Overview

Dataset statistics

Number of variables9
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory81.0 B

Variable types

Text6
Numeric3

Dataset

Description부산광역시해운대구_물가관리_20220720
Author부산광역시 해운대구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15063783

Alerts

우동(센텀홈플러스) is highly overall correlated with 중동(이마트 해운대점) and 1 other fieldsHigh correlation
중동(이마트 해운대점) is highly overall correlated with 우동(센텀홈플러스) and 1 other fieldsHigh correlation
송정동 is highly overall correlated with 우동(센텀홈플러스) and 1 other fieldsHigh correlation
품 목 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:49:01.364372
Analysis finished2023-12-10 16:49:04.121026
Duration2.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품 목
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-11T01:49:04.701125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.4090909
Min length2

Characters and Unicode

Total characters75
Distinct characters49
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row수 박
2nd row참 외
3rd row소고기(국산)
4th row돼지고기(국산)
5th row달걀
ValueCountFrequency (%)
주 2
 
6.5%
텔 2
 
6.5%
수 1
 
3.2%
브 1
 
3.2%
튜 1
 
3.2%
파라솔 1
 
3.2%
스크류바 1
 
3.2%
월드콘 1
 
3.2%
모 1
 
3.2%
호 1
 
3.2%
Other values (19) 19
61.3%
2023-12-11T01:49:05.238348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
 
12.0%
주 4
 
5.3%
고 4
 
5.3%
기 3
 
4.0%
산 2
 
2.7%
국 2
 
2.7%
면 2
 
2.7%
닭 2
 
2.7%
) 2
 
2.7%
자 2
 
2.7%
Other values (39) 43
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62
82.7%
Space Separator 9
 
12.0%
Close Punctuation 2
 
2.7%
Open Punctuation 2
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 4
 
6.5%
고 4
 
6.5%
기 3
 
4.8%
산 2
 
3.2%
국 2
 
3.2%
면 2
 
3.2%
닭 2
 
3.2%
자 2
 
3.2%
소 2
 
3.2%
텔 2
 
3.2%
Other values (36) 37
59.7%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62
82.7%
Common 13
 
17.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 4
 
6.5%
고 4
 
6.5%
기 3
 
4.8%
산 2
 
3.2%
국 2
 
3.2%
면 2
 
3.2%
닭 2
 
3.2%
자 2
 
3.2%
소 2
 
3.2%
텔 2
 
3.2%
Other values (36) 37
59.7%
Common
ValueCountFrequency (%)
9
69.2%
) 2
 
15.4%
( 2
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62
82.7%
ASCII 13
 
17.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
69.2%
) 2
 
15.4%
( 2
 
15.4%
Hangul
ValueCountFrequency (%)
주 4
 
6.5%
고 4
 
6.5%
기 3
 
4.8%
산 2
 
3.2%
국 2
 
3.2%
면 2
 
3.2%
닭 2
 
3.2%
자 2
 
3.2%
소 2
 
3.2%
텔 2
 
3.2%
Other values (36) 37
59.7%

규 격
Text

Distinct20
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-11T01:49:05.522168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length8.3181818
Min length2

Characters and Unicode

Total characters183
Distinct characters76
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)81.8%

Sample

1st row7kg 1통
2nd row상품 10개
3rd row등심 상등육 500g
4th row삼겹살 500g
5th row대란 30개(한판)
ValueCountFrequency (%)
1일 3
 
6.4%
외식 3
 
6.4%
1인분(보통 2
 
4.3%
1개 2
 
4.3%
대여료 2
 
4.3%
500g 2
 
4.3%
1병 2
 
4.3%
평일 2
 
4.3%
360㎖ 1
 
2.1%
500cc 1
 
2.1%
Other values (27) 27
57.4%
2023-12-11T01:49:06.056201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27
 
14.8%
1 14
 
7.7%
0 14
 
7.7%
, 8
 
4.4%
일 5
 
2.7%
) 5
 
2.7%
( 5
 
2.7%
개 4
 
2.2%
통 4
 
2.2%
5 4
 
2.2%
Other values (66) 93
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89
48.6%
Decimal Number 38
20.8%
Space Separator 27
 
14.8%
Other Punctuation 8
 
4.4%
Lowercase Letter 7
 
3.8%
Close Punctuation 5
 
2.7%
Open Punctuation 5
 
2.7%
Other Symbol 4
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 5
 
5.6%
개 4
 
4.5%
통 4
 
4.5%
기 3
 
3.4%
외 3
 
3.4%
식 3
 
3.4%
대 3
 
3.4%
료 2
 
2.2%
보 2
 
2.2%
인 2
 
2.2%
Other values (49) 58
65.2%
Decimal Number
ValueCountFrequency (%)
1 14
36.8%
0 14
36.8%
5 4
 
10.5%
3 3
 
7.9%
6 1
 
2.6%
7 1
 
2.6%
2 1
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
g 4
57.1%
c 2
28.6%
k 1
 
14.3%
Other Symbol
ValueCountFrequency (%)
㎖ 2
50.0%
㎏ 1
25.0%
㎝ 1
25.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89
48.6%
Common 87
47.5%
Latin 7
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 5
 
5.6%
개 4
 
4.5%
통 4
 
4.5%
기 3
 
3.4%
외 3
 
3.4%
식 3
 
3.4%
대 3
 
3.4%
료 2
 
2.2%
보 2
 
2.2%
인 2
 
2.2%
Other values (49) 58
65.2%
Common
ValueCountFrequency (%)
27
31.0%
1 14
16.1%
0 14
16.1%
, 8
 
9.2%
) 5
 
5.7%
( 5
 
5.7%
5 4
 
4.6%
3 3
 
3.4%
㎖ 2
 
2.3%
6 1
 
1.1%
Other values (4) 4
 
4.6%
Latin
ValueCountFrequency (%)
g 4
57.1%
c 2
28.6%
k 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
49.2%
Hangul 89
48.6%
CJK Compat 4
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27
30.0%
1 14
15.6%
0 14
15.6%
, 8
 
8.9%
) 5
 
5.6%
( 5
 
5.6%
5 4
 
4.4%
g 4
 
4.4%
3 3
 
3.3%
c 2
 
2.2%
Other values (4) 4
 
4.4%
Hangul
ValueCountFrequency (%)
일 5
 
5.6%
개 4
 
4.5%
통 4
 
4.5%
기 3
 
3.4%
외 3
 
3.4%
식 3
 
3.4%
대 3
 
3.4%
료 2
 
2.2%
보 2
 
2.2%
인 2
 
2.2%
Other values (49) 58
65.2%
CJK Compat
ValueCountFrequency (%)
㎖ 2
50.0%
㎏ 1
25.0%
㎝ 1
25.0%

우동(센텀홈플러스)
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25248.182
Minimum500
Maximum226000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-11T01:49:06.230945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile1044.5
Q15125
median10000
Q320717.5
95-th percentile69437.5
Maximum226000
Range225500
Interquartile range (IQR)15592.5

Descriptive statistics

Standard deviation48034.704
Coefficient of variation (CV)1.9025015
Kurtosis15.950032
Mean25248.182
Median Absolute Deviation (MAD)5605
Skewness3.8373272
Sum555460
Variance2.3073328 × 109
MonotonicityNot monotonic
2023-12-11T01:49:06.420250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
10000 3
 
13.6%
5000 3
 
13.6%
20990 1
 
4.5%
22000 1
 
4.5%
15000 1
 
4.5%
500 1
 
4.5%
900 1
 
4.5%
70000 1
 
4.5%
226000 1
 
4.5%
19900 1
 
4.5%
Other values (8) 8
36.4%
ValueCountFrequency (%)
500 1
 
4.5%
900 1
 
4.5%
3790 1
 
4.5%
5000 3
13.6%
5500 1
 
4.5%
6290 1
 
4.5%
7990 1
 
4.5%
10000 3
13.6%
12950 1
 
4.5%
15000 1
 
4.5%
ValueCountFrequency (%)
226000 1
4.5%
70000 1
4.5%
58750 1
4.5%
22900 1
4.5%
22000 1
4.5%
20990 1
4.5%
19900 1
4.5%
17000 1
4.5%
15000 1
4.5%
12950 1
4.5%

중동(이마트 해운대점)
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32983.864
Minimum500
Maximum380000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-11T01:49:06.608935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile1149
Q15250
median10000
Q318175
95-th percentile79816.75
Maximum380000
Range379500
Interquartile range (IQR)12925

Descriptive statistics

Standard deviation80294.401
Coefficient of variation (CV)2.434354
Kurtosis18.664153
Mean32983.864
Median Absolute Deviation (MAD)6010
Skewness4.218169
Sum725645
Variance6.4471908 × 109
MonotonicityNot monotonic
2023-12-11T01:49:06.871157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
10000 3
 
13.6%
4000 2
 
9.1%
22800 1
 
4.5%
8000 1
 
4.5%
500 1
 
4.5%
1000 1
 
4.5%
80000 1
 
4.5%
380000 1
 
4.5%
15900 1
 
4.5%
5000 1
 
4.5%
Other values (9) 9
40.9%
ValueCountFrequency (%)
500 1
 
4.5%
1000 1
 
4.5%
3980 1
 
4.5%
4000 2
9.1%
5000 1
 
4.5%
6000 1
 
4.5%
6650 1
 
4.5%
8000 1
 
4.5%
8580 1
 
4.5%
10000 3
13.6%
ValueCountFrequency (%)
380000 1
 
4.5%
80000 1
 
4.5%
76335 1
 
4.5%
22800 1
 
4.5%
20000 1
 
4.5%
18300 1
 
4.5%
17800 1
 
4.5%
16800 1
 
4.5%
15900 1
 
4.5%
10000 3
13.6%

좌동(GS수퍼마켓)
Text

Distinct18
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-11T01:49:07.142875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.5454545
Min length3

Characters and Unicode

Total characters100
Distinct characters14
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

Unique16 ?
Unique (%)72.7%

Sample

1st row18800
2nd row21600
3rd row74670
4th row17800
5th row9980
ValueCountFrequency (%)
데이터없음 4
18.2%
15000 2
 
9.1%
21600 1
 
4.5%
1000 1
 
4.5%
22000 1
 
4.5%
4000 1
 
4.5%
4500 1
 
4.5%
5000 1
 
4.5%
17500 1
 
4.5%
18800 1
 
4.5%
Other values (8) 8
36.4%
2023-12-11T01:49:07.667152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 42
42.0%
1 8
 
8.0%
5 7
 
7.0%
8 6
 
6.0%
데 4
 
4.0%
이 4
 
4.0%
터 4
 
4.0%
없 4
 
4.0%
음 4
 
4.0%
7 4
 
4.0%
Other values (4) 13
 
13.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
80.0%
Other Letter 20
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 42
52.5%
1 8
 
10.0%
5 7
 
8.8%
8 6
 
7.5%
7 4
 
5.0%
6 4
 
5.0%
4 3
 
3.8%
9 3
 
3.8%
2 3
 
3.8%
Other Letter
ValueCountFrequency (%)
데 4
20.0%
이 4
20.0%
터 4
20.0%
없 4
20.0%
음 4
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80
80.0%
Hangul 20
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 42
52.5%
1 8
 
10.0%
5 7
 
8.8%
8 6
 
7.5%
7 4
 
5.0%
6 4
 
5.0%
4 3
 
3.8%
9 3
 
3.8%
2 3
 
3.8%
Hangul
ValueCountFrequency (%)
데 4
20.0%
이 4
20.0%
터 4
20.0%
없 4
20.0%
음 4
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
80.0%
Hangul 20
 
20.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 42
52.5%
1 8
 
10.0%
5 7
 
8.8%
8 6
 
7.5%
7 4
 
5.0%
6 4
 
5.0%
4 3
 
3.8%
9 3
 
3.8%
2 3
 
3.8%
Hangul
ValueCountFrequency (%)
데 4
20.0%
이 4
20.0%
터 4
20.0%
없 4
20.0%
음 4
20.0%

송정동
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28421.818
Minimum1200
Maximum350000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-11T01:49:07.878208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1200
5-th percentile1910
Q16000
median7750
Q315650
95-th percentile59475
Maximum350000
Range348800
Interquartile range (IQR)9650

Descriptive statistics

Standard deviation73292.264
Coefficient of variation (CV)2.5787324
Kurtosis20.029499
Mean28421.818
Median Absolute Deviation (MAD)3000
Skewness4.4064326
Sum625280
Variance5.371756 × 109
MonotonicityNot monotonic
2023-12-11T01:49:08.059365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
10000 2
 
9.1%
7500 2
 
9.1%
6000 2
 
9.1%
8000 2
 
9.1%
22000 1
 
4.5%
4000 1
 
4.5%
1200 1
 
4.5%
1800 1
 
4.5%
60000 1
 
4.5%
350000 1
 
4.5%
Other values (8) 8
36.4%
ValueCountFrequency (%)
1200 1
4.5%
1800 1
4.5%
4000 1
4.5%
4500 1
4.5%
5000 1
4.5%
6000 2
9.1%
6500 1
4.5%
6980 1
4.5%
7500 2
9.1%
8000 2
9.1%
ValueCountFrequency (%)
350000 1
4.5%
60000 1
4.5%
49500 1
4.5%
22000 1
4.5%
20000 1
4.5%
15900 1
4.5%
14900 1
4.5%
10000 2
9.1%
8000 2
9.1%
7500 2
9.1%

반여2동(골목시장)
Text

Distinct17
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-11T01:49:08.330363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.3636364
Min length3

Characters and Unicode

Total characters96
Distinct characters15
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

Unique13 ?
Unique (%)59.1%

Sample

1st row17000
2nd row10000
3rd row40000
4th row14450
5th row8800
ValueCountFrequency (%)
데이터없음 3
13.6%
6500 2
 
9.1%
4000 2
 
9.1%
40000 2
 
9.1%
3300 1
 
4.5%
17000 1
 
4.5%
500 1
 
4.5%
1000 1
 
4.5%
10900 1
 
4.5%
7000 1
 
4.5%
Other values (7) 7
31.8%
2023-12-11T01:49:08.860415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 52
54.2%
4 7
 
7.3%
5 5
 
5.2%
1 5
 
5.2%
데 3
 
3.1%
이 3
 
3.1%
터 3
 
3.1%
없 3
 
3.1%
음 3
 
3.1%
6 3
 
3.1%
Other values (5) 9
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
84.4%
Other Letter 15
 
15.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 52
64.2%
4 7
 
8.6%
5 5
 
6.2%
1 5
 
6.2%
6 3
 
3.7%
9 2
 
2.5%
8 2
 
2.5%
3 2
 
2.5%
7 2
 
2.5%
2 1
 
1.2%
Other Letter
ValueCountFrequency (%)
데 3
20.0%
이 3
20.0%
터 3
20.0%
없 3
20.0%
음 3
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 81
84.4%
Hangul 15
 
15.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 52
64.2%
4 7
 
8.6%
5 5
 
6.2%
1 5
 
6.2%
6 3
 
3.7%
9 2
 
2.5%
8 2
 
2.5%
3 2
 
2.5%
7 2
 
2.5%
2 1
 
1.2%
Hangul
ValueCountFrequency (%)
데 3
20.0%
이 3
20.0%
터 3
20.0%
없 3
20.0%
음 3
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81
84.4%
Hangul 15
 
15.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 52
64.2%
4 7
 
8.6%
5 5
 
6.2%
1 5
 
6.2%
6 3
 
3.7%
9 2
 
2.5%
8 2
 
2.5%
3 2
 
2.5%
7 2
 
2.5%
2 1
 
1.2%
Hangul
ValueCountFrequency (%)
데 3
20.0%
이 3
20.0%
터 3
20.0%
없 3
20.0%
음 3
20.0%

반송동(탑마트)
Text

Distinct16
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-11T01:49:09.132046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4.5
Mean length4.4090909
Min length3

Characters and Unicode

Total characters97
Distinct characters14
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

Unique12 ?
Unique (%)54.5%

Sample

1st row19000
2nd row9900
3rd row54900
4th row14400
5th row9000
ValueCountFrequency (%)
데이터없음 4
18.2%
19000 2
 
9.1%
7000 2
 
9.1%
4000 2
 
9.1%
9900 1
 
4.5%
54900 1
 
4.5%
14400 1
 
4.5%
9000 1
 
4.5%
8000 1
 
4.5%
5900 1
 
4.5%
Other values (6) 6
27.3%
2023-12-11T01:49:09.673527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 48
49.5%
9 7
 
7.2%
1 6
 
6.2%
4 6
 
6.2%
5 5
 
5.2%
데 4
 
4.1%
이 4
 
4.1%
터 4
 
4.1%
없 4
 
4.1%
음 4
 
4.1%
Other values (4) 5
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
79.4%
Other Letter 20
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 48
62.3%
9 7
 
9.1%
1 6
 
7.8%
4 6
 
7.8%
5 5
 
6.5%
7 2
 
2.6%
8 1
 
1.3%
6 1
 
1.3%
2 1
 
1.3%
Other Letter
ValueCountFrequency (%)
데 4
20.0%
이 4
20.0%
터 4
20.0%
없 4
20.0%
음 4
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 77
79.4%
Hangul 20
 
20.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 48
62.3%
9 7
 
9.1%
1 6
 
7.8%
4 6
 
7.8%
5 5
 
6.5%
7 2
 
2.6%
8 1
 
1.3%
6 1
 
1.3%
2 1
 
1.3%
Hangul
ValueCountFrequency (%)
데 4
20.0%
이 4
20.0%
터 4
20.0%
없 4
20.0%
음 4
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77
79.4%
Hangul 20
 
20.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 48
62.3%
9 7
 
9.1%
1 6
 
7.8%
4 6
 
7.8%
5 5
 
6.5%
7 2
 
2.6%
8 1
 
1.3%
6 1
 
1.3%
2 1
 
1.3%
Hangul
ValueCountFrequency (%)
데 4
20.0%
이 4
20.0%
터 4
20.0%
없 4
20.0%
음 4
20.0%

재송동(한마음시장)
Text

Distinct18
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-11T01:49:09.971295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4.5
Mean length4.4090909
Min length3

Characters and Unicode

Total characters97
Distinct characters15
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

Unique15 ?
Unique (%)68.2%

Sample

1st row16000
2nd row13000
3rd row47500
4th row13500
5th row7200
ValueCountFrequency (%)
4000 3
 
13.6%
데이터없음 2
 
9.1%
6000 2
 
9.1%
20000 1
 
4.5%
16000 1
 
4.5%
600 1
 
4.5%
900 1
 
4.5%
40000 1
 
4.5%
50000 1
 
4.5%
14900 1
 
4.5%
Other values (8) 8
36.4%
2023-12-11T01:49:10.480667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 55
56.7%
4 6
 
6.2%
6 5
 
5.2%
1 5
 
5.2%
5 4
 
4.1%
3 3
 
3.1%
7 3
 
3.1%
데 2
 
2.1%
이 2
 
2.1%
터 2
 
2.1%
Other values (5) 10
 
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 87
89.7%
Other Letter 10
 
10.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 55
63.2%
4 6
 
6.9%
6 5
 
5.7%
1 5
 
5.7%
5 4
 
4.6%
3 3
 
3.4%
7 3
 
3.4%
2 2
 
2.3%
8 2
 
2.3%
9 2
 
2.3%
Other Letter
ValueCountFrequency (%)
데 2
20.0%
이 2
20.0%
터 2
20.0%
없 2
20.0%
음 2
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 87
89.7%
Hangul 10
 
10.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 55
63.2%
4 6
 
6.9%
6 5
 
5.7%
1 5
 
5.7%
5 4
 
4.6%
3 3
 
3.4%
7 3
 
3.4%
2 2
 
2.3%
8 2
 
2.3%
9 2
 
2.3%
Hangul
ValueCountFrequency (%)
데 2
20.0%
이 2
20.0%
터 2
20.0%
없 2
20.0%
음 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 87
89.7%
Hangul 10
 
10.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 55
63.2%
4 6
 
6.9%
6 5
 
5.7%
1 5
 
5.7%
5 4
 
4.6%
3 3
 
3.4%
7 3
 
3.4%
2 2
 
2.3%
8 2
 
2.3%
9 2
 
2.3%
Hangul
ValueCountFrequency (%)
데 2
20.0%
이 2
20.0%
터 2
20.0%
없 2
20.0%
음 2
20.0%

Interactions

2023-12-11T01:49:03.164227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:02.043986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:02.613369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:03.327398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:02.201874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:02.787374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:03.539362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:02.387522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:02.994237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:49:10.650467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품 목규 격우동(센텀홈플러스)중동(이마트 해운대점)좌동(GS수퍼마켓)송정동반여2동(골목시장)반송동(탑마트)재송동(한마음시장)
품 목1.0001.0001.0001.0001.0001.0001.0001.0001.000
규 격1.0001.0001.0001.0000.9671.0000.9610.9570.967
우동(센텀홈플러스)1.0001.0001.0001.0000.0001.0000.0000.0001.000
중동(이마트 해운대점)1.0001.0001.0001.0000.0001.0000.0000.0001.000
좌동(GS수퍼마켓)1.0000.9670.0000.0001.0000.0000.9620.9780.927
송정동1.0001.0001.0001.0000.0001.0000.0000.0001.000
반여2동(골목시장)1.0000.9610.0000.0000.9620.0001.0000.9670.944
반송동(탑마트)1.0000.9570.0000.0000.9780.0000.9671.0000.978
재송동(한마음시장)1.0000.9671.0001.0000.9271.0000.9440.9781.000
2023-12-11T01:49:10.857113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우동(센텀홈플러스)중동(이마트 해운대점)송정동
우동(센텀홈플러스)1.0000.9660.883
중동(이마트 해운대점)0.9661.0000.912
송정동0.8830.9121.000

Missing values

2023-12-11T01:49:03.785801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:49:04.030689image/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

품 목규 격우동(센텀홈플러스)중동(이마트 해운대점)좌동(GS수퍼마켓)송정동반여2동(골목시장)반송동(탑마트)재송동(한마음시장)
0수 박7kg 1통20990228001880022000170001900016000
1참 외상품 10개229001780021600800010000990013000
2소고기(국산)등심 상등육 500g58750763357467049500400005490047500
3돼지고기(국산)삼겹살 500g12950168001780014900144501440013500
4달걀대란 30개(한판)7990665099806980880090007200
5닭고기육계 1㎏6290858089607500650080006700
6고등어30㎝ 1마리(냉동)3790398058004500500059005000
7자장면1인분(보통)5500600060006000600070006000
8냉 면물냉면, 1인분(보통)1000010000100007500700070006000
9삼겹살외식, 200g 정도1700018300150002000090001500013800
품 목규 격우동(센텀홈플러스)중동(이마트 해운대점)좌동(GS수퍼마켓)송정동반여2동(골목시장)반송동(탑마트)재송동(한마음시장)
12소 주외식, 시원소주 360㎖ 1병5000400045004000400040004000
13생맥주500cc 한잔5000500040006000330050004000
14피 자기본형(야채, 고기)19900159002200015900109001900014900
15호 텔평일, 스탠다드, 부가세226000380000데이터없음350000데이터없음데이터없음50000
16모 텔평일, 1박7000080000데이터없음6000040000데이터없음40000
17월드콘1개90010001000180010001000900
18스크류바1개5005005001200500500600
19파라솔1일 대여료1000010000데이터없음10000데이터없음데이터없음데이터없음
20튜 브1일 대여료1000010000데이터없음10000데이터없음데이터없음데이터없음
21주차료1일 기준150008000150008000420024008000