Overview

Dataset statistics

Number of variables7
Number of observations33
Missing cells3
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory63.0 B

Variable types

Numeric3
Categorical1
Text3

Dataset

Description인천광역시 미추홀구의 착한가격업소 데이터로 유형, 상호명, 도로명주소, 전화번호, 좌표값 등의 정보를 제공하고 있습니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3081244&srcSe=7661IVAWM27C61E190

Alerts

전화번호 has 3 (9.1%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique
도로명주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-03-18 04:13:53.843150
Analysis finished2024-03-18 04:13:56.733031
Duration2.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-03-18T13:13:56.803575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.6
Q19
median17
Q325
95-th percentile31.4
Maximum33
Range32
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.6695398
Coefficient of variation (CV)0.56879646
Kurtosis-1.2
Mean17
Median Absolute Deviation (MAD)8
Skewness0
Sum561
Variance93.5
MonotonicityStrictly increasing
2024-03-18T13:13:56.921785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 1
 
3.0%
26 1
 
3.0%
20 1
 
3.0%
21 1
 
3.0%
22 1
 
3.0%
23 1
 
3.0%
24 1
 
3.0%
25 1
 
3.0%
27 1
 
3.0%
2 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
1 1
3.0%
2 1
3.0%
3 1
3.0%
4 1
3.0%
5 1
3.0%
6 1
3.0%
7 1
3.0%
8 1
3.0%
9 1
3.0%
10 1
3.0%
ValueCountFrequency (%)
33 1
3.0%
32 1
3.0%
31 1
3.0%
30 1
3.0%
29 1
3.0%
28 1
3.0%
27 1
3.0%
26 1
3.0%
25 1
3.0%
24 1
3.0%

유형
Categorical

Distinct6
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size396.0 B
한식
18 
중식
7 
이미용업
5 
세탁업
 
1
일식
 
1

Length

Max length5
Median length2
Mean length2.4242424
Min length2

Unique

Unique3 ?
Unique (%)9.1%

Sample

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

Common Values

ValueCountFrequency (%)
한식 18
54.5%
중식 7
 
21.2%
이미용업 5
 
15.2%
세탁업 1
 
3.0%
일식 1
 
3.0%
인테리어업 1
 
3.0%

Length

2024-03-18T13:13:57.042345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:13:57.148589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 18
54.5%
중식 7
 
21.2%
이미용업 5
 
15.2%
세탁업 1
 
3.0%
일식 1
 
3.0%
인테리어업 1
 
3.0%

업소명
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-03-18T13:13:57.321250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length4.6969697
Min length2

Characters and Unicode

Total characters155
Distinct characters104
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row동방세탁
2nd row인하뷰티에스테틱
3rd row종로이발
4th row반도미용실
5th row아빠이발관
ValueCountFrequency (%)
대박집 2
 
5.7%
김밥타운 1
 
2.9%
김밥나라 1
 
2.9%
백년갈비 1
 
2.9%
맛사랑 1
 
2.9%
시내비골 1
 
2.9%
쑥골국수집 1
 
2.9%
새우물식당 1
 
2.9%
동방세탁 1
 
2.9%
다우리식당 1
 
2.9%
Other values (24) 24
68.6%
2024-03-18T13:13:57.705426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 5
 
3.2%
당 4
 
2.6%
대 4
 
2.6%
방 4
 
2.6%
집 4
 
2.6%
밥 3
 
1.9%
가 3
 
1.9%
국 3
 
1.9%
김 3
 
1.9%
식 3
 
1.9%
Other values (94) 119
76.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 148
95.5%
Space Separator 2
 
1.3%
Open Punctuation 2
 
1.3%
Close Punctuation 2
 
1.3%
Other Symbol 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 5
 
3.4%
당 4
 
2.7%
대 4
 
2.7%
방 4
 
2.7%
집 4
 
2.7%
밥 3
 
2.0%
가 3
 
2.0%
국 3
 
2.0%
김 3
 
2.0%
식 3
 
2.0%
Other values (90) 112
75.7%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149
96.1%
Common 6
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 5
 
3.4%
당 4
 
2.7%
대 4
 
2.7%
방 4
 
2.7%
집 4
 
2.7%
밥 3
 
2.0%
가 3
 
2.0%
국 3
 
2.0%
김 3
 
2.0%
식 3
 
2.0%
Other values (91) 113
75.8%
Common
ValueCountFrequency (%)
2
33.3%
( 2
33.3%
) 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 148
95.5%
ASCII 6
 
3.9%
None 1
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 5
 
3.4%
당 4
 
2.7%
대 4
 
2.7%
방 4
 
2.7%
집 4
 
2.7%
밥 3
 
2.0%
가 3
 
2.0%
국 3
 
2.0%
김 3
 
2.0%
식 3
 
2.0%
Other values (90) 112
75.7%
ASCII
ValueCountFrequency (%)
2
33.3%
( 2
33.3%
) 2
33.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명주소
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-03-18T13:13:57.913831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length20.393939
Min length16

Characters and Unicode

Total characters673
Distinct characters52
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

Unique33 ?
Unique (%)100.0%

Sample

1st row인천광역시 미추홀구 수봉로 40
2nd row인천광역시 미추홀구 석정로 228
3rd row인천광역시 미추홀구 석정로 150-1
4th row인천광역시 미추홀구 수봉로27번길 4
5th row인천광역시 미추홀구 인주대로366번길 17
ValueCountFrequency (%)
인천광역시 33
24.4%
미추홀구 32
23.7%
인하로 7
 
5.2%
30번길 2
 
1.5%
경인남길 2
 
1.5%
인하로77번길 2
 
1.5%
주안로 2
 
1.5%
39 2
 
1.5%
석정로 2
 
1.5%
40 2
 
1.5%
Other values (49) 49
36.3%
2024-03-18T13:13:58.191532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
102
 
15.2%
인 46
 
6.8%
추 35
 
5.2%
미 35
 
5.2%
천 33
 
4.9%
홀 33
 
4.9%
시 33
 
4.9%
역 33
 
4.9%
광 33
 
4.9%
구 32
 
4.8%
Other values (42) 258
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 441
65.5%
Decimal Number 121
 
18.0%
Space Separator 102
 
15.2%
Dash Punctuation 9
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 46
10.4%
추 35
 
7.9%
미 35
 
7.9%
천 33
 
7.5%
홀 33
 
7.5%
시 33
 
7.5%
역 33
 
7.5%
광 33
 
7.5%
구 32
 
7.3%
로 30
 
6.8%
Other values (30) 98
22.2%
Decimal Number
ValueCountFrequency (%)
2 18
14.9%
7 17
14.0%
6 17
14.0%
3 16
13.2%
1 15
12.4%
9 12
9.9%
0 11
9.1%
4 7
 
5.8%
5 4
 
3.3%
8 4
 
3.3%
Space Separator
ValueCountFrequency (%)
102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 441
65.5%
Common 232
34.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 46
10.4%
추 35
 
7.9%
미 35
 
7.9%
천 33
 
7.5%
홀 33
 
7.5%
시 33
 
7.5%
역 33
 
7.5%
광 33
 
7.5%
구 32
 
7.3%
로 30
 
6.8%
Other values (30) 98
22.2%
Common
ValueCountFrequency (%)
102
44.0%
2 18
 
7.8%
7 17
 
7.3%
6 17
 
7.3%
3 16
 
6.9%
1 15
 
6.5%
9 12
 
5.2%
0 11
 
4.7%
- 9
 
3.9%
4 7
 
3.0%
Other values (2) 8
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 441
65.5%
ASCII 232
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
102
44.0%
2 18
 
7.8%
7 17
 
7.3%
6 17
 
7.3%
3 16
 
6.9%
1 15
 
6.5%
9 12
 
5.2%
0 11
 
4.7%
- 9
 
3.9%
4 7
 
3.0%
Other values (2) 8
 
3.4%
Hangul
ValueCountFrequency (%)
인 46
10.4%
추 35
 
7.9%
미 35
 
7.9%
천 33
 
7.5%
홀 33
 
7.5%
시 33
 
7.5%
역 33
 
7.5%
광 33
 
7.5%
구 32
 
7.3%
로 30
 
6.8%
Other values (30) 98
22.2%

전화번호
Text

MISSING 

Distinct30
Distinct (%)100.0%
Missing3
Missing (%)9.1%
Memory size396.0 B
2024-03-18T13:13:58.425205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters360
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

Unique30 ?
Unique (%)100.0%

Sample

1st row032-873-1811
2nd row032-888-0250
3rd row032-867-9690
4th row032-867-4286
5th row032-861-0660
ValueCountFrequency (%)
032-866-1991 1
 
3.3%
032-867-9690 1
 
3.3%
032-874-6616 1
 
3.3%
032-872-7380 1
 
3.3%
032-214-4544 1
 
3.3%
032-937-9265 1
 
3.3%
032-872-6651 1
 
3.3%
032-888-6300 1
 
3.3%
032-421-1243 1
 
3.3%
032-863-6690 1
 
3.3%
Other values (20) 20
66.7%
2024-03-18T13:13:58.716766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 60
16.7%
2 51
14.2%
0 46
12.8%
3 46
12.8%
8 40
11.1%
6 38
10.6%
4 23
 
6.4%
7 18
 
5.0%
1 17
 
4.7%
9 12
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 300
83.3%
Dash Punctuation 60
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 51
17.0%
0 46
15.3%
3 46
15.3%
8 40
13.3%
6 38
12.7%
4 23
7.7%
7 18
 
6.0%
1 17
 
5.7%
9 12
 
4.0%
5 9
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 360
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 60
16.7%
2 51
14.2%
0 46
12.8%
3 46
12.8%
8 40
11.1%
6 38
10.6%
4 23
 
6.4%
7 18
 
5.0%
1 17
 
4.7%
9 12
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 60
16.7%
2 51
14.2%
0 46
12.8%
3 46
12.8%
8 40
11.1%
6 38
10.6%
4 23
 
6.4%
7 18
 
5.0%
1 17
 
4.7%
9 12
 
3.3%

위도
Real number (ℝ)

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.456294
Minimum37.443248
Maximum37.468277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-03-18T13:13:58.826119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.443248
5-th percentile37.447441
Q137.451226
median37.452653
Q337.462199
95-th percentile37.467932
Maximum37.468277
Range0.02502949
Interquartile range (IQR)0.01097352

Descriptive statistics

Standard deviation0.0070113865
Coefficient of variation (CV)0.00018718848
Kurtosis-1.2289452
Mean37.456294
Median Absolute Deviation (MAD)0.00588164
Skewness0.16315905
Sum1236.0577
Variance4.915954 × 10-5
MonotonicityNot monotonic
2024-03-18T13:13:58.923100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
37.4627146 1
 
3.0%
37.44814268 1
 
3.0%
37.46804468 1
 
3.0%
37.4511891 1
 
3.0%
37.45097541 1
 
3.0%
37.46404959 1
 
3.0%
37.46182564 1
 
3.0%
37.44838287 1
 
3.0%
37.46378644 1
 
3.0%
37.467857 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
37.44324776 1
3.0%
37.446771 1
3.0%
37.44788691 1
3.0%
37.44814268 1
3.0%
37.44838287 1
3.0%
37.45058159 1
3.0%
37.45097541 1
3.0%
37.4511891 1
3.0%
37.45122598 1
3.0%
37.451359 1
3.0%
ValueCountFrequency (%)
37.46827725 1
3.0%
37.46804468 1
3.0%
37.467857 1
3.0%
37.46404959 1
3.0%
37.46385022 1
3.0%
37.46378644 1
3.0%
37.46357592 1
3.0%
37.4627146 1
3.0%
37.4621995 1
3.0%
37.46182564 1
3.0%

경도
Real number (ℝ)

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.66524
Minimum126.63689
Maximum126.69668
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-03-18T13:13:59.038611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63689
5-th percentile126.64729
Q1126.65665
median126.65992
Q3126.67791
95-th percentile126.68219
Maximum126.69668
Range0.0597929
Interquartile range (IQR)0.021258

Descriptive statistics

Standard deviation0.013499955
Coefficient of variation (CV)0.00010657979
Kurtosis-0.5301048
Mean126.66524
Median Absolute Deviation (MAD)0.0108753
Skewness0.200465
Sum4179.953
Variance0.00018224878
MonotonicityNot monotonic
2024-03-18T13:13:59.177824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
126.6567456 1
 
3.0%
126.6807951 1
 
3.0%
126.6616169 1
 
3.0%
126.6577765 1
 
3.0%
126.6585365 1
 
3.0%
126.670147 1
 
3.0%
126.6466187 1
 
3.0%
126.6769385 1
 
3.0%
126.6477431 1
 
3.0%
126.6599215 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
126.6368864 1
3.0%
126.6466187 1
3.0%
126.6477431 1
3.0%
126.6490462 1
3.0%
126.6519737 1
3.0%
126.6563035 1
3.0%
126.6565742 1
3.0%
126.656646 1
3.0%
126.65665 1
3.0%
126.656692 1
3.0%
ValueCountFrequency (%)
126.6966793 1
3.0%
126.6828373 1
3.0%
126.6817558 1
3.0%
126.6807951 1
3.0%
126.6798378 1
3.0%
126.679626 1
3.0%
126.6792217 1
3.0%
126.6783776 1
3.0%
126.677908 1
3.0%
126.6771003 1
3.0%

Interactions

2024-03-18T13:13:56.277889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:13:55.731975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:13:56.010908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:13:56.384100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:13:55.869204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:13:56.113462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:13:56.462333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:13:55.934835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:13:56.204313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T13:13:59.286014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번유형업소명도로명주소전화번호위도경도
연번1.0000.6691.0001.0001.0000.3190.498
유형0.6691.0001.0001.0001.0000.0000.000
업소명1.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000
위도0.3190.0001.0001.0001.0001.0000.811
경도0.4980.0001.0001.0001.0000.8111.000
2024-03-18T13:13:59.424038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도유형
연번1.000-0.394-0.1230.384
위도-0.3941.000-0.1470.000
경도-0.123-0.1471.0000.000
유형0.3840.0000.0001.000

Missing values

2024-03-18T13:13:56.571472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:13:56.677653image/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

연번유형업소명도로명주소전화번호위도경도
01세탁업동방세탁인천광역시 미추홀구 수봉로 40032-873-181137.462715126.656746
12이미용업인하뷰티에스테틱인천광역시 미추홀구 석정로 228032-888-025037.467857126.659921
23이미용업종로이발인천광역시 미추홀구 석정로 150-1<NA>37.468277126.651974
34이미용업반도미용실인천광역시 미추홀구 수봉로27번길 4032-867-969037.463576126.656574
45이미용업아빠이발관인천광역시 미추홀구 인주대로366번길 17<NA>37.450582126.6771
56일식신포횟집인천광역시 미추홀구 제일로27번길 3-1032-867-428637.459264126.673866
67중식짜장전설인천광역시 미추홀구 인하로 77번길 33032-861-066037.452653126.657509
78중식김밥짜장인천광역시 미추홀구 주안로 86032-873-823437.46385126.679222
89중식차이나인천광역시 미추홀구 석산로 42032-442-666637.461404126.696679
910중식청해루인천광역시 미추홀구 학익소로61번길 21-19032-876-400737.443248126.671195
연번유형업소명도로명주소전화번호위도경도
2324한식새우물식당인천광역시 미추홀구 미추로19번길 14032-886-523937.461826126.646619
2425한식김밥타운인천광역시 미추홀구 인하로 259032-863-669037.448383126.676939
2526한식소와돼지방인천광역시 미추홀구 인하로 293032-421-124337.448143126.680795
2627한식현대식당인천광역시 미추홀구 미추로36번길 19-1032-888-630037.463786126.647743
2728한식삼삼오오인천광역시 미추홀구 인하로 83032-872-665137.451226126.657631
2829인테리어업㈜채가인천광역시 미추홀구 동주길 120번길 63032-937-926537.451823126.65665
2930한식숯불구이먹방(인하대점)인천광역시 미추홀구 경인남길 30번길 39032-214-454437.451986126.656692
3031한식원조가격파괴인천광역시 미추홀구 경인남길 30번길 40032-872-738037.451752126.656646
3132한식착한탕국인천광역시 미추홀구 인하로 266번길 29032-872-829437.446771126.677908
3233이미용업모디쉬헤어인천광역시 한나루로 489번길 59<NA>37.451359126.664017