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_20220809
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 16:48:50.774413
Analysis finished2023-12-10 16:48:52.547538
Duration1.77 second
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
2023-12-11T01:48:52.710711image/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%
2023-12-11T01:48:53.152140image/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
2023-12-11T01:48:53.388653image/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%
2023-12-11T01:48:53.847193image/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%
Mean24561.364
Minimum500
Maximum226000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-11T01:48:54.029783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile1029.5
Q15125
median8000
Q319975
95-th percentile59452.5
Maximum226000
Range225500
Interquartile range (IQR)14850

Descriptive statistics

Standard deviation47459.313
Coefficient of variation (CV)1.9322752
Kurtosis17.145629
Mean24561.364
Median Absolute Deviation (MAD)6225
Skewness3.9899437
Sum540350
Variance2.2523864 × 109
MonotonicityNot monotonic
2023-12-11T01:48:54.262705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
8000 3
 
13.6%
5000 3
 
13.6%
27900 1
 
4.5%
20000 1
 
4.5%
15000 1
 
4.5%
500 1
 
4.5%
900 1
 
4.5%
50000 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%
3490 1
 
4.5%
5000 3
13.6%
5500 1
 
4.5%
7190 1
 
4.5%
7990 1
 
4.5%
8000 3
13.6%
13450 1
 
4.5%
15000 1
 
4.5%
ValueCountFrequency (%)
226000 1
4.5%
59950 1
4.5%
50000 1
4.5%
27900 1
4.5%
26580 1
4.5%
20000 1
4.5%
19900 1
4.5%
17000 1
4.5%
15000 1
4.5%
13450 1
4.5%

중동(이마트 해운대점)
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31549.545
Minimum500
Maximum380000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-11T01:48:54.472655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile1149
Q14985
median10000
Q316650
95-th percentile78962.5
Maximum380000
Range379500
Interquartile range (IQR)11665

Descriptive statistics

Standard deviation80074.308
Coefficient of variation (CV)2.5380495
Kurtosis19.275243
Mean31549.545
Median Absolute Deviation (MAD)5950
Skewness4.304315
Sum694090
Variance6.4118947 × 109
MonotonicityNot monotonic
2023-12-11T01:48:54.760017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
10000 3
 
13.6%
4000 2
 
9.1%
16900 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%
4980 1
 
4.5%
5000 1
 
4.5%
6000 1
 
4.5%
7980 1
 
4.5%
8000 1
 
4.5%
10000 3
13.6%
ValueCountFrequency (%)
380000 1
 
4.5%
80000 1
 
4.5%
59250 1
 
4.5%
20000 1
 
4.5%
18300 1
 
4.5%
16900 1
 
4.5%
15900 1
 
4.5%
14900 1
 
4.5%
13400 1
 
4.5%
10000 3
13.6%

좌동(GS수퍼마켓)
Text

Distinct19
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-11T01:48:55.059985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.1363636
Min length2

Characters and Unicode

Total characters91
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
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 row19800
2nd row39000
3rd row74670
4th row17800
5th row8980
ValueCountFrequency (%)
없음 4
18.2%
19800 1
 
4.5%
17000 1
 
4.5%
500 1
 
4.5%
1,000 1
 
4.5%
22000 1
 
4.5%
4000 1
 
4.5%
4500 1
 
4.5%
5000 1
 
4.5%
15000 1
 
4.5%
Other values (9) 9
40.9%
2023-12-11T01:48:55.644161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 45
49.5%
1 8
 
8.8%
8 6
 
6.6%
5 6
 
6.6%
없 4
 
4.4%
음 4
 
4.4%
7 4
 
4.4%
4 4
 
4.4%
9 3
 
3.3%
6 2
 
2.2%
Other values (3) 5
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
89.0%
Other Letter 8
 
8.8%
Other Punctuation 2
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45
55.6%
1 8
 
9.9%
8 6
 
7.4%
5 6
 
7.4%
7 4
 
4.9%
4 4
 
4.9%
9 3
 
3.7%
6 2
 
2.5%
2 2
 
2.5%
3 1
 
1.2%
Other Letter
ValueCountFrequency (%)
없 4
50.0%
음 4
50.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 83
91.2%
Hangul 8
 
8.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 45
54.2%
1 8
 
9.6%
8 6
 
7.2%
5 6
 
7.2%
7 4
 
4.8%
4 4
 
4.8%
9 3
 
3.6%
6 2
 
2.4%
2 2
 
2.4%
, 2
 
2.4%
Hangul
ValueCountFrequency (%)
없 4
50.0%
음 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
91.2%
Hangul 8
 
8.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 45
54.2%
1 8
 
9.6%
8 6
 
7.2%
5 6
 
7.2%
7 4
 
4.8%
4 4
 
4.8%
9 3
 
3.6%
6 2
 
2.4%
2 2
 
2.4%
, 2
 
2.4%
Hangul
ValueCountFrequency (%)
없 4
50.0%
음 4
50.0%

송정동
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18299.091
Minimum1200
Maximum130000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-11T01:48:55.905758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1200
5-th percentile1910
Q15985
median7750
Q314975
95-th percentile59475
Maximum130000
Range128800
Interquartile range (IQR)8990

Descriptive statistics

Standard deviation28872.67
Coefficient of variation (CV)1.5778199
Kurtosis11.123049
Mean18299.091
Median Absolute Deviation (MAD)3000
Skewness3.1911743
Sum402580
Variance8.3363107 × 108
MonotonicityNot monotonic
2023-12-11T01:48:56.275171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
10000 3
 
13.6%
6000 2
 
9.1%
19800 1
 
4.5%
5000 1
 
4.5%
1200 1
 
4.5%
1800 1
 
4.5%
60000 1
 
4.5%
130000 1
 
4.5%
15000 1
 
4.5%
4000 1
 
4.5%
Other values (9) 9
40.9%
ValueCountFrequency (%)
1200 1
4.5%
1800 1
4.5%
4000 1
4.5%
4500 1
4.5%
5000 1
4.5%
5980 1
4.5%
6000 2
9.1%
6500 1
4.5%
6900 1
4.5%
7500 1
4.5%
ValueCountFrequency (%)
130000 1
 
4.5%
60000 1
 
4.5%
49500 1
 
4.5%
20000 1
 
4.5%
19800 1
 
4.5%
15000 1
 
4.5%
14900 1
 
4.5%
10000 3
13.6%
8000 1
 
4.5%
7500 1
 
4.5%

반여2동(골목시장)
Text

Distinct17
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-11T01:48:56.627272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9545455
Min length2

Characters and Unicode

Total characters87
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

Unique13 ?
Unique (%)59.1%

Sample

1st row19900
2nd row10000
3rd row40000
4th row14450
5th row8800
ValueCountFrequency (%)
없음 3
13.6%
6500 2
 
9.1%
4000 2
 
9.1%
40000 2
 
9.1%
3300 1
 
4.5%
19900 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%
2023-12-11T01:48:57.321117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 51
58.6%
4 7
 
8.0%
5 5
 
5.7%
1 5
 
5.7%
9 4
 
4.6%
없 3
 
3.4%
음 3
 
3.4%
6 3
 
3.4%
8 2
 
2.3%
3 2
 
2.3%
Other values (2) 2
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
93.1%
Other Letter 6
 
6.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 51
63.0%
4 7
 
8.6%
5 5
 
6.2%
1 5
 
6.2%
9 4
 
4.9%
6 3
 
3.7%
8 2
 
2.5%
3 2
 
2.5%
7 1
 
1.2%
2 1
 
1.2%
Other Letter
ValueCountFrequency (%)
없 3
50.0%
음 3
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 81
93.1%
Hangul 6
 
6.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 51
63.0%
4 7
 
8.6%
5 5
 
6.2%
1 5
 
6.2%
9 4
 
4.9%
6 3
 
3.7%
8 2
 
2.5%
3 2
 
2.5%
7 1
 
1.2%
2 1
 
1.2%
Hangul
ValueCountFrequency (%)
없 3
50.0%
음 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81
93.1%
Hangul 6
 
6.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 51
63.0%
4 7
 
8.6%
5 5
 
6.2%
1 5
 
6.2%
9 4
 
4.9%
6 3
 
3.7%
8 2
 
2.5%
3 2
 
2.5%
7 1
 
1.2%
2 1
 
1.2%
Hangul
ValueCountFrequency (%)
없 3
50.0%
음 3
50.0%

반송동(탑마트)
Text

Distinct16
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-11T01:48:57.652905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9090909
Min length2

Characters and Unicode

Total characters86
Distinct characters11
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 row15000
2nd row10000
3rd row56250
4th row12500
5th row9000
ValueCountFrequency (%)
없음 4
18.2%
15000 2
 
9.1%
7000 2
 
9.1%
4000 2
 
9.1%
10000 1
 
4.5%
56250 1
 
4.5%
12500 1
 
4.5%
9000 1
 
4.5%
8000 1
 
4.5%
6000 1
 
4.5%
Other values (6) 6
27.3%
2023-12-11T01:48:58.499716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 49
57.0%
1 7
 
8.1%
5 7
 
8.1%
없 4
 
4.7%
음 4
 
4.7%
4 3
 
3.5%
6 3
 
3.5%
2 3
 
3.5%
9 3
 
3.5%
7 2
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
90.7%
Other Letter 8
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 49
62.8%
1 7
 
9.0%
5 7
 
9.0%
4 3
 
3.8%
6 3
 
3.8%
2 3
 
3.8%
9 3
 
3.8%
7 2
 
2.6%
8 1
 
1.3%
Other Letter
ValueCountFrequency (%)
없 4
50.0%
음 4
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78
90.7%
Hangul 8
 
9.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 49
62.8%
1 7
 
9.0%
5 7
 
9.0%
4 3
 
3.8%
6 3
 
3.8%
2 3
 
3.8%
9 3
 
3.8%
7 2
 
2.6%
8 1
 
1.3%
Hangul
ValueCountFrequency (%)
없 4
50.0%
음 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78
90.7%
Hangul 8
 
9.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 49
62.8%
1 7
 
9.0%
5 7
 
9.0%
4 3
 
3.8%
6 3
 
3.8%
2 3
 
3.8%
9 3
 
3.8%
7 2
 
2.6%
8 1
 
1.3%
Hangul
ValueCountFrequency (%)
없 4
50.0%
음 4
50.0%

재송동(한마음시장)
Text

Distinct18
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-11T01:48:58.874342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1818182
Min length2

Characters and Unicode

Total characters92
Distinct characters13
Distinct categories3 ?
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 row19000
2nd row15000
3rd row37500
4th row10500
5th row6200
ValueCountFrequency (%)
4000 3
 
13.6%
없음 2
 
9.1%
6000 2
 
9.1%
20000 1
 
4.5%
19000 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%
2023-12-11T01:48:59.449810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 57
62.0%
4 5
 
5.4%
1 5
 
5.4%
5 5
 
5.4%
6 4
 
4.3%
9 3
 
3.3%
없 2
 
2.2%
음 2
 
2.2%
3 2
 
2.2%
7 2
 
2.2%
Other values (3) 5
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 87
94.6%
Other Letter 4
 
4.3%
Other Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 57
65.5%
4 5
 
5.7%
1 5
 
5.7%
5 5
 
5.7%
6 4
 
4.6%
9 3
 
3.4%
3 2
 
2.3%
7 2
 
2.3%
2 2
 
2.3%
8 2
 
2.3%
Other Letter
ValueCountFrequency (%)
없 2
50.0%
음 2
50.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88
95.7%
Hangul 4
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 57
64.8%
4 5
 
5.7%
1 5
 
5.7%
5 5
 
5.7%
6 4
 
4.5%
9 3
 
3.4%
3 2
 
2.3%
7 2
 
2.3%
2 2
 
2.3%
8 2
 
2.3%
Hangul
ValueCountFrequency (%)
없 2
50.0%
음 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
95.7%
Hangul 4
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 57
64.8%
4 5
 
5.7%
1 5
 
5.7%
5 5
 
5.7%
6 4
 
4.5%
9 3
 
3.4%
3 2
 
2.3%
7 2
 
2.3%
2 2
 
2.3%
8 2
 
2.3%
Hangul
ValueCountFrequency (%)
없 2
50.0%
음 2
50.0%

Interactions

2023-12-11T01:48:51.896224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:51.163745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:51.499062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:52.008585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:51.263505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:51.656784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:52.156975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:51.377126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:51.782812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:48:59.672368image/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 격1.0001.0001.0001.0000.9721.0000.9610.9570.967
우동(센텀홈플러스)1.0001.0001.0000.9740.0000.8170.7180.0001.000
중동(이마트 해운대점)1.0001.0000.9741.0000.0001.0000.0000.0001.000
좌동(GS수퍼마켓)1.0000.9720.0000.0001.0000.0000.9861.0000.924
송정동1.0001.0000.8171.0000.0001.0000.0000.0001.000
반여2동(골목시장)1.0000.9610.7180.0000.9860.0001.0000.9670.944
반송동(탑마트)1.0000.9570.0000.0001.0000.0000.9671.0000.978
재송동(한마음시장)1.0000.9671.0001.0000.9241.0000.9440.9781.000
2023-12-11T01:48:59.982811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우동(센텀홈플러스)중동(이마트 해운대점)송정동
우동(센텀홈플러스)1.0000.9440.903
중동(이마트 해운대점)0.9441.0000.911
송정동0.9030.9111.000

Missing values

2023-12-11T01:48:52.309082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:48:52.469049image/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 1통27900169001980019800199001500019000
1참 외상품 10개2658014900390008000100001000015000
2소고기(국산)등심 상등육 500g59950592507467049500400005625037500
3돼지고기(국산)삼겹살 500g13450134001780014900144501250010500
4달걀대란 30개(한판)7990398089805980880090006200
5닭고기육계 1㎏71907980104806900650080007000
6고등어30㎝ 1마리(냉동)3490498058004500500060005000
7자장면1인분(보통)5500600060006000600070006000
8냉 면물냉면, 1인분(보통)800010000100007500700070006000
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)19900159002200015000109001990014900
15호 텔평일, 스탠다드, 부가세226000380000없음130000없음없음50000
16모 텔평일, 1박5000080000없음6000040000없음40000
17월드콘1개90010001,000180010001000900
18스크류바1개5005005001200500500600
19파라솔1일 대여료800010000없음10000없음없음없음
20튜 브1일 대여료800010000없음10000없음없음없음
21주차료1일 기준15000800015,00010000420024008,000