Overview

Dataset statistics

Number of variables11
Number of observations32
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory95.0 B

Variable types

Categorical3
Text5
Numeric3

Dataset

Description경기도 남양주시의 착한가격업소 현황 데이터로 업종구분, 상호명, 지역, 소재지주소, 위도 및 경도, 전화번호, 품목 및 가격 정보를 제공합니다.
Author경기도 남양주시
URLhttps://www.data.go.kr/data/15126789/fileData.do

Alerts

데이터기준일 has constant value ""Constant
위도 is highly overall correlated with 지역High correlation
경도 is highly overall correlated with 지역High correlation
지역 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
상호명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 10:42:26.494183
Analysis finished2024-03-14 10:42:29.692414
Duration3.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종구분
Categorical

Distinct5
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size384.0 B
한식
20 
이·미용
7 
세탁소
3 
중식
 
1
커피
 
1

Length

Max length4
Median length2
Mean length2.53125
Min length2

Unique

Unique2 ?
Unique (%)6.2%

Sample

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

Common Values

ValueCountFrequency (%)
한식 20
62.5%
이·미용 7
 
21.9%
세탁소 3
 
9.4%
중식 1
 
3.1%
커피 1
 
3.1%

Length

2024-03-14T19:42:29.821506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:42:30.079045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 20
62.5%
이·미용 7
 
21.9%
세탁소 3
 
9.4%
중식 1
 
3.1%
커피 1
 
3.1%

상호명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size384.0 B
2024-03-14T19:42:30.880527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.625
Min length2

Characters and Unicode

Total characters180
Distinct characters107
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row강남식당
2nd row경성멧돼지
3rd row고향손칼국수
4th row명성막고기
5th row명성식당
ValueCountFrequency (%)
강남식당 1
 
2.9%
짱미용실 1
 
2.9%
최가네칼국수 1
 
2.9%
현리만두 1
 
2.9%
홍두깨손칼국수 1
 
2.9%
홍원 1
 
2.9%
더로스터스커피랩 1
 
2.9%
양미용실 1
 
2.9%
티와이헤어 1
 
2.9%
경성멧돼지 1
 
2.9%
Other values (24) 24
70.6%
2024-03-14T19:42:32.281912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 9
 
5.0%
국 9
 
5.0%
칼 8
 
4.4%
골 5
 
2.8%
헤 5
 
2.8%
어 5
 
2.8%
사 4
 
2.2%
명 3
 
1.7%
식 3
 
1.7%
두 3
 
1.7%
Other values (97) 126
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 172
95.6%
Decimal Number 3
 
1.7%
Space Separator 2
 
1.1%
Open Punctuation 1
 
0.6%
Close Punctuation 1
 
0.6%
Other Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 9
 
5.2%
국 9
 
5.2%
칼 8
 
4.7%
골 5
 
2.9%
헤 5
 
2.9%
어 5
 
2.9%
사 4
 
2.3%
명 3
 
1.7%
식 3
 
1.7%
두 3
 
1.7%
Other values (90) 118
68.6%
Decimal Number
ValueCountFrequency (%)
5 1
33.3%
7 1
33.3%
3 1
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 172
95.6%
Common 8
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 9
 
5.2%
국 9
 
5.2%
칼 8
 
4.7%
골 5
 
2.9%
헤 5
 
2.9%
어 5
 
2.9%
사 4
 
2.3%
명 3
 
1.7%
식 3
 
1.7%
두 3
 
1.7%
Other values (90) 118
68.6%
Common
ValueCountFrequency (%)
2
25.0%
5 1
12.5%
( 1
12.5%
) 1
12.5%
7 1
12.5%
3 1
12.5%
& 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 172
95.6%
ASCII 8
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 9
 
5.2%
국 9
 
5.2%
칼 8
 
4.7%
골 5
 
2.9%
헤 5
 
2.9%
어 5
 
2.9%
사 4
 
2.3%
명 3
 
1.7%
식 3
 
1.7%
두 3
 
1.7%
Other values (90) 118
68.6%
ASCII
ValueCountFrequency (%)
2
25.0%
5 1
12.5%
( 1
12.5%
) 1
12.5%
7 1
12.5%
3 1
12.5%
& 1
12.5%

지역
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)40.6%
Missing0
Missing (%)0.0%
Memory size384.0 B
금곡동
9 
진접읍
5 
다산동
4 
오남읍
3 
수동면
2 
Other values (8)
9 

Length

Max length4
Median length3
Mean length3.0625
Min length3

Unique

Unique7 ?
Unique (%)21.9%

Sample

1st row금곡동
2nd row금곡동
3rd row와부읍
4th row금곡동
5th row금곡동

Common Values

ValueCountFrequency (%)
금곡동 9
28.1%
진접읍 5
15.6%
다산동 4
12.5%
오남읍 3
 
9.4%
수동면 2
 
6.2%
퇴계원읍 2
 
6.2%
와부읍 1
 
3.1%
화도읍 1
 
3.1%
호평동 1
 
3.1%
진건읍 1
 
3.1%
Other values (3) 3
 
9.4%

Length

2024-03-14T19:42:32.704555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
금곡동 9
28.1%
진접읍 5
15.6%
다산동 4
12.5%
오남읍 3
 
9.4%
수동면 2
 
6.2%
퇴계원읍 2
 
6.2%
와부읍 1
 
3.1%
화도읍 1
 
3.1%
호평동 1
 
3.1%
진건읍 1
 
3.1%
Other values (3) 3
 
9.4%

소재지주소(도로명)
Text

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size384.0 B
2024-03-14T19:42:33.518398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length21.6875
Min length15

Characters and Unicode

Total characters694
Distinct characters73
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

Unique30 ?
Unique (%)93.8%

Sample

1st row경기도 남양주시 홍유릉로248번길 64-37
2nd row경기도 남양주시 홍유릉로 327
3rd row경기도 남양주시 와부읍 수레로 72
4th row경기도 남양주시 홍유릉로248번길 39
5th row경기도 남양주시 홍유릉로248번길 9
ValueCountFrequency (%)
경기도 32
21.8%
남양주시 32
21.8%
홍유릉로248번길 5
 
3.4%
진접읍 5
 
3.4%
39 3
 
2.0%
오남읍 3
 
2.0%
1 2
 
1.4%
48 2
 
1.4%
다산지금로16번길 2
 
1.4%
해밀예당3로 2
 
1.4%
Other values (54) 59
40.1%
2024-03-14T19:42:34.876693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
115
 
16.6%
남 37
 
5.3%
경 35
 
5.0%
도 34
 
4.9%
양 32
 
4.6%
주 32
 
4.6%
시 32
 
4.6%
기 32
 
4.6%
로 32
 
4.6%
1 25
 
3.6%
Other values (63) 288
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 431
62.1%
Decimal Number 136
 
19.6%
Space Separator 115
 
16.6%
Dash Punctuation 9
 
1.3%
Other Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 37
 
8.6%
경 35
 
8.1%
도 34
 
7.9%
양 32
 
7.4%
주 32
 
7.4%
시 32
 
7.4%
기 32
 
7.4%
로 32
 
7.4%
번 18
 
4.2%
길 18
 
4.2%
Other values (50) 129
29.9%
Decimal Number
ValueCountFrequency (%)
1 25
18.4%
4 19
14.0%
2 16
11.8%
3 14
10.3%
8 14
10.3%
6 12
8.8%
7 12
8.8%
9 9
 
6.6%
5 9
 
6.6%
0 6
 
4.4%
Space Separator
ValueCountFrequency (%)
115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 431
62.1%
Common 263
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 37
 
8.6%
경 35
 
8.1%
도 34
 
7.9%
양 32
 
7.4%
주 32
 
7.4%
시 32
 
7.4%
기 32
 
7.4%
로 32
 
7.4%
번 18
 
4.2%
길 18
 
4.2%
Other values (50) 129
29.9%
Common
ValueCountFrequency (%)
115
43.7%
1 25
 
9.5%
4 19
 
7.2%
2 16
 
6.1%
3 14
 
5.3%
8 14
 
5.3%
6 12
 
4.6%
7 12
 
4.6%
9 9
 
3.4%
- 9
 
3.4%
Other values (3) 18
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 431
62.1%
ASCII 263
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
115
43.7%
1 25
 
9.5%
4 19
 
7.2%
2 16
 
6.1%
3 14
 
5.3%
8 14
 
5.3%
6 12
 
4.6%
7 12
 
4.6%
9 9
 
3.4%
- 9
 
3.4%
Other values (3) 18
 
6.8%
Hangul
ValueCountFrequency (%)
남 37
 
8.6%
경 35
 
8.1%
도 34
 
7.9%
양 32
 
7.4%
주 32
 
7.4%
시 32
 
7.4%
기 32
 
7.4%
로 32
 
7.4%
번 18
 
4.2%
길 18
 
4.2%
Other values (50) 129
29.9%

소재지주소(지번)
Text

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size384.0 B
2024-03-14T19:42:35.665842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length35
Mean length21.375
Min length16

Characters and Unicode

Total characters684
Distinct characters66
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

Unique29 ?
Unique (%)90.6%

Sample

1st row경기도 남양주시 금곡동 454-21
2nd row경기도 남양주시 금곡동 680-25
3rd row경기도 남양주시 와부읍 덕소리 187-3
4th row경기도 남양주시 금곡동 651-1
5th row경기도 남양주시 금곡동 659-1
ValueCountFrequency (%)
경기도 32
21.3%
남양주시 32
21.3%
금곡동 9
 
6.0%
진접읍 5
 
3.3%
다산동 4
 
2.7%
651-1 3
 
2.0%
장현리 3
 
2.0%
오남읍 3
 
2.0%
수동면 2
 
1.3%
금곡리 2
 
1.3%
Other values (52) 55
36.7%
2024-03-14T19:42:36.970630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
118
17.3%
남 36
 
5.3%
양 34
 
5.0%
도 33
 
4.8%
주 33
 
4.8%
경 32
 
4.7%
시 32
 
4.7%
기 32
 
4.7%
1 31
 
4.5%
- 29
 
4.2%
Other values (56) 274
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 389
56.9%
Decimal Number 146
 
21.3%
Space Separator 118
 
17.3%
Dash Punctuation 29
 
4.2%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 36
 
9.3%
양 34
 
8.7%
도 33
 
8.5%
주 33
 
8.5%
경 32
 
8.2%
시 32
 
8.2%
기 32
 
8.2%
동 19
 
4.9%
리 16
 
4.1%
읍 13
 
3.3%
Other values (43) 109
28.0%
Decimal Number
ValueCountFrequency (%)
1 31
21.2%
5 19
13.0%
2 19
13.0%
6 16
11.0%
3 16
11.0%
0 13
8.9%
4 10
 
6.8%
9 9
 
6.2%
8 7
 
4.8%
7 6
 
4.1%
Space Separator
ValueCountFrequency (%)
118
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 389
56.9%
Common 295
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 36
 
9.3%
양 34
 
8.7%
도 33
 
8.5%
주 33
 
8.5%
경 32
 
8.2%
시 32
 
8.2%
기 32
 
8.2%
동 19
 
4.9%
리 16
 
4.1%
읍 13
 
3.3%
Other values (43) 109
28.0%
Common
ValueCountFrequency (%)
118
40.0%
1 31
 
10.5%
- 29
 
9.8%
5 19
 
6.4%
2 19
 
6.4%
6 16
 
5.4%
3 16
 
5.4%
0 13
 
4.4%
4 10
 
3.4%
9 9
 
3.1%
Other values (3) 15
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 389
56.9%
ASCII 295
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
118
40.0%
1 31
 
10.5%
- 29
 
9.8%
5 19
 
6.4%
2 19
 
6.4%
6 16
 
5.4%
3 16
 
5.4%
0 13
 
4.4%
4 10
 
3.4%
9 9
 
3.1%
Other values (3) 15
 
5.1%
Hangul
ValueCountFrequency (%)
남 36
 
9.3%
양 34
 
8.7%
도 33
 
8.5%
주 33
 
8.5%
경 32
 
8.2%
시 32
 
8.2%
기 32
 
8.2%
동 19
 
4.9%
리 16
 
4.1%
읍 13
 
3.3%
Other values (43) 109
28.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.658545
Minimum37.590185
Maximum37.73144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size416.0 B
2024-03-14T19:42:37.347129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.590185
5-th percentile37.607538
Q137.627253
median37.645764
Q337.703831
95-th percentile37.72
Maximum37.73144
Range0.14125483
Interquartile range (IQR)0.076577655

Descriptive statistics

Standard deviation0.041931097
Coefficient of variation (CV)0.001113455
Kurtosis-1.2740246
Mean37.658545
Median Absolute Deviation (MAD)0.028233775
Skewness0.36262932
Sum1205.0734
Variance0.0017582169
MonotonicityNot monotonic
2024-03-14T19:42:37.725505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
37.62725328 3
 
9.4%
37.629367601 1
 
3.1%
37.65793977 1
 
3.1%
37.64116604 1
 
3.1%
37.70968353 1
 
3.1%
37.60717513 1
 
3.1%
37.636180204 1
 
3.1%
37.70253826 1
 
3.1%
37.71884766 1
 
3.1%
37.72002639 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
37.59018488 1
 
3.1%
37.60717513 1
 
3.1%
37.60783549 1
 
3.1%
37.609149896 1
 
3.1%
37.60980941 1
 
3.1%
37.62525145 1
 
3.1%
37.62725328 3
9.4%
37.629367601 1
 
3.1%
37.63112701 1
 
3.1%
37.63412811 1
 
3.1%
ValueCountFrequency (%)
37.73143971 1
3.1%
37.72002639 1
3.1%
37.71997887 1
3.1%
37.71884766 1
3.1%
37.71672219 1
3.1%
37.70968353 1
3.1%
37.70936678 1
3.1%
37.70770896 1
3.1%
37.70253826 1
3.1%
37.69726573 1
3.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.20022
Minimum127.1095
Maximum127.32668
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size416.0 B
2024-03-14T19:42:38.009161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.1095
5-th percentile127.13098
Q1127.17534
median127.2021
Q3127.21129
95-th percentile127.31398
Maximum127.32668
Range0.2171868
Interquartile range (IQR)0.03594216

Descriptive statistics

Standard deviation0.049465158
Coefficient of variation (CV)0.00038887635
Kurtosis1.7402322
Mean127.20022
Median Absolute Deviation (MAD)0.01712325
Skewness0.91604476
Sum4070.4071
Variance0.0024468019
MonotonicityNot monotonic
2024-03-14T19:42:38.413671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
127.2024116 3
 
9.4%
127.2039433 1
 
3.1%
127.1768558 1
 
3.1%
127.2332379 1
 
3.1%
127.1147568 1
 
3.1%
127.1708059 1
 
3.1%
127.21106998 1
 
3.1%
127.3266841 1
 
3.1%
127.1974009 1
 
3.1%
127.19702803 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
127.1094973 1
3.1%
127.1147568 1
3.1%
127.1442503 1
3.1%
127.1450304 1
3.1%
127.1521148 1
3.1%
127.1523326 1
3.1%
127.1706589 1
3.1%
127.1708059 1
3.1%
127.1768558 1
3.1%
127.1795808 1
3.1%
ValueCountFrequency (%)
127.3266841 1
3.1%
127.3238668 1
3.1%
127.3058951 1
3.1%
127.2458646 1
3.1%
127.2332379 1
3.1%
127.2180197 1
3.1%
127.2120322 1
3.1%
127.2119319999 1
3.1%
127.21106998 1
3.1%
127.2100752 1
3.1%

전화번호
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size384.0 B
2024-03-14T19:42:39.218855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.25
Min length12

Characters and Unicode

Total characters392
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row031-559-5535
2nd row031-592-9733
3rd row031-577-3237
4th row031-595-9115
5th row0507-1358-6776
ValueCountFrequency (%)
031-559-5535 1
 
3.1%
031-592-9733 1
 
3.1%
0507-1446-5101 1
 
3.1%
031-551-1477 1
 
3.1%
031-511-8950 1
 
3.1%
031-593-3437 1
 
3.1%
031-572-3060 1
 
3.1%
031-528-6054 1
 
3.1%
031-592-5342 1
 
3.1%
031-573-1023 1
 
3.1%
Other values (22) 22
68.8%
2024-03-14T19:42:40.490051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 64
16.3%
5 60
15.3%
3 57
14.5%
1 55
14.0%
0 48
12.2%
7 29
7.4%
9 22
 
5.6%
2 22
 
5.6%
6 14
 
3.6%
4 11
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 328
83.7%
Dash Punctuation 64
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 60
18.3%
3 57
17.4%
1 55
16.8%
0 48
14.6%
7 29
8.8%
9 22
 
6.7%
2 22
 
6.7%
6 14
 
4.3%
4 11
 
3.4%
8 10
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 392
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 64
16.3%
5 60
15.3%
3 57
14.5%
1 55
14.0%
0 48
12.2%
7 29
7.4%
9 22
 
5.6%
2 22
 
5.6%
6 14
 
3.6%
4 11
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 392
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 64
16.3%
5 60
15.3%
3 57
14.5%
1 55
14.0%
0 48
12.2%
7 29
7.4%
9 22
 
5.6%
2 22
 
5.6%
6 14
 
3.6%
4 11
 
2.8%

품목
Text

Distinct19
Distinct (%)59.4%
Missing0
Missing (%)0.0%
Memory size384.0 B
2024-03-14T19:42:41.099531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length3.65625
Min length2

Characters and Unicode

Total characters117
Distinct characters58
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 (%)46.9%

Sample

1st row삼겹살
2nd row삼겹살 600g
3rd row칼국수
4th row삼겹살
5th row닭볶음탕
ValueCountFrequency (%)
커트 6
17.1%
칼국수 6
17.1%
삼겹살 4
 
11.4%
세탁 3
 
8.6%
600g 1
 
2.9%
보쌈(소 1
 
2.9%
500g 1
 
2.9%
만둣국 1
 
2.9%
콩나물국밥 1
 
2.9%
김치찌개 1
 
2.9%
Other values (10) 10
28.6%
2024-03-14T19:42:41.921230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 9
 
7.7%
칼 7
 
6.0%
수 7
 
6.0%
커 6
 
5.1%
트 6
 
5.1%
삼 5
 
4.3%
겹 5
 
4.3%
살 5
 
4.3%
0 5
 
4.3%
세 3
 
2.6%
Other values (48) 59
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 100
85.5%
Decimal Number 9
 
7.7%
Lowercase Letter 3
 
2.6%
Space Separator 3
 
2.6%
Open Punctuation 1
 
0.9%
Close Punctuation 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 9
 
9.0%
칼 7
 
7.0%
수 7
 
7.0%
커 6
 
6.0%
트 6
 
6.0%
삼 5
 
5.0%
겹 5
 
5.0%
살 5
 
5.0%
세 3
 
3.0%
탁 3
 
3.0%
Other values (39) 44
44.0%
Decimal Number
ValueCountFrequency (%)
0 5
55.6%
6 1
 
11.1%
5 1
 
11.1%
8 1
 
11.1%
1 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
g 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 100
85.5%
Common 14
 
12.0%
Latin 3
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 9
 
9.0%
칼 7
 
7.0%
수 7
 
7.0%
커 6
 
6.0%
트 6
 
6.0%
삼 5
 
5.0%
겹 5
 
5.0%
살 5
 
5.0%
세 3
 
3.0%
탁 3
 
3.0%
Other values (39) 44
44.0%
Common
ValueCountFrequency (%)
0 5
35.7%
3
21.4%
6 1
 
7.1%
5 1
 
7.1%
( 1
 
7.1%
) 1
 
7.1%
8 1
 
7.1%
1 1
 
7.1%
Latin
ValueCountFrequency (%)
g 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 100
85.5%
ASCII 17
 
14.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 9
 
9.0%
칼 7
 
7.0%
수 7
 
7.0%
커 6
 
6.0%
트 6
 
6.0%
삼 5
 
5.0%
겹 5
 
5.0%
살 5
 
5.0%
세 3
 
3.0%
탁 3
 
3.0%
Other values (39) 44
44.0%
ASCII
ValueCountFrequency (%)
0 5
29.4%
g 3
17.6%
3
17.6%
6 1
 
5.9%
5 1
 
5.9%
( 1
 
5.9%
) 1
 
5.9%
8 1
 
5.9%
1 1
 
5.9%

가격
Real number (ℝ)

Distinct17
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11575
Minimum3000
Maximum40000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size416.0 B
2024-03-14T19:42:42.279327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000
5-th percentile4000
Q15750
median7500
Q313000
95-th percentile35000
Maximum40000
Range37000
Interquartile range (IQR)7250

Descriptive statistics

Standard deviation9462.7964
Coefficient of variation (CV)0.81752021
Kurtosis3.0863132
Mean11575
Median Absolute Deviation (MAD)3050
Skewness1.9188939
Sum370400
Variance89544516
MonotonicityNot monotonic
2024-03-14T19:42:42.654809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
7000 5
15.6%
5000 4
12.5%
12000 3
9.4%
13000 3
9.4%
6000 2
 
6.2%
8000 2
 
6.2%
35000 2
 
6.2%
4000 2
 
6.2%
6500 1
 
3.1%
40000 1
 
3.1%
Other values (7) 7
21.9%
ValueCountFrequency (%)
3000 1
 
3.1%
4000 2
 
6.2%
4900 1
 
3.1%
5000 4
12.5%
6000 2
 
6.2%
6500 1
 
3.1%
7000 5
15.6%
8000 2
 
6.2%
10000 1
 
3.1%
11000 1
 
3.1%
ValueCountFrequency (%)
40000 1
 
3.1%
35000 2
6.2%
24000 1
 
3.1%
20000 1
 
3.1%
15000 1
 
3.1%
13000 3
9.4%
12000 3
9.4%
11000 1
 
3.1%
10000 1
 
3.1%
8000 2
6.2%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size384.0 B
2023-12-31
32 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12-31
2nd row2023-12-31
3rd row2023-12-31
4th row2023-12-31
5th row2023-12-31

Common Values

ValueCountFrequency (%)
2023-12-31 32
100.0%

Length

2024-03-14T19:42:43.062043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:42:43.367949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-31 32
100.0%

Interactions

2024-03-14T19:42:28.690592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:42:27.190857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:42:27.959029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:42:28.954833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:42:27.444721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:42:28.206893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:42:29.097646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:42:27.701071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:42:28.441799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T19:42:43.561430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종구분상호명지역소재지주소(도로명)소재지주소(지번)위도경도전화번호품목가격
업종구분1.0001.0000.7131.0000.0000.0000.5281.0001.0000.313
상호명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지역0.7131.0001.0001.0001.0000.8990.9581.0000.0000.000
소재지주소(도로명)1.0001.0001.0001.0001.0001.0001.0001.0000.9340.000
소재지주소(지번)0.0001.0001.0001.0001.0001.0001.0001.0000.3810.000
위도0.0001.0000.8991.0001.0001.0000.4321.0000.6880.632
경도0.5281.0000.9581.0001.0000.4321.0001.0000.0000.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
품목1.0001.0000.0000.9340.3810.6880.0001.0001.0000.979
가격0.3131.0000.0000.0000.0000.6320.0001.0000.9791.000
2024-03-14T19:42:43.871392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역업종구분
지역1.0000.398
업종구분0.3981.000
2024-03-14T19:42:44.120311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도가격업종구분지역
위도1.0000.021-0.0470.0000.613
경도0.0211.0000.2600.3280.764
가격-0.0470.2601.0000.0000.000
업종구분0.0000.3280.0001.0000.398
지역0.6130.7640.0000.3981.000

Missing values

2024-03-14T19:42:29.317925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:42:29.588018image/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

업종구분상호명지역소재지주소(도로명)소재지주소(지번)위도경도전화번호품목가격데이터기준일
0한식강남식당금곡동경기도 남양주시 홍유릉로248번길 64-37경기도 남양주시 금곡동 454-2137.629368127.203943031-559-5535삼겹살120002023-12-31
1한식경성멧돼지금곡동경기도 남양주시 홍유릉로 327경기도 남양주시 금곡동 680-2537.631127127.203756031-592-9733삼겹살 600g350002023-12-31
2한식고향손칼국수와부읍경기도 남양주시 와부읍 수레로 72경기도 남양주시 와부읍 덕소리 187-337.590185127.21802031-577-3237칼국수60002023-12-31
3한식명성막고기금곡동경기도 남양주시 홍유릉로248번길 39경기도 남양주시 금곡동 651-137.627253127.202412031-595-9115삼겹살130002023-12-31
4한식명성식당금곡동경기도 남양주시 홍유릉로248번길 9경기도 남양주시 금곡동 659-137.625251127.2003170507-1358-6776닭볶음탕350002023-12-31
5한식밀마당칼국수 & 보쌈금곡동경기도 남양주시 홍유릉로248번길 39경기도 남양주시 금곡동 651-137.627253127.202412031-591-7412보쌈(소)200002023-12-31
6한식시골본가오남읍경기도 남양주시 오남읍 진건오남로 617경기도 남양주시 오남읍 오남리 683-537.688373127.212032031-575-2626삼겹살 500g240002023-12-31
7한식신주사골칼국수화도읍경기도 남양주시 화도읍 마석로45번길 1경기도 남양주시 화도읍 마석우리 297-3937.654864127.305895031-595-3319칼국수70002023-12-31
8한식순화네만두수동면경기도 남양주시 수동면 비룡로782번길 6경기도 남양주시 수동면 입석리 347-237.707709127.3238670507-1357-6995만둣국80002023-12-31
9한식안골콩나물국밥퇴계원읍경기도 남양주시 퇴계원읍 도제원로 57경기도 남양주시 퇴계원읍 퇴계원리 110-1037.653224127.14503031-527-6676콩나물국밥50002023-12-31
업종구분상호명지역소재지주소(도로명)소재지주소(지번)위도경도전화번호품목가격데이터기준일
22이·미용양미용실금곡동경기도 남양주시 금곡로 65-15경기도 남양주시 금곡동 159-5037.63515127.210075031-559-9875커트70002023-12-31
23이·미용짱미용실진접읍경기도 남양주시 진접읍 장현로 59-10경기도 남양주시 진접읍 장현리 633-1337.716722127.179581031-573-1023커트120002023-12-31
24이·미용티와이헤어금곡동경기도 남양주시 경춘로992번길 1-1경기도 남양주시 금곡동 154-1037.634128127.211932031-592-5342커트130002023-12-31
25이·미용헤어573진접읍경기도 남양주시 진접읍 해밀예당3로 116경기도 남양주시 진접읍 금곡리 974-137.720026127.197028031-528-6054커트110002023-12-31
26이·미용헤어살롱크리스탈진접읍경기도 남양주시 진접읍 해밀예당3로 102경기도 남양주시 진접읍 금곡리 1075, 지웰아파트 상가동 1층37.718848127.197401031-572-3060파마400002023-12-31
27이·미용헤어체인지수동면경기도 남양주시 수동면 비룡로 713경기도 남양주시 수동면 운수리 120-337.702538127.326684031-593-3437커트130002023-12-31
28이·미용헤어천사금곡동경기도 남양주시 사릉로34번길 24경기도 남양주시 금곡동 159-6637.63618127.21107031-511-8950커트120002023-12-31
29세탁소삐삐수선(크린업)다산동경기도 남양주시 다산지금로16번길 88, 103호경기도 남양주시 다산동 620837.607175127.170806031-551-1477세탁50002023-12-31
30세탁소청학세탁소별내면경기도 남양주시 별내면 청학로114번길 16, 103호경기도 남양주시 별내면 청학리 419-2, 주공2단지 상가 103호37.709684127.1147570507-1446-5101세탁70002023-12-31
31세탁소평내주공세탁소평내동경기도 남양주시 평내로 48경기도 남양주시 평내동 56237.641166127.233238031-511-3077세탁70002023-12-31