Overview

Dataset statistics

Number of variables6
Number of observations386
Missing cells14
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.6 KiB
Average record size in memory49.3 B

Variable types

Numeric1
Categorical3
Text2

Dataset

Description김해시 전통시장 입점 점포 현황(시장명, 점포명, 업종, 주요품목, 결제옵션(온누리상품권, 카드 등))에 대한 데이터를 제공합니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15092968/fileData.do

Alerts

연번 is highly overall correlated with 시장명High correlation
시장명 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
업종 is highly overall correlated with 시장명High correlation
결제옵션(온누리상품권_카드 등) is highly imbalanced (55.6%)Imbalance
주요품목 has 14 (3.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 11:42:47.228134
Analysis finished2024-03-14 11:42:48.750535
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct386
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean193.5
Minimum1
Maximum386
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-03-14T20:42:48.909209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.25
Q197.25
median193.5
Q3289.75
95-th percentile366.75
Maximum386
Range385
Interquartile range (IQR)192.5

Descriptive statistics

Standard deviation111.57285
Coefficient of variation (CV)0.57660386
Kurtosis-1.2
Mean193.5
Median Absolute Deviation (MAD)96.5
Skewness0
Sum74691
Variance12448.5
MonotonicityStrictly increasing
2024-03-14T20:42:49.348002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
291 1
 
0.3%
265 1
 
0.3%
264 1
 
0.3%
263 1
 
0.3%
262 1
 
0.3%
261 1
 
0.3%
260 1
 
0.3%
259 1
 
0.3%
258 1
 
0.3%
Other values (376) 376
97.4%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
386 1
0.3%
385 1
0.3%
384 1
0.3%
383 1
0.3%
382 1
0.3%
381 1
0.3%
380 1
0.3%
379 1
0.3%
378 1
0.3%
377 1
0.3%

시장명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
김해동상시장
139 
외동전통시장
112 
진영전통시장
68 
삼방전통시장
67 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
김해동상시장 139
36.0%
외동전통시장 112
29.0%
진영전통시장 68
17.6%
삼방전통시장 67
17.4%

Length

2024-03-14T20:42:49.760944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:42:50.082061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
김해동상시장 139
36.0%
외동전통시장 112
29.0%
진영전통시장 68
17.6%
삼방전통시장 67
17.4%

점포명
Text

Distinct382
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-03-14T20:42:51.135332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.4352332
Min length2

Characters and Unicode

Total characters1712
Distinct characters370
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

Unique378 ?
Unique (%)97.9%

Sample

1st row꽃미남과일
2nd row꽃미남야채
3rd row선우축산
4th row착한생선
5th row햇살고운과일촌
ValueCountFrequency (%)
민물나라 2
 
0.5%
byc 2
 
0.5%
생림상회 2
 
0.5%
부산상회 2
 
0.5%
옷가계 2
 
0.5%
경남청과 1
 
0.3%
인제떡방앗간 1
 
0.3%
홍아상회 1
 
0.3%
정그릇 1
 
0.3%
삼방상회(제일상회 1
 
0.3%
Other values (373) 373
96.1%
2024-03-14T20:42:52.694683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
상 52
 
3.0%
회 52
 
3.0%
수 41
 
2.4%
식 35
 
2.0%
산 32
 
1.9%
이 26
 
1.5%
장 25
 
1.5%
성 23
 
1.3%
국 23
 
1.3%
리 22
 
1.3%
Other values (360) 1381
80.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1671
97.6%
Uppercase Letter 12
 
0.7%
Decimal Number 11
 
0.6%
Other Punctuation 10
 
0.6%
Space Separator 4
 
0.2%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 52
 
3.1%
회 52
 
3.1%
수 41
 
2.5%
식 35
 
2.1%
산 32
 
1.9%
이 26
 
1.6%
장 25
 
1.5%
성 23
 
1.4%
국 23
 
1.4%
리 22
 
1.3%
Other values (337) 1340
80.2%
Decimal Number
ValueCountFrequency (%)
3 2
18.2%
1 2
18.2%
2 1
9.1%
4 1
9.1%
5 1
9.1%
6 1
9.1%
7 1
9.1%
8 1
9.1%
9 1
9.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
25.0%
C 3
25.0%
Y 2
16.7%
M 1
 
8.3%
D 1
 
8.3%
A 1
 
8.3%
L 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 5
50.0%
/ 2
 
20.0%
, 2
 
20.0%
& 1
 
10.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1671
97.6%
Common 29
 
1.7%
Latin 12
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 52
 
3.1%
회 52
 
3.1%
수 41
 
2.5%
식 35
 
2.1%
산 32
 
1.9%
이 26
 
1.6%
장 25
 
1.5%
성 23
 
1.4%
국 23
 
1.4%
리 22
 
1.3%
Other values (337) 1340
80.2%
Common
ValueCountFrequency (%)
. 5
17.2%
4
13.8%
/ 2
 
6.9%
, 2
 
6.9%
) 2
 
6.9%
3 2
 
6.9%
1 2
 
6.9%
( 2
 
6.9%
& 1
 
3.4%
2 1
 
3.4%
Other values (6) 6
20.7%
Latin
ValueCountFrequency (%)
B 3
25.0%
C 3
25.0%
Y 2
16.7%
M 1
 
8.3%
D 1
 
8.3%
A 1
 
8.3%
L 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1671
97.6%
ASCII 41
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
상 52
 
3.1%
회 52
 
3.1%
수 41
 
2.5%
식 35
 
2.1%
산 32
 
1.9%
이 26
 
1.6%
장 25
 
1.5%
성 23
 
1.4%
국 23
 
1.4%
리 22
 
1.3%
Other values (337) 1340
80.2%
ASCII
ValueCountFrequency (%)
. 5
 
12.2%
4
 
9.8%
B 3
 
7.3%
C 3
 
7.3%
/ 2
 
4.9%
, 2
 
4.9%
) 2
 
4.9%
3 2
 
4.9%
1 2
 
4.9%
( 2
 
4.9%
Other values (13) 14
34.1%

업종
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
141 
식품류
34 
의류
32 
수산물
21 
축산물
17 
Other values (41)
141 

Length

Max length8
Median length7
Mean length3.4740933
Min length2

Unique

Unique22 ?
Unique (%)5.7%

Sample

1st row과일류
2nd row야채류
3rd row축산물
4th row수산물
5th row과일류

Common Values

ValueCountFrequency (%)
<NA> 141
36.5%
식품류 34
 
8.8%
의류 32
 
8.3%
수산물 21
 
5.4%
축산물 17
 
4.4%
요식업 14
 
3.6%
농산물 14
 
3.6%
잡화류 12
 
3.1%
즉석제조 12
 
3.1%
과일류 10
 
2.6%
Other values (36) 79
20.5%

Length

2024-03-14T20:42:53.330944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 141
35.9%
식품류 34
 
8.7%
의류 32
 
8.1%
수산물 22
 
5.6%
축산물 17
 
4.3%
농산물 16
 
4.1%
요식업 14
 
3.6%
즉석제조 13
 
3.3%
잡화류 12
 
3.1%
즉석제조업 10
 
2.5%
Other values (34) 82
20.9%

주요품목
Text

MISSING 

Distinct142
Distinct (%)38.2%
Missing14
Missing (%)3.6%
Memory size3.1 KiB
2024-03-14T20:42:54.656313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length3.188172
Min length1

Characters and Unicode

Total characters1186
Distinct characters168
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

Unique89 ?
Unique (%)23.9%

Sample

1st row과일
2nd row야채
3rd row육류
4th row생선
5th row과일
ValueCountFrequency (%)
여성복 17
 
4.3%
과일 17
 
4.3%
수산물 15
 
3.8%
한식 14
 
3.6%
생선 13
 
3.3%
청년몰 12
 
3.1%
반찬 12
 
3.1%
건어물 10
 
2.6%
채소,식품잡화 10
 
2.6%
축산물 10
 
2.6%
Other values (131) 261
66.8%
2024-03-14T20:42:56.414614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 64
 
5.4%
식 62
 
5.2%
물 43
 
3.6%
류 35
 
3.0%
수 33
 
2.8%
화 31
 
2.6%
채 30
 
2.5%
산 28
 
2.4%
품 28
 
2.4%
과 26
 
2.2%
Other values (158) 806
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1097
92.5%
Other Punctuation 67
 
5.6%
Space Separator 20
 
1.7%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 62
 
5.7%
물 43
 
3.9%
류 35
 
3.2%
수 33
 
3.0%
화 31
 
2.8%
채 30
 
2.7%
산 28
 
2.6%
품 28
 
2.6%
과 26
 
2.4%
잡 26
 
2.4%
Other values (153) 755
68.8%
Other Punctuation
ValueCountFrequency (%)
, 64
95.5%
. 3
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
X 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1097
92.5%
Common 87
 
7.3%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 62
 
5.7%
물 43
 
3.9%
류 35
 
3.2%
수 33
 
3.0%
화 31
 
2.8%
채 30
 
2.7%
산 28
 
2.6%
품 28
 
2.6%
과 26
 
2.4%
잡 26
 
2.4%
Other values (153) 755
68.8%
Common
ValueCountFrequency (%)
, 64
73.6%
20
 
23.0%
. 3
 
3.4%
Latin
ValueCountFrequency (%)
X 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1097
92.5%
ASCII 89
 
7.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 64
71.9%
20
 
22.5%
. 3
 
3.4%
X 1
 
1.1%
G 1
 
1.1%
Hangul
ValueCountFrequency (%)
식 62
 
5.7%
물 43
 
3.9%
류 35
 
3.2%
수 33
 
3.0%
화 31
 
2.8%
채 30
 
2.7%
산 28
 
2.6%
품 28
 
2.6%
과 26
 
2.4%
잡 26
 
2.4%
Other values (153) 755
68.8%

결제옵션(온누리상품권_카드 등)
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
온누리상품권지류,모바일,카드,제로페이
284 
<NA>
89 
온누리상품권지류
 
6
카드
 
4
온누리상품권지류,제로페이
 
3

Length

Max length20
Median length20
Mean length15.88342
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row온누리상품권지류,모바일,카드,제로페이
2nd row온누리상품권지류,모바일,카드,제로페이
3rd row온누리상품권지류,모바일,카드,제로페이
4th row온누리상품권지류,모바일,카드,제로페이
5th row온누리상품권지류,모바일,카드,제로페이

Common Values

ValueCountFrequency (%)
온누리상품권지류,모바일,카드,제로페이 284
73.6%
<NA> 89
 
23.1%
온누리상품권지류 6
 
1.6%
카드 4
 
1.0%
온누리상품권지류,제로페이 3
 
0.8%

Length

2024-03-14T20:42:56.857485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:42:57.218165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
온누리상품권지류,모바일,카드,제로페이 284
73.6%
na 89
 
23.1%
온누리상품권지류 6
 
1.6%
카드 4
 
1.0%
온누리상품권지류,제로페이 3
 
0.8%

Interactions

2024-03-14T20:42:47.887909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T20:42:57.452494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시장명업종결제옵션(온누리상품권_카드 등)
연번1.0000.9720.8240.297
시장명0.9721.0000.9380.214
업종0.8240.9381.0000.580
결제옵션(온누리상품권_카드 등)0.2970.2140.5801.000
2024-03-14T20:42:57.709243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
결제옵션(온누리상품권_카드 등)시장명업종
결제옵션(온누리상품권_카드 등)1.0000.2040.302
시장명0.2041.0000.688
업종0.3020.6881.000
2024-03-14T20:42:57.961037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시장명업종결제옵션(온누리상품권_카드 등)
연번1.0000.9090.4710.190
시장명0.9091.0000.6880.204
업종0.4710.6881.0000.302
결제옵션(온누리상품권_카드 등)0.1900.2040.3021.000

Missing values

2024-03-14T20:42:48.254788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T20:42:48.609002image/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

연번시장명점포명업종주요품목결제옵션(온누리상품권_카드 등)
01외동전통시장꽃미남과일과일류과일온누리상품권지류,모바일,카드,제로페이
12외동전통시장꽃미남야채야채류야채온누리상품권지류,모바일,카드,제로페이
23외동전통시장선우축산축산물육류온누리상품권지류,모바일,카드,제로페이
34외동전통시장착한생선수산물생선온누리상품권지류,모바일,카드,제로페이
45외동전통시장햇살고운과일촌과일류과일온누리상품권지류,모바일,카드,제로페이
56외동전통시장남해수산수산물생선온누리상품권지류,모바일,카드,제로페이
67외동전통시장맛고을떡집떡가공류떡온누리상품권지류,모바일,카드,제로페이
78외동전통시장에쓰시가공식품한과온누리상품권지류,모바일,카드,제로페이
89외동전통시장크린피아의류속옷온누리상품권지류,모바일,카드,제로페이
910외동전통시장즉석두부오뎅식품류두부,어묵온누리상품권지류,모바일,카드,제로페이
연번시장명점포명업종주요품목결제옵션(온누리상품권_카드 등)
376377진영전통시장형제참기름즉석제조업참기름<NA>
377378진영전통시장충무분식요식업한식<NA>
378379진영전통시장시장떡집즉석제조업떡<NA>
379380진영전통시장맷돌순두부즉석제조업두부<NA>
380381진영전통시장비,와이.씨의류속옷<NA>
381382진영전통시장수림과일농산물과일<NA>
382383진영전통시장속옷가계의류옷<NA>
383384진영전통시장옷가계의류옷<NA>
384385진영전통시장봉화약초농산물약초<NA>
385386진영전통시장야채농산물야채<NA>