Overview

Dataset statistics

Number of variables6
Number of observations91
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory52.5 B

Variable types

Numeric3
Text3

Dataset

Description인천광역시 미추홀구의 한의원에 대한 데이터로 상호명, 도로명주소, 전화번호, 위도, 경도 등의 정보를 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15087079/fileData.do

Alerts

연번 has unique valuesUnique
의료기관명 has unique valuesUnique
도로명주소 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:31:38.592447
Analysis finished2023-12-12 16:31:40.065166
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46
Minimum1
Maximum91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-13T01:31:40.145335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.5
Q123.5
median46
Q368.5
95-th percentile86.5
Maximum91
Range90
Interquartile range (IQR)45

Descriptive statistics

Standard deviation26.41338
Coefficient of variation (CV)0.57420392
Kurtosis-1.2
Mean46
Median Absolute Deviation (MAD)23
Skewness0
Sum4186
Variance697.66667
MonotonicityStrictly increasing
2023-12-13T01:31:40.266428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
59 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
61 1
 
1.1%
Other values (81) 81
89.0%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%
82 1
1.1%

의료기관명
Text

UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
2023-12-13T01:31:40.483514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.6153846
Min length4

Characters and Unicode

Total characters511
Distinct characters111
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)100.0%

Sample

1st row감초당한의원
2nd row감초한의원
3rd row거북이한의원
4th row경희강생당한의원
5th row경희금강한의원
ValueCountFrequency (%)
감초당한의원 1
 
1.1%
쑥향한의원 1
 
1.1%
자연봄한의원 1
 
1.1%
임배문한의원 1
 
1.1%
임국경한의원 1
 
1.1%
일진두드림한의원 1
 
1.1%
인천시원한의원 1
 
1.1%
인제한의원 1
 
1.1%
익생춘한의원 1
 
1.1%
우리한의원 1
 
1.1%
Other values (81) 81
89.0%
2023-12-13T01:31:40.896329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 93
18.2%
의 92
18.0%
한 91
17.8%
경 10
 
2.0%
희 9
 
1.8%
제 9
 
1.8%
당 8
 
1.6%
인 8
 
1.6%
동 6
 
1.2%
성 6
 
1.2%
Other values (101) 179
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 511
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 93
18.2%
의 92
18.0%
한 91
17.8%
경 10
 
2.0%
희 9
 
1.8%
제 9
 
1.8%
당 8
 
1.6%
인 8
 
1.6%
동 6
 
1.2%
성 6
 
1.2%
Other values (101) 179
35.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 511
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 93
18.2%
의 92
18.0%
한 91
17.8%
경 10
 
2.0%
희 9
 
1.8%
제 9
 
1.8%
당 8
 
1.6%
인 8
 
1.6%
동 6
 
1.2%
성 6
 
1.2%
Other values (101) 179
35.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 511
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 93
18.2%
의 92
18.0%
한 91
17.8%
경 10
 
2.0%
희 9
 
1.8%
제 9
 
1.8%
당 8
 
1.6%
인 8
 
1.6%
동 6
 
1.2%
성 6
 
1.2%
Other values (101) 179
35.0%

도로명주소
Text

UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
2023-12-13T01:31:41.195275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length40
Mean length28.626374
Min length23

Characters and Unicode

Total characters2605
Distinct characters126
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)100.0%

Sample

1st row인천광역시 미추홀구 인하로 276 (주안동,남부종합 2층)
2nd row인천광역시 미추홀구 소성로 136 (학익동)
3rd row인천광역시 미추홀구 매소홀로 442 (학익동)
4th row인천광역시 미추홀구 인하로 304 (주안동)
5th row인천광역시 미추홀구 소성로 333 (문학동)
ValueCountFrequency (%)
인천광역시 91
17.7%
미추홀구 91
17.7%
주안동 41
 
8.0%
용현동 23
 
4.5%
경인로 12
 
2.3%
도화동 11
 
2.1%
2층 9
 
1.7%
인하로 8
 
1.6%
경원대로 7
 
1.4%
인주대로 7
 
1.4%
Other values (159) 215
41.7%
2023-12-13T01:31:41.643920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
425
 
16.3%
인 120
 
4.6%
홀 102
 
3.9%
미 98
 
3.8%
추 98
 
3.8%
( 93
 
3.6%
구 93
 
3.6%
) 93
 
3.6%
광 92
 
3.5%
역 91
 
3.5%
Other values (116) 1300
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1579
60.6%
Space Separator 425
 
16.3%
Decimal Number 355
 
13.6%
Open Punctuation 93
 
3.6%
Close Punctuation 93
 
3.6%
Other Punctuation 42
 
1.6%
Dash Punctuation 13
 
0.5%
Uppercase Letter 4
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 120
 
7.6%
홀 102
 
6.5%
미 98
 
6.2%
추 98
 
6.2%
구 93
 
5.9%
광 92
 
5.8%
역 91
 
5.8%
시 91
 
5.8%
천 91
 
5.8%
동 91
 
5.8%
Other values (96) 612
38.8%
Decimal Number
ValueCountFrequency (%)
2 63
17.7%
1 54
15.2%
3 53
14.9%
4 51
14.4%
6 29
8.2%
0 27
7.6%
5 25
 
7.0%
7 24
 
6.8%
8 18
 
5.1%
9 11
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
I 1
25.0%
P 1
25.0%
N 1
25.0%
E 1
25.0%
Space Separator
ValueCountFrequency (%)
425
100.0%
Open Punctuation
ValueCountFrequency (%)
( 93
100.0%
Close Punctuation
ValueCountFrequency (%)
) 93
100.0%
Other Punctuation
ValueCountFrequency (%)
, 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1579
60.6%
Common 1022
39.2%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 120
 
7.6%
홀 102
 
6.5%
미 98
 
6.2%
추 98
 
6.2%
구 93
 
5.9%
광 92
 
5.8%
역 91
 
5.8%
시 91
 
5.8%
천 91
 
5.8%
동 91
 
5.8%
Other values (96) 612
38.8%
Common
ValueCountFrequency (%)
425
41.6%
( 93
 
9.1%
) 93
 
9.1%
2 63
 
6.2%
1 54
 
5.3%
3 53
 
5.2%
4 51
 
5.0%
, 42
 
4.1%
6 29
 
2.8%
0 27
 
2.6%
Other values (6) 92
 
9.0%
Latin
ValueCountFrequency (%)
I 1
25.0%
P 1
25.0%
N 1
25.0%
E 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1579
60.6%
ASCII 1026
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
425
41.4%
( 93
 
9.1%
) 93
 
9.1%
2 63
 
6.1%
1 54
 
5.3%
3 53
 
5.2%
4 51
 
5.0%
, 42
 
4.1%
6 29
 
2.8%
0 27
 
2.6%
Other values (10) 96
 
9.4%
Hangul
ValueCountFrequency (%)
인 120
 
7.6%
홀 102
 
6.5%
미 98
 
6.2%
추 98
 
6.2%
구 93
 
5.9%
광 92
 
5.8%
역 91
 
5.8%
시 91
 
5.8%
천 91
 
5.8%
동 91
 
5.8%
Other values (96) 612
38.8%

전화번호
Text

UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
2023-12-13T01:31:41.924910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1092
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

Unique91 ?
Unique (%)100.0%

Sample

1st row032-872-7475
2nd row032-875-8900
3rd row032-861-7733
4th row032-422-8800
5th row032-435-6555
ValueCountFrequency (%)
032-872-7475 1
 
1.1%
032-872-3193 1
 
1.1%
032-426-9200 1
 
1.1%
032-881-9073 1
 
1.1%
032-885-7510 1
 
1.1%
032-883-0128 1
 
1.1%
032-888-5200 1
 
1.1%
032-425-5545 1
 
1.1%
032-875-1721 1
 
1.1%
032-424-8455 1
 
1.1%
Other values (81) 81
89.0%
2023-12-13T01:31:42.311946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 182
16.7%
2 153
14.0%
0 147
13.5%
3 137
12.5%
8 129
11.8%
7 76
7.0%
5 69
 
6.3%
4 62
 
5.7%
1 60
 
5.5%
6 46
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 910
83.3%
Dash Punctuation 182
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 153
16.8%
0 147
16.2%
3 137
15.1%
8 129
14.2%
7 76
8.4%
5 69
7.6%
4 62
6.8%
1 60
 
6.6%
6 46
 
5.1%
9 31
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1092
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 182
16.7%
2 153
14.0%
0 147
13.5%
3 137
12.5%
8 129
11.8%
7 76
7.0%
5 69
 
6.3%
4 62
 
5.7%
1 60
 
5.5%
6 46
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1092
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 182
16.7%
2 153
14.0%
0 147
13.5%
3 137
12.5%
8 129
11.8%
7 76
7.0%
5 69
 
6.3%
4 62
 
5.7%
1 60
 
5.5%
6 46
 
4.2%

위도
Real number (ℝ)

Distinct87
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.454833
Minimum37.437603
Maximum37.470134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-13T01:31:42.538299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.437603
5-th percentile37.442586
Q137.448524
median37.456227
Q337.459972
95-th percentile37.466507
Maximum37.470134
Range0.03253132
Interquartile range (IQR)0.011447975

Descriptive statistics

Standard deviation0.0078345795
Coefficient of variation (CV)0.00020917406
Kurtosis-0.83956574
Mean37.454833
Median Absolute Deviation (MAD)0.00686209
Skewness-0.014528252
Sum3408.3898
Variance6.1380635 × 10-5
MonotonicityNot monotonic
2023-12-13T01:31:42.713948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.44853011 2
 
2.2%
37.44779291 2
 
2.2%
37.44814624 2
 
2.2%
37.4701339 2
 
2.2%
37.44786721 1
 
1.1%
37.45866508 1
 
1.1%
37.44862004 1
 
1.1%
37.46196514 1
 
1.1%
37.45071575 1
 
1.1%
37.4566531 1
 
1.1%
Other values (77) 77
84.6%
ValueCountFrequency (%)
37.43760258 1
1.1%
37.43949224 1
1.1%
37.43953362 1
1.1%
37.4414509 1
1.1%
37.44250258 1
1.1%
37.44266927 1
1.1%
37.44290208 1
1.1%
37.44331142 1
1.1%
37.44435212 1
1.1%
37.44483568 1
1.1%
ValueCountFrequency (%)
37.4701339 2
2.2%
37.4681054 1
1.1%
37.4679645 1
1.1%
37.46652442 1
1.1%
37.46648961 1
1.1%
37.46641324 1
1.1%
37.46633226 1
1.1%
37.46599819 1
1.1%
37.46569769 1
1.1%
37.4651559 1
1.1%

경도
Real number (ℝ)

Distinct87
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.66872
Minimum126.63367
Maximum126.69668
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-13T01:31:42.872328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63367
5-th percentile126.63724
Q1126.65177
median126.67181
Q3126.68263
95-th percentile126.69461
Maximum126.69668
Range0.0630079
Interquartile range (IQR)0.03086625

Descriptive statistics

Standard deviation0.018686322
Coefficient of variation (CV)0.00014752121
Kurtosis-1.0577202
Mean126.66872
Median Absolute Deviation (MAD)0.0148903
Skewness-0.35047317
Sum11526.853
Variance0.00034917863
MonotonicityNot monotonic
2023-12-13T01:31:43.063331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6903431 2
 
2.2%
126.6492579 2
 
2.2%
126.6491202 2
 
2.2%
126.66299 2
 
2.2%
126.6787198 1
 
1.1%
126.6804785 1
 
1.1%
126.6799962 1
 
1.1%
126.6797888 1
 
1.1%
126.6859272 1
 
1.1%
126.6509714 1
 
1.1%
Other values (77) 77
84.6%
ValueCountFrequency (%)
126.6336714 1
1.1%
126.6341373 1
1.1%
126.6341424 1
1.1%
126.6356716 1
1.1%
126.6371097 1
1.1%
126.6373623 1
1.1%
126.6378064 1
1.1%
126.6378889 1
1.1%
126.6380872 1
1.1%
126.6385354 1
1.1%
ValueCountFrequency (%)
126.6966793 1
1.1%
126.6962602 1
1.1%
126.6962105 1
1.1%
126.6952992 1
1.1%
126.6947749 1
1.1%
126.6944484 1
1.1%
126.6933886 1
1.1%
126.6928626 1
1.1%
126.6915265 1
1.1%
126.691111 1
1.1%

Interactions

2023-12-13T01:31:39.673916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:38.894459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.439578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.746074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:38.954465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.520234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.830833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.357955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.595292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:31:43.192809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번의료기관명도로명주소전화번호위도경도
연번1.0001.0001.0001.0000.2840.189
의료기관명1.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
위도0.2841.0001.0001.0001.0000.700
경도0.1891.0001.0001.0000.7001.000
2023-12-13T01:31:43.315917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.160-0.254
위도0.1601.0000.076
경도-0.2540.0761.000

Missing values

2023-12-13T01:31:39.930795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:31:40.028773image/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

연번의료기관명도로명주소전화번호위도경도
01감초당한의원인천광역시 미추홀구 인하로 276 (주안동,남부종합 2층)032-872-747537.447867126.67872
12감초한의원인천광역시 미추홀구 소성로 136 (학익동)032-875-890037.442902126.663685
23거북이한의원인천광역시 미추홀구 매소홀로 442 (학익동)032-861-773337.439534126.671036
34경희강생당한의원인천광역시 미추홀구 인하로 304 (주안동)032-422-880037.447798126.681787
45경희금강한의원인천광역시 미추홀구 소성로 333 (문학동)032-435-655537.437603126.684256
56경희만석한의원인천광역시 미추홀구 인주대로 261 (주안동)032-221-955537.45303126.665792
67경희보배한의원인천광역시 미추홀구 인하로 261 (주안동)032-872-168837.448409126.677239
78경희삼성한의원인천광역시 미추홀구 경원대로 740, 502호 (주안동)032-205-700037.44853126.690343
89경희우정한의원인천광역시 미추홀구 제일로 38 (도화동)032-863-007537.458584126.674401
910경희최한의원인천광역시 미추홀구 매소홀로 355 (학익동)032-875-759437.441451126.661976
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8182푸른솔한의원인천광역시 미추홀구 아암대로29번길 47 (용현동)032-882-849437.45747126.639249
8283하나로한의원인천광역시 미추홀구 토금중로 13 (용현동)032-885-243437.453868126.635672
8384학익한의원인천광역시 미추홀구 매소홀로 446 (학익동)032-875-959537.439492126.671744
8485행림한의원인천광역시 미추홀구 능해길 11 (용현동)032-710-107537.459654126.638535
8586현한의원인천광역시 미추홀구 인주대로 460 (주안동)032-431-111637.450622126.68781
8687홍익한의원인천광역시 미추홀구 길파로 7 (3, 4층)층 (주안동)032-715-740337.466413126.678963
8788홍일한의원인천광역시 미추홀구 제일로 26 (도화동)032-862-923637.45871126.673171
8889홍제한의원인천광역시 미추홀구 미추홀대로 577 (주안동)032-864-228837.44879126.679351
8990홍한의원인천광역시 미추홀구 경인로 386 (주안동)032-429-424637.458073126.682778
9091흠당한의원인천광역시 미추홀구 독배로 309, 노블레스타워 403호 (용현동)032-573-758837.447793126.649258