Overview

Dataset statistics

Number of variables24
Number of observations60
Missing cells429
Missing cells (%)29.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory206.2 B

Variable types

Categorical2
Text10
Numeric12

Dataset

Description인천광역시 각 구별 전통시장에 대한 전통시장의 주간 농축수산물, 가공식품, 공산품 등의 가격에 대한 동향을 알 수 있는 데이터로 구성되어 있습니다. *코로나19 로 물가조사가 중단(2020.2월 3주차 ~ 상황종료시까지)됨에 따라 생필품 등 가격정보에 대해 한국소비자원에서 게시하는 참가격 홈페이지 자료를 참고해주시기 바랍니다 https://www.price.go.kr/tprice/portal/dailynecessitypriceinfo/priceiteminfo/getPriceItemInfoList.do
Author인천광역시
URLhttps://www.data.go.kr/data/15053082/fileData.do

Alerts

중구(신포)_참고 사항 has constant value ""Constant
부평구(부평)_참고 사항 has constant value ""Constant
중구(신포)_가격 has 1 (1.7%) missing valuesMissing
중구(신포)_참고 사항 has 59 (98.3%) missing valuesMissing
동구(송현)_가격 has 1 (1.7%) missing valuesMissing
동구(송현)_참고 사항 has 58 (96.7%) missing valuesMissing
미추홀구(신기)_가격 has 1 (1.7%) missing valuesMissing
미추홀구(신기)_참고 사항 has 50 (83.3%) missing valuesMissing
남동구(모래내)_참고 사항 has 57 (95.0%) missing valuesMissing
연수구(옥련)_가격 has 1 (1.7%) missing valuesMissing
연수구(옥련)_참고 사항 has 45 (75.0%) missing valuesMissing
부평구(부평)_참고 사항 has 59 (98.3%) missing valuesMissing
계양구(작전)_가격 has 2 (3.3%) missing valuesMissing
계양구(작전)_참고 사항 has 45 (75.0%) missing valuesMissing
서구(중앙)_참고 사항 has 50 (83.3%) missing valuesMissing
품목 has unique valuesUnique
등락가격(원) has 45 (75.0%) zerosZeros
등락률(퍼센트) has 45 (75.0%) zerosZeros

Reproduction

Analysis started2023-12-12 07:38:18.830645
Analysis finished2023-12-12 07:38:19.380653
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct5
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
외식비(25)
25 
농축수산물(18)
18 
가공식품(10)
10 
유류(4)
4 
공산품(3)
3 

Length

Max length9
Median length8
Mean length7.5833333
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row농축수산물(18)
2nd row농축수산물(18)
3rd row농축수산물(18)
4th row농축수산물(18)
5th row농축수산물(18)

Common Values

ValueCountFrequency (%)
외식비(25) 25
41.7%
농축수산물(18) 18
30.0%
가공식품(10) 10
 
16.7%
유류(4) 4
 
6.7%
공산품(3) 3
 
5.0%

Length

2023-12-12T16:38:19.453294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:38:19.571515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외식비(25 25
41.7%
농축수산물(18 18
30.0%
가공식품(10 10
 
16.7%
유류(4 4
 
6.7%
공산품(3 3
 
5.0%

품목
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-12T16:38:19.812759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length2.7833333
Min length1

Characters and Unicode

Total characters167
Distinct characters101
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row쌀
2nd row콩나물
3rd row마늘
4th row양파
5th row대파
ValueCountFrequency (%)
쌀 1
 
1.7%
콩나물 1
 
1.7%
자장면 1
 
1.7%
등유 1
 
1.7%
경유 1
 
1.7%
lpg(취사용 1
 
1.7%
설렁탕 1
 
1.7%
냉면 1
 
1.7%
비빔밥 1
 
1.7%
갈비탕 1
 
1.7%
Other values (50) 50
83.3%
2023-12-12T16:38:20.353239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
고 8
 
4.8%
유 6
 
3.6%
탕 5
 
3.0%
기 5
 
3.0%
장 4
 
2.4%
면 4
 
2.4%
자 4
 
2.4%
비 3
 
1.8%
지 3
 
1.8%
치 3
 
1.8%
Other values (91) 122
73.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 160
95.8%
Uppercase Letter 3
 
1.8%
Close Punctuation 2
 
1.2%
Open Punctuation 2
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 8
 
5.0%
유 6
 
3.8%
탕 5
 
3.1%
기 5
 
3.1%
장 4
 
2.5%
면 4
 
2.5%
자 4
 
2.5%
비 3
 
1.9%
지 3
 
1.9%
치 3
 
1.9%
Other values (86) 115
71.9%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
P 1
33.3%
L 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 160
95.8%
Common 4
 
2.4%
Latin 3
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 8
 
5.0%
유 6
 
3.8%
탕 5
 
3.1%
기 5
 
3.1%
장 4
 
2.5%
면 4
 
2.5%
자 4
 
2.5%
비 3
 
1.9%
지 3
 
1.9%
치 3
 
1.9%
Other values (86) 115
71.9%
Latin
ValueCountFrequency (%)
G 1
33.3%
P 1
33.3%
L 1
33.3%
Common
ValueCountFrequency (%)
) 2
50.0%
( 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 160
95.8%
ASCII 7
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
고 8
 
5.0%
유 6
 
3.8%
탕 5
 
3.1%
기 5
 
3.1%
장 4
 
2.5%
면 4
 
2.5%
자 4
 
2.5%
비 3
 
1.9%
지 3
 
1.9%
치 3
 
1.9%
Other values (86) 115
71.9%
ASCII
ValueCountFrequency (%)
) 2
28.6%
( 2
28.6%
G 1
14.3%
P 1
14.3%
L 1
14.3%

규격 및 단위
Text

Distinct49
Distinct (%)81.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-12T16:38:20.705119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length16
Mean length11
Min length1

Characters and Unicode

Total characters660
Distinct characters190
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)75.0%

Sample

1st row강화미, 햅쌀/10kg
2nd row풀무원 국산콩 무농약 콩나물/200g
3rd row깐마늘(중품) 100g
4th row양파 중망/1망
5th row흙대파/1단
ValueCountFrequency (%)
1그릇(보통 7
 
6.7%
조사가격을200g으로 4
 
3.8%
환산한 4
 
3.8%
가격 4
 
3.8%
sk/1ℓ 3
 
2.9%
100g~250g의 3
 
2.9%
1인분 2
 
1.9%
풀무원 2
 
1.9%
100g 2
 
1.9%
참이슬 1
 
1.0%
Other values (73) 73
69.5%
2023-12-12T16:38:21.212929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 50
 
7.6%
0 50
 
7.6%
45
 
6.8%
/ 35
 
5.3%
g 31
 
4.7%
( 18
 
2.7%
) 18
 
2.7%
2 13
 
2.0%
통 12
 
1.8%
릇 11
 
1.7%
Other values (180) 377
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 321
48.6%
Decimal Number 142
21.5%
Lowercase Letter 49
 
7.4%
Space Separator 45
 
6.8%
Other Punctuation 45
 
6.8%
Open Punctuation 18
 
2.7%
Close Punctuation 18
 
2.7%
Uppercase Letter 11
 
1.7%
Math Symbol 8
 
1.2%
Other Symbol 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
통 12
 
3.7%
릇 11
 
3.4%
그 11
 
3.4%
보 10
 
3.1%
가 9
 
2.8%
격 8
 
2.5%
산 6
 
1.9%
개 6
 
1.9%
리 5
 
1.6%
중 5
 
1.6%
Other values (148) 238
74.1%
Decimal Number
ValueCountFrequency (%)
1 50
35.2%
0 50
35.2%
2 13
 
9.2%
5 10
 
7.0%
3 9
 
6.3%
8 5
 
3.5%
9 2
 
1.4%
7 1
 
0.7%
6 1
 
0.7%
4 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
S 3
27.3%
K 3
27.3%
L 1
 
9.1%
O 1
 
9.1%
X 1
 
9.1%
J 1
 
9.1%
C 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
g 31
63.3%
k 9
 
18.4%
ℓ 5
 
10.2%
c 2
 
4.1%
m 2
 
4.1%
Other Punctuation
ValueCountFrequency (%)
/ 35
77.8%
, 7
 
15.6%
. 2
 
4.4%
% 1
 
2.2%
Math Symbol
ValueCountFrequency (%)
~ 7
87.5%
∼ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Other Symbol
ValueCountFrequency (%)
㎖ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 321
48.6%
Common 284
43.0%
Latin 55
 
8.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
통 12
 
3.7%
릇 11
 
3.4%
그 11
 
3.4%
보 10
 
3.1%
가 9
 
2.8%
격 8
 
2.5%
산 6
 
1.9%
개 6
 
1.9%
리 5
 
1.6%
중 5
 
1.6%
Other values (148) 238
74.1%
Common
ValueCountFrequency (%)
1 50
17.6%
0 50
17.6%
45
15.8%
/ 35
12.3%
( 18
 
6.3%
) 18
 
6.3%
2 13
 
4.6%
5 10
 
3.5%
3 9
 
3.2%
~ 7
 
2.5%
Other values (11) 29
10.2%
Latin
ValueCountFrequency (%)
g 31
56.4%
k 9
 
16.4%
S 3
 
5.5%
K 3
 
5.5%
c 2
 
3.6%
m 2
 
3.6%
L 1
 
1.8%
O 1
 
1.8%
X 1
 
1.8%
J 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 330
50.0%
Hangul 321
48.6%
Letterlike Symbols 5
 
0.8%
CJK Compat 3
 
0.5%
Math Operators 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 50
15.2%
0 50
15.2%
45
13.6%
/ 35
10.6%
g 31
9.4%
( 18
 
5.5%
) 18
 
5.5%
2 13
 
3.9%
5 10
 
3.0%
k 9
 
2.7%
Other values (19) 51
15.5%
Hangul
ValueCountFrequency (%)
통 12
 
3.7%
릇 11
 
3.4%
그 11
 
3.4%
보 10
 
3.1%
가 9
 
2.8%
격 8
 
2.5%
산 6
 
1.9%
개 6
 
1.9%
리 5
 
1.6%
중 5
 
1.6%
Other values (148) 238
74.1%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 5
100.0%
CJK Compat
ValueCountFrequency (%)
㎖ 3
100.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

2월 2주차가격(평균_원)
Real number (ℝ)

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8063.5167
Minimum297
Maximum39429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T16:38:21.393318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum297
5-th percentile1121.3
Q12626.75
median4761
Q39856.25
95-th percentile28292.75
Maximum39429
Range39132
Interquartile range (IQR)7229.5

Descriptive statistics

Standard deviation8819.4666
Coefficient of variation (CV)1.0937494
Kurtosis3.5652232
Mean8063.5167
Median Absolute Deviation (MAD)2934
Skewness1.9822078
Sum483811
Variance77782991
MonotonicityNot monotonic
2023-12-12T16:38:21.560333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3250 2
 
3.3%
33850 1
 
1.7%
1496 1
 
1.7%
1032 1
 
1.7%
1361 1
 
1.7%
39429 1
 
1.7%
7688 1
 
1.7%
6375 1
 
1.7%
5625 1
 
1.7%
9500 1
 
1.7%
Other values (49) 49
81.7%
ValueCountFrequency (%)
297 1
1.7%
991 1
1.7%
1032 1
1.7%
1126 1
1.7%
1361 1
1.7%
1405 1
1.7%
1423 1
1.7%
1496 1
1.7%
1543 1
1.7%
1598 1
1.7%
ValueCountFrequency (%)
39429 1
1.7%
33850 1
1.7%
32335 1
1.7%
28080 1
1.7%
27925 1
1.7%
21300 1
1.7%
19875 1
1.7%
15750 1
1.7%
14364 1
1.7%
14029 1
1.7%

2월 1주차가격(평균_원)
Real number (ℝ)

Distinct58
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8065.5833
Minimum306
Maximum39429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T16:38:21.760978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum306
5-th percentile1121.55
Q12639.25
median4828
Q39856.25
95-th percentile28292.75
Maximum39429
Range39123
Interquartile range (IQR)7217

Descriptive statistics

Standard deviation8816.3709
Coefficient of variation (CV)1.0930853
Kurtosis3.5717375
Mean8065.5833
Median Absolute Deviation (MAD)2857
Skewness1.9844463
Sum483935
Variance77728396
MonotonicityNot monotonic
2023-12-12T16:38:21.951880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3250 3
 
5.0%
33850 1
 
1.7%
6000 1
 
1.7%
1037 1
 
1.7%
1386 1
 
1.7%
39429 1
 
1.7%
7688 1
 
1.7%
6375 1
 
1.7%
5625 1
 
1.7%
9500 1
 
1.7%
Other values (48) 48
80.0%
ValueCountFrequency (%)
306 1
1.7%
865 1
1.7%
1037 1
1.7%
1126 1
1.7%
1386 1
1.7%
1405 1
1.7%
1423 1
1.7%
1496 1
1.7%
1559 1
1.7%
1811 1
1.7%
ValueCountFrequency (%)
39429 1
1.7%
33850 1
1.7%
32335 1
1.7%
28080 1
1.7%
27925 1
1.7%
21300 1
1.7%
19875 1
1.7%
15750 1
1.7%
14364 1
1.7%
14029 1
1.7%

등락여부
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
<NA>
45 
하락
11 
상승
 
4

Length

Max length4
Median length4
Mean length3.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 45
75.0%
하락 11
 
18.3%
상승 4
 
6.7%

Length

2023-12-12T16:38:22.108550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:38:22.229683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
75.0%
하락 11
 
18.3%
상승 4
 
6.7%

등락가격(원)
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.516667
Minimum0
Maximum376
Zeros45
Zeros (%)75.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T16:38:22.354130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile126.4
Maximum376
Range376
Interquartile range (IQR)1

Descriptive statistics

Standard deviation67.551485
Coefficient of variation (CV)3.0000659
Kurtosis17.680458
Mean22.516667
Median Absolute Deviation (MAD)0
Skewness4.0833335
Sum1351
Variance4563.2031
MonotonicityNot monotonic
2023-12-12T16:38:22.511462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 45
75.0%
50 3
 
5.0%
126 1
 
1.7%
376 1
 
1.7%
313 1
 
1.7%
4 1
 
1.7%
30 1
 
1.7%
125 1
 
1.7%
38 1
 
1.7%
9 1
 
1.7%
Other values (4) 4
 
6.7%
ValueCountFrequency (%)
0 45
75.0%
4 1
 
1.7%
5 1
 
1.7%
9 1
 
1.7%
16 1
 
1.7%
25 1
 
1.7%
30 1
 
1.7%
38 1
 
1.7%
50 3
 
5.0%
125 1
 
1.7%
ValueCountFrequency (%)
376 1
 
1.7%
313 1
 
1.7%
134 1
 
1.7%
126 1
 
1.7%
125 1
 
1.7%
50 3
5.0%
38 1
 
1.7%
30 1
 
1.7%
25 1
 
1.7%
16 1
 
1.7%

등락률(퍼센트)
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0166667
Minimum0
Maximum19.1
Zeros45
Zeros (%)75.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T16:38:22.700633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.025
95-th percentile3.16
Maximum19.1
Range19.1
Interquartile range (IQR)0.025

Descriptive statistics

Standard deviation3.2497284
Coefficient of variation (CV)3.1964541
Kurtosis20.997616
Mean1.0166667
Median Absolute Deviation (MAD)0
Skewness4.469677
Sum61
Variance10.560734
MonotonicityNot monotonic
2023-12-12T16:38:22.835236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 45
75.0%
2.8 2
 
3.3%
14.6 1
 
1.7%
1.9 1
 
1.7%
19.1 1
 
1.7%
8.1 1
 
1.7%
0.1 1
 
1.7%
0.6 1
 
1.7%
1.6 1
 
1.7%
2.4 1
 
1.7%
Other values (5) 5
 
8.3%
ValueCountFrequency (%)
0.0 45
75.0%
0.1 1
 
1.7%
0.5 1
 
1.7%
0.6 1
 
1.7%
0.8 1
 
1.7%
1.0 1
 
1.7%
1.6 1
 
1.7%
1.8 1
 
1.7%
1.9 1
 
1.7%
2.4 1
 
1.7%
ValueCountFrequency (%)
19.1 1
1.7%
14.6 1
1.7%
8.1 1
1.7%
2.9 1
1.7%
2.8 2
3.3%
2.4 1
1.7%
1.9 1
1.7%
1.8 1
1.7%
1.6 1
1.7%
1.0 1
1.7%

중구(신포)_가격
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)67.8%
Missing1
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean8268.2034
Minimum300
Maximum46670
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T16:38:22.979327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile1185
Q12400
median4500
Q310150
95-th percentile27230
Maximum46670
Range46370
Interquartile range (IQR)7750

Descriptive statistics

Standard deviation9464.9869
Coefficient of variation (CV)1.1447453
Kurtosis5.2925166
Mean8268.2034
Median Absolute Deviation (MAD)2550
Skewness2.2204853
Sum487824
Variance89585977
MonotonicityNot monotonic
2023-12-12T16:38:23.147791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
6000 4
 
6.7%
3000 3
 
5.0%
2500 3
 
5.0%
2000 3
 
5.0%
4000 3
 
5.0%
8000 3
 
5.0%
7000 3
 
5.0%
4500 2
 
3.3%
18000 2
 
3.3%
3650 2
 
3.3%
Other values (30) 31
51.7%
ValueCountFrequency (%)
300 1
1.7%
800 1
1.7%
1050 1
1.7%
1200 1
1.7%
1300 1
1.7%
1367 1
1.7%
1480 1
1.7%
1500 1
1.7%
1557 1
1.7%
1750 1
1.7%
ValueCountFrequency (%)
46670 1
1.7%
37000 1
1.7%
33800 1
1.7%
26500 1
1.7%
24000 1
1.7%
21000 1
1.7%
18000 2
3.3%
16000 1
1.7%
15000 2
3.3%
13900 1
1.7%

중구(신포)_참고 사항
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing59
Missing (%)98.3%
Memory size612.0 B
2023-12-12T16:38:23.299207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row(3+1행사)
ValueCountFrequency (%)
3+1행사 1
100.0%
2023-12-12T16:38:23.931672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 1
14.3%
3 1
14.3%
+ 1
14.3%
1 1
14.3%
행 1
14.3%
사 1
14.3%
) 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
28.6%
Other Letter 2
28.6%
Open Punctuation 1
14.3%
Math Symbol 1
14.3%
Close Punctuation 1
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1
50.0%
1 1
50.0%
Other Letter
ValueCountFrequency (%)
행 1
50.0%
사 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
71.4%
Hangul 2
 
28.6%

Most frequent character per script

Common
ValueCountFrequency (%)
( 1
20.0%
3 1
20.0%
+ 1
20.0%
1 1
20.0%
) 1
20.0%
Hangul
ValueCountFrequency (%)
행 1
50.0%
사 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
71.4%
Hangul 2
 
28.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 1
20.0%
3 1
20.0%
+ 1
20.0%
1 1
20.0%
) 1
20.0%
Hangul
ValueCountFrequency (%)
행 1
50.0%
사 1
50.0%

동구(송현)_가격
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)59.3%
Missing1
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean7292.6949
Minimum200
Maximum40000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T16:38:24.119384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200
5-th percentile1000
Q12000
median4000
Q37900
95-th percentile28200
Maximum40000
Range39800
Interquartile range (IQR)5900

Descriptive statistics

Standard deviation8826.5363
Coefficient of variation (CV)1.2103257
Kurtosis4.5445591
Mean7292.6949
Median Absolute Deviation (MAD)2492
Skewness2.2275748
Sum430269
Variance77907744
MonotonicityNot monotonic
2023-12-12T16:38:24.287463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
4000 6
 
10.0%
5000 5
 
8.3%
1000 4
 
6.7%
6000 3
 
5.0%
1500 3
 
5.0%
2500 3
 
5.0%
2000 2
 
3.3%
12000 2
 
3.3%
2700 2
 
3.3%
20000 2
 
3.3%
Other values (25) 27
45.0%
ValueCountFrequency (%)
200 1
 
1.7%
1000 4
6.7%
1007 1
 
1.7%
1100 1
 
1.7%
1210 1
 
1.7%
1328 1
 
1.7%
1500 3
5.0%
1508 1
 
1.7%
1633 1
 
1.7%
2000 2
3.3%
ValueCountFrequency (%)
40000 1
1.7%
35000 1
1.7%
30000 1
1.7%
28000 1
1.7%
27900 1
1.7%
20000 2
3.3%
14900 1
1.7%
12000 2
3.3%
10000 2
3.3%
9633 1
1.7%

동구(송현)_참고 사항
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing58
Missing (%)96.7%
Memory size612.0 B
2023-12-12T16:38:24.489196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14.5
Mean length14.5
Min length12

Characters and Unicode

Total characters29
Distinct characters22
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

Unique2 ?
Unique (%)100.0%

Sample

1st row380g 환산=2300
2nd row풀무원국산콩두부(찌게용)340g
ValueCountFrequency (%)
380g 1
33.3%
환산=2300 1
33.3%
풀무원국산콩두부(찌게용)340g 1
33.3%
2023-12-12T16:38:24.884712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4
 
13.8%
3 3
 
10.3%
g 2
 
6.9%
산 2
 
6.9%
콩 1
 
3.4%
) 1
 
3.4%
용 1
 
3.4%
게 1
 
3.4%
찌 1
 
3.4%
( 1
 
3.4%
Other values (12) 12
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13
44.8%
Decimal Number 10
34.5%
Lowercase Letter 2
 
6.9%
Close Punctuation 1
 
3.4%
Open Punctuation 1
 
3.4%
Math Symbol 1
 
3.4%
Space Separator 1
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 2
15.4%
콩 1
7.7%
용 1
7.7%
게 1
7.7%
찌 1
7.7%
부 1
7.7%
두 1
7.7%
원 1
7.7%
국 1
7.7%
무 1
7.7%
Other values (2) 2
15.4%
Decimal Number
ValueCountFrequency (%)
0 4
40.0%
3 3
30.0%
8 1
 
10.0%
2 1
 
10.0%
4 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
g 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14
48.3%
Hangul 13
44.8%
Latin 2
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 2
15.4%
콩 1
7.7%
용 1
7.7%
게 1
7.7%
찌 1
7.7%
부 1
7.7%
두 1
7.7%
원 1
7.7%
국 1
7.7%
무 1
7.7%
Other values (2) 2
15.4%
Common
ValueCountFrequency (%)
0 4
28.6%
3 3
21.4%
) 1
 
7.1%
( 1
 
7.1%
8 1
 
7.1%
2 1
 
7.1%
= 1
 
7.1%
1
 
7.1%
4 1
 
7.1%
Latin
ValueCountFrequency (%)
g 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
55.2%
Hangul 13
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4
25.0%
3 3
18.8%
g 2
12.5%
) 1
 
6.2%
( 1
 
6.2%
8 1
 
6.2%
2 1
 
6.2%
= 1
 
6.2%
1
 
6.2%
4 1
 
6.2%
Hangul
ValueCountFrequency (%)
산 2
15.4%
콩 1
7.7%
용 1
7.7%
게 1
7.7%
찌 1
7.7%
부 1
7.7%
두 1
7.7%
원 1
7.7%
국 1
7.7%
무 1
7.7%
Other values (2) 2
15.4%

미추홀구(신기)_가격
Real number (ℝ)

MISSING 

Distinct46
Distinct (%)78.0%
Missing1
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean7191.9153
Minimum299
Maximum32500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T16:38:25.063394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum299
5-th percentile1134.8
Q12600
median4980
Q38666.5
95-th percentile22210
Maximum32500
Range32201
Interquartile range (IQR)6066.5

Descriptive statistics

Standard deviation7144.5418
Coefficient of variation (CV)0.99341296
Kurtosis2.9042228
Mean7191.9153
Median Absolute Deviation (MAD)2527
Skewness1.7946045
Sum424323
Variance51044478
MonotonicityNot monotonic
2023-12-12T16:38:25.235563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
6000 6
 
10.0%
11000 2
 
3.3%
5000 2
 
3.3%
2800 2
 
3.3%
13000 2
 
3.3%
4000 2
 
3.3%
3000 2
 
3.3%
6500 2
 
3.3%
1990 2
 
3.3%
2000 1
 
1.7%
Other values (36) 36
60.0%
ValueCountFrequency (%)
299 1
1.7%
959 1
1.7%
998 1
1.7%
1150 1
1.7%
1290 1
1.7%
1349 1
1.7%
1400 1
1.7%
1529 1
1.7%
1800 1
1.7%
1966 1
1.7%
ValueCountFrequency (%)
32500 1
1.7%
27800 1
1.7%
25000 1
1.7%
21900 1
1.7%
20310 1
1.7%
19500 1
1.7%
16000 1
1.7%
15000 1
1.7%
14900 1
1.7%
13000 2
3.3%

미추홀구(신기)_참고 사항
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing50
Missing (%)83.3%
Memory size612.0 B
2023-12-12T16:38:25.447819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length8.5
Min length4

Characters and Unicode

Total characters85
Distinct characters53
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

Unique10 ?
Unique (%)100.0%

Sample

1st row250g-2200원
2nd row3개한망 14900
3rd row130G 3190
4th row340g-3900
5th row3.2kg세일
ValueCountFrequency (%)
250g-2200원 1
8.3%
3개한망 1
8.3%
14900 1
8.3%
130g 1
8.3%
3190 1
8.3%
340g-3900 1
8.3%
3.2kg세일 1
8.3%
엘라스틴데미지680mi 1
8.3%
크리넥스데코소프트24롤 1
8.3%
모듬초밥 1
8.3%
Other values (2) 2
16.7%
2023-12-12T16:38:25.797468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
 
12.9%
3 6
 
7.1%
2 5
 
5.9%
g 3
 
3.5%
9 3
 
3.5%
4 3
 
3.5%
1 3
 
3.5%
2
 
2.4%
데 2
 
2.4%
스 2
 
2.4%
Other values (43) 45
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39
45.9%
Decimal Number 34
40.0%
Lowercase Letter 5
 
5.9%
Space Separator 2
 
2.4%
Dash Punctuation 2
 
2.4%
Uppercase Letter 2
 
2.4%
Other Punctuation 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
데 2
 
5.1%
스 2
 
5.1%
프 2
 
5.1%
밥 1
 
2.6%
트 1
 
2.6%
소 1
 
2.6%
모 1
 
2.6%
듬 1
 
2.6%
초 1
 
2.6%
롤 1
 
2.6%
Other values (26) 26
66.7%
Decimal Number
ValueCountFrequency (%)
0 11
32.4%
3 6
17.6%
2 5
14.7%
9 3
 
8.8%
4 3
 
8.8%
1 3
 
8.8%
6 1
 
2.9%
5 1
 
2.9%
8 1
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
g 3
60.0%
k 1
 
20.0%
m 1
 
20.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
I 1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39
45.9%
Hangul 39
45.9%
Latin 7
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
데 2
 
5.1%
스 2
 
5.1%
프 2
 
5.1%
밥 1
 
2.6%
트 1
 
2.6%
소 1
 
2.6%
모 1
 
2.6%
듬 1
 
2.6%
초 1
 
2.6%
롤 1
 
2.6%
Other values (26) 26
66.7%
Common
ValueCountFrequency (%)
0 11
28.2%
3 6
15.4%
2 5
12.8%
9 3
 
7.7%
4 3
 
7.7%
1 3
 
7.7%
2
 
5.1%
- 2
 
5.1%
6 1
 
2.6%
. 1
 
2.6%
Other values (2) 2
 
5.1%
Latin
ValueCountFrequency (%)
g 3
42.9%
G 1
 
14.3%
k 1
 
14.3%
m 1
 
14.3%
I 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46
54.1%
Hangul 39
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
23.9%
3 6
13.0%
2 5
10.9%
g 3
 
6.5%
9 3
 
6.5%
4 3
 
6.5%
1 3
 
6.5%
2
 
4.3%
- 2
 
4.3%
6 1
 
2.2%
Other values (7) 7
15.2%
Hangul
ValueCountFrequency (%)
데 2
 
5.1%
스 2
 
5.1%
프 2
 
5.1%
밥 1
 
2.6%
트 1
 
2.6%
소 1
 
2.6%
모 1
 
2.6%
듬 1
 
2.6%
초 1
 
2.6%
롤 1
 
2.6%
Other values (26) 26
66.7%

남동구(모래내)_가격
Real number (ℝ)

Distinct46
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8367.2833
Minimum300
Maximum39000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T16:38:25.968689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile1046.5
Q12650
median5250
Q310000
95-th percentile32541.65
Maximum39000
Range38700
Interquartile range (IQR)7350

Descriptive statistics

Standard deviation9105.8661
Coefficient of variation (CV)1.0882703
Kurtosis3.2846248
Mean8367.2833
Median Absolute Deviation (MAD)3435
Skewness1.9352614
Sum502037
Variance82916797
MonotonicityNot monotonic
2023-12-12T16:38:26.115418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
7000 4
 
6.7%
8000 3
 
5.0%
16000 2
 
3.3%
3000 2
 
3.3%
2000 2
 
3.3%
1500 2
 
3.3%
3500 2
 
3.3%
4000 2
 
3.3%
5500 2
 
3.3%
10000 2
 
3.3%
Other values (36) 37
61.7%
ValueCountFrequency (%)
300 1
1.7%
900 1
1.7%
980 1
1.7%
1050 1
1.7%
1250 1
1.7%
1320 1
1.7%
1327 1
1.7%
1350 1
1.7%
1497 1
1.7%
1500 2
3.3%
ValueCountFrequency (%)
39000 1
1.7%
35000 1
1.7%
33333 1
1.7%
32500 1
1.7%
27500 1
1.7%
22800 1
1.7%
20000 1
1.7%
16000 2
3.3%
14000 2
3.3%
12000 1
1.7%

남동구(모래내)_참고 사항
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing57
Missing (%)95.0%
Memory size612.0 B
2023-12-12T16:38:26.279896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length7.6666667
Min length3

Characters and Unicode

Total characters23
Distinct characters10
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row8개
2nd row400g 6000원
3rd row1kg 10000원
ValueCountFrequency (%)
8개 1
20.0%
400g 1
20.0%
6000원 1
20.0%
1kg 1
20.0%
10000원 1
20.0%
2023-12-12T16:38:26.612777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
39.1%
3
 
13.0%
g 2
 
8.7%
원 2
 
8.7%
1 2
 
8.7%
8 1
 
4.3%
개 1
 
4.3%
4 1
 
4.3%
6 1
 
4.3%
k 1
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
60.9%
Space Separator 3
 
13.0%
Lowercase Letter 3
 
13.0%
Other Letter 3
 
13.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
64.3%
1 2
 
14.3%
8 1
 
7.1%
4 1
 
7.1%
6 1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
g 2
66.7%
k 1
33.3%
Other Letter
ValueCountFrequency (%)
원 2
66.7%
개 1
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17
73.9%
Latin 3
 
13.0%
Hangul 3
 
13.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
52.9%
3
 
17.6%
1 2
 
11.8%
8 1
 
5.9%
4 1
 
5.9%
6 1
 
5.9%
Latin
ValueCountFrequency (%)
g 2
66.7%
k 1
33.3%
Hangul
ValueCountFrequency (%)
원 2
66.7%
개 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
87.0%
Hangul 3
 
13.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
45.0%
3
 
15.0%
g 2
 
10.0%
1 2
 
10.0%
8 1
 
5.0%
4 1
 
5.0%
6 1
 
5.0%
k 1
 
5.0%
Hangul
ValueCountFrequency (%)
원 2
66.7%
개 1
33.3%

연수구(옥련)_가격
Real number (ℝ)

MISSING 

Distinct46
Distinct (%)78.0%
Missing1
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean7355.7288
Minimum480
Maximum42000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T16:38:26.773935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum480
5-th percentile1089
Q12775
median5000
Q38900
95-th percentile25000
Maximum42000
Range41520
Interquartile range (IQR)6125

Descriptive statistics

Standard deviation7942.3075
Coefficient of variation (CV)1.0797445
Kurtosis6.2713147
Mean7355.7288
Median Absolute Deviation (MAD)3000
Skewness2.3264524
Sum433988
Variance63080248
MonotonicityNot monotonic
2023-12-12T16:38:26.913936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
5000 4
 
6.7%
14000 3
 
5.0%
3000 3
 
5.0%
2000 3
 
5.0%
1500 2
 
3.3%
15000 2
 
3.3%
8000 2
 
3.3%
25000 2
 
3.3%
28500 1
 
1.7%
1619 1
 
1.7%
Other values (36) 36
60.0%
ValueCountFrequency (%)
480 1
1.7%
580 1
1.7%
990 1
1.7%
1100 1
1.7%
1150 1
1.7%
1350 1
1.7%
1410 1
1.7%
1429 1
1.7%
1500 2
3.3%
1619 1
1.7%
ValueCountFrequency (%)
42000 1
 
1.7%
28500 1
 
1.7%
25000 2
3.3%
24800 1
 
1.7%
15000 2
3.3%
14000 3
5.0%
12220 1
 
1.7%
11100 1
 
1.7%
11000 1
 
1.7%
9900 1
 
1.7%

연수구(옥련)_참고 사항
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing45
Missing (%)75.0%
Memory size612.0 B
2023-12-12T16:38:27.086725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length9
Mean length7.4
Min length2

Characters and Unicode

Total characters111
Distinct characters54
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)100.0%

Sample

1st row340g 환산
2nd row1kg 환산
3rd row1.5kg
4th row7-12개입
5th row1등급
ValueCountFrequency (%)
340g 2
 
10.0%
환산 2
 
10.0%
대체조사 2
 
10.0%
1.5kg 1
 
5.0%
7-12개입 1
 
5.0%
1등급 1
 
5.0%
특란 1
 
5.0%
비트3kg 1
 
5.0%
1kg 1
 
5.0%
마린콜라겐680ml 1
 
5.0%
Other values (7) 7
35.0%
2023-12-12T16:38:27.380391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
 
14.4%
1 10
 
9.0%
g 9
 
8.1%
5
 
4.5%
2 5
 
4.5%
3 3
 
2.7%
산 3
 
2.7%
k 3
 
2.7%
8 3
 
2.7%
4 3
 
2.7%
Other values (44) 51
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46
41.4%
Decimal Number 43
38.7%
Lowercase Letter 15
 
13.5%
Space Separator 5
 
4.5%
Other Punctuation 1
 
0.9%
Dash Punctuation 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 3
 
6.5%
등 2
 
4.3%
트 2
 
4.3%
조 2
 
4.3%
사 2
 
4.3%
대 2
 
4.3%
체 2
 
4.3%
환 2
 
4.3%
소 1
 
2.2%
코 1
 
2.2%
Other values (27) 27
58.7%
Decimal Number
ValueCountFrequency (%)
0 16
37.2%
1 10
23.3%
2 5
 
11.6%
3 3
 
7.0%
8 3
 
7.0%
4 3
 
7.0%
5 1
 
2.3%
7 1
 
2.3%
6 1
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
g 9
60.0%
k 3
 
20.0%
p 1
 
6.7%
l 1
 
6.7%
m 1
 
6.7%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50
45.0%
Hangul 46
41.4%
Latin 15
 
13.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 3
 
6.5%
등 2
 
4.3%
트 2
 
4.3%
조 2
 
4.3%
사 2
 
4.3%
대 2
 
4.3%
체 2
 
4.3%
환 2
 
4.3%
소 1
 
2.2%
코 1
 
2.2%
Other values (27) 27
58.7%
Common
ValueCountFrequency (%)
0 16
32.0%
1 10
20.0%
5
 
10.0%
2 5
 
10.0%
3 3
 
6.0%
8 3
 
6.0%
4 3
 
6.0%
. 1
 
2.0%
5 1
 
2.0%
7 1
 
2.0%
Other values (2) 2
 
4.0%
Latin
ValueCountFrequency (%)
g 9
60.0%
k 3
 
20.0%
p 1
 
6.7%
l 1
 
6.7%
m 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
58.6%
Hangul 46
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16
24.6%
1 10
15.4%
g 9
13.8%
5
 
7.7%
2 5
 
7.7%
3 3
 
4.6%
k 3
 
4.6%
8 3
 
4.6%
4 3
 
4.6%
p 1
 
1.5%
Other values (7) 7
10.8%
Hangul
ValueCountFrequency (%)
산 3
 
6.5%
등 2
 
4.3%
트 2
 
4.3%
조 2
 
4.3%
사 2
 
4.3%
대 2
 
4.3%
체 2
 
4.3%
환 2
 
4.3%
소 1
 
2.2%
코 1
 
2.2%
Other values (27) 27
58.7%

부평구(부평)_가격
Real number (ℝ)

Distinct45
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8613.3333
Minimum250
Maximum40000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T16:38:27.525061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum250
5-th percentile1284.5
Q12700
median4600
Q310500
95-th percentile30444
Maximum40000
Range39750
Interquartile range (IQR)7800

Descriptive statistics

Standard deviation9615.1049
Coefficient of variation (CV)1.1163047
Kurtosis3.7629116
Mean8613.3333
Median Absolute Deviation (MAD)2725
Skewness2.0348434
Sum516800
Variance92450242
MonotonicityNot monotonic
2023-12-12T16:38:27.679357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
7000 5
 
8.3%
4500 3
 
5.0%
3000 3
 
5.0%
4000 2
 
3.3%
6500 2
 
3.3%
2700 2
 
3.3%
3500 2
 
3.3%
12000 2
 
3.3%
13000 2
 
3.3%
1300 2
 
3.3%
Other values (35) 35
58.3%
ValueCountFrequency (%)
250 1
1.7%
650 1
1.7%
990 1
1.7%
1300 2
3.3%
1415 1
1.7%
1500 1
1.7%
1615 1
1.7%
1650 1
1.7%
1750 1
1.7%
2000 1
1.7%
ValueCountFrequency (%)
40000 1
1.7%
39000 1
1.7%
38880 1
1.7%
30000 1
1.7%
28000 1
1.7%
25000 1
1.7%
18000 1
1.7%
17000 1
1.7%
16000 1
1.7%
15000 1
1.7%

부평구(부평)_참고 사항
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing59
Missing (%)98.3%
Memory size612.0 B
2023-12-12T16:38:27.856149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters12
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

Unique1 ?
Unique (%)100.0%

Sample

1st row크리넥스 순수 소프트 입고
ValueCountFrequency (%)
크리넥스 1
25.0%
순수 1
25.0%
소프트 1
25.0%
입고 1
25.0%
2023-12-12T16:38:28.199418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3
21.4%
크 1
 
7.1%
리 1
 
7.1%
넥 1
 
7.1%
스 1
 
7.1%
순 1
 
7.1%
수 1
 
7.1%
소 1
 
7.1%
프 1
 
7.1%
트 1
 
7.1%
Other values (2) 2
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11
78.6%
Space Separator 3
 
21.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
크 1
9.1%
리 1
9.1%
넥 1
9.1%
스 1
9.1%
순 1
9.1%
수 1
9.1%
소 1
9.1%
프 1
9.1%
트 1
9.1%
입 1
9.1%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11
78.6%
Common 3
 
21.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
크 1
9.1%
리 1
9.1%
넥 1
9.1%
스 1
9.1%
순 1
9.1%
수 1
9.1%
소 1
9.1%
프 1
9.1%
트 1
9.1%
입 1
9.1%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11
78.6%
ASCII 3
 
21.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3
100.0%
Hangul
ValueCountFrequency (%)
크 1
9.1%
리 1
9.1%
넥 1
9.1%
스 1
9.1%
순 1
9.1%
수 1
9.1%
소 1
9.1%
프 1
9.1%
트 1
9.1%
입 1
9.1%

계양구(작전)_가격
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)69.0%
Missing2
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean7854.9655
Minimum300
Maximum45000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T16:38:28.390682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile1025.5
Q12000
median4900
Q39000
95-th percentile30450
Maximum45000
Range44700
Interquartile range (IQR)7000

Descriptive statistics

Standard deviation9340.3867
Coefficient of variation (CV)1.189106
Kurtosis6.0469158
Mean7854.9655
Median Absolute Deviation (MAD)3321.5
Skewness2.4259202
Sum455588
Variance87242824
MonotonicityNot monotonic
2023-12-12T16:38:28.536453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
5000 4
 
6.7%
2000 3
 
5.0%
6000 3
 
5.0%
3500 3
 
5.0%
9000 3
 
5.0%
1000 2
 
3.3%
13000 2
 
3.3%
7000 2
 
3.3%
7500 2
 
3.3%
1500 2
 
3.3%
Other values (30) 32
53.3%
ValueCountFrequency (%)
300 1
1.7%
1000 2
3.3%
1030 1
1.7%
1100 1
1.7%
1200 1
1.7%
1337 1
1.7%
1400 1
1.7%
1450 1
1.7%
1500 2
3.3%
1507 1
1.7%
ValueCountFrequency (%)
45000 1
1.7%
39000 1
1.7%
33000 1
1.7%
30000 1
1.7%
23000 1
1.7%
19000 1
1.7%
17000 1
1.7%
14000 1
1.7%
13000 2
3.3%
10000 2
3.3%

계양구(작전)_참고 사항
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing45
Missing (%)75.0%
Memory size612.0 B
2023-12-12T16:38:28.781430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.9333333
Min length3

Characters and Unicode

Total characters134
Distinct characters66
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

Unique15 ?
Unique (%)100.0%

Sample

1st rowcj무농약 콩나물380g
2nd row소포장
3rd row낱개 판매 중 4개 2000
4th row3포기 한묶음 12000
5th row5개 한묶음
ValueCountFrequency (%)
소포장 2
 
7.1%
한묶음 2
 
7.1%
cj무농약 1
 
3.6%
백설표 1
 
3.6%
버섯불고기(미국산 1
 
3.6%
200g(한우 1
 
3.6%
15000 1
 
3.6%
350g 1
 
3.6%
차돌된장찌개 1
 
3.6%
es집중영양샴푸680ml 1
 
3.6%
Other values (16) 16
57.1%
2023-12-12T16:38:29.189790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19
 
14.2%
15
 
11.2%
g 6
 
4.5%
2 5
 
3.7%
5 4
 
3.0%
개 4
 
3.0%
장 3
 
2.2%
1 3
 
2.2%
포 3
 
2.2%
한 3
 
2.2%
Other values (56) 69
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59
44.0%
Decimal Number 40
29.9%
Space Separator 15
 
11.2%
Lowercase Letter 13
 
9.7%
Close Punctuation 2
 
1.5%
Open Punctuation 2
 
1.5%
Uppercase Letter 2
 
1.5%
Other Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 4
 
6.8%
장 3
 
5.1%
포 3
 
5.1%
한 3
 
5.1%
중 2
 
3.4%
기 2
 
3.4%
묶 2
 
3.4%
음 2
 
3.4%
소 2
 
3.4%
우 1
 
1.7%
Other values (35) 35
59.3%
Decimal Number
ValueCountFrequency (%)
0 19
47.5%
2 5
 
12.5%
5 4
 
10.0%
1 3
 
7.5%
3 3
 
7.5%
8 2
 
5.0%
7 2
 
5.0%
6 1
 
2.5%
4 1
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
g 6
46.2%
j 2
 
15.4%
c 2
 
15.4%
l 1
 
7.7%
m 1
 
7.7%
k 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
E 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60
44.8%
Hangul 59
44.0%
Latin 15
 
11.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 4
 
6.8%
장 3
 
5.1%
포 3
 
5.1%
한 3
 
5.1%
중 2
 
3.4%
기 2
 
3.4%
묶 2
 
3.4%
음 2
 
3.4%
소 2
 
3.4%
우 1
 
1.7%
Other values (35) 35
59.3%
Common
ValueCountFrequency (%)
0 19
31.7%
15
25.0%
2 5
 
8.3%
5 4
 
6.7%
1 3
 
5.0%
3 3
 
5.0%
) 2
 
3.3%
( 2
 
3.3%
8 2
 
3.3%
7 2
 
3.3%
Other values (3) 3
 
5.0%
Latin
ValueCountFrequency (%)
g 6
40.0%
j 2
 
13.3%
c 2
 
13.3%
l 1
 
6.7%
m 1
 
6.7%
k 1
 
6.7%
E 1
 
6.7%
S 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
56.0%
Hangul 59
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19
25.3%
15
20.0%
g 6
 
8.0%
2 5
 
6.7%
5 4
 
5.3%
1 3
 
4.0%
3 3
 
4.0%
) 2
 
2.7%
j 2
 
2.7%
c 2
 
2.7%
Other values (11) 14
18.7%
Hangul
ValueCountFrequency (%)
개 4
 
6.8%
장 3
 
5.1%
포 3
 
5.1%
한 3
 
5.1%
중 2
 
3.4%
기 2
 
3.4%
묶 2
 
3.4%
음 2
 
3.4%
소 2
 
3.4%
우 1
 
1.7%
Other values (35) 35
59.3%

서구(중앙)_가격
Real number (ℝ)

Distinct41
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7677.1
Minimum250
Maximum40000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T16:38:29.364690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum250
5-th percentile1076.95
Q12375
median4900
Q310550
95-th percentile27465
Maximum40000
Range39750
Interquartile range (IQR)8175

Descriptive statistics

Standard deviation8536.5905
Coefficient of variation (CV)1.1119551
Kurtosis4.4001462
Mean7677.1
Median Absolute Deviation (MAD)3000
Skewness2.1020928
Sum460626
Variance72873378
MonotonicityNot monotonic
2023-12-12T16:38:29.525947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
6000 6
 
10.0%
3000 4
 
6.7%
2500 3
 
5.0%
5000 3
 
5.0%
13000 3
 
5.0%
2000 2
 
3.3%
1500 2
 
3.3%
21000 2
 
3.3%
4000 2
 
3.3%
3900 2
 
3.3%
Other values (31) 31
51.7%
ValueCountFrequency (%)
250 1
1.7%
1000 1
1.7%
1019 1
1.7%
1080 1
1.7%
1335 1
1.7%
1400 1
1.7%
1428 1
1.7%
1450 1
1.7%
1500 2
3.3%
1515 1
1.7%
ValueCountFrequency (%)
40000 1
 
1.7%
33000 1
 
1.7%
32500 1
 
1.7%
27200 1
 
1.7%
21000 2
3.3%
17000 1
 
1.7%
16800 1
 
1.7%
13000 3
5.0%
12500 1
 
1.7%
12000 1
 
1.7%

서구(중앙)_참고 사항
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing50
Missing (%)83.3%
Memory size612.0 B
2023-12-12T16:38:29.704471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7.5
Mean length5.7
Min length2

Characters and Unicode

Total characters57
Distinct characters31
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)100.0%

Sample

1st row4개입(바구니)
2nd row3마리5천원
3rd row특란
4th row400x13000
5th row1x11000
ValueCountFrequency (%)
4개입(바구니 1
10.0%
3마리5천원 1
10.0%
특란 1
10.0%
400x13000 1
10.0%
1x11000 1
10.0%
300g 1
10.0%
2.7x7400 1
10.0%
680g 1
10.0%
데코24롤 1
10.0%
인천주유 1
10.0%
2023-12-12T16:38:30.068794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
22.8%
1 4
 
7.0%
4 4
 
7.0%
x 3
 
5.3%
3 3
 
5.3%
7 2
 
3.5%
천 2
 
3.5%
2 2
 
3.5%
g 2
 
3.5%
인 1
 
1.8%
Other values (21) 21
36.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31
54.4%
Other Letter 18
31.6%
Lowercase Letter 5
 
8.8%
Other Punctuation 1
 
1.8%
Close Punctuation 1
 
1.8%
Open Punctuation 1
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 2
 
11.1%
인 1
 
5.6%
롤 1
 
5.6%
코 1
 
5.6%
데 1
 
5.6%
주 1
 
5.6%
란 1
 
5.6%
개 1
 
5.6%
특 1
 
5.6%
원 1
 
5.6%
Other values (7) 7
38.9%
Decimal Number
ValueCountFrequency (%)
0 13
41.9%
1 4
 
12.9%
4 4
 
12.9%
3 3
 
9.7%
7 2
 
6.5%
2 2
 
6.5%
8 1
 
3.2%
6 1
 
3.2%
5 1
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
x 3
60.0%
g 2
40.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34
59.6%
Hangul 18
31.6%
Latin 5
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 2
 
11.1%
인 1
 
5.6%
롤 1
 
5.6%
코 1
 
5.6%
데 1
 
5.6%
주 1
 
5.6%
란 1
 
5.6%
개 1
 
5.6%
특 1
 
5.6%
원 1
 
5.6%
Other values (7) 7
38.9%
Common
ValueCountFrequency (%)
0 13
38.2%
1 4
 
11.8%
4 4
 
11.8%
3 3
 
8.8%
7 2
 
5.9%
2 2
 
5.9%
8 1
 
2.9%
6 1
 
2.9%
. 1
 
2.9%
5 1
 
2.9%
Other values (2) 2
 
5.9%
Latin
ValueCountFrequency (%)
x 3
60.0%
g 2
40.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39
68.4%
Hangul 18
31.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
33.3%
1 4
 
10.3%
4 4
 
10.3%
x 3
 
7.7%
3 3
 
7.7%
7 2
 
5.1%
2 2
 
5.1%
g 2
 
5.1%
8 1
 
2.6%
6 1
 
2.6%
Other values (4) 4
 
10.3%
Hangul
ValueCountFrequency (%)
천 2
 
11.1%
인 1
 
5.6%
롤 1
 
5.6%
코 1
 
5.6%
데 1
 
5.6%
주 1
 
5.6%
란 1
 
5.6%
개 1
 
5.6%
특 1
 
5.6%
원 1
 
5.6%
Other values (7) 7
38.9%

Sample

구분품목규격 및 단위2월 2주차가격(평균_원)2월 1주차가격(평균_원)등락여부등락가격(원)등락률(퍼센트)중구(신포)_가격중구(신포)_참고 사항동구(송현)_가격동구(송현)_참고 사항미추홀구(신기)_가격미추홀구(신기)_참고 사항남동구(모래내)_가격남동구(모래내)_참고 사항연수구(옥련)_가격연수구(옥련)_참고 사항부평구(부평)_가격부평구(부평)_참고 사항계양구(작전)_가격계양구(작전)_참고 사항서구(중앙)_가격서구(중앙)_참고 사항
0농축수산물(18)쌀강화미, 햅쌀/10kg3385033850<NA>00.033800<NA>35000<NA>32500<NA>35000<NA>28500<NA>40000<NA>33000<NA>33000<NA>
1농축수산물(18)콩나물풀무원 국산콩 무농약 콩나물/200g14961496<NA>00.01950<NA>1210380g 환산=23001800250g-2200원1320<NA>1410340g 환산1650<NA>1200cj무농약 콩나물380g1428<NA>
2농축수산물(18)마늘깐마늘(중품) 100g991865상승12614.6800<NA>1000<NA>998<NA>900<NA>5801kg 환산650<NA>2000소포장1000<NA>
3농축수산물(18)양파양파 중망/1망25842634하락501.92500<NA>2000<NA>3490<NA>3000<NA>29801.5kg2700<NA>2000낱개 판매 중 4개 20002000<NA>
4농축수산물(18)대파흙대파/1단17611811하락502.82000<NA>1500<NA>1990<NA>2000<NA>1500<NA>2100<NA>1500<NA>1500<NA>
5농축수산물(18)무재래종, 잎없음 15~20cm15981974하락37619.12000<NA>1000<NA>1990<NA>1500<NA>990<NA>2300<NA>1500<NA>1500<NA>
6농축수산물(18)배추통배추/1포기41583846상승3138.14000<NA>5000<NA>49673개한망 149003500<NA>4300<NA>4500<NA>40003포기 한묶음 120003000<NA>
7농축수산물(18)사과5~12개/2.5~3kg68606860<NA>00.06000<NA>5000<NA>4980<NA>80008개99007-12개입6000<NA>100005개 한묶음50004개입(바구니)
8농축수산물(18)고등어1마리/35∼38cm32463250하락40.14000<NA>5000<NA>2500<NA>3300<NA>3000<NA>3000<NA>3500<NA>16663마리5천원
9농축수산물(18)멸치국물용 멸치/100g19811981<NA>00.01750<NA>1000<NA>2453130G 31901500400g 6000원2000<NA>2000<NA>2143소포장 70g 15003000<NA>
구분품목규격 및 단위2월 2주차가격(평균_원)2월 1주차가격(평균_원)등락여부등락가격(원)등락률(퍼센트)중구(신포)_가격중구(신포)_참고 사항동구(송현)_가격동구(송현)_참고 사항미추홀구(신기)_가격미추홀구(신기)_참고 사항남동구(모래내)_가격남동구(모래내)_참고 사항연수구(옥련)_가격연수구(옥련)_참고 사항부평구(부평)_가격부평구(부평)_참고 사항계양구(작전)_가격계양구(작전)_참고 사항서구(중앙)_가격서구(중앙)_참고 사항
50외식비(25)불고기180g~200g의 조사가격을200g으로 환산한 가격1402914029<NA>00.015000<NA><NA><NA>13000버섯불고기16000<NA>15000200g 미국산15000<NA>13000버섯불고기(미국산)11200<NA>
51외식비(25)김밥1줄21252125<NA>00.02500<NA>1000<NA>2000<NA>2000<NA>2000<NA>3500<NA>2000<NA>2000<NA>
52외식비(25)돈가스1인분68756875<NA>00.08000<NA>4500<NA>6500<NA>8000<NA>6000<NA>7000<NA>9000<NA>6000<NA>
53외식비(25)탕수육중1987519875<NA>00.018000<NA>20000<NA>15000<NA>20000<NA>14000<NA>28000<NA>23000<NA>21000<NA>
54외식비(25)치킨프라이드 1마리1575015750<NA>00.018000<NA>9000<NA>16000<NA>16000<NA>15000<NA>18000<NA>17000<NA>17000<NA>
55외식비(25)햄버거불고기버거 1개36753675<NA>00.02000<NA>5000<NA>3000<NA>3900<NA>3800<NA>3900<NA>3900<NA>3900<NA>
56외식비(25)피자일반피자(L)/1판1436414364<NA>00.013900<NA>14900<NA>20310수퍼슈프림피자9900<NA>14000<NA>9900<NA>19000<NA>13000<NA>
57외식비(25)생맥주500㎖/1잔32503250<NA>00.02500<NA>2500<NA>3500<NA>4000<NA>4000<NA>3500<NA>3500<NA>2500<NA>
58외식비(25)국산차녹차/1잔30383038<NA>00.03000<NA>2000<NA>2800<NA>4000<NA>3000<NA>3000<NA>4000<NA>2500<NA>
59외식비(25)커피1잔28382838<NA>00.03000<NA>2500<NA>3200<NA>2500<NA>3000<NA>3000<NA>3000아메리카노2500<NA>