Overview

Dataset statistics

Number of variables6
Number of observations59
Missing cells24
Missing cells (%)6.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory53.2 B

Variable types

Numeric3
Text3

Dataset

Description인천광역시 미추홀구 셀프빨래방 현황에 대한 데이터입니다. 상호명, 도로명주소, 전화번호, 죄표값 등의 항목을 제공하고 있습니다.
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15087031/fileData.do

Alerts

전화번호 has 24 (40.7%) missing valuesMissing
연번 has unique valuesUnique
상호명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:56:53.919487
Analysis finished2023-12-12 13:56:55.319227
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30
Minimum1
Maximum59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2023-12-12T22:56:55.393097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.9
Q115.5
median30
Q344.5
95-th percentile56.1
Maximum59
Range58
Interquartile range (IQR)29

Descriptive statistics

Standard deviation17.175564
Coefficient of variation (CV)0.5725188
Kurtosis-1.2
Mean30
Median Absolute Deviation (MAD)15
Skewness0
Sum1770
Variance295
MonotonicityStrictly increasing
2023-12-12T22:56:55.581449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.7%
2 1
 
1.7%
33 1
 
1.7%
34 1
 
1.7%
35 1
 
1.7%
36 1
 
1.7%
37 1
 
1.7%
38 1
 
1.7%
39 1
 
1.7%
40 1
 
1.7%
Other values (49) 49
83.1%
ValueCountFrequency (%)
1 1
1.7%
2 1
1.7%
3 1
1.7%
4 1
1.7%
5 1
1.7%
6 1
1.7%
7 1
1.7%
8 1
1.7%
9 1
1.7%
10 1
1.7%
ValueCountFrequency (%)
59 1
1.7%
58 1
1.7%
57 1
1.7%
56 1
1.7%
55 1
1.7%
54 1
1.7%
53 1
1.7%
52 1
1.7%
51 1
1.7%
50 1
1.7%

상호명
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-12T22:56:55.826624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length13.983051
Min length5

Characters and Unicode

Total characters825
Distinct characters117
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)100.0%

Sample

1st row코인워시24 인천인하대점
2nd row워시테리아 인천문학점
3rd row위니아24크린샵 인천용현점
4th row워시테리아 인천용현점
5th row셀프빨래방 주안점
ValueCountFrequency (%)
셀프빨래방 18
 
12.9%
워시엔조이 9
 
6.4%
크린토피아 8
 
5.7%
주안점 6
 
4.3%
인천용현점 6
 
4.3%
코인워시 6
 
4.3%
인천숭의점 4
 
2.9%
제물포점 3
 
2.1%
크린업24 3
 
2.1%
인하대점 3
 
2.1%
Other values (57) 74
52.9%
2023-12-12T22:56:56.243840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
 
9.8%
점 51
 
6.2%
인 48
 
5.8%
시 43
 
5.2%
워 36
 
4.4%
천 33
 
4.0%
빨 30
 
3.6%
프 30
 
3.6%
래 30
 
3.6%
방 30
 
3.6%
Other values (107) 413
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 688
83.4%
Space Separator 81
 
9.8%
Decimal Number 35
 
4.2%
Uppercase Letter 13
 
1.6%
Lowercase Letter 8
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 51
 
7.4%
인 48
 
7.0%
시 43
 
6.2%
워 36
 
5.2%
천 33
 
4.8%
빨 30
 
4.4%
프 30
 
4.4%
래 30
 
4.4%
방 30
 
4.4%
셀 27
 
3.9%
Other values (86) 330
48.0%
Uppercase Letter
ValueCountFrequency (%)
M 4
30.8%
A 2
15.4%
P 2
15.4%
H 1
 
7.7%
E 1
 
7.7%
T 1
 
7.7%
L 1
 
7.7%
D 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
4 11
31.4%
2 11
31.4%
6 4
 
11.4%
3 4
 
11.4%
5 4
 
11.4%
1 1
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
a 2
25.0%
y 2
25.0%
u 1
12.5%
n 1
12.5%
d 1
12.5%
r 1
12.5%
Space Separator
ValueCountFrequency (%)
81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 688
83.4%
Common 116
 
14.1%
Latin 21
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 51
 
7.4%
인 48
 
7.0%
시 43
 
6.2%
워 36
 
5.2%
천 33
 
4.8%
빨 30
 
4.4%
프 30
 
4.4%
래 30
 
4.4%
방 30
 
4.4%
셀 27
 
3.9%
Other values (86) 330
48.0%
Latin
ValueCountFrequency (%)
M 4
19.0%
a 2
9.5%
A 2
9.5%
y 2
9.5%
P 2
9.5%
H 1
 
4.8%
E 1
 
4.8%
T 1
 
4.8%
L 1
 
4.8%
u 1
 
4.8%
Other values (4) 4
19.0%
Common
ValueCountFrequency (%)
81
69.8%
4 11
 
9.5%
2 11
 
9.5%
6 4
 
3.4%
3 4
 
3.4%
5 4
 
3.4%
1 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 688
83.4%
ASCII 137
 
16.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
59.1%
4 11
 
8.0%
2 11
 
8.0%
6 4
 
2.9%
3 4
 
2.9%
5 4
 
2.9%
M 4
 
2.9%
a 2
 
1.5%
A 2
 
1.5%
y 2
 
1.5%
Other values (11) 12
 
8.8%
Hangul
ValueCountFrequency (%)
점 51
 
7.4%
인 48
 
7.0%
시 43
 
6.2%
워 36
 
5.2%
천 33
 
4.8%
빨 30
 
4.4%
프 30
 
4.4%
래 30
 
4.4%
방 30
 
4.4%
셀 27
 
3.9%
Other values (86) 330
48.0%

도로명주소
Text

Distinct58
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-12T22:56:56.502626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length31
Mean length23.677966
Min length17

Characters and Unicode

Total characters1397
Distinct characters113
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)96.6%

Sample

1st row인천광역시 미추홀구 인하로91번길 48
2nd row인천광역시 미추홀구 소성로 336-13
3rd row인천광역시 미추홀구 토금중로 50
4th row인천광역시 미추홀구 인하로133번길 46
5th row인천광역시 미추홀구 인주대로417번길 99 구룸
ValueCountFrequency (%)
인천광역시 59
21.1%
미추홀구 59
21.1%
1층 13
 
4.6%
인주대로 4
 
1.4%
소성로 4
 
1.4%
102호 3
 
1.1%
석정로 3
 
1.1%
주안로 3
 
1.1%
101호 3
 
1.1%
16 3
 
1.1%
Other values (114) 126
45.0%
2023-12-12T22:56:56.949760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
221
 
15.8%
인 77
 
5.5%
1 77
 
5.5%
천 64
 
4.6%
홀 62
 
4.4%
시 61
 
4.4%
미 61
 
4.4%
추 61
 
4.4%
구 60
 
4.3%
광 59
 
4.2%
Other values (103) 594
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 890
63.7%
Decimal Number 274
 
19.6%
Space Separator 221
 
15.8%
Dash Punctuation 6
 
0.4%
Uppercase Letter 3
 
0.2%
Open Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 77
 
8.7%
천 64
 
7.2%
홀 62
 
7.0%
시 61
 
6.9%
미 61
 
6.9%
추 61
 
6.9%
구 60
 
6.7%
광 59
 
6.6%
역 59
 
6.6%
로 57
 
6.4%
Other values (86) 269
30.2%
Decimal Number
ValueCountFrequency (%)
1 77
28.1%
2 35
12.8%
4 32
11.7%
3 32
11.7%
8 21
 
7.7%
6 19
 
6.9%
0 18
 
6.6%
5 14
 
5.1%
7 14
 
5.1%
9 12
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
221
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 890
63.7%
Common 504
36.1%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 77
 
8.7%
천 64
 
7.2%
홀 62
 
7.0%
시 61
 
6.9%
미 61
 
6.9%
추 61
 
6.9%
구 60
 
6.7%
광 59
 
6.6%
역 59
 
6.6%
로 57
 
6.4%
Other values (86) 269
30.2%
Common
ValueCountFrequency (%)
221
43.8%
1 77
 
15.3%
2 35
 
6.9%
4 32
 
6.3%
3 32
 
6.3%
8 21
 
4.2%
6 19
 
3.8%
0 18
 
3.6%
5 14
 
2.8%
7 14
 
2.8%
Other values (5) 21
 
4.2%
Latin
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 890
63.7%
ASCII 507
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
221
43.6%
1 77
 
15.2%
2 35
 
6.9%
4 32
 
6.3%
3 32
 
6.3%
8 21
 
4.1%
6 19
 
3.7%
0 18
 
3.6%
5 14
 
2.8%
7 14
 
2.8%
Other values (7) 24
 
4.7%
Hangul
ValueCountFrequency (%)
인 77
 
8.7%
천 64
 
7.2%
홀 62
 
7.0%
시 61
 
6.9%
미 61
 
6.9%
추 61
 
6.9%
구 60
 
6.7%
광 59
 
6.6%
역 59
 
6.6%
로 57
 
6.4%
Other values (86) 269
30.2%

전화번호
Text

MISSING 

Distinct34
Distinct (%)97.1%
Missing24
Missing (%)40.7%
Memory size604.0 B
2023-12-12T22:56:57.191854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13
Min length9

Characters and Unicode

Total characters455
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

Unique33 ?
Unique (%)94.3%

Sample

1st row032-867-8285
2nd row1577-8394
3rd row1577-8394
4th row032-875-2087
5th row0507-1403-9629
ValueCountFrequency (%)
1577-8394 2
 
5.7%
032-867-8285 1
 
2.9%
0507-1422-8472 1
 
2.9%
0507-1439-7891 1
 
2.9%
032-423-3062 1
 
2.9%
032-866-7900 1
 
2.9%
032-423-5200 1
 
2.9%
0507-1323-0660 1
 
2.9%
0507-1365-6326 1
 
2.9%
032-875-2087 1
 
2.9%
Other values (24) 24
68.6%
2023-12-12T22:56:57.586241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 77
16.9%
- 68
14.9%
3 51
11.2%
7 43
9.5%
1 42
9.2%
5 40
8.8%
8 33
7.3%
2 33
7.3%
4 25
 
5.5%
9 22
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 387
85.1%
Dash Punctuation 68
 
14.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 77
19.9%
3 51
13.2%
7 43
11.1%
1 42
10.9%
5 40
10.3%
8 33
8.5%
2 33
8.5%
4 25
 
6.5%
9 22
 
5.7%
6 21
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 455
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 77
16.9%
- 68
14.9%
3 51
11.2%
7 43
9.5%
1 42
9.2%
5 40
8.8%
8 33
7.3%
2 33
7.3%
4 25
 
5.5%
9 22
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 455
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 77
16.9%
- 68
14.9%
3 51
11.2%
7 43
9.5%
1 42
9.2%
5 40
8.8%
8 33
7.3%
2 33
7.3%
4 25
 
5.5%
9 22
 
4.8%

위도
Real number (ℝ)

Distinct58
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.456499
Minimum37.437101
Maximum37.476986
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2023-12-12T22:56:57.775872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.437101
5-th percentile37.439736
Q137.450512
median37.458648
Q337.462704
95-th percentile37.468986
Maximum37.476986
Range0.03988443
Interquartile range (IQR)0.012191925

Descriptive statistics

Standard deviation0.0093151274
Coefficient of variation (CV)0.00024869188
Kurtosis-0.32222005
Mean37.456499
Median Absolute Deviation (MAD)0.00710784
Skewness-0.12053127
Sum2209.9335
Variance8.6771599 × 10-5
MonotonicityNot monotonic
2023-12-12T22:56:57.944327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.45388937 2
 
3.4%
37.45131097 1
 
1.7%
37.46575593 1
 
1.7%
37.45062473 1
 
1.7%
37.44530576 1
 
1.7%
37.46073913 1
 
1.7%
37.46133281 1
 
1.7%
37.46415835 1
 
1.7%
37.45870167 1
 
1.7%
37.44825595 1
 
1.7%
Other values (48) 48
81.4%
ValueCountFrequency (%)
37.4371012 1
1.7%
37.43743863 1
1.7%
37.43953362 1
1.7%
37.43975877 1
1.7%
37.44108555 1
1.7%
37.44187234 1
1.7%
37.44517862 1
1.7%
37.44530576 1
1.7%
37.44749098 1
1.7%
37.44756775 1
1.7%
ValueCountFrequency (%)
37.47698563 1
1.7%
37.47579295 1
1.7%
37.4740307 1
1.7%
37.46842501 1
1.7%
37.46774176 1
1.7%
37.46740988 1
1.7%
37.46664869 1
1.7%
37.46651648 1
1.7%
37.46575593 1
1.7%
37.46569701 1
1.7%

경도
Real number (ℝ)

Distinct58
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.6674
Minimum126.63563
Maximum126.69494
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2023-12-12T22:56:58.115709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63563
5-th percentile126.6449
Q1126.65556
median126.6689
Q3126.68087
95-th percentile126.69071
Maximum126.69494
Range0.059313
Interquartile range (IQR)0.0253091

Descriptive statistics

Standard deviation0.015513881
Coefficient of variation (CV)0.0001224773
Kurtosis-1.0215927
Mean126.6674
Median Absolute Deviation (MAD)0.0136218
Skewness-0.15613563
Sum7473.3763
Variance0.00024068049
MonotonicityNot monotonic
2023-12-12T22:56:58.274349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6616698 2
 
3.4%
126.6604188 1
 
1.7%
126.6468609 1
 
1.7%
126.6356306 1
 
1.7%
126.6910339 1
 
1.7%
126.6501048 1
 
1.7%
126.6494371 1
 
1.7%
126.683425 1
 
1.7%
126.6710907 1
 
1.7%
126.6865226 1
 
1.7%
Other values (48) 48
81.4%
ValueCountFrequency (%)
126.6356306 1
1.7%
126.6385435 1
1.7%
126.6385843 1
1.7%
126.6456051 1
1.7%
126.6462403 1
1.7%
126.6464872 1
1.7%
126.6468609 1
1.7%
126.647698 1
1.7%
126.6485908 1
1.7%
126.6494371 1
1.7%
ValueCountFrequency (%)
126.6949436 1
1.7%
126.6916542 1
1.7%
126.6910339 1
1.7%
126.6906755 1
1.7%
126.6868028 1
1.7%
126.6865226 1
1.7%
126.6856698 1
1.7%
126.6854021 1
1.7%
126.6846407 1
1.7%
126.684151 1
1.7%

Interactions

2023-12-12T22:56:54.840422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:56:54.219680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:56:54.507850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:56:54.937688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:56:54.309785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:56:54.625153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:56:55.063967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:56:54.417006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:56:54.730425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:56:58.390038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명도로명주소전화번호위도경도
연번1.0001.0000.9381.0000.2610.622
상호명1.0001.0001.0001.0001.0001.000
도로명주소0.9381.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0000.9360.966
위도0.2611.0001.0000.9361.0000.371
경도0.6221.0001.0000.9660.3711.000
2023-12-12T22:56:58.506952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.112-0.020
위도0.1121.000-0.135
경도-0.020-0.1351.000

Missing values

2023-12-12T22:56:55.172361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:56:55.276124image/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

연번상호명도로명주소전화번호위도경도
01코인워시24 인천인하대점인천광역시 미추홀구 인하로91번길 48032-867-828537.451311126.660419
12워시테리아 인천문학점인천광역시 미추홀구 소성로 336-131577-839437.437101126.684641
23위니아24크린샵 인천용현점인천광역시 미추홀구 토금중로 50<NA>37.452109126.638543
34워시테리아 인천용현점인천광역시 미추홀구 인하로133번길 461577-839437.451417126.66377
45셀프빨래방 주안점인천광역시 미추홀구 인주대로417번길 99 구룸<NA>37.455862126.683206
56워시엔조이 셀프빨래방 인천문학점인천광역시 미추홀구 소성로 288-5 롯데탑스빌<NA>37.437439126.679148
67드림시티셀프빨래방인천광역시 미추홀구 염창로 38032-875-208737.465697126.677697
78셀프빨래방 석바위점인천광역시 미추홀구 주안동로25번길 4<NA>37.460776126.68567
89Laundry Day 셀프빨래방인천광역시 미추홀구 주안로 116 지하1층 B107호 (주안동, 주안리가스퀘어)0507-1403-962937.463477126.682519
910더런드리 셀프빨래방 제물포점인천광역시 미추홀구 경인로41번길 18-23 1층032-886-891637.46524126.647698
연번상호명도로명주소전화번호위도경도
4950크린토피아 코인워시 인천주안더월드스테이트점인천광역시 미추홀구 경원대로864번길 40 1층032-423-520037.460422126.691654
5051크린토피아 코인워시 인천도화금강펜테리움점인천광역시 미추홀구 염전로202번길 48-37032-866-790037.475793126.660885
5152크린토피아 코인워시 인천관교점인천광역시 미추홀구 주승로 238032-423-306237.441872126.694944
5253워시엔조이 인천숭의역점인천광역시 미추홀구 장천로 6 1층0507-1439-789137.458648126.645605
5354워시프렌즈 주안점인천광역시 미추홀구 석정로 365<NA>37.46741126.67633
5455워시프렌즈 인천주안1동점인천광역시 미추홀구 주안서로 36 휴오피스텔0507-1422-847237.461935126.678029
5556크린토피아 코인워시365 인천주안센트레빌점인천광역시 미추홀구 석정로 437 1층<NA>37.466649126.684151
5657크린토피아 코인워시 인천숭의점인천광역시 미추홀구 장천로14번길 2032-891-700137.458934126.646487
5758크린토피아 코인워시365 인천도화점인천광역시 미추홀구 경인로 314<NA>37.459332126.6748
5859크린토피아 코인워시 인천학익신동아점인천광역시 미추홀구 매소홀로 473032-875-933937.439759126.674841