워드정보설명0.5500.0000.1000.1150.0000.0000.2041.0000.320
온라인화진행여부0.1550.3400.2730.1180.1650.0980.0510.3201.000

Missing values

2023-12-12T21:23:30.181092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:23:30.828986image/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.
2023-12-12T21:23:31.057788image/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

식당(ID)식당명지점명지역명어워드정보설명(RTI)지수온라인화진행여부수용태세지수인기도트립어드바이저평점씨트립평점네이버평점
6041144945엘리펀트피자울산북구점북구<NA>4.377745N0.2250.02<NA><NA>4.52
9620152598참살이 산들바람삼산점남구<NA>4.224607N0.2360.07<NA><NA>4.51
12643911882옹심이메밀칼국수시청점남구<NA>0.018621<NA>0.029<NA><NA><NA><NA>
886131588역전의통닭<NA>동구<NA>3.815154N0.2020.01<NA><NA>5.0
15035923362더엠가든<NA>울주군<NA>0.910544N0.12<NA><NA><NA><NA>
2972136996진만두<NA>동구<NA>4.021096N0.1890.03<NA><NA><NA>
2475135744삼삼국수<NA>남구<NA>3.982788Y0.2180.27<NA><NA>4.46
7757148465병영생아구찜<NA>중구<NA>0.018621<NA>0.029<NA><NA><NA><NA>
11050155514콩깍지순두부<NA>울주군<NA>4.128365Y0.2650.04<NA><NA>4.04
334130411고갯마루해장국<NA>북구<NA>0.018621<NA>0.029<NA><NA><NA><NA>
식당(ID)식당명지점명지역명어워드정보설명(RTI)지수온라인화진행여부수용태세지수인기도트립어드바이저평점씨트립평점네이버평점
3409138175과수원집<NA>동구<NA>3.815154N0.2010.01<NA><NA>4.71
1139132181족사랑야음점남구<NA>4.34634N0.220.12<NA><NA>4.38
10265153977만파식적<NA>중구<NA>0.018621<NA>0.029<NA><NA><NA><NA>
10455154310왕손피자남구점남구<NA>3.815154N0.2010.01<NA><NA>4.69
16895930819화명당 마라탕<NA>동구<NA>0.018621<NA><NA><NA><NA><NA><NA>
15469925556참맛있는고기비빔밥무거점남구<NA>0.018621<NA>0.029<NA><NA><NA><NA>
2649136159울산갈매기살<NA>남구<NA>4.360699Y0.2190.1<NA><NA>4.72
11394156330베리굿카페<NA>울주군<NA>4.391383N0.2340.32<NA><NA>4.55
234130213고궁삼계탕<NA>남구<NA>3.843136N0.2010.16<NA><NA>4.34
3214137655온산자연산횟집<NA>남구<NA>4.360699Y0.2330.1<NA><NA>4.46