Overview

Dataset statistics

Number of variables12
Number of observations7700
Missing cells21987
Missing cells (%)23.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory774.6 KiB
Average record size in memory103.0 B

Variable types

Numeric6
Text2
Categorical3
Boolean1

Dataset

Description서울특별시 영등포구에 위치한 식당의 품질정보를 적어놓은 데이터 입니다.식당명, 어워드정보, RTI지수, 온라인화진행여부, 수용태세지수, 인기도 등 식당품질정보를 포함하고 있습니다.
Author서울특별시 영등포구
URLhttps://www.data.go.kr/data/15099327/fileData.do

Alerts

지역명 has constant value ""Constant
씨트립평점 is highly overall correlated with (RTI)지수 and 3 other fieldsHigh correlation
어워드정보설명 is highly overall correlated with 네이버평점 and 1 other fieldsHigh correlation
식당(ID) is highly overall correlated with (RTI)지수 and 1 other fieldsHigh correlation
(RTI)지수 is highly overall correlated with 식당(ID) and 4 other fieldsHigh correlation
수용태세지수 is highly overall correlated with 식당(ID) and 2 other fieldsHigh correlation
인기도 is highly overall correlated with (RTI)지수High correlation
네이버평점 is highly overall correlated with 어워드정보설명 and 1 other fieldsHigh correlation
온라인화진행여부 is highly overall correlated with (RTI)지수 and 2 other fieldsHigh correlation
어워드정보설명 is highly imbalanced (93.4%)Imbalance
씨트립평점 is highly imbalanced (99.3%)Imbalance
지점명 has 5761 (74.8%) missing valuesMissing
온라인화진행여부 has 1154 (15.0%) missing valuesMissing
수용태세지수 has 506 (6.6%) missing valuesMissing
인기도 has 3904 (50.7%) missing valuesMissing
트립어드바이저평점 has 7380 (95.8%) missing valuesMissing
네이버평점 has 3205 (41.6%) missing valuesMissing
식당(ID) has unique valuesUnique

Reproduction

Analysis started2024-03-14 20:58:49.100122
Analysis finished2024-03-14 20:59:02.762459
Duration13.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

식당(ID)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct7700
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean306301.49
Minimum10754
Maximum948035
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.8 KiB
2024-03-15T05:59:02.980799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10754
5-th percentile28515.95
Q136238.5
median38573.5
Q3823877.75
95-th percentile846105.15
Maximum948035
Range937281
Interquartile range (IQR)787639.25

Descriptive statistics

Standard deviation377235.07
Coefficient of variation (CV)1.2315809
Kurtosis-1.5399008
Mean306301.49
Median Absolute Deviation (MAD)8985
Skewness0.67546711
Sum2.3585215 × 109
Variance1.423063 × 1011
MonotonicityStrictly increasing
2024-03-15T05:59:03.247878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10754 1
 
< 0.1%
40132 1
 
< 0.1%
788086 1
 
< 0.1%
788034 1
 
< 0.1%
787956 1
 
< 0.1%
787922 1
 
< 0.1%
787886 1
 
< 0.1%
787843 1
 
< 0.1%
787801 1
 
< 0.1%
787740 1
 
< 0.1%
Other values (7690) 7690
99.9%
ValueCountFrequency (%)
10754 1
< 0.1%
10755 1
< 0.1%
10757 1
< 0.1%
10758 1
< 0.1%
12278 1
< 0.1%
12279 1
< 0.1%
12288 1
< 0.1%
12329 1
< 0.1%
12385 1
< 0.1%
12436 1
< 0.1%
ValueCountFrequency (%)
948035 1
< 0.1%
948026 1
< 0.1%
947912 1
< 0.1%
920050 1
< 0.1%
869446 1
< 0.1%
865343 1
< 0.1%
847242 1
< 0.1%
847239 1
< 0.1%
847236 1
< 0.1%
847233 1
< 0.1%

식당명
Text

Distinct6742
Distinct (%)87.6%
Missing0
Missing (%)0.0%
Memory size60.3 KiB
2024-03-15T05:59:04.569350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length5.3979221
Min length1

Characters and Unicode

Total characters41564
Distinct characters1072
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6204 ?
Unique (%)80.6%

Sample

1st row63뷔페 파빌리온
2nd row슈치쿠
3rd row워킹온더클라우드
4th row백리향
5th row고구려
ValueCountFrequency (%)
스타벅스 36
 
0.4%
파리바게뜨 35
 
0.4%
카페 18
 
0.2%
coffee 18
 
0.2%
여의도 15
 
0.2%
김밥천국 14
 
0.2%
본죽 14
 
0.2%
전주식당 11
 
0.1%
공차 11
 
0.1%
피자스쿨 10
 
0.1%
Other values (7185) 8265
97.8%
2024-03-15T05:59:06.159755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 978
 
2.4%
스 946
 
2.3%
747
 
1.8%
리 688
 
1.7%
식 564
 
1.4%
당 503
 
1.2%
피 482
 
1.2%
마 419
 
1.0%
치 405
 
1.0%
커 380
 
0.9%
Other values (1062) 35452
85.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37020
89.1%
Uppercase Letter 1406
 
3.4%
Lowercase Letter 1015
 
2.4%
Space Separator 747
 
1.8%
Decimal Number 539
 
1.3%
Close Punctuation 336
 
0.8%
Open Punctuation 336
 
0.8%
Other Punctuation 146
 
0.4%
Dash Punctuation 8
 
< 0.1%
Connector Punctuation 4
 
< 0.1%
Other values (3) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 978
 
2.6%
스 946
 
2.6%
리 688
 
1.9%
식 564
 
1.5%
당 503
 
1.4%
피 482
 
1.3%
마 419
 
1.1%
치 405
 
1.1%
커 380
 
1.0%
국 353
 
1.0%
Other values (982) 31302
84.6%
Uppercase Letter
ValueCountFrequency (%)
E 149
 
10.6%
O 118
 
8.4%
A 110
 
7.8%
C 98
 
7.0%
S 77
 
5.5%
F 76
 
5.4%
L 73
 
5.2%
R 71
 
5.0%
I 71
 
5.0%
B 69
 
4.9%
Other values (16) 494
35.1%
Lowercase Letter
ValueCountFrequency (%)
e 166
16.4%
a 97
 
9.6%
o 84
 
8.3%
i 61
 
6.0%
s 60
 
5.9%
n 59
 
5.8%
l 58
 
5.7%
f 51
 
5.0%
t 49
 
4.8%
r 46
 
4.5%
Other values (15) 284
28.0%
Other Punctuation
ValueCountFrequency (%)
& 74
50.7%
. 25
 
17.1%
, 15
 
10.3%
' 12
 
8.2%
/ 9
 
6.2%
! 3
 
2.1%
· 3
 
2.1%
: 2
 
1.4%
; 1
 
0.7%
# 1
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 93
17.3%
2 79
14.7%
3 75
13.9%
0 50
9.3%
9 50
9.3%
5 45
8.3%
8 42
7.8%
6 37
 
6.9%
7 36
 
6.7%
4 32
 
5.9%
Space Separator
ValueCountFrequency (%)
747
100.0%
Close Punctuation
ValueCountFrequency (%)
) 336
100.0%
Open Punctuation
ValueCountFrequency (%)
( 336
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36984
89.0%
Latin 2422
 
5.8%
Common 2122
 
5.1%
Han 36
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 978
 
2.6%
스 946
 
2.6%
리 688
 
1.9%
식 564
 
1.5%
당 503
 
1.4%
피 482
 
1.3%
마 419
 
1.1%
치 405
 
1.1%
커 380
 
1.0%
국 353
 
1.0%
Other values (951) 31266
84.5%
Latin
ValueCountFrequency (%)
e 166
 
6.9%
E 149
 
6.2%
O 118
 
4.9%
A 110
 
4.5%
C 98
 
4.0%
a 97
 
4.0%
o 84
 
3.5%
S 77
 
3.2%
F 76
 
3.1%
L 73
 
3.0%
Other values (42) 1374
56.7%
Han
ValueCountFrequency (%)
大 4
 
11.1%
元 2
 
5.6%
串 2
 
5.6%
新 1
 
2.8%
趣 1
 
2.8%
來 1
 
2.8%
盛 1
 
2.8%
食 1
 
2.8%
館 1
 
2.8%
和 1
 
2.8%
Other values (21) 21
58.3%
Common
ValueCountFrequency (%)
747
35.2%
) 336
15.8%
( 336
15.8%
1 93
 
4.4%
2 79
 
3.7%
3 75
 
3.5%
& 74
 
3.5%
0 50
 
2.4%
9 50
 
2.4%
5 45
 
2.1%
Other values (18) 237
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36980
89.0%
ASCII 4540
 
10.9%
CJK 34
 
0.1%
Compat Jamo 4
 
< 0.1%
None 3
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 978
 
2.6%
스 946
 
2.6%
리 688
 
1.9%
식 564
 
1.5%
당 503
 
1.4%
피 482
 
1.3%
마 419
 
1.1%
치 405
 
1.1%
커 380
 
1.0%
국 353
 
1.0%
Other values (948) 31262
84.5%
ASCII
ValueCountFrequency (%)
747
 
16.5%
) 336
 
7.4%
( 336
 
7.4%
e 166
 
3.7%
E 149
 
3.3%
O 118
 
2.6%
A 110
 
2.4%
C 98
 
2.2%
a 97
 
2.1%
1 93
 
2.0%
Other values (68) 2290
50.4%
CJK
ValueCountFrequency (%)
大 4
 
11.8%
元 2
 
5.9%
新 1
 
2.9%
趣 1
 
2.9%
來 1
 
2.9%
盛 1
 
2.9%
食 1
 
2.9%
館 1
 
2.9%
和 1
 
2.9%
美 1
 
2.9%
Other values (20) 20
58.8%
None
ValueCountFrequency (%)
· 3
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
串 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅋ 2
50.0%
ㅁ 1
25.0%
ㅎ 1
25.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

지점명
Text

MISSING 

Distinct436
Distinct (%)22.5%
Missing5761
Missing (%)74.8%
Memory size60.3 KiB
2024-03-15T05:59:07.271986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length4.9525529
Min length2

Characters and Unicode

Total characters9603
Distinct characters268
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

Unique294 ?
Unique (%)15.2%

Sample

1st row선유도점
2nd row본점
3rd row유스호스텔점
4th row중앙여의도지점
5th row서여의도점
ValueCountFrequency (%)
여의도점 221
 
11.0%
영등포점 219
 
10.9%
당산점 82
 
4.1%
문래점 72
 
3.6%
본점 66
 
3.3%
신길점 65
 
3.2%
더현대서울점 59
 
2.9%
대림점 57
 
2.8%
타임스퀘어점 54
 
2.7%
영등포구청점 51
 
2.5%
Other values (431) 1062
52.9%
2024-03-15T05:59:09.247062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 1992
20.7%
영 507
 
5.3%
도 503
 
5.2%
포 470
 
4.9%
등 467
 
4.9%
의 447
 
4.7%
여 425
 
4.4%
대 203
 
2.1%
역 200
 
2.1%
신 172
 
1.8%
Other values (258) 4217
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9166
95.4%
Uppercase Letter 247
 
2.6%
Decimal Number 116
 
1.2%
Space Separator 69
 
0.7%
Lowercase Letter 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1992
21.7%
영 507
 
5.5%
도 503
 
5.5%
포 470
 
5.1%
등 467
 
5.1%
의 447
 
4.9%
여 425
 
4.6%
대 203
 
2.2%
역 200
 
2.2%
신 172
 
1.9%
Other values (225) 3780
41.2%
Uppercase Letter
ValueCountFrequency (%)
K 37
15.0%
F 37
15.0%
C 36
14.6%
I 34
13.8%
S 33
13.4%
B 25
10.1%
T 8
 
3.2%
E 6
 
2.4%
L 6
 
2.4%
R 5
 
2.0%
Other values (10) 20
8.1%
Decimal Number
ValueCountFrequency (%)
2 49
42.2%
1 41
35.3%
3 16
 
13.8%
6 5
 
4.3%
4 3
 
2.6%
9 1
 
0.9%
5 1
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
h 1
50.0%
Space Separator
ValueCountFrequency (%)
69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9166
95.4%
Latin 249
 
2.6%
Common 188
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1992
21.7%
영 507
 
5.5%
도 503
 
5.5%
포 470
 
5.1%
등 467
 
5.1%
의 447
 
4.9%
여 425
 
4.6%
대 203
 
2.2%
역 200
 
2.2%
신 172
 
1.9%
Other values (225) 3780
41.2%
Latin
ValueCountFrequency (%)
K 37
14.9%
F 37
14.9%
C 36
14.5%
I 34
13.7%
S 33
13.3%
B 25
10.0%
T 8
 
3.2%
E 6
 
2.4%
L 6
 
2.4%
R 5
 
2.0%
Other values (12) 22
8.8%
Common
ValueCountFrequency (%)
69
36.7%
2 49
26.1%
1 41
21.8%
3 16
 
8.5%
6 5
 
2.7%
4 3
 
1.6%
9 1
 
0.5%
( 1
 
0.5%
- 1
 
0.5%
) 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9166
95.4%
ASCII 437
 
4.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 1992
21.7%
영 507
 
5.5%
도 503
 
5.5%
포 470
 
5.1%
등 467
 
5.1%
의 447
 
4.9%
여 425
 
4.6%
대 203
 
2.2%
역 200
 
2.2%
신 172
 
1.9%
Other values (225) 3780
41.2%
ASCII
ValueCountFrequency (%)
69
15.8%
2 49
11.2%
1 41
9.4%
K 37
8.5%
F 37
8.5%
C 36
8.2%
I 34
7.8%
S 33
7.6%
B 25
 
5.7%
3 16
 
3.7%
Other values (23) 60
13.7%

지역명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size60.3 KiB
영등포구
7700 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영등포구 7700
100.0%

Length

2024-03-15T05:59:09.979966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:59:10.420078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영등포구 7700
100.0%

어워드정보설명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct41
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size60.3 KiB
<NA>
7432 
안심식당(2020)
 
79
위생등급제 지정업소(2020)
 
40
블루리본(2021)
 
21
위생등급제 지정업소(2019)
 
17
Other values (36)
 
111

Length

Max length39
Median length4
Mean length4.412987
Min length4

Unique

Unique13 ?
Unique (%)0.2%

Sample

1st row블루리본(2021)
2nd row모범음식점(2004),블루리본(2021),안심식당(2020)
3rd row모범음식점(2004),블루리본(2021),안심식당(2020)
4th row모범음식점(2004),블루리본(2021),안심식당(2020)
5th row모범음식점(2010),안심식당(2020)

Common Values

ValueCountFrequency (%)
<NA> 7432
96.5%
안심식당(2020) 79
 
1.0%
위생등급제 지정업소(2020) 40
 
0.5%
블루리본(2021) 21
 
0.3%
위생등급제 지정업소(2019) 17
 
0.2%
모범음식점(2004),안심식당(2020) 14
 
0.2%
안심식당(2020),위생등급제 지정업소(2020) 12
 
0.2%
모범음식점(2008),안심식당(2020) 6
 
0.1%
모범음식점(2006),안심식당(2020) 5
 
0.1%
모범음식점(2006) 5
 
0.1%
Other values (31) 69
 
0.9%

Length

2024-03-15T05:59:10.891682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7432
95.6%
안심식당(2020 79
 
1.0%
위생등급제 57
 
0.7%
지정업소(2020 54
 
0.7%
지정업소(2019 22
 
0.3%
블루리본(2021 21
 
0.3%
안심식당(2020),위생등급제 16
 
0.2%
모범음식점(2004),안심식당(2020 14
 
0.2%
모범음식점(2008),안심식당(2020 6
 
0.1%
모범음식점(2010 5
 
0.1%
Other values (32) 72
 
0.9%

(RTI)지수
Real number (ℝ)

HIGH CORRELATION 

Distinct2317
Distinct (%)30.4%
Missing77
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean2.536735
Minimum0.0117244
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.8 KiB
2024-03-15T05:59:11.428988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0117244
5-th percentile0.0186212
Q10.910544
median3.8151542
Q34.2972152
95-th percentile4.4686292
Maximum5
Range4.9882756
Interquartile range (IQR)3.3866712

Descriptive statistics

Standard deviation1.8336688
Coefficient of variation (CV)0.72284603
Kurtosis-1.8254192
Mean2.536735
Median Absolute Deviation (MAD)0.6968981
Skewness-0.17667151
Sum19337.531
Variance3.3623412
MonotonicityNot monotonic
2024-03-15T05:59:12.019081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.910544 2229
28.9%
0.0186212 1077
 
14.0%
3.8151542 198
 
2.6%
4.0717341 118
 
1.5%
0.1577147 107
 
1.4%
3.2736601 91
 
1.2%
4.0210963 63
 
0.8%
4.2453604 58
 
0.8%
4.2834283 55
 
0.7%
4.1162244 48
 
0.6%
Other values (2307) 3579
46.5%
(Missing) 77
 
1.0%
ValueCountFrequency (%)
0.0117244 2
 
< 0.1%
0.0186212 1077
14.0%
0.0189351 1
 
< 0.1%
0.0411959 1
 
< 0.1%
0.0416878 2
 
< 0.1%
0.0716172 1
 
< 0.1%
0.1016405 7
 
0.1%
0.1577147 107
 
1.4%
0.1751647 1
 
< 0.1%
0.1765808 1
 
< 0.1%
ValueCountFrequency (%)
5.0 1
< 0.1%
4.9665173 1
< 0.1%
4.9120734 1
< 0.1%
4.8935395 1
< 0.1%
4.8676522 1
< 0.1%
4.8668634 1
< 0.1%
4.8665501 1
< 0.1%
4.8450574 1
< 0.1%
4.8412101 1
< 0.1%
4.8387559 1
< 0.1%

온라인화진행여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1154
Missing (%)15.0%
Memory size15.2 KiB
False
4366 
True
2180 
(Missing)
1154 
ValueCountFrequency (%)
False 4366
56.7%
True 2180
28.3%
(Missing) 1154
 
15.0%
2024-03-15T05:59:12.467735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

수용태세지수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct317
Distinct (%)4.4%
Missing506
Missing (%)6.6%
Infinite0
Infinite (%)0.0%
Mean0.19850987
Minimum0.029
Maximum0.644
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.8 KiB
2024-03-15T05:59:12.756941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.029
5-th percentile0.029
Q10.17
median0.215
Q30.241
95-th percentile0.34635
Maximum0.644
Range0.615
Interquartile range (IQR)0.071

Descriptive statistics

Standard deviation0.086273289
Coefficient of variation (CV)0.43460453
Kurtosis1.1857746
Mean0.19850987
Median Absolute Deviation (MAD)0.045
Skewness0.053573359
Sum1428.08
Variance0.0074430805
MonotonicityNot monotonic
2024-03-15T05:59:13.049033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.17 1016
 
13.2%
0.029 672
 
8.7%
0.12 527
 
6.8%
0.216 442
 
5.7%
0.215 415
 
5.4%
0.233 184
 
2.4%
0.201 165
 
2.1%
0.241 148
 
1.9%
0.204 122
 
1.6%
0.2 114
 
1.5%
Other values (307) 3389
44.0%
(Missing) 506
 
6.6%
ValueCountFrequency (%)
0.029 672
8.7%
0.044 62
 
0.8%
0.048 1
 
< 0.1%
0.051 1
 
< 0.1%
0.053 6
 
0.1%
0.055 1
 
< 0.1%
0.057 2
 
< 0.1%
0.062 6
 
0.1%
0.063 87
 
1.1%
0.066 10
 
0.1%
ValueCountFrequency (%)
0.644 1
< 0.1%
0.621 1
< 0.1%
0.576 1
< 0.1%
0.551 1
< 0.1%
0.541 1
< 0.1%
0.539 1
< 0.1%
0.532 1
< 0.1%
0.528 1
< 0.1%
0.526 1
< 0.1%
0.525 1
< 0.1%

인기도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct57
Distinct (%)1.5%
Missing3904
Missing (%)50.7%
Infinite0
Infinite (%)0.0%
Mean0.18460221
Minimum0.01
Maximum0.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.8 KiB
2024-03-15T05:59:13.407422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.01
Q10.04
median0.17
Q30.33
95-th percentile0.33
Maximum0.8
Range0.79
Interquartile range (IQR)0.29

Descriptive statistics

Standard deviation0.13844659
Coefficient of variation (CV)0.74997251
Kurtosis-0.96248798
Mean0.18460221
Median Absolute Deviation (MAD)0.15
Skewness0.24789071
Sum700.75
Variance0.019167457
MonotonicityNot monotonic
2024-03-15T05:59:13.876042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.33 1222
 
15.9%
0.01 374
 
4.9%
0.02 252
 
3.3%
0.03 193
 
2.5%
0.04 161
 
2.1%
0.06 154
 
2.0%
0.07 128
 
1.7%
0.08 102
 
1.3%
0.1 97
 
1.3%
0.09 93
 
1.2%
Other values (47) 1020
 
13.2%
(Missing) 3904
50.7%
ValueCountFrequency (%)
0.01 374
4.9%
0.02 252
3.3%
0.03 193
2.5%
0.04 161
2.1%
0.06 154
2.0%
0.07 128
 
1.7%
0.08 102
 
1.3%
0.09 93
 
1.2%
0.1 97
 
1.3%
0.11 88
 
1.1%
ValueCountFrequency (%)
0.8 1
 
< 0.1%
0.71 1
 
< 0.1%
0.68 1
 
< 0.1%
0.67 11
0.1%
0.66 1
 
< 0.1%
0.63 1
 
< 0.1%
0.62 1
 
< 0.1%
0.6 1
 
< 0.1%
0.59 3
 
< 0.1%
0.57 1
 
< 0.1%

트립어드바이저평점
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)2.2%
Missing7380
Missing (%)95.8%
Infinite0
Infinite (%)0.0%
Mean4.0859375
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.8 KiB
2024-03-15T05:59:14.267373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q14
median4
Q34.5
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.64299144
Coefficient of variation (CV)0.15736693
Kurtosis2.4301923
Mean4.0859375
Median Absolute Deviation (MAD)0.5
Skewness-0.89389267
Sum1307.5
Variance0.41343799
MonotonicityNot monotonic
2024-03-15T05:59:14.611020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
4.0 132
 
1.7%
4.5 68
 
0.9%
5.0 52
 
0.7%
3.0 36
 
0.5%
3.5 29
 
0.4%
1.0 2
 
< 0.1%
2.0 1
 
< 0.1%
(Missing) 7380
95.8%
ValueCountFrequency (%)
1.0 2
 
< 0.1%
2.0 1
 
< 0.1%
3.0 36
 
0.5%
3.5 29
 
0.4%
4.0 132
1.7%
4.5 68
0.9%
5.0 52
 
0.7%
ValueCountFrequency (%)
5.0 52
 
0.7%
4.5 68
0.9%
4.0 132
1.7%
3.5 29
 
0.4%
3.0 36
 
0.5%
2.0 1
 
< 0.1%
1.0 2
 
< 0.1%

씨트립평점
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size60.3 KiB
<NA>
7690 
4.0
 
4
5.0
 
3
4.3
 
1
4.5
 
1

Length

Max length4
Median length4
Mean length3.9987013
Min length3

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row4.3
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7690
99.9%
4.0 4
 
0.1%
5.0 3
 
< 0.1%
4.3 1
 
< 0.1%
4.5 1
 
< 0.1%
4.2 1
 
< 0.1%

Length

2024-03-15T05:59:14.876077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:59:15.197758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7690
99.9%
4.0 4
 
0.1%
5.0 3
 
< 0.1%
4.3 1
 
< 0.1%
4.5 1
 
< 0.1%
4.2 1
 
< 0.1%

네이버평점
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct147
Distinct (%)3.3%
Missing3205
Missing (%)41.6%
Infinite0
Infinite (%)0.0%
Mean4.3632102
Minimum0.5
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.8 KiB
2024-03-15T05:59:15.641981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile4
Q14.25
median4.37
Q34.5
95-th percentile4.77
Maximum5
Range4.5
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation0.28092771
Coefficient of variation (CV)0.064385554
Kurtosis29.988318
Mean4.3632102
Median Absolute Deviation (MAD)0.12
Skewness-2.8362655
Sum19612.63
Variance0.078920377
MonotonicityNot monotonic
2024-03-15T05:59:15.951953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.5 141
 
1.8%
4.39 124
 
1.6%
4.33 121
 
1.6%
4.25 119
 
1.5%
5.0 115
 
1.5%
4.38 115
 
1.5%
4.34 112
 
1.5%
4.3 110
 
1.4%
4.37 107
 
1.4%
4.41 106
 
1.4%
Other values (137) 3325
43.2%
(Missing) 3205
41.6%
ValueCountFrequency (%)
0.5 2
 
< 0.1%
1.0 2
 
< 0.1%
2.0 1
 
< 0.1%
2.5 4
 
0.1%
2.75 1
 
< 0.1%
2.83 1
 
< 0.1%
2.9 2
 
< 0.1%
3.0 13
0.2%
3.17 1
 
< 0.1%
3.25 3
 
< 0.1%
ValueCountFrequency (%)
5.0 115
1.5%
4.97 5
 
0.1%
4.96 2
 
< 0.1%
4.95 1
 
< 0.1%
4.94 5
 
0.1%
4.92 4
 
0.1%
4.91 5
 
0.1%
4.9 11
 
0.1%
4.89 3
 
< 0.1%
4.88 8
 
0.1%

Interactions

2024-03-15T05:58:59.581020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:50.839260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:52.637761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:54.422105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:56.171755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:57.608944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:59.843501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:51.100350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:52.889846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:54.693721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:56.466783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:57.833003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:59:00.120227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:51.355005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:53.245569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:54.977117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:56.827589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:58.285267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:59:00.400766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:51.619529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:53.542824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:55.366115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:57.068288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:58.610030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:59:00.718564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:51.895664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:53.857303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:55.614304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:57.259631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:58.982233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:59:01.010276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:52.382260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:54.142076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:55.906261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:57.443349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:58:59.299774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:59:16.161195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
식당(ID)어워드정보설명(RTI)지수온라인화진행여부수용태세지수인기도트립어드바이저평점씨트립평점네이버평점
식당(ID)1.0000.5610.5200.4660.4840.0870.2650.0000.000
어워드정보설명0.5611.0000.1780.1470.6760.6920.6181.0000.807
(RTI)지수0.5200.1781.0000.7310.8080.5460.221NaN0.215
온라인화진행여부0.4660.1470.7311.0000.6890.2430.0240.6080.147
수용태세지수0.4840.6760.8080.6891.0000.3470.2270.6760.140
인기도0.0870.6920.5460.2430.3471.0000.2700.8780.122
트립어드바이저평점0.2650.6180.2210.0240.2270.2701.0000.0000.225
씨트립평점0.0001.000NaN0.6080.6760.8780.0001.0001.000
네이버평점0.0000.8070.2150.1470.1400.1220.2251.0001.000
2024-03-15T05:59:16.475624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온라인화진행여부씨트립평점어워드정보설명
온라인화진행여부1.0000.5590.106
씨트립평점0.5591.0001.000
어워드정보설명0.1061.0001.000
2024-03-15T05:59:16.737854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
식당(ID)(RTI)지수수용태세지수인기도트립어드바이저평점네이버평점어워드정보설명온라인화진행여부씨트립평점
식당(ID)1.000-0.524-0.507-0.040-0.0120.1490.4170.3140.000
(RTI)지수-0.5241.0000.7810.525-0.1770.1270.0550.5721.000
수용태세지수-0.5070.7811.0000.342-0.1310.0910.2670.5360.000
인기도-0.0400.5250.3421.0000.0580.0630.2960.1860.447
트립어드바이저평점-0.012-0.177-0.1310.0581.0000.0040.2640.0250.000
네이버평점0.1490.1270.0910.0630.0041.0000.5240.1440.756
어워드정보설명0.4170.0550.2670.2960.2640.5241.0000.1061.000
온라인화진행여부0.3140.5720.5360.1860.0250.1440.1061.0000.559
씨트립평점0.0001.0000.0000.4470.0000.7561.0000.5591.000

Missing values

2024-03-15T05:59:01.406527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:59:02.057662image/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.
2024-03-15T05:59:02.493341image/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
01075463뷔페 파빌리온<NA>영등포구블루리본(2021)4.300097N0.5180.674.0<NA>4.49
110755슈치쿠<NA>영등포구모범음식점(2004),블루리본(2021),안심식당(2020)4.322418N0.5180.385.0<NA>4.67
210757워킹온더클라우드<NA>영등포구모범음식점(2004),블루리본(2021),안심식당(2020)4.454008N0.5510.84.04.34.68
310758백리향<NA>영등포구모범음식점(2004),블루리본(2021),안심식당(2020)4.413188N0.5160.494.5<NA>4.6
412278고구려선유도점영등포구모범음식점(2010),안심식당(2020)4.063338Y0.3050.33<NA><NA>4.27
512279너섬가<NA>영등포구모범음식점(2010)4.205759Y0.2230.124.0<NA>4.47
612288동해도본점영등포구모범음식점(2004)4.343204N0.3030.434.0<NA>4.23
712329상하이몽<NA>영등포구모범음식점(2009)3.703597N0.2630.01<NA><NA>4.44
812385함흥냉면<NA>영등포구모범음식점(2004),안심식당(2020),위생등급제 지정업소(2020)4.278508Y0.6210.364.5<NA>4.29
912436선유삼계탕<NA>영등포구모범음식점(2014),안심식당(2020)1.245173N0.262<NA><NA><NA>4.41
식당(ID)식당명지점명지역명어워드정보설명(RTI)지수온라인화진행여부수용태세지수인기도트립어드바이저평점씨트립평점네이버평점
7690847233후니드 KDB산업은행여의도1점영등포구<NA>0.018621<NA><NA><NA><NA><NA><NA>
7691847236본우리집밥우체국금융개발원점영등포구<NA>0.018621<NA><NA><NA><NA><NA><NA>
7692847239아라마크 코스트코코리아양평점영등포구<NA>0.018621<NA><NA><NA><NA><NA><NA>
7693847242푸디스트한국예탁결제원점영등포구<NA>0.018621<NA><NA><NA><NA><NA><NA>
7694865343케이에스에이치여의나루치킨<NA>영등포구<NA>0.018621<NA>0.029<NA><NA><NA><NA>
7695869446개성손만두여의도점<NA>영등포구<NA>0.018621<NA>0.029<NA><NA><NA><NA>
7696920050냠냠쩝쩝<NA>영등포구<NA>0.910544N0.17<NA><NA><NA><NA>
7697947912미슐램<NA>영등포구<NA>4.12018N0.2160.02<NA><NA>4.45
7698948026포이스트영등포지하상가점<NA>영등포구<NA>4.040497N0.2320.01<NA><NA>4.25
7699948035마마트영등포점영등포구<NA>0.157715Y0.063<NA><NA><NA><NA>