Overview

Dataset statistics

Number of variables8
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory73.7 B

Variable types

Text2
Numeric5
Categorical1

Dataset

Description부산광역시 서구 내 생필품의 품목, 단위별 대형마트의 판매가격 정보를 나타내는 데이터로 생활필수 품목에 대한 업소별 판매가격을 표시해놓은 데이터입니다.
URLhttps://www.data.go.kr/data/3057408/fileData.do

Alerts

기준일자 has constant value ""Constant
가격(홈플러스) is highly overall correlated with 세용마트 가격 and 3 other fieldsHigh correlation
세용마트 가격 is highly overall correlated with 가격(홈플러스) and 3 other fieldsHigh correlation
서대신동 TOP마트 가격 is highly overall correlated with 가격(홈플러스) and 3 other fieldsHigh correlation
모두마트 가격 is highly overall correlated with 가격(홈플러스) and 3 other fieldsHigh correlation
충무동 TOP마트 가격 is highly overall correlated with 가격(홈플러스) and 3 other fieldsHigh correlation
품목 has unique valuesUnique
모두마트 가격 has unique valuesUnique
충무동 TOP마트 가격 has unique valuesUnique

Reproduction

Analysis started2023-12-13 01:00:31.387704
Analysis finished2023-12-13 01:00:33.664327
Duration2.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-13T10:00:33.774421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.7857143
Min length1

Characters and Unicode

Total characters106
Distinct characters76
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

Unique28 ?
Unique (%)100.0%

Sample

1st row쌀
2nd row배추
3rd row무
4th row대파
5th row양파
ValueCountFrequency (%)
쌀 1
 
3.6%
배추 1
 
3.6%
뽀삐화장지 1
 
3.6%
테크가루비누 1
 
3.6%
cj두부찌개 1
 
3.6%
오뚜기참기름 1
 
3.6%
백설옥수수기름 1
 
3.6%
밀가루 1
 
3.6%
오복간장 1
 
3.6%
백설설탕 1
 
3.6%
Other values (18) 18
64.3%
2023-12-13T10:00:34.042377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 6
 
5.7%
설 3
 
2.8%
부 3
 
2.8%
고 3
 
2.8%
백 2
 
1.9%
라 2
 
1.9%
수 2
 
1.9%
맥 2
 
1.9%
이 2
 
1.9%
화 2
 
1.9%
Other values (66) 79
74.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104
98.1%
Uppercase Letter 2
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 6
 
5.8%
설 3
 
2.9%
부 3
 
2.9%
고 3
 
2.9%
백 2
 
1.9%
라 2
 
1.9%
수 2
 
1.9%
맥 2
 
1.9%
이 2
 
1.9%
화 2
 
1.9%
Other values (64) 77
74.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
J 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 104
98.1%
Latin 2
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 6
 
5.8%
설 3
 
2.9%
부 3
 
2.9%
고 3
 
2.9%
백 2
 
1.9%
라 2
 
1.9%
수 2
 
1.9%
맥 2
 
1.9%
이 2
 
1.9%
화 2
 
1.9%
Other values (64) 77
74.0%
Latin
ValueCountFrequency (%)
C 1
50.0%
J 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 104
98.1%
ASCII 2
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 6
 
5.8%
설 3
 
2.9%
부 3
 
2.9%
고 3
 
2.9%
백 2
 
1.9%
라 2
 
1.9%
수 2
 
1.9%
맥 2
 
1.9%
이 2
 
1.9%
화 2
 
1.9%
Other values (64) 77
74.0%
ASCII
ValueCountFrequency (%)
C 1
50.0%
J 1
50.0%

단위
Text

Distinct21
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-13T10:00:34.182296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.3214286
Min length2

Characters and Unicode

Total characters93
Distinct characters21
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)60.7%

Sample

1st row20kg
2nd row1포기
3rd row1개
4th row1단
5th row1kg
ValueCountFrequency (%)
1kg 4
 
14.3%
1병 3
 
10.7%
300g 2
 
7.1%
500g 2
 
7.1%
3kg 1
 
3.6%
20kg 1
 
3.6%
5개 1
 
3.6%
30롤 1
 
3.6%
2.7kg 1
 
3.6%
320㎖ 1
 
3.6%
Other values (11) 11
39.3%
2023-12-13T10:00:34.409924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
17.2%
0 16
17.2%
g 14
15.1%
k 8
8.6%
3 5
 
5.4%
5 5
 
5.4%
2 4
 
4.3%
. 4
 
4.3%
ℓ 3
 
3.2%
병 3
 
3.2%
Other values (11) 15
16.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 51
54.8%
Lowercase Letter 26
28.0%
Other Letter 11
 
11.8%
Other Punctuation 4
 
4.3%
Other Symbol 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
31.4%
0 16
31.4%
3 5
 
9.8%
5 5
 
9.8%
2 4
 
7.8%
7 3
 
5.9%
8 1
 
2.0%
4 1
 
2.0%
Other Letter
ValueCountFrequency (%)
병 3
27.3%
개 3
27.3%
기 1
 
9.1%
포 1
 
9.1%
단 1
 
9.1%
캔 1
 
9.1%
롤 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
g 14
53.8%
k 8
30.8%
ℓ 3
 
11.5%
m 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Other Symbol
ValueCountFrequency (%)
㎖ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 59
63.4%
Latin 23
 
24.7%
Hangul 11
 
11.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
27.1%
0 16
27.1%
3 5
 
8.5%
5 5
 
8.5%
2 4
 
6.8%
. 4
 
6.8%
ℓ 3
 
5.1%
7 3
 
5.1%
㎖ 1
 
1.7%
8 1
 
1.7%
Hangul
ValueCountFrequency (%)
병 3
27.3%
개 3
27.3%
기 1
 
9.1%
포 1
 
9.1%
단 1
 
9.1%
캔 1
 
9.1%
롤 1
 
9.1%
Latin
ValueCountFrequency (%)
g 14
60.9%
k 8
34.8%
m 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78
83.9%
Hangul 11
 
11.8%
Letterlike Symbols 3
 
3.2%
CJK Compat 1
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
20.5%
0 16
20.5%
g 14
17.9%
k 8
10.3%
3 5
 
6.4%
5 5
 
6.4%
2 4
 
5.1%
. 4
 
5.1%
7 3
 
3.8%
8 1
 
1.3%
Other values (2) 2
 
2.6%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 3
100.0%
Hangul
ValueCountFrequency (%)
병 3
27.3%
개 3
27.3%
기 1
 
9.1%
포 1
 
9.1%
단 1
 
9.1%
캔 1
 
9.1%
롤 1
 
9.1%
CJK Compat
ValueCountFrequency (%)
㎖ 1
100.0%

가격(홈플러스)
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8811.4286
Minimum1250
Maximum64900
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T10:00:34.524928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1250
5-th percentile1628.5
Q12490
median4990
Q310225
95-th percentile17503.5
Maximum64900
Range63650
Interquartile range (IQR)7735

Descriptive statistics

Standard deviation11984.502
Coefficient of variation (CV)1.3601088
Kurtosis18.908601
Mean8811.4286
Median Absolute Deviation (MAD)3145
Skewness4.0496797
Sum246720
Variance1.4362828 × 108
MonotonicityNot monotonic
2023-12-13T10:00:34.607385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2490 3
 
10.7%
8990 2
 
7.1%
4990 2
 
7.1%
64900 1
 
3.6%
7490 1
 
3.6%
5500 1
 
3.6%
18900 1
 
3.6%
10900 1
 
3.6%
1250 1
 
3.6%
11690 1
 
3.6%
Other values (14) 14
50.0%
ValueCountFrequency (%)
1250 1
 
3.6%
1590 1
 
3.6%
1700 1
 
3.6%
1990 1
 
3.6%
2190 1
 
3.6%
2490 3
10.7%
2990 1
 
3.6%
3990 1
 
3.6%
4100 1
 
3.6%
4490 1
 
3.6%
ValueCountFrequency (%)
64900 1
3.6%
18900 1
3.6%
14910 1
3.6%
13930 1
3.6%
13900 1
3.6%
11690 1
3.6%
10900 1
3.6%
10000 1
3.6%
9990 1
3.6%
8990 2
7.1%

세용마트 가격
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8106.0714
Minimum1350
Maximum52000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T10:00:34.696158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1350
5-th percentile1528
Q12512.5
median4240
Q38900
95-th percentile29625
Maximum52000
Range50650
Interquartile range (IQR)6387.5

Descriptive statistics

Standard deviation11060.865
Coefficient of variation (CV)1.3645162
Kurtosis9.6512947
Mean8106.0714
Median Absolute Deviation (MAD)2425
Skewness2.9955297
Sum226970
Variance1.2234274 × 108
MonotonicityNot monotonic
2023-12-13T10:00:34.787874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
8900 2
 
7.1%
5000 2
 
7.1%
52000 1
 
3.6%
2700 1
 
3.6%
3900 1
 
3.6%
21500 1
 
3.6%
1350 1
 
3.6%
5600 1
 
3.6%
9500 1
 
3.6%
12200 1
 
3.6%
Other values (16) 16
57.1%
ValueCountFrequency (%)
1350 1
3.6%
1500 1
3.6%
1580 1
3.6%
1600 1
3.6%
1750 1
3.6%
1880 1
3.6%
1950 1
3.6%
2700 1
3.6%
2980 1
3.6%
3100 1
3.6%
ValueCountFrequency (%)
52000 1
3.6%
34000 1
3.6%
21500 1
3.6%
12200 1
3.6%
11200 1
3.6%
9500 1
3.6%
8900 2
7.1%
8000 1
3.6%
5900 1
3.6%
5600 1
3.6%

서대신동 TOP마트 가격
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10981.071
Minimum1400
Maximum59880
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T10:00:34.871618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1400
5-th percentile1460.5
Q12737.5
median4775
Q310800
95-th percentile47880
Maximum59880
Range58480
Interquartile range (IQR)8062.5

Descriptive statistics

Standard deviation15354.621
Coefficient of variation (CV)1.3982808
Kurtosis4.4616808
Mean10981.071
Median Absolute Deviation (MAD)3210
Skewness2.2969417
Sum307470
Variance2.3576439 × 108
MonotonicityNot monotonic
2023-12-13T10:00:34.962565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1480 2
 
7.1%
45800 1
 
3.6%
1730 1
 
3.6%
4200 1
 
3.6%
25900 1
 
3.6%
11500 1
 
3.6%
10600 1
 
3.6%
8480 1
 
3.6%
5350 1
 
3.6%
13500 1
 
3.6%
Other values (17) 17
60.7%
ValueCountFrequency (%)
1400 1
3.6%
1450 1
3.6%
1480 2
7.1%
1730 1
3.6%
1980 1
3.6%
2280 1
3.6%
2890 1
3.6%
2980 1
3.6%
3480 1
3.6%
3650 1
3.6%
ValueCountFrequency (%)
59880 1
3.6%
49000 1
3.6%
45800 1
3.6%
25900 1
3.6%
13500 1
3.6%
11500 1
3.6%
11400 1
3.6%
10600 1
3.6%
8700 1
3.6%
8480 1
3.6%

모두마트 가격
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10853.929
Minimum1250
Maximum74500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T10:00:35.054908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1250
5-th percentile1517.5
Q12625
median5700
Q310775
95-th percentile41920
Maximum74500
Range73250
Interquartile range (IQR)8150

Descriptive statistics

Standard deviation16179.2
Coefficient of variation (CV)1.4906308
Kurtosis10.28088
Mean10853.929
Median Absolute Deviation (MAD)3825
Skewness3.1595204
Sum303910
Variance2.6176651 × 108
MonotonicityNot monotonic
2023-12-13T10:00:35.148759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
54800 1
 
3.6%
1950 1
 
3.6%
5600 1
 
3.6%
18000 1
 
3.6%
16200 1
 
3.6%
1250 1
 
3.6%
10400 1
 
3.6%
11900 1
 
3.6%
5800 1
 
3.6%
15600 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1250 1
3.6%
1500 1
3.6%
1550 1
3.6%
1800 1
3.6%
1950 1
3.6%
2000 1
3.6%
2550 1
3.6%
2650 1
3.6%
3450 1
3.6%
3500 1
3.6%
ValueCountFrequency (%)
74500 1
3.6%
54800 1
3.6%
18000 1
3.6%
16200 1
3.6%
15600 1
3.6%
13900 1
3.6%
11900 1
3.6%
10400 1
3.6%
10000 1
3.6%
9800 1
3.6%

충무동 TOP마트 가격
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12022.857
Minimum1150
Maximum111700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T10:00:35.245708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1150
5-th percentile1417.5
Q12205
median5165
Q38925
95-th percentile45485
Maximum111700
Range110550
Interquartile range (IQR)6720

Descriptive statistics

Standard deviation22481.093
Coefficient of variation (CV)1.8698628
Kurtosis14.987074
Mean12022.857
Median Absolute Deviation (MAD)3375
Skewness3.6895205
Sum336640
Variance5.0539955 × 108
MonotonicityNot monotonic
2023-12-13T10:00:35.338354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
45800 1
 
3.6%
1730 1
 
3.6%
4200 1
 
3.6%
15900 1
 
3.6%
1150 1
 
3.6%
1480 1
 
3.6%
10600 1
 
3.6%
8480 1
 
3.6%
5350 1
 
3.6%
13500 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1150 1
3.6%
1400 1
3.6%
1450 1
3.6%
1480 1
3.6%
1580 1
3.6%
1730 1
3.6%
1980 1
3.6%
2280 1
3.6%
2890 1
3.6%
3480 1
3.6%
ValueCountFrequency (%)
111700 1
3.6%
45800 1
3.6%
44900 1
3.6%
15900 1
3.6%
13500 1
3.6%
10600 1
3.6%
9600 1
3.6%
8700 1
3.6%
8480 1
3.6%
8400 1
3.6%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-04-30
28 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-04-30
2nd row2023-04-30
3rd row2023-04-30
4th row2023-04-30
5th row2023-04-30

Common Values

ValueCountFrequency (%)
2023-04-30 28
100.0%

Length

2023-12-13T10:00:35.428091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T10:00:35.500209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-04-30 28
100.0%

Interactions

2023-12-13T10:00:32.967104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:31.610791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:31.930465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:32.278311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:32.618621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:33.040351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:31.675820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:31.994275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:32.370353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:32.684703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:33.105952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:31.737650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:32.067887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:32.432695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:32.745329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:33.174583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:31.806231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:32.139317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:32.495522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:32.810519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:33.246868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:31.871496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:32.210903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:32.559806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:32.887420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T10:00:35.563409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목단위가격(홈플러스)세용마트 가격서대신동 TOP마트 가격모두마트 가격충무동 TOP마트 가격
품목1.0001.0001.0001.0001.0001.0001.000
단위1.0001.0000.8490.8710.9570.8730.716
가격(홈플러스)1.0000.8491.0000.8770.8680.7590.794
세용마트 가격1.0000.8710.8771.0000.9580.9030.910
서대신동 TOP마트 가격1.0000.9570.8680.9581.0000.8970.904
모두마트 가격1.0000.8730.7590.9030.8971.0000.977
충무동 TOP마트 가격1.0000.7160.7940.9100.9040.9771.000
2023-12-13T10:00:35.677693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가격(홈플러스)세용마트 가격서대신동 TOP마트 가격모두마트 가격충무동 TOP마트 가격
가격(홈플러스)1.0000.8850.9180.9340.818
세용마트 가격0.8851.0000.9180.9620.897
서대신동 TOP마트 가격0.9180.9181.0000.9520.807
모두마트 가격0.9340.9620.9521.0000.812
충무동 TOP마트 가격0.8180.8970.8070.8121.000

Missing values

2023-12-13T10:00:33.534272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T10:00:33.626266image/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.

Sample

품목단위가격(홈플러스)세용마트 가격서대신동 TOP마트 가격모두마트 가격충무동 TOP마트 가격기준일자
0쌀20kg64900520004580054800458002023-04-30
1배추1포기499031003480350034802023-04-30
2무1개249015801480200015802023-04-30
3대파1단249018802280180022802023-04-30
4양파1kg499029802980398049802023-04-30
5사과300g999089006900980096002023-04-30
6배450g10000448059880780064002023-04-30
7쇠고기500g13930340004900074500449002023-04-30
8돼지고기500g149101120011400139001117002023-04-30
9닭고기1kg899080007900798084002023-04-30
품목단위가격(홈플러스)세용마트 가격서대신동 TOP마트 가격모두마트 가격충무동 TOP마트 가격기준일자
18신라면5개410040004100435041002023-04-30
19백설설탕1kg249019501980255019802023-04-30
20오복간장1.7ℓ13900122001350015600135002023-04-30
21밀가루3kg219050005350580053502023-04-30
22백설옥수수기름1.8ℓ8990950084801190084802023-04-30
23오뚜기참기름320㎖1169056001060010400106002023-04-30
24CJ두부찌개300g125013501480125014802023-04-30
25테크가루비누2.7kg109005000115001620011502023-04-30
26뽀삐화장지30롤18900215002590018000159002023-04-30
27자연퐁부엌세제1.2kg550039004200560042002023-04-30