Overview

Dataset statistics

Number of variables6
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory55.7 B

Variable types

Categorical1
Text3
Numeric2

Dataset

Description강원도 원주시의 정신건강 증진시설(병의원, 정신건강센터) 및 요양병원 현황에 대한 데이터입니다. 기관구분, 기관명, 주소, 전화번호 및 위경도 데이터를 제공하고 있습니다.
Author강원도 원주시
URLhttps://www.data.go.kr/data/15103977/fileData.do

Alerts

위도 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 위도High correlation
기관명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:42:14.156610
Analysis finished2023-12-12 20:42:15.075311
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
의원
11 
요양병원
6 
종합병원
3 
정신병원
2 
정신재활시설(생활)
 
1

Length

Max length10
Median length4
Mean length3.3043478
Min length2

Unique

Unique1 ?
Unique (%)4.3%

Sample

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

Common Values

ValueCountFrequency (%)
의원 11
47.8%
요양병원 6
26.1%
종합병원 3
 
13.0%
정신병원 2
 
8.7%
정신재활시설(생활) 1
 
4.3%

Length

2023-12-13T05:42:15.177329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:42:15.399642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의원 11
47.8%
요양병원 6
26.1%
종합병원 3
 
13.0%
정신병원 2
 
8.7%
정신재활시설(생활 1
 
4.3%

기관명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T05:42:15.645033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length8.9565217
Min length3

Characters and Unicode

Total characters206
Distinct characters72
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 row연세명인요양병원
2nd row문막요양병원
3rd row현대요양병원
4th row원주민중요양병원
5th row연세요양병원
ValueCountFrequency (%)
연세명인요양병원 1
 
3.8%
문막요양병원 1
 
3.8%
원주시중독관리통합지원센터 1
 
3.8%
원주시정신건강복지센터 1
 
3.8%
하늘빛정신건강의학과의원 1
 
3.8%
정신건강의학과의원 1
 
3.8%
연세소울 1
 
3.8%
고석만정신건강의학과 1
 
3.8%
좋은마음정신건강의학과의원 1
 
3.8%
마음편한정신의학과 1
 
3.8%
Other values (16) 16
61.5%
2023-12-13T05:42:16.064685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 25
 
12.1%
신 13
 
6.3%
의 13
 
6.3%
병 10
 
4.9%
정 10
 
4.9%
과 9
 
4.4%
강 8
 
3.9%
학 7
 
3.4%
세 6
 
2.9%
요 6
 
2.9%
Other values (62) 99
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 203
98.5%
Space Separator 3
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 25
 
12.3%
신 13
 
6.4%
의 13
 
6.4%
병 10
 
4.9%
정 10
 
4.9%
과 9
 
4.4%
강 8
 
3.9%
학 7
 
3.4%
세 6
 
3.0%
요 6
 
3.0%
Other values (61) 96
47.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 203
98.5%
Common 3
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 25
 
12.3%
신 13
 
6.4%
의 13
 
6.4%
병 10
 
4.9%
정 10
 
4.9%
과 9
 
4.4%
강 8
 
3.9%
학 7
 
3.4%
세 6
 
3.0%
요 6
 
3.0%
Other values (61) 96
47.3%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 203
98.5%
ASCII 3
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 25
 
12.3%
신 13
 
6.4%
의 13
 
6.4%
병 10
 
4.9%
정 10
 
4.9%
과 9
 
4.4%
강 8
 
3.9%
학 7
 
3.4%
세 6
 
3.0%
요 6
 
3.0%
Other values (61) 96
47.3%
ASCII
ValueCountFrequency (%)
3
100.0%

주소
Text

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T05:42:16.304845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length16.391304
Min length13

Characters and Unicode

Total characters377
Distinct characters45
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

Unique21 ?
Unique (%)91.3%

Sample

1st row강원도 원주시 평원로 100
2nd row강원도 원주시 문막읍 문막시장1길 16
3rd row강원도 원주시 치악로1604번길 22
4th row강원도 원주시 북원로 2636
5th row강원도 원주시 남원로 631
ValueCountFrequency (%)
강원도 23
24.0%
원주시 23
24.0%
원일로 4
 
4.2%
서원대로 4
 
4.2%
능라동길 3
 
3.1%
남원로 2
 
2.1%
문막읍 2
 
2.1%
평원로 2
 
2.1%
139 2
 
2.1%
16 1
 
1.0%
Other values (30) 30
31.2%
2023-12-13T05:42:16.650327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
73
19.4%
원 59
15.6%
시 24
 
6.4%
강 23
 
6.1%
도 23
 
6.1%
주 23
 
6.1%
로 19
 
5.0%
1 19
 
5.0%
6 10
 
2.7%
3 9
 
2.4%
Other values (35) 95
25.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 230
61.0%
Space Separator 73
 
19.4%
Decimal Number 71
 
18.8%
Dash Punctuation 3
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 59
25.7%
시 24
10.4%
강 23
 
10.0%
도 23
 
10.0%
주 23
 
10.0%
로 19
 
8.3%
길 5
 
2.2%
일 5
 
2.2%
문 4
 
1.7%
서 4
 
1.7%
Other values (23) 41
17.8%
Decimal Number
ValueCountFrequency (%)
1 19
26.8%
6 10
14.1%
3 9
12.7%
2 9
12.7%
0 6
 
8.5%
9 5
 
7.0%
5 5
 
7.0%
4 3
 
4.2%
7 3
 
4.2%
8 2
 
2.8%
Space Separator
ValueCountFrequency (%)
73
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 230
61.0%
Common 147
39.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 59
25.7%
시 24
10.4%
강 23
 
10.0%
도 23
 
10.0%
주 23
 
10.0%
로 19
 
8.3%
길 5
 
2.2%
일 5
 
2.2%
문 4
 
1.7%
서 4
 
1.7%
Other values (23) 41
17.8%
Common
ValueCountFrequency (%)
73
49.7%
1 19
 
12.9%
6 10
 
6.8%
3 9
 
6.1%
2 9
 
6.1%
0 6
 
4.1%
9 5
 
3.4%
5 5
 
3.4%
4 3
 
2.0%
7 3
 
2.0%
Other values (2) 5
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 230
61.0%
ASCII 147
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
73
49.7%
1 19
 
12.9%
6 10
 
6.8%
3 9
 
6.1%
2 9
 
6.1%
0 6
 
4.1%
9 5
 
3.4%
5 5
 
3.4%
4 3
 
2.0%
7 3
 
2.0%
Other values (2) 5
 
3.4%
Hangul
ValueCountFrequency (%)
원 59
25.7%
시 24
10.4%
강 23
 
10.0%
도 23
 
10.0%
주 23
 
10.0%
로 19
 
8.3%
길 5
 
2.2%
일 5
 
2.2%
문 4
 
1.7%
서 4
 
1.7%
Other values (23) 41
17.8%

전화번호
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T05:42:16.852957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters276
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

Unique23 ?
Unique (%)100.0%

Sample

1st row033-813-1111
2nd row033-813-9922
3rd row033-900-9977
4th row033-732-0270
5th row033-765-5001
ValueCountFrequency (%)
033-813-1111 1
 
4.3%
033-749-9900 1
 
4.3%
033-748-5119 1
 
4.3%
033-746-0199 1
 
4.3%
033-743-7975 1
 
4.3%
033-762-9964 1
 
4.3%
033-744-0223 1
 
4.3%
033-733-6300 1
 
4.3%
033-766-7675 1
 
4.3%
033-744-1142 1
 
4.3%
Other values (13) 13
56.5%
2023-12-13T05:42:17.225533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 61
22.1%
- 46
16.7%
0 42
15.2%
7 29
10.5%
1 24
 
8.7%
4 21
 
7.6%
9 16
 
5.8%
6 12
 
4.3%
2 11
 
4.0%
5 8
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230
83.3%
Dash Punctuation 46
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 61
26.5%
0 42
18.3%
7 29
12.6%
1 24
 
10.4%
4 21
 
9.1%
9 16
 
7.0%
6 12
 
5.2%
2 11
 
4.8%
5 8
 
3.5%
8 6
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 276
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 61
22.1%
- 46
16.7%
0 42
15.2%
7 29
10.5%
1 24
 
8.7%
4 21
 
7.6%
9 16
 
5.8%
6 12
 
4.3%
2 11
 
4.0%
5 8
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 276
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 61
22.1%
- 46
16.7%
0 42
15.2%
7 29
10.5%
1 24
 
8.7%
4 21
 
7.6%
9 16
 
5.8%
6 12
 
4.3%
2 11
 
4.0%
5 8
 
2.9%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.339497
Minimum37.265112
Maximum37.43937
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T05:42:17.409718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.265112
5-th percentile37.29463
Q137.330891
median37.33442
Q337.351397
95-th percentile37.376216
Maximum37.43937
Range0.17425852
Interquartile range (IQR)0.020505739

Descriptive statistics

Standard deviation0.031541154
Coefficient of variation (CV)0.00084471287
Kurtosis4.8918707
Mean37.339497
Median Absolute Deviation (MAD)0.014698083
Skewness0.82308328
Sum858.80844
Variance0.0009948444
MonotonicityNot monotonic
2023-12-13T05:42:17.575255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
37.3515850793 2
 
8.7%
37.353462641 1
 
4.3%
37.3262032211 1
 
4.3%
37.4393704274 1
 
4.3%
37.3341487868 1
 
4.3%
37.3315842149 1
 
4.3%
37.3344195591 1
 
4.3%
37.3438737236 1
 
4.3%
37.3301987644 1
 
4.3%
37.349987393 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
37.2651119107 1
4.3%
37.2931560343 1
4.3%
37.3078938495 1
4.3%
37.3262032211 1
4.3%
37.326242031 1
4.3%
37.3301987644 1
4.3%
37.3315842149 1
4.3%
37.3319920156 1
4.3%
37.3327902465 1
4.3%
37.333948364 1
4.3%
ValueCountFrequency (%)
37.4393704274 1
4.3%
37.3787437746 1
4.3%
37.353462641 1
4.3%
37.3520639117 1
4.3%
37.3515850793 2
8.7%
37.3512093778 1
4.3%
37.349987393 1
4.3%
37.3491176419 1
4.3%
37.3438737236 1
4.3%
37.3397525039 1
4.3%

경도
Real number (ℝ)

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.93944
Minimum127.81701
Maximum127.99088
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T05:42:17.709601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.81701
5-th percentile127.83596
Q1127.93878
median127.94857
Q3127.9503
95-th percentile127.98654
Maximum127.99088
Range0.1738791
Interquartile range (IQR)0.011521785

Descriptive statistics

Standard deviation0.040561635
Coefficient of variation (CV)0.00031703777
Kurtosis5.486804
Mean127.93944
Median Absolute Deviation (MAD)0.0023354599
Skewness-2.226
Sum2942.6071
Variance0.0016452462
MonotonicityNot monotonic
2023-12-13T05:42:17.914397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
127.946794698 2
 
8.7%
127.948596925 1
 
4.3%
127.975195336 1
 
4.3%
127.9877955994 1
 
4.3%
127.9312331982 1
 
4.3%
127.9261785652 1
 
4.3%
127.9308182544 1
 
4.3%
127.9293536762 1
 
4.3%
127.9496906798 1
 
4.3%
127.9487225978 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
127.8170050971 1
4.3%
127.8259367036 1
4.3%
127.9261785652 1
4.3%
127.9293536762 1
4.3%
127.9308182544 1
4.3%
127.9312331982 1
4.3%
127.9463178214 1
4.3%
127.9467233063 1
4.3%
127.946794698 2
8.7%
127.9471832055 1
4.3%
ValueCountFrequency (%)
127.9908841993 1
4.3%
127.9877955994 1
4.3%
127.975195336 1
4.3%
127.9628995595 1
4.3%
127.951853802 1
4.3%
127.9509039094 1
4.3%
127.9496906798 1
4.3%
127.9490358045 1
4.3%
127.9487225978 1
4.3%
127.9486458576 1
4.3%

Interactions

2023-12-13T05:42:14.642541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:42:14.424798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:42:14.735476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:42:14.543162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:42:18.354594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분기관명주소전화번호위도경도
구분1.0001.0001.0001.0000.7330.637
기관명1.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
위도0.7331.0001.0001.0001.0000.656
경도0.6371.0001.0001.0000.6561.000
2023-12-13T05:42:18.466491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도구분
위도1.0000.0250.507
경도0.0251.0000.268
구분0.5070.2681.000

Missing values

2023-12-13T05:42:14.869784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:42:15.025520image/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

구분기관명주소전화번호위도경도
0요양병원연세명인요양병원강원도 원주시 평원로 100033-813-111137.353463127.948597
1요양병원문막요양병원강원도 원주시 문막읍 문막시장1길 16033-813-992237.307894127.817005
2요양병원현대요양병원강원도 원주시 치악로1604번길 22033-900-997737.326242127.9629
3요양병원원주민중요양병원강원도 원주시 북원로 2636033-732-027037.378744127.946318
4요양병원연세요양병원강원도 원주시 남원로 631033-765-500137.339753127.951854
5요양병원바른요양병원강원도 원주시 판부면 치악로 1139033-762-010037.293156127.990884
6정신병원내안에병원강원도 원주시 남원로 562-5033-733-119937.333948127.948646
7의원강봉선신경정신과강원도 원주시 서원대로 383033-744-388437.331992127.948568
8의원마음사랑정신건강의학과 의원강원도 원주시 평원로 62033-744-246837.351209127.950904
9종합병원연세대학교 원주세브란스기독병원강원도 원주시 일산로 20033-741-011437.349118127.946723
구분기관명주소전화번호위도경도
13의원홍성국신경정신과의원강원도 원주시 원일로 150-1033-743-535637.352064127.947183
14의원이신경정신과의원강원도 원주시 원일로 114033-744-114237.349987127.948723
15의원마음편한정신의학과강원도 원주시 서원대로 406033-766-767537.330199127.949691
16의원좋은마음정신건강의학과의원강원도 원주시 서원대로 162033-733-630037.343874127.929354
17의원고석만정신건강의학과강원도 원주시 능라동길 59033-744-022337.33442127.930818
18의원연세소울 정신건강의학과의원강원도 원주시 능라동길 3033-762-996437.331584127.926179
19의원하늘빛정신건강의학과의원강원도 원주시 능라동길 61033-743-797537.334149127.931233
20의원원주시정신건강복지센터강원도 원주시 원일로 139033-746-019937.351585127.946795
21의원원주시중독관리통합지원센터강원도 원주시 원일로 139033-748-511937.351585127.946795
22정신재활시설(생활)별자리강원도 원주시 소초면 둔둔로 217-19033-747-112737.43937127.987796