Overview

Dataset statistics

Number of variables20
Number of observations36
Missing cells8
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory170.7 B

Variable types

Numeric7
Categorical5
DateTime2
Text6

Dataset

Description안양시 물가안정 모범업소 및 착한가격업소 현황(관내 착한가격 업소 인건비, 재료비 등 지속적 상승에도 원가 절감, 효율화 노력을 통해 저렴한 가격으로 서비스를 제공하고 있는 업소)
URLhttps://www.data.go.kr/data/3045160/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
기준일 has constant value ""Constant
전체 메뉴 수 is highly overall correlated with 착한가격 메뉴 수High correlation
착한가격 메뉴 수 is highly overall correlated with 전체 메뉴 수High correlation
가격1 is highly overall correlated with 가격2 and 1 other fieldsHigh correlation
가격2 is highly overall correlated with 가격1 and 1 other fieldsHigh correlation
가격3 is highly overall correlated with 가격1 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 업종 대분류 and 1 other fieldsHigh correlation
업종 대분류 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
업종 세분류 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
연락처 has 2 (5.6%) missing valuesMissing
품목2 has 1 (2.8%) missing valuesMissing
가격2 has 1 (2.8%) missing valuesMissing
품목3 has 2 (5.6%) missing valuesMissing
가격3 has 2 (5.6%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:03:03.362275
Analysis finished2023-12-12 07:03:09.889108
Duration6.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.5
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T16:03:09.972245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.75
Q19.75
median18.5
Q327.25
95-th percentile34.25
Maximum36
Range35
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation10.535654
Coefficient of variation (CV)0.5694948
Kurtosis-1.2
Mean18.5
Median Absolute Deviation (MAD)9
Skewness0
Sum666
Variance111
MonotonicityStrictly increasing
2023-12-12T16:03:10.140314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 1
 
2.8%
20 1
 
2.8%
22 1
 
2.8%
23 1
 
2.8%
24 1
 
2.8%
25 1
 
2.8%
26 1
 
2.8%
27 1
 
2.8%
28 1
 
2.8%
29 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
1 1
2.8%
2 1
2.8%
3 1
2.8%
4 1
2.8%
5 1
2.8%
6 1
2.8%
7 1
2.8%
8 1
2.8%
9 1
2.8%
10 1
2.8%
ValueCountFrequency (%)
36 1
2.8%
35 1
2.8%
34 1
2.8%
33 1
2.8%
32 1
2.8%
31 1
2.8%
30 1
2.8%
29 1
2.8%
28 1
2.8%
27 1
2.8%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
경기
36 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기 36
100.0%

Length

2023-12-12T16:03:10.335171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:03:10.435737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기 36
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
안양시
36 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안양시 36
100.0%

Length

2023-12-12T16:03:10.533874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:03:10.958170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안양시 36
100.0%

최초지정연월
Date

Distinct9
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2011-11-01 00:00:00
Maximum2022-10-01 00:00:00
2023-12-12T16:03:11.060785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:11.190756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
외식업
26 
기타개인서비스업
10 

Length

Max length8
Median length3
Mean length4.3888889
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
외식업 26
72.2%
기타개인서비스업 10
 
27.8%

Length

2023-12-12T16:03:11.355537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:03:11.470947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외식업 26
72.2%
기타개인서비스업 10
 
27.8%

업종 대분류
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
한식
20 
이용업
4 
미용업
4 
세탁업
3 
중식
 
2
Other values (3)
3 

Length

Max length6
Median length2
Mean length2.5555556
Min length2

Unique

Unique3 ?
Unique (%)8.3%

Sample

1st row한식
2nd row기타비요식업
3rd row한식
4th row한식
5th row중식

Common Values

ValueCountFrequency (%)
한식 20
55.6%
이용업 4
 
11.1%
미용업 4
 
11.1%
세탁업 3
 
8.3%
중식 2
 
5.6%
기타비요식업 1
 
2.8%
기타요식업 1
 
2.8%
<NA> 1
 
2.8%

Length

2023-12-12T16:03:11.606929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:03:11.786055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 20
55.6%
이용업 4
 
11.1%
미용업 4
 
11.1%
세탁업 3
 
8.3%
중식 2
 
5.6%
기타비요식업 1
 
2.8%
기타요식업 1
 
2.8%
na 1
 
2.8%

업종 세분류
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
한식_기타
20 
이용업
4 
한식_육류
3 
세탁업
3 
미용업
3 
Other values (2)
3 

Length

Max length5
Median length5
Mean length4.2777778
Min length2

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row한식_기타
2nd row한식_기타
3rd row한식_기타
4th row한식_육류
5th row중식

Common Values

ValueCountFrequency (%)
한식_기타 20
55.6%
이용업 4
 
11.1%
한식_육류 3
 
8.3%
세탁업 3
 
8.3%
미용업 3
 
8.3%
중식 2
 
5.6%
한식_일반 1
 
2.8%

Length

2023-12-12T16:03:11.945280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:03:12.081747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식_기타 20
55.6%
이용업 4
 
11.1%
한식_육류 3
 
8.3%
세탁업 3
 
8.3%
미용업 3
 
8.3%
중식 2
 
5.6%
한식_일반 1
 
2.8%

업소명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T16:03:12.308505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.0555556
Min length3

Characters and Unicode

Total characters182
Distinct characters122
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row돈모아참삼겹
2nd row남부고기집
3rd row설악명품추어탕
4th row참풍년집 정육식당
5th row홍보석
ValueCountFrequency (%)
돈모아참삼겹 1
 
2.4%
명당만두 1
 
2.4%
오동도 1
 
2.4%
산아나고 1
 
2.4%
팥선생 1
 
2.4%
자매식당 1
 
2.4%
뉴현대이발관 1
 
2.4%
오늘은 1
 
2.4%
머리하는날 1
 
2.4%
순천갈비 1
 
2.4%
Other values (32) 32
76.2%
2023-12-12T16:03:12.701317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
3.3%
세 5
 
2.7%
리 4
 
2.2%
당 4
 
2.2%
제 4
 
2.2%
우 4
 
2.2%
집 4
 
2.2%
어 4
 
2.2%
탁 3
 
1.6%
소 3
 
1.6%
Other values (112) 141
77.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 176
96.7%
Space Separator 6
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 5
 
2.8%
리 4
 
2.3%
당 4
 
2.3%
제 4
 
2.3%
우 4
 
2.3%
집 4
 
2.3%
어 4
 
2.3%
탁 3
 
1.7%
소 3
 
1.7%
대 3
 
1.7%
Other values (111) 138
78.4%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 176
96.7%
Common 6
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 5
 
2.8%
리 4
 
2.3%
당 4
 
2.3%
제 4
 
2.3%
우 4
 
2.3%
집 4
 
2.3%
어 4
 
2.3%
탁 3
 
1.7%
소 3
 
1.7%
대 3
 
1.7%
Other values (111) 138
78.4%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 176
96.7%
ASCII 6
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
100.0%
Hangul
ValueCountFrequency (%)
세 5
 
2.8%
리 4
 
2.3%
당 4
 
2.3%
제 4
 
2.3%
우 4
 
2.3%
집 4
 
2.3%
어 4
 
2.3%
탁 3
 
1.7%
소 3
 
1.7%
대 3
 
1.7%
Other values (111) 138
78.4%

주소(도로명 주소)
Text

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T16:03:12.967103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length24.666667
Min length19

Characters and Unicode

Total characters888
Distinct characters77
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)94.4%

Sample

1st row안양시 만안구 장내로 138 (안양동)
2nd row안양시 만안구 장내로150번길 34 (안양동)
3rd row안양시 만안구 장내로 154 (안양동)
4th row안양시 만안구 안양로 358 (안양동)
5th row안양시 만안구 안양로 358 (안양동)
ValueCountFrequency (%)
안양시 36
18.9%
만안구 19
 
10.0%
동안구 17
 
8.9%
안양동 14
 
7.4%
호계동 8
 
4.2%
안양로 4
 
2.1%
비산동 4
 
2.1%
동안로 3
 
1.6%
14 2
 
1.1%
시민대로 2
 
1.1%
Other values (71) 81
42.6%
2023-12-12T16:03:13.382798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
155
17.5%
안 96
 
10.8%
양 61
 
6.9%
동 56
 
6.3%
시 38
 
4.3%
구 36
 
4.1%
로 36
 
4.1%
) 35
 
3.9%
( 35
 
3.9%
1 33
 
3.7%
Other values (67) 307
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 507
57.1%
Space Separator 155
 
17.5%
Decimal Number 142
 
16.0%
Close Punctuation 35
 
3.9%
Open Punctuation 35
 
3.9%
Other Punctuation 11
 
1.2%
Dash Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 96
18.9%
양 61
12.0%
동 56
11.0%
시 38
 
7.5%
구 36
 
7.1%
로 36
 
7.1%
만 19
 
3.7%
번 14
 
2.8%
길 14
 
2.8%
호 13
 
2.6%
Other values (52) 124
24.5%
Decimal Number
ValueCountFrequency (%)
1 33
23.2%
2 24
16.9%
3 20
14.1%
4 13
 
9.2%
8 12
 
8.5%
5 11
 
7.7%
7 9
 
6.3%
0 8
 
5.6%
6 7
 
4.9%
9 5
 
3.5%
Space Separator
ValueCountFrequency (%)
155
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 507
57.1%
Common 381
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 96
18.9%
양 61
12.0%
동 56
11.0%
시 38
 
7.5%
구 36
 
7.1%
로 36
 
7.1%
만 19
 
3.7%
번 14
 
2.8%
길 14
 
2.8%
호 13
 
2.6%
Other values (52) 124
24.5%
Common
ValueCountFrequency (%)
155
40.7%
) 35
 
9.2%
( 35
 
9.2%
1 33
 
8.7%
2 24
 
6.3%
3 20
 
5.2%
4 13
 
3.4%
8 12
 
3.1%
, 11
 
2.9%
5 11
 
2.9%
Other values (5) 32
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 507
57.1%
ASCII 381
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
155
40.7%
) 35
 
9.2%
( 35
 
9.2%
1 33
 
8.7%
2 24
 
6.3%
3 20
 
5.2%
4 13
 
3.4%
8 12
 
3.1%
, 11
 
2.9%
5 11
 
2.9%
Other values (5) 32
 
8.4%
Hangul
ValueCountFrequency (%)
안 96
18.9%
양 61
12.0%
동 56
11.0%
시 38
 
7.5%
구 36
 
7.1%
로 36
 
7.1%
만 19
 
3.7%
번 14
 
2.8%
길 14
 
2.8%
호 13
 
2.6%
Other values (52) 124
24.5%

연락처
Text

MISSING 

Distinct34
Distinct (%)100.0%
Missing2
Missing (%)5.6%
Memory size420.0 B
2023-12-12T16:03:13.651115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters408
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

Unique34 ?
Unique (%)100.0%

Sample

1st row031-466-1647
2nd row031-444-6305
3rd row031-466-0012
4th row031-464-9898
5th row031-443-8485
ValueCountFrequency (%)
031-444-8676 1
 
2.9%
031-466-1647 1
 
2.9%
031-389-0555 1
 
2.9%
031-383-6717 1
 
2.9%
031-387-6464 1
 
2.9%
031-421-8887 1
 
2.9%
031-456-2524 1
 
2.9%
031-427-9275 1
 
2.9%
031-427-7888 1
 
2.9%
031-464-0354 1
 
2.9%
Other values (24) 24
70.6%
2023-12-12T16:03:14.028062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 68
16.7%
3 54
13.2%
1 53
13.0%
4 53
13.0%
0 47
11.5%
7 29
7.1%
6 28
6.9%
8 25
 
6.1%
5 22
 
5.4%
2 17
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 340
83.3%
Dash Punctuation 68
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 54
15.9%
1 53
15.6%
4 53
15.6%
0 47
13.8%
7 29
8.5%
6 28
8.2%
8 25
7.4%
5 22
6.5%
2 17
 
5.0%
9 12
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 408
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 68
16.7%
3 54
13.2%
1 53
13.0%
4 53
13.0%
0 47
11.5%
7 29
7.1%
6 28
6.9%
8 25
 
6.1%
5 22
 
5.4%
2 17
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 68
16.7%
3 54
13.2%
1 53
13.0%
4 53
13.0%
0 47
11.5%
7 29
7.1%
6 28
6.9%
8 25
 
6.1%
5 22
 
5.4%
2 17
 
4.2%

전체 메뉴 수
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.7222222
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T16:03:14.177252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q15
median8
Q310.5
95-th percentile17.75
Maximum30
Range29
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation5.8583816
Coefficient of variation (CV)0.67166158
Kurtosis3.7699613
Mean8.7222222
Median Absolute Deviation (MAD)3
Skewness1.6423955
Sum314
Variance34.320635
MonotonicityNot monotonic
2023-12-12T16:03:14.292966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
5 6
16.7%
10 5
13.9%
8 4
11.1%
3 4
11.1%
4 3
8.3%
6 3
8.3%
12 3
8.3%
17 2
 
5.6%
15 2
 
5.6%
30 1
 
2.8%
Other values (3) 3
8.3%
ValueCountFrequency (%)
1 1
 
2.8%
3 4
11.1%
4 3
8.3%
5 6
16.7%
6 3
8.3%
8 4
11.1%
9 1
 
2.8%
10 5
13.9%
12 3
8.3%
15 2
 
5.6%
ValueCountFrequency (%)
30 1
 
2.8%
20 1
 
2.8%
17 2
 
5.6%
15 2
 
5.6%
12 3
8.3%
10 5
13.9%
9 1
 
2.8%
8 4
11.1%
6 3
8.3%
5 6
16.7%

착한가격 메뉴 수
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9444444
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T16:03:14.419022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.75
Q14
median6
Q310
95-th percentile15
Maximum20
Range19
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.2287752
Coefficient of variation (CV)0.60894363
Kurtosis1.3330275
Mean6.9444444
Median Absolute Deviation (MAD)2.5
Skewness1.1762686
Sum250
Variance17.88254
MonotonicityNot monotonic
2023-12-12T16:03:14.564484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
3 6
16.7%
6 6
16.7%
10 4
11.1%
5 4
11.1%
4 4
11.1%
12 3
8.3%
8 3
8.3%
15 2
 
5.6%
20 1
 
2.8%
2 1
 
2.8%
Other values (2) 2
 
5.6%
ValueCountFrequency (%)
1 1
 
2.8%
2 1
 
2.8%
3 6
16.7%
4 4
11.1%
5 4
11.1%
6 6
16.7%
7 1
 
2.8%
8 3
8.3%
10 4
11.1%
12 3
8.3%
ValueCountFrequency (%)
20 1
 
2.8%
15 2
 
5.6%
12 3
8.3%
10 4
11.1%
8 3
8.3%
7 1
 
2.8%
6 6
16.7%
5 4
11.1%
4 4
11.1%
3 6
16.7%

착한가격메뉴 비중
Real number (ℝ)

Distinct10
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.461111
Minimum50
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T16:03:14.740840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile50
Q175
median83.3
Q3100
95-th percentile100
Maximum100
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation16.337551
Coefficient of variation (CV)0.19575047
Kurtosis-0.60141757
Mean83.461111
Median Absolute Deviation (MAD)16.7
Skewness-0.61273593
Sum3004.6
Variance266.91559
MonotonicityNot monotonic
2023-12-12T16:03:14.890702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
100.0 14
38.9%
80.0 6
16.7%
75.0 3
 
8.3%
50.0 3
 
8.3%
83.3 3
 
8.3%
60.0 2
 
5.6%
66.7 2
 
5.6%
70.6 1
 
2.8%
88.2 1
 
2.8%
87.5 1
 
2.8%
ValueCountFrequency (%)
50.0 3
 
8.3%
60.0 2
 
5.6%
66.7 2
 
5.6%
70.6 1
 
2.8%
75.0 3
 
8.3%
80.0 6
16.7%
83.3 3
 
8.3%
87.5 1
 
2.8%
88.2 1
 
2.8%
100.0 14
38.9%
ValueCountFrequency (%)
100.0 14
38.9%
88.2 1
 
2.8%
87.5 1
 
2.8%
83.3 3
 
8.3%
80.0 6
16.7%
75.0 3
 
8.3%
70.6 1
 
2.8%
66.7 2
 
5.6%
60.0 2
 
5.6%
50.0 3
 
8.3%

품목1
Text

Distinct28
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T16:03:15.169230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.6388889
Min length1

Characters and Unicode

Total characters131
Distinct characters78
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)66.7%

Sample

1st row생삼겹(130g)
2nd row해장국
3rd row명품추어탕
4th row소한마리(800g)
5th row짜장면
ValueCountFrequency (%)
컷트 5
 
13.5%
백반 3
 
8.1%
짜장면 2
 
5.4%
양복 2
 
5.4%
단팥죽 1
 
2.7%
생삼겹(130g 1
 
2.7%
꽃등심(600g 1
 
2.7%
양파백세탕 1
 
2.7%
펌 1
 
2.7%
추어탕 1
 
2.7%
Other values (19) 19
51.4%
2023-12-12T16:03:15.480881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
컷 6
 
4.6%
트 6
 
4.6%
0 5
 
3.8%
백 4
 
3.1%
반 4
 
3.1%
면 4
 
3.1%
개 3
 
2.3%
g 3
 
2.3%
탕 3
 
2.3%
) 3
 
2.3%
Other values (68) 90
68.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111
84.7%
Decimal Number 9
 
6.9%
Lowercase Letter 3
 
2.3%
Close Punctuation 3
 
2.3%
Open Punctuation 3
 
2.3%
Space Separator 1
 
0.8%
Math Symbol 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
컷 6
 
5.4%
트 6
 
5.4%
백 4
 
3.6%
반 4
 
3.6%
면 4
 
3.6%
개 3
 
2.7%
탕 3
 
2.7%
찌 3
 
2.7%
양 3
 
2.7%
장 3
 
2.7%
Other values (58) 72
64.9%
Decimal Number
ValueCountFrequency (%)
0 5
55.6%
6 1
 
11.1%
1 1
 
11.1%
3 1
 
11.1%
8 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
g 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111
84.7%
Common 17
 
13.0%
Latin 3
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
컷 6
 
5.4%
트 6
 
5.4%
백 4
 
3.6%
반 4
 
3.6%
면 4
 
3.6%
개 3
 
2.7%
탕 3
 
2.7%
찌 3
 
2.7%
양 3
 
2.7%
장 3
 
2.7%
Other values (58) 72
64.9%
Common
ValueCountFrequency (%)
0 5
29.4%
) 3
17.6%
( 3
17.6%
6 1
 
5.9%
1 1
 
5.9%
3 1
 
5.9%
1
 
5.9%
+ 1
 
5.9%
8 1
 
5.9%
Latin
ValueCountFrequency (%)
g 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111
84.7%
ASCII 20
 
15.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
컷 6
 
5.4%
트 6
 
5.4%
백 4
 
3.6%
반 4
 
3.6%
면 4
 
3.6%
개 3
 
2.7%
탕 3
 
2.7%
찌 3
 
2.7%
양 3
 
2.7%
장 3
 
2.7%
Other values (58) 72
64.9%
ASCII
ValueCountFrequency (%)
0 5
25.0%
g 3
15.0%
) 3
15.0%
( 3
15.0%
6 1
 
5.0%
1 1
 
5.0%
3 1
 
5.0%
1
 
5.0%
+ 1
 
5.0%
8 1
 
5.0%

가격1
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14380.556
Minimum1500
Maximum88000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T16:03:15.623734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1500
5-th percentile2600
Q15375
median7000
Q39250
95-th percentile59675
Maximum88000
Range86500
Interquartile range (IQR)3875

Descriptive statistics

Standard deviation20948.874
Coefficient of variation (CV)1.45675
Kurtosis6.0126565
Mean14380.556
Median Absolute Deviation (MAD)2000
Skewness2.5981059
Sum517700
Variance4.3885533 × 108
MonotonicityNot monotonic
2023-12-12T16:03:15.735541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
7000 7
19.4%
8000 4
 
11.1%
5000 3
 
8.3%
5500 2
 
5.6%
6000 2
 
5.6%
10000 2
 
5.6%
13000 1
 
2.8%
9000 1
 
2.8%
40000 1
 
2.8%
2000 1
 
2.8%
Other values (12) 12
33.3%
ValueCountFrequency (%)
1500 1
 
2.8%
2000 1
 
2.8%
2800 1
 
2.8%
3000 1
 
2.8%
4000 1
 
2.8%
4500 1
 
2.8%
5000 3
8.3%
5500 2
5.6%
6000 2
5.6%
6500 1
 
2.8%
ValueCountFrequency (%)
88000 1
 
2.8%
80000 1
 
2.8%
52900 1
 
2.8%
52000 1
 
2.8%
40000 1
 
2.8%
13000 1
 
2.8%
12000 1
 
2.8%
10000 2
5.6%
9000 1
 
2.8%
8000 4
11.1%

품목2
Text

MISSING 

Distinct30
Distinct (%)85.7%
Missing1
Missing (%)2.8%
Memory size420.0 B
2023-12-12T16:03:15.959122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length4.6285714
Min length1

Characters and Unicode

Total characters162
Distinct characters87
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

Unique26 ?
Unique (%)74.3%

Sample

1st row참삼겹(130g)
2nd row육회,육사시미(300g)
3rd row우럭추어탕
4th row돼지한마리(800g)
5th row짬뽕
ValueCountFrequency (%)
바지 3
 
8.1%
짬뽕 2
 
5.4%
펌 2
 
5.4%
된장찌개 2
 
5.4%
참삼겹(130g 1
 
2.7%
학생컷 1
 
2.7%
매운탕 1
 
2.7%
닭 1
 
2.7%
블루라이트렌즈 1
 
2.7%
뿌리염색 1
 
2.7%
Other values (22) 22
59.5%
2023-12-12T16:03:16.329453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
 
5.6%
지 7
 
4.3%
찌 5
 
3.1%
개 5
 
3.1%
) 5
 
3.1%
g 5
 
3.1%
( 5
 
3.1%
비 4
 
2.5%
장 4
 
2.5%
돼 4
 
2.5%
Other values (77) 109
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 128
79.0%
Decimal Number 15
 
9.3%
Close Punctuation 5
 
3.1%
Lowercase Letter 5
 
3.1%
Open Punctuation 5
 
3.1%
Space Separator 2
 
1.2%
Math Symbol 1
 
0.6%
Other Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 7
 
5.5%
찌 5
 
3.9%
개 5
 
3.9%
비 4
 
3.1%
장 4
 
3.1%
돼 4
 
3.1%
부 3
 
2.3%
리 3
 
2.3%
국 3
 
2.3%
바 3
 
2.3%
Other values (66) 87
68.0%
Decimal Number
ValueCountFrequency (%)
0 9
60.0%
3 3
 
20.0%
1 1
 
6.7%
6 1
 
6.7%
8 1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 128
79.0%
Common 29
 
17.9%
Latin 5
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 7
 
5.5%
찌 5
 
3.9%
개 5
 
3.9%
비 4
 
3.1%
장 4
 
3.1%
돼 4
 
3.1%
부 3
 
2.3%
리 3
 
2.3%
국 3
 
2.3%
바 3
 
2.3%
Other values (66) 87
68.0%
Common
ValueCountFrequency (%)
0 9
31.0%
) 5
17.2%
( 5
17.2%
3 3
 
10.3%
2
 
6.9%
1 1
 
3.4%
6 1
 
3.4%
+ 1
 
3.4%
8 1
 
3.4%
, 1
 
3.4%
Latin
ValueCountFrequency (%)
g 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 128
79.0%
ASCII 34
 
21.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
26.5%
) 5
14.7%
g 5
14.7%
( 5
14.7%
3 3
 
8.8%
2
 
5.9%
1 1
 
2.9%
6 1
 
2.9%
+ 1
 
2.9%
8 1
 
2.9%
Hangul
ValueCountFrequency (%)
지 7
 
5.5%
찌 5
 
3.9%
개 5
 
3.9%
비 4
 
3.1%
장 4
 
3.1%
돼 4
 
3.1%
부 3
 
2.3%
리 3
 
2.3%
국 3
 
2.3%
바 3
 
2.3%
Other values (66) 87
68.0%

가격2
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)62.9%
Missing1
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean13888.571
Minimum1700
Maximum66000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T16:03:16.470255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1700
5-th percentile2700
Q15500
median7000
Q317250
95-th percentile42270
Maximum66000
Range64300
Interquartile range (IQR)11750

Descriptive statistics

Standard deviation14474.943
Coefficient of variation (CV)1.0422197
Kurtosis4.0759846
Mean13888.571
Median Absolute Deviation (MAD)4000
Skewness1.9807805
Sum486100
Variance2.0952398 × 108
MonotonicityNot monotonic
2023-12-12T16:03:16.594393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
7000 6
16.7%
3000 4
 
11.1%
6000 3
 
8.3%
5000 2
 
5.6%
12000 2
 
5.6%
30000 2
 
5.6%
4500 1
 
2.8%
66000 1
 
2.8%
20000 1
 
2.8%
35000 1
 
2.8%
Other values (12) 12
33.3%
ValueCountFrequency (%)
1700 1
 
2.8%
2000 1
 
2.8%
3000 4
11.1%
4500 1
 
2.8%
5000 2
 
5.6%
6000 3
8.3%
6500 1
 
2.8%
7000 6
16.7%
8000 1
 
2.8%
9000 1
 
2.8%
ValueCountFrequency (%)
66000 1
2.8%
42900 1
2.8%
42000 1
2.8%
35000 1
2.8%
30000 2
5.6%
25000 1
2.8%
20000 1
2.8%
19500 1
2.8%
15000 1
2.8%
13000 1
2.8%

품목3
Text

MISSING 

Distinct30
Distinct (%)88.2%
Missing2
Missing (%)5.6%
Memory size420.0 B
2023-12-12T16:03:16.783173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length4.6470588
Min length2

Characters and Unicode

Total characters158
Distinct characters93
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)82.4%

Sample

1st row돼지양념구이(130g)
2nd row초밥(10개)
3rd row통추어탕
4th row생등심(180g)
5th row간짜장
ValueCountFrequency (%)
염색 4
 
10.8%
제육볶음 2
 
5.4%
컷 1
 
2.7%
디자인 1
 
2.7%
전체염색 1
 
2.7%
블라우스 1
 
2.7%
해장국 1
 
2.7%
원피스 1
 
2.7%
차돌박이(600g 1
 
2.7%
부대찌개+알밥 1
 
2.7%
Other values (23) 23
62.2%
2023-12-12T16:03:17.158527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7
 
4.4%
염 6
 
3.8%
색 6
 
3.8%
이 5
 
3.2%
( 5
 
3.2%
) 5
 
3.2%
g 4
 
2.5%
양 3
 
1.9%
3
 
1.9%
개 3
 
1.9%
Other values (83) 111
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
79.1%
Decimal Number 14
 
8.9%
Open Punctuation 5
 
3.2%
Close Punctuation 5
 
3.2%
Lowercase Letter 4
 
2.5%
Space Separator 3
 
1.9%
Math Symbol 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
염 6
 
4.8%
색 6
 
4.8%
이 5
 
4.0%
양 3
 
2.4%
개 3
 
2.4%
밥 3
 
2.4%
장 3
 
2.4%
국 3
 
2.4%
비 2
 
1.6%
스 2
 
1.6%
Other values (72) 89
71.2%
Decimal Number
ValueCountFrequency (%)
0 7
50.0%
1 3
21.4%
3 1
 
7.1%
8 1
 
7.1%
2 1
 
7.1%
6 1
 
7.1%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 4
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125
79.1%
Common 29
 
18.4%
Latin 4
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
염 6
 
4.8%
색 6
 
4.8%
이 5
 
4.0%
양 3
 
2.4%
개 3
 
2.4%
밥 3
 
2.4%
장 3
 
2.4%
국 3
 
2.4%
비 2
 
1.6%
스 2
 
1.6%
Other values (72) 89
71.2%
Common
ValueCountFrequency (%)
0 7
24.1%
( 5
17.2%
) 5
17.2%
3
10.3%
1 3
10.3%
+ 2
 
6.9%
3 1
 
3.4%
8 1
 
3.4%
2 1
 
3.4%
6 1
 
3.4%
Latin
ValueCountFrequency (%)
g 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125
79.1%
ASCII 33
 
20.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7
21.2%
( 5
15.2%
) 5
15.2%
g 4
12.1%
3
9.1%
1 3
9.1%
+ 2
 
6.1%
3 1
 
3.0%
8 1
 
3.0%
2 1
 
3.0%
Hangul
ValueCountFrequency (%)
염 6
 
4.8%
색 6
 
4.8%
이 5
 
4.0%
양 3
 
2.4%
개 3
 
2.4%
밥 3
 
2.4%
장 3
 
2.4%
국 3
 
2.4%
비 2
 
1.6%
스 2
 
1.6%
Other values (72) 89
71.2%

가격3
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)55.9%
Missing2
Missing (%)5.6%
Infinite0
Infinite (%)0.0%
Mean11917.647
Minimum2000
Maximum50000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T16:03:17.286254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2195
Q16000
median8000
Q314500
95-th percentile32000
Maximum50000
Range48000
Interquartile range (IQR)8500

Descriptive statistics

Standard deviation11124.869
Coefficient of variation (CV)0.93347864
Kurtosis4.8763784
Mean11917.647
Median Absolute Deviation (MAD)3000
Skewness2.1565097
Sum405200
Variance1.2376271 × 108
MonotonicityNot monotonic
2023-12-12T16:03:17.426007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
10000 4
11.1%
6000 4
11.1%
5000 3
 
8.3%
8000 3
 
8.3%
7000 3
 
8.3%
2000 2
 
5.6%
15000 2
 
5.6%
25000 2
 
5.6%
6500 1
 
2.8%
2300 1
 
2.8%
Other values (9) 9
25.0%
(Missing) 2
 
5.6%
ValueCountFrequency (%)
2000 2
5.6%
2300 1
 
2.8%
3000 1
 
2.8%
4000 1
 
2.8%
5000 3
8.3%
6000 4
11.1%
6500 1
 
2.8%
7000 3
8.3%
8000 3
8.3%
8500 1
 
2.8%
ValueCountFrequency (%)
50000 1
 
2.8%
45000 1
 
2.8%
25000 2
5.6%
22900 1
 
2.8%
22000 1
 
2.8%
20000 1
 
2.8%
15000 2
5.6%
13000 1
 
2.8%
10000 4
11.1%
8500 1
 
2.8%

기준일
Date

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2023-07-19 00:00:00
Maximum2023-07-19 00:00:00
2023-12-12T16:03:17.558770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:17.700608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T16:03:08.518976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:04.293350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:05.115952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:05.694722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:06.399651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:06.968376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:07.768758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:08.635972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:04.376348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:05.193509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:05.798235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:06.477642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:07.054734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:07.878966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:08.764368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:04.455271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:05.271666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:05.908766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:06.552636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:07.152617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:07.980371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:08.882035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:04.551447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:05.372521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:05.993462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:06.637485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:07.272338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:08.104573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:08.983712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:04.630487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:05.452384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:06.079779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:06.729946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:07.365826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:08.224135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:09.094651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:04.703843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:05.520791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:06.205729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:06.811685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:07.578744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:08.334709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:09.208687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:05.041639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:05.597833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:06.328196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:06.891387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:07.681642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:08.422116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:03:17.840937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번최초지정연월구분업종 대분류업종 세분류업소명주소(도로명 주소)연락처전체 메뉴 수착한가격 메뉴 수착한가격메뉴 비중품목1가격1품목2가격2품목3가격3
연번1.0000.0000.3960.3880.4561.0000.9261.0000.4390.5820.0000.7390.0000.5650.0000.7760.413
최초지정연월0.0001.0000.5540.3640.4871.0000.7571.0000.2710.3090.0000.9330.2550.8730.4270.0000.000
구분0.3960.5541.0000.8640.7881.0001.0001.0000.3770.5920.4980.8810.1090.8840.4600.5960.257
업종 대분류0.3880.3640.8641.0000.9721.0000.7691.0000.2740.3660.1340.9730.0000.9710.5090.8600.000
업종 세분류0.4560.4870.7880.9721.0001.0000.0001.0000.4130.4020.2900.8220.2820.7250.4690.3630.587
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주소(도로명 주소)0.9260.7571.0000.7690.0001.0001.0001.0000.0000.0000.7200.9800.0000.9840.8720.9710.934
연락처1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전체 메뉴 수0.4390.2710.3770.2740.4131.0000.0001.0001.0000.9500.7360.0000.0000.7970.0000.5160.000
착한가격 메뉴 수0.5820.3090.5920.3660.4021.0000.0001.0000.9501.0000.6850.0000.0000.0000.0000.7240.000
착한가격메뉴 비중0.0000.0000.4980.1340.2901.0000.7201.0000.7360.6851.0000.8580.0000.0000.0000.9380.000
품목10.7390.9330.8810.9730.8221.0000.9801.0000.0000.0000.8581.0001.0000.9880.4500.9830.862
가격10.0000.2550.1090.0000.2821.0000.0001.0000.0000.0000.0001.0001.0001.0000.9080.9260.875
품목20.5650.8730.8840.9710.7251.0000.9841.0000.7970.0000.0000.9881.0001.0000.8930.9370.999
가격20.0000.4270.4600.5090.4691.0000.8721.0000.0000.0000.0000.4500.9080.8931.0000.0000.864
품목30.7760.0000.5960.8600.3631.0000.9711.0000.5160.7240.9380.9830.9260.9370.0001.0000.937
가격30.4130.0000.2570.0000.5871.0000.9341.0000.0000.0000.0000.8620.8750.9990.8640.9371.000
2023-12-12T16:03:18.046118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종 세분류구분업종 대분류
업종 세분류1.0000.7890.737
구분0.7891.0000.860
업종 대분류0.7370.8601.000
2023-12-12T16:03:18.138791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번전체 메뉴 수착한가격 메뉴 수착한가격메뉴 비중가격1가격2가격3구분업종 대분류업종 세분류
연번1.000-0.233-0.2690.1420.2540.1690.1550.4130.2300.269
전체 메뉴 수-0.2331.0000.938-0.415-0.086-0.0010.0350.2470.1220.218
착한가격 메뉴 수-0.2690.9381.000-0.114-0.153-0.116-0.0010.4010.1840.210
착한가격메뉴 비중0.142-0.415-0.1141.000-0.146-0.284-0.0870.3330.0000.134
가격10.254-0.086-0.153-0.1461.0000.7820.7670.1220.0000.178
가격20.169-0.001-0.116-0.2840.7821.0000.7780.3150.1950.267
가격30.1550.035-0.001-0.0870.7670.7781.0000.1390.0000.251
구분0.4130.2470.4010.3330.1220.3150.1391.0000.8600.789
업종 대분류0.2300.1220.1840.0000.0000.1950.0000.8601.0000.737
업종 세분류0.2690.2180.2100.1340.1780.2670.2510.7890.7371.000

Missing values

2023-12-12T16:03:09.366414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:03:09.621447image/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.
2023-12-12T16:03:09.805717image/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

연번시도시군구최초지정연월구분업종 대분류업종 세분류업소명주소(도로명 주소)연락처전체 메뉴 수착한가격 메뉴 수착한가격메뉴 비중품목1가격1품목2가격2품목3가격3기준일
01경기안양시2011-11-01외식업한식한식_기타돈모아참삼겹안양시 만안구 장내로 138 (안양동)031-466-16474375.0생삼겹(130g)5500참삼겹(130g)4500돼지양념구이(130g)50002023-07-19
12경기안양시2011-11-01외식업기타비요식업한식_기타남부고기집안양시 만안구 장내로150번길 34 (안양동)031-444-63055360.0해장국2800육회,육사시미(300g)19500초밥(10개)60002023-07-19
23경기안양시2020-09-01외식업한식한식_기타설악명품추어탕안양시 만안구 장내로 154 (안양동)031-466-0012171270.6명품추어탕8000우럭추어탕10000통추어탕100002023-07-19
34경기안양시2017-07-01외식업한식한식_육류참풍년집 정육식당안양시 만안구 안양로 358 (안양동)031-464-9898151280.0소한마리(800g)52900돼지한마리(800g)42900생등심(180g)229002023-07-19
45경기안양시2019-07-01외식업중식중식홍보석안양시 만안구 안양로 358 (안양동)031-443-8485302066.7짜장면5000짬뽕6000간짜장60002023-07-19
56경기안양시2012-06-01외식업한식한식_기타톰과제리안양시 만안구 양화로37번길 23 (안양동)031-465-1515171588.2김치찌개6500순두부찌개6500매콤불뚝65002023-07-19
67경기안양시2011-11-01기타개인서비스업세탁업세탁업진흥세탁소안양시 만안구 양화로71번길 24 (안양동)031-442-762388100.0양복5000바지2000와이셔츠20002023-07-19
78경기안양시2018-07-01외식업한식한식_기타멸치국수집안양시 만안구 병목안로 15 (안양동)031-445-09571010100.0멸치국수4000비빔국수5000간장비빔국수50002023-07-19
89경기안양시2012-06-01외식업한식한식_기타송주불냉면안양시 만안구 안양로257번길 14 (안양동)031-468-9298151280.0물냉면5500비빔냉면6000불냉면60002023-07-19
910경기안양시2011-11-01기타개인서비스업이용업이용업남성헤어안양시 만안구 삼덕로 68 (안양동)<NA>33100.0컷트7000컷트+면도15000염색+컷트150002023-07-19
연번시도시군구최초지정연월구분업종 대분류업종 세분류업소명주소(도로명 주소)연락처전체 메뉴 수착한가격 메뉴 수착한가격메뉴 비중품목1가격1품목2가격2품목3가격3기준일
2627경기안양시2018-07-01외식업한식한식_기타오동도 산아나고안양시 동안구 귀인로 109 (호계동)031-427-927512650.0아나고52000꼼장어42000골뱅이무침200002023-07-19
2728경기안양시2018-07-01외식업한식한식_기타부대의전설안양시 동안구 시민대로 138 (호계동)031-477-77875480.0부대찌개7500매운부대찌개8000부대찌개+알밥85002023-07-19
2829경기안양시2018-07-01외식업미용업미용업미세스봉 헤어샵안양시 동안구 엘에스로 48 (호계동)031-457-356255100.0컷트10000펌30000염색250002023-07-19
2930경기안양시2017-04-01외식업중식중식안동장안양시 동안구 경수대로 519번길 32 (호계동)031-453-1177121083.3짜장면4500짬뽕6000우동60002023-07-19
3031경기안양시2017-07-01기타개인서비스업세탁업세탁업동현세탁소안양시 동안구 평촌대로179번길 27, 2층(호계동, 목련상가)031-381-27191010100.0난방2000바지3000원피스80002023-07-19
3132경기안양시2012-06-01외식업한식한식_기타초가집안양시 동안구 평촌대로127번길 82 (호계동)031-385-244610550.0추어탕7000순대국7000해장국70002023-07-19
3233경기안양시2011-11-01기타개인서비스업세탁업세탁업제일세탁소안양시 동안구 동안로 11(호계동, 무궁화상가)031-383-11505480.0양복7000바지3000블라우스40002023-07-19
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