Overview

Dataset statistics

Number of variables7
Number of observations23
Missing cells2
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory64.7 B

Variable types

Numeric3
Categorical1
Text3

Dataset

Description경기도 포천시에서 제공하는 한의원 현황(연번, 구분, 한의원명, 한의원 주소, 한의원 위경도, 한의원 전화번호 등)데이터 입니다.
Author경기도 포천시
URLhttps://www.data.go.kr/data/15104475/fileData.do

Alerts

구분 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
전화번호 has 2 (8.7%) missing valuesMissing
연번 has unique valuesUnique
한의원명 has unique valuesUnique
주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:53:28.524657
Analysis finished2023-12-12 04:53:29.775091
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T13:53:29.845063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2023-12-12T13:53:29.954568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
23 1
 
4.3%
22 1
 
4.3%
21 1
 
4.3%
20 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
16 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
6 1
4.3%
7 1
4.3%
8 1
4.3%
9 1
4.3%
10 1
4.3%
ValueCountFrequency (%)
23 1
4.3%
22 1
4.3%
21 1
4.3%
20 1
4.3%
19 1
4.3%
18 1
4.3%
17 1
4.3%
16 1
4.3%
15 1
4.3%
14 1
4.3%

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
한의원
23 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한의원 23
100.0%

Length

2023-12-12T13:53:30.081541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:30.184305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한의원 23
100.0%

한의원명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T13:53:30.343870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6
Min length4

Characters and Unicode

Total characters138
Distinct characters56
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row경희서울한의원
2nd row우리경희한의원
3rd row이엽한의원
4th row정한의원
5th row동의보감한의원
ValueCountFrequency (%)
경희서울한의원 1
 
4.0%
수한의원 1
 
4.0%
신성한의원 1
 
4.0%
일동대영한의원 1
 
4.0%
경희장백한의원 1
 
4.0%
대곡한의원 1
 
4.0%
송우한의원 1
 
4.0%
솔모루한의원 1
 
4.0%
한의원 1
 
4.0%
바로 1
 
4.0%
Other values (15) 15
60.0%
2023-12-12T13:53:30.632588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
의 24
17.4%
한 23
16.7%
원 23
16.7%
경 3
 
2.2%
리 3
 
2.2%
동 3
 
2.2%
이 3
 
2.2%
희 3
 
2.2%
우 3
 
2.2%
2
 
1.4%
Other values (46) 48
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 136
98.6%
Space Separator 2
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 24
17.6%
한 23
16.9%
원 23
16.9%
경 3
 
2.2%
리 3
 
2.2%
동 3
 
2.2%
이 3
 
2.2%
희 3
 
2.2%
우 3
 
2.2%
해 2
 
1.5%
Other values (45) 46
33.8%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 136
98.6%
Common 2
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 24
17.6%
한 23
16.9%
원 23
16.9%
경 3
 
2.2%
리 3
 
2.2%
동 3
 
2.2%
이 3
 
2.2%
희 3
 
2.2%
우 3
 
2.2%
해 2
 
1.5%
Other values (45) 46
33.8%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136
98.6%
ASCII 2
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
의 24
17.6%
한 23
16.9%
원 23
16.9%
경 3
 
2.2%
리 3
 
2.2%
동 3
 
2.2%
이 3
 
2.2%
희 3
 
2.2%
우 3
 
2.2%
해 2
 
1.5%
Other values (45) 46
33.8%
ASCII
ValueCountFrequency (%)
2
100.0%

주소
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T13:53:30.823298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length23.913043
Min length18

Characters and Unicode

Total characters550
Distinct characters66
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

Unique23 ?
Unique (%)100.0%

Sample

1st row경기도 포천시 소흘읍 송우로 79, 삼화프라자 3층 303호
2nd row경기도 포천시 소흘읍 솔모루로 44, 2층
3rd row경기도 포천시 호국로 997, 2층 (선단동)
4th row경기도 포천시 가산면 가산로 380
5th row경기도 포천시 영북면 운천안길 31-1
ValueCountFrequency (%)
경기도 23
16.9%
포천시 23
16.9%
소흘읍 10
 
7.4%
2층 7
 
5.1%
솔모루로 5
 
3.7%
신읍동 4
 
2.9%
송우로 3
 
2.2%
1층 3
 
2.2%
중앙로 3
 
2.2%
3층 2
 
1.5%
Other values (48) 53
39.0%
2023-12-12T13:53:31.156105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
20.5%
천 25
 
4.5%
포 24
 
4.4%
경 23
 
4.2%
도 23
 
4.2%
시 23
 
4.2%
기 23
 
4.2%
로 20
 
3.6%
1 18
 
3.3%
읍 16
 
2.9%
Other values (56) 242
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 321
58.4%
Space Separator 113
 
20.5%
Decimal Number 84
 
15.3%
Other Punctuation 15
 
2.7%
Close Punctuation 7
 
1.3%
Open Punctuation 7
 
1.3%
Dash Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 25
 
7.8%
포 24
 
7.5%
경 23
 
7.2%
도 23
 
7.2%
시 23
 
7.2%
기 23
 
7.2%
로 20
 
6.2%
읍 16
 
5.0%
층 14
 
4.4%
동 12
 
3.7%
Other values (41) 118
36.8%
Decimal Number
ValueCountFrequency (%)
1 18
21.4%
2 11
13.1%
4 10
11.9%
3 9
10.7%
9 8
9.5%
0 8
9.5%
8 6
 
7.1%
7 5
 
6.0%
5 5
 
6.0%
6 4
 
4.8%
Space Separator
ValueCountFrequency (%)
113
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 321
58.4%
Common 229
41.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 25
 
7.8%
포 24
 
7.5%
경 23
 
7.2%
도 23
 
7.2%
시 23
 
7.2%
기 23
 
7.2%
로 20
 
6.2%
읍 16
 
5.0%
층 14
 
4.4%
동 12
 
3.7%
Other values (41) 118
36.8%
Common
ValueCountFrequency (%)
113
49.3%
1 18
 
7.9%
, 15
 
6.6%
2 11
 
4.8%
4 10
 
4.4%
3 9
 
3.9%
9 8
 
3.5%
0 8
 
3.5%
) 7
 
3.1%
( 7
 
3.1%
Other values (5) 23
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 321
58.4%
ASCII 229
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
49.3%
1 18
 
7.9%
, 15
 
6.6%
2 11
 
4.8%
4 10
 
4.4%
3 9
 
3.9%
9 8
 
3.5%
0 8
 
3.5%
) 7
 
3.1%
( 7
 
3.1%
Other values (5) 23
 
10.0%
Hangul
ValueCountFrequency (%)
천 25
 
7.8%
포 24
 
7.5%
경 23
 
7.2%
도 23
 
7.2%
시 23
 
7.2%
기 23
 
7.2%
로 20
 
6.2%
읍 16
 
5.0%
층 14
 
4.4%
동 12
 
3.7%
Other values (41) 118
36.8%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.893648
Minimum37.824746
Maximum38.091054
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T13:53:31.313939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.824746
5-th percentile37.826295
Q137.828121
median37.852698
Q337.928299
95-th percentile38.084623
Maximum38.091054
Range0.2663076
Interquartile range (IQR)0.1001787

Descriptive statistics

Standard deviation0.0868673
Coefficient of variation (CV)0.0022923974
Kurtosis0.5017464
Mean37.893648
Median Absolute Deviation (MAD)0.0265315
Skewness1.2773955
Sum871.5539
Variance0.0075459278
MonotonicityNot monotonic
2023-12-12T13:53:31.439487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
37.8298745 1
 
4.3%
37.8261667 1
 
4.3%
37.8955358 1
 
4.3%
37.8985688 1
 
4.3%
37.958752 1
 
4.3%
37.8278851 1
 
4.3%
38.0910537 1
 
4.3%
37.8297482 1
 
4.3%
37.827449 1
 
4.3%
37.8275976 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
37.8247461 1
4.3%
37.8261667 1
4.3%
37.827449 1
4.3%
37.8275976 1
4.3%
37.8278777 1
4.3%
37.8278851 1
4.3%
37.8283563 1
4.3%
37.8297482 1
4.3%
37.8298745 1
4.3%
37.8300715 1
4.3%
ValueCountFrequency (%)
38.0910537 1
4.3%
38.0901002 1
4.3%
38.0353328 1
4.3%
38.0005891 1
4.3%
37.958752 1
4.3%
37.95803 1
4.3%
37.8985688 1
4.3%
37.8961748 1
4.3%
37.8956191 1
4.3%
37.8955358 1
4.3%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.19883
Minimum127.14021
Maximum127.36687
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T13:53:31.561681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.14021
5-th percentile127.1413
Q1127.1453
median127.16608
Q3127.22352
95-th percentile127.31845
Maximum127.36687
Range0.226652
Interquartile range (IQR)0.078215

Descriptive statistics

Standard deviation0.068003535
Coefficient of variation (CV)0.00053462391
Kurtosis0.346737
Mean127.19883
Median Absolute Deviation (MAD)0.025095
Skewness1.1715824
Sum2925.573
Variance0.0046244808
MonotonicityNot monotonic
2023-12-12T13:53:31.702887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
127.140213 1
 
4.3%
127.144295 1
 
4.3%
127.202343 1
 
4.3%
127.204171 1
 
4.3%
127.318056 1
 
4.3%
127.146309 1
 
4.3%
127.274101 1
 
4.3%
127.147789 1
 
4.3%
127.149205 1
 
4.3%
127.145627 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
127.140213 1
4.3%
127.141236 1
4.3%
127.141873 1
4.3%
127.144095 1
4.3%
127.144295 1
4.3%
127.14498 1
4.3%
127.145627 1
4.3%
127.146309 1
4.3%
127.147789 1
4.3%
127.149205 1
4.3%
ValueCountFrequency (%)
127.366865 1
4.3%
127.318497 1
4.3%
127.318056 1
4.3%
127.274101 1
4.3%
127.273482 1
4.3%
127.242866 1
4.3%
127.204171 1
4.3%
127.20272 1
4.3%
127.202343 1
4.3%
127.201013 1
4.3%

전화번호
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing2
Missing (%)8.7%
Memory size316.0 B
2023-12-12T13:53:31.945442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters252
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

Unique21 ?
Unique (%)100.0%

Sample

1st row031-544-5442
2nd row031-544-2277
3rd row031-544-1075
4th row031-543-7551
5th row031-543-0110
ValueCountFrequency (%)
031-544-5442 1
 
4.8%
031-544-1010 1
 
4.8%
031-535-5770 1
 
4.8%
031-533-8713 1
 
4.8%
031-541-7533 1
 
4.8%
031-532-9181 1
 
4.8%
031-542-8180 1
 
4.8%
031-541-7577 1
 
4.8%
031-541-5327 1
 
4.8%
031-534-7533 1
 
4.8%
Other values (11) 11
52.4%
2023-12-12T13:53:32.314137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 44
17.5%
- 42
16.7%
1 38
15.1%
5 37
14.7%
0 28
11.1%
4 22
8.7%
7 19
7.5%
2 12
 
4.8%
8 5
 
2.0%
9 3
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 210
83.3%
Dash Punctuation 42
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 44
21.0%
1 38
18.1%
5 37
17.6%
0 28
13.3%
4 22
10.5%
7 19
9.0%
2 12
 
5.7%
8 5
 
2.4%
9 3
 
1.4%
6 2
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 44
17.5%
- 42
16.7%
1 38
15.1%
5 37
14.7%
0 28
11.1%
4 22
8.7%
7 19
7.5%
2 12
 
4.8%
8 5
 
2.0%
9 3
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 44
17.5%
- 42
16.7%
1 38
15.1%
5 37
14.7%
0 28
11.1%
4 22
8.7%
7 19
7.5%
2 12
 
4.8%
8 5
 
2.0%
9 3
 
1.2%

Interactions

2023-12-12T13:53:29.351455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:28.817936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:29.107407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:29.431234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:28.906639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:29.188152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:29.513655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:29.015890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:29.273709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:53:32.463156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번한의원명주소위도경도전화번호
연번1.0001.0001.0000.4540.4601.000
한의원명1.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.000
위도0.4541.0001.0001.0001.0001.000
경도0.4601.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
2023-12-12T13:53:32.596910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.0720.273
위도0.0721.0000.868
경도0.2730.8681.000

Missing values

2023-12-12T13:53:29.618089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:53:29.726956image/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

연번구분한의원명주소위도경도전화번호
01한의원경희서울한의원경기도 포천시 소흘읍 송우로 79, 삼화프라자 3층 303호37.829875127.140213<NA>
12한의원우리경희한의원경기도 포천시 소흘읍 솔모루로 44, 2층37.826167127.144295031-544-5442
23한의원이엽한의원경기도 포천시 호국로 997, 2층 (선단동)37.854077127.166075031-544-2277
34한의원정한의원경기도 포천시 가산면 가산로 38037.847597127.19117031-544-1075
45한의원동의보감한의원경기도 포천시 영북면 운천안길 31-138.0901127.273482<NA>
56한의원소망한의원경기도 포천시 소흘읍 송우로 41, 2,4층37.828356127.144095031-543-7551
67한의원해맞이한의원경기도 포천시 소흘읍 송우로 74, 우진프라자 2층37.830072127.141236031-543-0110
78한의원이동해담한의원경기도 포천시 이동면 장암1길 14-2, 1층38.035333127.366865031-533-9976
89한의원양문한의원경기도 포천시 영중면 양문로 8838.000589127.242866031-532-3175
910한의원지리산쌍계한의원경기도 포천시 일동면 화동로 1064, 2층37.95803127.318497031-534-2241
연번구분한의원명주소위도경도전화번호
1314한의원수한의원경기도 포천시 소흘읍 솔모루로 15, 가동 5층 501호37.824746127.141873031-544-1010
1415한의원금강한의원경기도 포천시 중앙로 110 (신읍동)37.896175127.20272031-534-7533
1516한의원몸 바로 한의원경기도 포천시 소흘읍 솔모루로 66-437.827598127.145627031-541-5327
1617한의원솔모루한의원경기도 포천시 소흘읍 죽엽산로 337.827449127.149205031-541-7577
1718한의원송우한의원경기도 포천시 소흘읍 솔모루로 95 (2층)37.829748127.147789031-542-8180
1819한의원대곡한의원경기도 포천시 영북면 영북로 18938.091054127.274101031-532-9181
1920한의원경희장백한의원경기도 포천시 소흘읍 솔모루로 72, 2층37.827885127.146309031-541-7533
2021한의원일동대영한의원경기도 포천시 일동면 화동로 106937.958752127.318056031-533-8713
2122한의원신성한의원경기도 포천시 중앙로 139 (신읍동)37.898569127.204171031-535-5770
2223한의원포천한의원경기도 포천시 중앙로 104, 2층 (신읍동, 포천농협신읍지점)37.895536127.202343031-535-2536