Overview

Dataset statistics

Number of variables7
Number of observations39
Missing cells1
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory60.4 B

Variable types

Numeric1
Categorical3
Text3

Dataset

Description인천광역시 서구 착한가격업소에 대한 현황(지정월, 업종, 업소명, 소재지, 연락처)데이터를 포함하고 있습니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15038882&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 최초 지정월High correlation
최초 지정월 is highly overall correlated with 연번High correlation
연락처 has 1 (2.6%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2024-01-28 09:45:54.371680
Analysis finished2024-01-28 09:45:54.898545
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2024-01-28T18:45:54.955519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.9
Q110.5
median20
Q329.5
95-th percentile37.1
Maximum39
Range38
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.401754
Coefficient of variation (CV)0.57008771
Kurtosis-1.2
Mean20
Median Absolute Deviation (MAD)10
Skewness0
Sum780
Variance130
MonotonicityStrictly increasing
2024-01-28T18:45:55.058711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 1
 
2.6%
2 1
 
2.6%
23 1
 
2.6%
24 1
 
2.6%
25 1
 
2.6%
26 1
 
2.6%
27 1
 
2.6%
28 1
 
2.6%
29 1
 
2.6%
30 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
1 1
2.6%
2 1
2.6%
3 1
2.6%
4 1
2.6%
5 1
2.6%
6 1
2.6%
7 1
2.6%
8 1
2.6%
9 1
2.6%
10 1
2.6%
ValueCountFrequency (%)
39 1
2.6%
38 1
2.6%
37 1
2.6%
36 1
2.6%
35 1
2.6%
34 1
2.6%
33 1
2.6%
32 1
2.6%
31 1
2.6%
30 1
2.6%

최초 지정월
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-06-12
12 
2023-09-19
8 
2023-11-11
4 
2023-06-22
4 
2023-05-12
3 
Other values (5)
8 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique3 ?
Unique (%)7.7%

Sample

1st row2023-11-11
2nd row2023-11-11
3rd row2023-11-11
4th row2023-11-11
5th row2023-05-12

Common Values

ValueCountFrequency (%)
2023-06-12 12
30.8%
2023-09-19 8
20.5%
2023-11-11 4
 
10.3%
2023-06-22 4
 
10.3%
2023-05-12 3
 
7.7%
2023-06-23 3
 
7.7%
2023-06-21 2
 
5.1%
2023-05-13 1
 
2.6%
2023-06-19 1
 
2.6%
2023-07-19 1
 
2.6%

Length

2024-01-28T18:45:55.157606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:45:55.248498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-12 12
30.8%
2023-09-19 8
20.5%
2023-11-11 4
 
10.3%
2023-06-22 4
 
10.3%
2023-05-12 3
 
7.7%
2023-06-23 3
 
7.7%
2023-06-21 2
 
5.1%
2023-05-13 1
 
2.6%
2023-06-19 1
 
2.6%
2023-07-19 1
 
2.6%

업종
Categorical

Distinct8
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size444.0 B
한식
17 
이미용업
11 
세탁업
6 
카페
 
1
제과업
 
1
Other values (3)
3 

Length

Max length7
Median length4
Mean length2.8974359
Min length2

Unique

Unique5 ?
Unique (%)12.8%

Sample

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

Common Values

ValueCountFrequency (%)
한식 17
43.6%
이미용업 11
28.2%
세탁업 6
 
15.4%
카페 1
 
2.6%
제과업 1
 
2.6%
중식 1
 
2.6%
기타 비요식업 1
 
2.6%
미용업 1
 
2.6%

Length

2024-01-28T18:45:55.349379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:45:55.439218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 17
42.5%
이미용업 11
27.5%
세탁업 6
 
15.0%
카페 1
 
2.5%
제과업 1
 
2.5%
중식 1
 
2.5%
기타 1
 
2.5%
비요식업 1
 
2.5%
미용업 1
 
2.5%

업소명
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-01-28T18:45:55.626394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.8461538
Min length2

Characters and Unicode

Total characters228
Distinct characters128
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

Unique39 ?
Unique (%)100.0%

Sample

1st row대동세탁
2nd row백양세탁
3rd row풍년막걸리
4th row새마음이발관
5th row삼원부대찌개전문
ValueCountFrequency (%)
대동세탁 1
 
2.0%
만흥 1
 
2.0%
바지락칼국수 1
 
2.0%
하나식당 1
 
2.0%
장터엔 1
 
2.0%
국수 1
 
2.0%
골든브라운 1
 
2.0%
카페 1
 
2.0%
왕소 1
 
2.0%
재래식 1
 
2.0%
Other values (39) 39
79.6%
2024-01-28T18:45:55.929045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
 
4.4%
헤 9
 
3.9%
어 9
 
3.9%
세 6
 
2.6%
탁 6
 
2.6%
리 6
 
2.6%
대 5
 
2.2%
수 5
 
2.2%
소 5
 
2.2%
이 5
 
2.2%
Other values (118) 162
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 213
93.4%
Space Separator 10
 
4.4%
Decimal Number 3
 
1.3%
Other Punctuation 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
헤 9
 
4.2%
어 9
 
4.2%
세 6
 
2.8%
탁 6
 
2.8%
리 6
 
2.8%
대 5
 
2.3%
수 5
 
2.3%
소 5
 
2.3%
이 5
 
2.3%
식 4
 
1.9%
Other values (114) 153
71.8%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 213
93.4%
Common 15
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
헤 9
 
4.2%
어 9
 
4.2%
세 6
 
2.8%
탁 6
 
2.8%
리 6
 
2.8%
대 5
 
2.3%
수 5
 
2.3%
소 5
 
2.3%
이 5
 
2.3%
식 4
 
1.9%
Other values (114) 153
71.8%
Common
ValueCountFrequency (%)
10
66.7%
1 2
 
13.3%
& 2
 
13.3%
9 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 213
93.4%
ASCII 15
 
6.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
66.7%
1 2
 
13.3%
& 2
 
13.3%
9 1
 
6.7%
Hangul
ValueCountFrequency (%)
헤 9
 
4.2%
어 9
 
4.2%
세 6
 
2.8%
탁 6
 
2.8%
리 6
 
2.8%
대 5
 
2.3%
수 5
 
2.3%
소 5
 
2.3%
이 5
 
2.3%
식 4
 
1.9%
Other values (114) 153
71.8%

소재지
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-01-28T18:45:56.153899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length28
Mean length24.923077
Min length15

Characters and Unicode

Total characters972
Distinct characters92
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 심곡로 133, 203호(심곡동, 대동아파트상가)
2nd row인천광역시 서구 승학로287번길 17(연희동)
3rd row인천광역시 서구 가정로 122(가좌동)
4th row인천광역시 서구 장고개로287번길 7, 105호(가좌동)
5th row인천광역시 서구 대평로7번길 4(심곡동)
ValueCountFrequency (%)
인천광역시 39
21.5%
서구 39
21.5%
1층 4
 
2.2%
석남동 4
 
2.2%
신석로 3
 
1.7%
가정로 3
 
1.7%
건지로249번길 2
 
1.1%
길주로76번길 2
 
1.1%
승학로 2
 
1.1%
내(석남동 1
 
0.6%
Other values (82) 82
45.3%
2024-01-28T18:45:56.480922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
142
 
14.6%
서 41
 
4.2%
시 40
 
4.1%
인 39
 
4.0%
천 39
 
4.0%
구 39
 
4.0%
로 39
 
4.0%
역 39
 
4.0%
광 39
 
4.0%
1 38
 
3.9%
Other values (82) 477
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 584
60.1%
Decimal Number 158
 
16.3%
Space Separator 142
 
14.6%
Open Punctuation 34
 
3.5%
Close Punctuation 34
 
3.5%
Other Punctuation 13
 
1.3%
Dash Punctuation 7
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 41
 
7.0%
시 40
 
6.8%
인 39
 
6.7%
천 39
 
6.7%
구 39
 
6.7%
로 39
 
6.7%
역 39
 
6.7%
광 39
 
6.7%
동 37
 
6.3%
길 22
 
3.8%
Other values (67) 210
36.0%
Decimal Number
ValueCountFrequency (%)
1 38
24.1%
2 21
13.3%
8 18
11.4%
7 16
10.1%
6 14
 
8.9%
3 13
 
8.2%
4 12
 
7.6%
9 10
 
6.3%
5 8
 
5.1%
0 8
 
5.1%
Space Separator
ValueCountFrequency (%)
142
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 584
60.1%
Common 388
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 41
 
7.0%
시 40
 
6.8%
인 39
 
6.7%
천 39
 
6.7%
구 39
 
6.7%
로 39
 
6.7%
역 39
 
6.7%
광 39
 
6.7%
동 37
 
6.3%
길 22
 
3.8%
Other values (67) 210
36.0%
Common
ValueCountFrequency (%)
142
36.6%
1 38
 
9.8%
( 34
 
8.8%
) 34
 
8.8%
2 21
 
5.4%
8 18
 
4.6%
7 16
 
4.1%
6 14
 
3.6%
3 13
 
3.4%
, 13
 
3.4%
Other values (5) 45
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 584
60.1%
ASCII 388
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
142
36.6%
1 38
 
9.8%
( 34
 
8.8%
) 34
 
8.8%
2 21
 
5.4%
8 18
 
4.6%
7 16
 
4.1%
6 14
 
3.6%
3 13
 
3.4%
, 13
 
3.4%
Other values (5) 45
 
11.6%
Hangul
ValueCountFrequency (%)
서 41
 
7.0%
시 40
 
6.8%
인 39
 
6.7%
천 39
 
6.7%
구 39
 
6.7%
로 39
 
6.7%
역 39
 
6.7%
광 39
 
6.7%
동 37
 
6.3%
길 22
 
3.8%
Other values (67) 210
36.0%

연락처
Text

MISSING 

Distinct38
Distinct (%)100.0%
Missing1
Missing (%)2.6%
Memory size444.0 B
2024-01-28T18:45:56.661044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.078947
Min length12

Characters and Unicode

Total characters459
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

Unique38 ?
Unique (%)100.0%

Sample

1st row032-561-3434
2nd row032-561-2060
3rd row032-574-2560
4th row032-579-8843
5th row032-561-9409
ValueCountFrequency (%)
032-561-3434 1
 
2.6%
032-564-2245 1
 
2.6%
032-574-5553 1
 
2.6%
032-581-7701 1
 
2.6%
032-583-5097 1
 
2.6%
032-575-5170 1
 
2.6%
032-579-1821 1
 
2.6%
032-218-1592 1
 
2.6%
032-577-7808 1
 
2.6%
0507-1441-7401 1
 
2.6%
Other values (28) 28
73.7%
2024-01-28T18:45:56.943308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 76
16.6%
2 65
14.2%
5 59
12.9%
0 57
12.4%
3 51
11.1%
7 33
7.2%
6 28
 
6.1%
1 28
 
6.1%
4 25
 
5.4%
8 22
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 383
83.4%
Dash Punctuation 76
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 65
17.0%
5 59
15.4%
0 57
14.9%
3 51
13.3%
7 33
8.6%
6 28
7.3%
1 28
7.3%
4 25
 
6.5%
8 22
 
5.7%
9 15
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 459
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 76
16.6%
2 65
14.2%
5 59
12.9%
0 57
12.4%
3 51
11.1%
7 33
7.2%
6 28
 
6.1%
1 28
 
6.1%
4 25
 
5.4%
8 22
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 459
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 76
16.6%
2 65
14.2%
5 59
12.9%
0 57
12.4%
3 51
11.1%
7 33
7.2%
6 28
 
6.1%
1 28
 
6.1%
4 25
 
5.4%
8 22
 
4.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-10-19
39 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-19
2nd row2023-10-19
3rd row2023-10-19
4th row2023-10-19
5th row2023-10-19

Common Values

ValueCountFrequency (%)
2023-10-19 39
100.0%

Length

2024-01-28T18:45:57.048305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:45:57.118157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-19 39
100.0%

Interactions

2024-01-28T18:45:54.664047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T18:45:57.169891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번최초 지정월업종업소명소재지연락처
연번1.0000.9540.4561.0001.0001.000
최초 지정월0.9541.0000.3241.0001.0001.000
업종0.4560.3241.0001.0001.0001.000
업소명1.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.000
2024-01-28T18:45:57.246198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최초 지정월업종
최초 지정월1.0000.130
업종0.1301.000
2024-01-28T18:45:57.308126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번최초 지정월업종
연번1.0000.6450.174
최초 지정월0.6451.0000.130
업종0.1740.1301.000

Missing values

2024-01-28T18:45:54.756604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T18:45:54.856457image/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

연번최초 지정월업종업소명소재지연락처데이터기준일자
012023-11-11세탁업대동세탁인천광역시 서구 심곡로 133, 203호(심곡동, 대동아파트상가)032-561-34342023-10-19
122023-11-11세탁업백양세탁인천광역시 서구 승학로287번길 17(연희동)032-561-20602023-10-19
232023-11-11한식풍년막걸리인천광역시 서구 가정로 122(가좌동)032-574-25602023-10-19
342023-11-11이미용업새마음이발관인천광역시 서구 장고개로287번길 7, 105호(가좌동)032-579-88432023-10-19
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