Overview

Dataset statistics

Number of variables13
Number of observations32
Missing cells32
Missing cells (%)7.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory114.1 B

Variable types

Unsupported1
Text6
Numeric5
DateTime1

Dataset

Description경기도_자살 예방센터 현황
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=2720

Alerts

소재지우편번호 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 소재지우편번호High correlation
집계년도 has 32 (100.0%) missing valuesMissing
시군명 has unique valuesUnique
시군코드 has unique valuesUnique
자살예방센터명 has unique valuesUnique
전화번호 has unique valuesUnique
소재지우편번호 has unique valuesUnique
소재지지번주소 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique
집계년도 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-01-09 21:51:22.909048
Analysis finished2024-01-09 21:51:25.470475
Duration2.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

시군명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-10T06:51:25.584209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.09375
Min length3

Characters and Unicode

Total characters99
Distinct characters41
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

Unique32 ?
Unique (%)100.0%

Sample

1st row연천군
2nd row의정부시
3rd row포천시
4th row경기도
5th row광명시
ValueCountFrequency (%)
연천군 1
 
3.1%
의정부시 1
 
3.1%
광주시 1
 
3.1%
과천시 1
 
3.1%
고양시 1
 
3.1%
가평군 1
 
3.1%
화성시 1
 
3.1%
하남시 1
 
3.1%
평택시 1
 
3.1%
파주시 1
 
3.1%
Other values (22) 22
68.8%
2024-01-10T06:51:25.842171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
남 3
 
3.0%
성 3
 
3.0%
포 3
 
3.0%
평 3
 
3.0%
Other values (31) 35
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
남 3
 
3.0%
성 3
 
3.0%
포 3
 
3.0%
평 3
 
3.0%
Other values (31) 35
35.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
남 3
 
3.0%
성 3
 
3.0%
포 3
 
3.0%
평 3
 
3.0%
Other values (31) 35
35.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
남 3
 
3.0%
성 3
 
3.0%
포 3
 
3.0%
평 3
 
3.0%
Other values (31) 35
35.4%

시군코드
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41410.938
Minimum41000
Maximum41830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-01-10T06:51:25.946542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41121
Q141242.5
median41400
Q341575
95-th percentile41809
Maximum41830
Range830
Interquartile range (IQR)332.5

Descriptive statistics

Standard deviation218.68167
Coefficient of variation (CV)0.0052807708
Kurtosis-0.68543225
Mean41410.938
Median Absolute Deviation (MAD)175
Skewness0.24810358
Sum1325150
Variance47821.673
MonotonicityNot monotonic
2024-01-10T06:51:26.036733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
41800 1
 
3.1%
41830 1
 
3.1%
41310 1
 
3.1%
41610 1
 
3.1%
41290 1
 
3.1%
41280 1
 
3.1%
41820 1
 
3.1%
41590 1
 
3.1%
41450 1
 
3.1%
41220 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
41000 1
3.1%
41110 1
3.1%
41130 1
3.1%
41150 1
3.1%
41170 1
3.1%
41190 1
3.1%
41210 1
3.1%
41220 1
3.1%
41250 1
3.1%
41270 1
3.1%
ValueCountFrequency (%)
41830 1
3.1%
41820 1
3.1%
41800 1
3.1%
41670 1
3.1%
41650 1
3.1%
41630 1
3.1%
41610 1
3.1%
41590 1
3.1%
41570 1
3.1%
41550 1
3.1%

자살예방센터명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-10T06:51:26.200132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9.09375
Min length9

Characters and Unicode

Total characters291
Distinct characters47
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

Unique32 ?
Unique (%)100.0%

Sample

1st row연천군자살예방센터
2nd row의정부시자살예방센터
3rd row포천시자살예방센터
4th row경기도자살예방센터
5th row광명시자살예방센터
ValueCountFrequency (%)
연천군자살예방센터 1
 
3.1%
의정부시자살예방센터 1
 
3.1%
광주시자살예방센터 1
 
3.1%
과천시자살예방센터 1
 
3.1%
고양시자살예방센터 1
 
3.1%
가평군자살예방센터 1
 
3.1%
화성시자살예방센터 1
 
3.1%
하남시자살예방센터 1
 
3.1%
평택시자살예방센터 1
 
3.1%
파주시자살예방센터 1
 
3.1%
Other values (22) 22
68.8%
2024-01-10T06:51:26.477721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
센 32
11.0%
터 32
11.0%
자 32
11.0%
살 32
11.0%
예 32
11.0%
방 32
11.0%
시 29
10.0%
천 6
 
2.1%
양 5
 
1.7%
주 5
 
1.7%
Other values (37) 54
18.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 291
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
센 32
11.0%
터 32
11.0%
자 32
11.0%
살 32
11.0%
예 32
11.0%
방 32
11.0%
시 29
10.0%
천 6
 
2.1%
양 5
 
1.7%
주 5
 
1.7%
Other values (37) 54
18.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 291
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
센 32
11.0%
터 32
11.0%
자 32
11.0%
살 32
11.0%
예 32
11.0%
방 32
11.0%
시 29
10.0%
천 6
 
2.1%
양 5
 
1.7%
주 5
 
1.7%
Other values (37) 54
18.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 291
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
센 32
11.0%
터 32
11.0%
자 32
11.0%
살 32
11.0%
예 32
11.0%
방 32
11.0%
시 29
10.0%
천 6
 
2.1%
양 5
 
1.7%
주 5
 
1.7%
Other values (37) 54
18.6%

전화번호
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-10T06:51:26.653512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length11

Characters and Unicode

Total characters384
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

Unique32 ?
Unique (%)100.0%

Sample

1st row031-835-8106
2nd row031-894-8089
3rd row031-532-1670
4th row031-212-0435
5th row02-2618-8255
ValueCountFrequency (%)
031-835-8106 1
 
3.1%
031-894-8089 1
 
3.1%
031-762-8728 1
 
3.1%
02-504-4440 1
 
3.1%
031-927-9275 1
 
3.1%
031-581-8881 1
 
3.1%
031-352-0175 1
 
3.1%
031-794-6508 1
 
3.1%
031-658-9818 1
 
3.1%
031-945-2117 1
 
3.1%
Other values (22) 22
68.8%
2024-01-10T06:51:26.928604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 64
16.7%
0 57
14.8%
3 52
13.5%
1 47
12.2%
8 33
8.6%
2 26
6.8%
4 24
 
6.2%
5 22
 
5.7%
7 22
 
5.7%
6 21
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 320
83.3%
Dash Punctuation 64
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 57
17.8%
3 52
16.2%
1 47
14.7%
8 33
10.3%
2 26
8.1%
4 24
7.5%
5 22
 
6.9%
7 22
 
6.9%
6 21
 
6.6%
9 16
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 384
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 64
16.7%
0 57
14.8%
3 52
13.5%
1 47
12.2%
8 33
8.6%
2 26
6.8%
4 24
 
6.2%
5 22
 
5.7%
7 22
 
5.7%
6 21
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 64
16.7%
0 57
14.8%
3 52
13.5%
1 47
12.2%
8 33
8.6%
2 26
6.8%
4 24
 
6.2%
5 22
 
5.7%
7 22
 
5.7%
6 21
 
5.5%

위탁기관명
Text

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-10T06:51:27.115418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length8.5
Min length4

Characters and Unicode

Total characters272
Distinct characters83
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

Unique30 ?
Unique (%)93.8%

Sample

1st row한서중앙병원
2nd row경기도의료원의정부병원
3rd row일심재단 우리병원
4th row경기도의료원
5th row고려대학교산학협력단
ValueCountFrequency (%)
고려대학교산학협력단 2
 
5.0%
보건소 1
 
2.5%
의원 1
 
2.5%
의)용인병원유지재단 1
 
2.5%
계요병원 1
 
2.5%
예닮의료재단 1
 
2.5%
이천소망병원 1
 
2.5%
동국대학교 1
 
2.5%
일산병원 1
 
2.5%
직영 1
 
2.5%
Other values (29) 29
72.5%
2024-01-10T06:51:27.391279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 25
 
9.2%
학 20
 
7.4%
병 18
 
6.6%
교 14
 
5.1%
대 13
 
4.8%
단 12
 
4.4%
의 11
 
4.0%
한 8
 
2.9%
산 8
 
2.9%
8
 
2.9%
Other values (73) 135
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 260
95.6%
Space Separator 8
 
2.9%
Close Punctuation 2
 
0.7%
Open Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 25
 
9.6%
학 20
 
7.7%
병 18
 
6.9%
교 14
 
5.4%
대 13
 
5.0%
단 12
 
4.6%
의 11
 
4.2%
한 8
 
3.1%
산 8
 
3.1%
재 5
 
1.9%
Other values (70) 126
48.5%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 260
95.6%
Common 12
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 25
 
9.6%
학 20
 
7.7%
병 18
 
6.9%
교 14
 
5.4%
대 13
 
5.0%
단 12
 
4.6%
의 11
 
4.2%
한 8
 
3.1%
산 8
 
3.1%
재 5
 
1.9%
Other values (70) 126
48.5%
Common
ValueCountFrequency (%)
8
66.7%
) 2
 
16.7%
( 2
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 260
95.6%
ASCII 12
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 25
 
9.6%
학 20
 
7.7%
병 18
 
6.9%
교 14
 
5.4%
대 13
 
5.0%
단 12
 
4.6%
의 11
 
4.2%
한 8
 
3.1%
산 8
 
3.1%
재 5
 
1.9%
Other values (70) 126
48.5%
ASCII
ValueCountFrequency (%)
8
66.7%
) 2
 
16.7%
( 2
 
16.7%

센터개소일
Date

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2001-06-18 00:00:00
Maximum2020-12-01 00:00:00
2024-01-10T06:51:27.498750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:27.588802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

인력현황
Real number (ℝ)

Distinct13
Distinct (%)40.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.46875
Minimum5
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-01-10T06:51:27.672249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile6
Q17
median8
Q311
95-th percentile16.45
Maximum22
Range17
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.6806764
Coefficient of variation (CV)0.3887183
Kurtosis3.4037369
Mean9.46875
Median Absolute Deviation (MAD)1
Skewness1.7328146
Sum303
Variance13.547379
MonotonicityNot monotonic
2024-01-10T06:51:27.760414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
7 7
21.9%
8 6
18.8%
9 5
15.6%
6 3
9.4%
12 2
 
6.2%
11 2
 
6.2%
22 1
 
3.1%
5 1
 
3.1%
16 1
 
3.1%
17 1
 
3.1%
Other values (3) 3
9.4%
ValueCountFrequency (%)
5 1
 
3.1%
6 3
9.4%
7 7
21.9%
8 6
18.8%
9 5
15.6%
10 1
 
3.1%
11 2
 
6.2%
12 2
 
6.2%
13 1
 
3.1%
14 1
 
3.1%
ValueCountFrequency (%)
22 1
 
3.1%
17 1
 
3.1%
16 1
 
3.1%
14 1
 
3.1%
13 1
 
3.1%
12 2
 
6.2%
11 2
 
6.2%
10 1
 
3.1%
9 5
15.6%
8 6
18.8%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13973.312
Minimum10111
Maximum18501
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-01-10T06:51:27.855979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10111
5-th percentile10689.5
Q111854.75
median13576
Q316136
95-th percentile18004.5
Maximum18501
Range8390
Interquartile range (IQR)4281.25

Descriptive statistics

Standard deviation2533.1161
Coefficient of variation (CV)0.18128243
Kurtosis-1.2005799
Mean13973.312
Median Absolute Deviation (MAD)2161
Skewness0.2893193
Sum447146
Variance6416677
MonotonicityNot monotonic
2024-01-10T06:51:27.949936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
11027 1
 
3.1%
12550 1
 
3.1%
11922 1
 
3.1%
12739 1
 
3.1%
13806 1
 
3.1%
10387 1
 
3.1%
12413 1
 
3.1%
18501 1
 
3.1%
12909 1
 
3.1%
17901 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
10111 1
3.1%
10387 1
3.1%
10937 1
3.1%
11027 1
3.1%
11147 1
3.1%
11344 1
3.1%
11486 1
3.1%
11653 1
3.1%
11922 1
3.1%
12284 1
3.1%
ValueCountFrequency (%)
18501 1
3.1%
18131 1
3.1%
17901 1
3.1%
17596 1
3.1%
17380 1
3.1%
16969 1
3.1%
16439 1
3.1%
16316 1
3.1%
16076 1
3.1%
15887 1
3.1%

소재지지번주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-10T06:51:28.160514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length19.6875
Min length15

Characters and Unicode

Total characters630
Distinct characters91
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

Unique32 ?
Unique (%)100.0%

Sample

1st row경기도 연천군 전곡읍 은대리 577-36번지
2nd row경기도 의정부시 의정부동 566-1번지
3rd row경기도 포천시 신읍동 64-1번지
4th row경기도 수원시 장안구 정자동 886-9번지
5th row경기도 광명시 하안동 230번지
ValueCountFrequency (%)
경기도 32
 
23.0%
수원시 2
 
1.4%
용인시 1
 
0.7%
조리읍 1
 
0.7%
파주시 1
 
0.7%
2번지 1
 
0.7%
증일동 1
 
0.7%
이천시 1
 
0.7%
108번지 1
 
0.7%
고천동 1
 
0.7%
Other values (97) 97
69.8%
2024-01-10T06:51:28.505408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
107
17.0%
기 34
 
5.4%
경 33
 
5.2%
도 33
 
5.2%
지 32
 
5.1%
번 32
 
5.1%
시 30
 
4.8%
동 29
 
4.6%
1 21
 
3.3%
- 19
 
3.0%
Other values (81) 260
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 389
61.7%
Decimal Number 115
 
18.3%
Space Separator 107
 
17.0%
Dash Punctuation 19
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 34
 
8.7%
경 33
 
8.5%
도 33
 
8.5%
지 32
 
8.2%
번 32
 
8.2%
시 30
 
7.7%
동 29
 
7.5%
구 8
 
2.1%
안 8
 
2.1%
천 8
 
2.1%
Other values (69) 142
36.5%
Decimal Number
ValueCountFrequency (%)
1 21
18.3%
3 14
12.2%
7 11
9.6%
2 11
9.6%
6 11
9.6%
5 11
9.6%
8 10
8.7%
0 10
8.7%
4 9
7.8%
9 7
 
6.1%
Space Separator
ValueCountFrequency (%)
107
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 389
61.7%
Common 241
38.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 34
 
8.7%
경 33
 
8.5%
도 33
 
8.5%
지 32
 
8.2%
번 32
 
8.2%
시 30
 
7.7%
동 29
 
7.5%
구 8
 
2.1%
안 8
 
2.1%
천 8
 
2.1%
Other values (69) 142
36.5%
Common
ValueCountFrequency (%)
107
44.4%
1 21
 
8.7%
- 19
 
7.9%
3 14
 
5.8%
7 11
 
4.6%
2 11
 
4.6%
6 11
 
4.6%
5 11
 
4.6%
8 10
 
4.1%
0 10
 
4.1%
Other values (2) 16
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 389
61.7%
ASCII 241
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
107
44.4%
1 21
 
8.7%
- 19
 
7.9%
3 14
 
5.8%
7 11
 
4.6%
2 11
 
4.6%
6 11
 
4.6%
5 11
 
4.6%
8 10
 
4.1%
0 10
 
4.1%
Other values (2) 16
 
6.6%
Hangul
ValueCountFrequency (%)
기 34
 
8.7%
경 33
 
8.5%
도 33
 
8.5%
지 32
 
8.2%
번 32
 
8.2%
시 30
 
7.7%
동 29
 
7.5%
구 8
 
2.1%
안 8
 
2.1%
천 8
 
2.1%
Other values (69) 142
36.5%

소재지도로명주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-10T06:51:28.767101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length17.75
Min length14

Characters and Unicode

Total characters568
Distinct characters100
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

Unique32 ?
Unique (%)100.0%

Sample

1st row경기도 연천군 전곡읍 은대성로 95
2nd row경기도 의정부시 신흥로 217
3rd row경기도 포천시 중앙로 80
4th row경기도 수원시 장안구 수성로245번길 69
5th row경기도 광명시 오리로 613
ValueCountFrequency (%)
경기도 32
 
23.0%
5 2
 
1.4%
수원시 2
 
1.4%
중앙로 2
 
1.4%
69 2
 
1.4%
34-21 1
 
0.7%
기흥구 1
 
0.7%
파주시 1
 
0.7%
1119 1
 
0.7%
이섭대천로 1
 
0.7%
Other values (94) 94
67.6%
2024-01-10T06:51:29.124384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
107
18.8%
기 35
 
6.2%
경 34
 
6.0%
로 32
 
5.6%
도 32
 
5.6%
시 30
 
5.3%
1 23
 
4.0%
5 14
 
2.5%
4 13
 
2.3%
2 12
 
2.1%
Other values (90) 236
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 357
62.9%
Space Separator 107
 
18.8%
Decimal Number 102
 
18.0%
Dash Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 35
 
9.8%
경 34
 
9.5%
로 32
 
9.0%
도 32
 
9.0%
시 30
 
8.4%
길 10
 
2.8%
구 8
 
2.2%
번 8
 
2.2%
천 8
 
2.2%
양 6
 
1.7%
Other values (78) 154
43.1%
Decimal Number
ValueCountFrequency (%)
1 23
22.5%
5 14
13.7%
4 13
12.7%
2 12
11.8%
8 9
 
8.8%
9 7
 
6.9%
6 7
 
6.9%
3 7
 
6.9%
0 5
 
4.9%
7 5
 
4.9%
Space Separator
ValueCountFrequency (%)
107
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 357
62.9%
Common 211
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 35
 
9.8%
경 34
 
9.5%
로 32
 
9.0%
도 32
 
9.0%
시 30
 
8.4%
길 10
 
2.8%
구 8
 
2.2%
번 8
 
2.2%
천 8
 
2.2%
양 6
 
1.7%
Other values (78) 154
43.1%
Common
ValueCountFrequency (%)
107
50.7%
1 23
 
10.9%
5 14
 
6.6%
4 13
 
6.2%
2 12
 
5.7%
8 9
 
4.3%
9 7
 
3.3%
6 7
 
3.3%
3 7
 
3.3%
0 5
 
2.4%
Other values (2) 7
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 357
62.9%
ASCII 211
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
107
50.7%
1 23
 
10.9%
5 14
 
6.6%
4 13
 
6.2%
2 12
 
5.7%
8 9
 
4.3%
9 7
 
3.3%
6 7
 
3.3%
3 7
 
3.3%
0 5
 
2.4%
Other values (2) 7
 
3.3%
Hangul
ValueCountFrequency (%)
기 35
 
9.8%
경 34
 
9.5%
로 32
 
9.0%
도 32
 
9.0%
시 30
 
8.4%
길 10
 
2.8%
구 8
 
2.2%
번 8
 
2.2%
천 8
 
2.2%
양 6
 
1.7%
Other values (78) 154
43.1%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.476069
Minimum36.99093
Maximum38.023438
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-01-10T06:51:29.252244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.99093
5-th percentile37.07591
Q137.288758
median37.444767
Q337.635179
95-th percentile37.898285
Maximum38.023438
Range1.0325088
Interquartile range (IQR)0.34642169

Descriptive statistics

Standard deviation0.25966158
Coefficient of variation (CV)0.0069287305
Kurtosis-0.45000514
Mean37.476069
Median Absolute Deviation (MAD)0.16913506
Skewness0.20180454
Sum1199.2342
Variance0.067424138
MonotonicityNot monotonic
2024-01-10T06:51:29.358422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
38.02343841 1
 
3.1%
37.49652846 1
 
3.1%
37.60475459 1
 
3.1%
37.41636427 1
 
3.1%
37.4292292 1
 
3.1%
37.67032442 1
 
3.1%
37.83293139 1
 
3.1%
37.13786295 1
 
3.1%
37.53994849 1
 
3.1%
36.99092963 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
36.99092963 1
3.1%
37.00018933 1
3.1%
37.13786295 1
3.1%
37.15942646 1
3.1%
37.26974915 1
3.1%
37.27032741 1
3.1%
37.27251397 1
3.1%
37.27931713 1
3.1%
37.29190434 1
3.1%
37.3007009 1
3.1%
ValueCountFrequency (%)
38.02343841 1
3.1%
37.90077173 1
3.1%
37.89625113 1
3.1%
37.83293139 1
3.1%
37.79956067 1
3.1%
37.74495412 1
3.1%
37.7359883 1
3.1%
37.67032442 1
3.1%
37.62346416 1
3.1%
37.6107841 1
3.1%

경도
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.07392
Minimum126.72272
Maximum127.63267
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-01-10T06:51:29.474900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.72272
5-th percentile126.77354
Q1126.92508
median127.05595
Q3127.17908
95-th percentile127.50765
Maximum127.63267
Range0.9099511
Interquartile range (IQR)0.2540069

Descriptive statistics

Standard deviation0.22696307
Coefficient of variation (CV)0.0017860712
Kurtosis0.22329572
Mean127.07392
Median Absolute Deviation (MAD)0.1317587
Skewness0.69913977
Sum4066.3655
Variance0.051512235
MonotonicityNot monotonic
2024-01-10T06:51:29.574167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
127.0602623 1
 
3.1%
127.5051148 1
 
3.1%
127.1450627 1
 
3.1%
127.2502801 1
 
3.1%
126.987712 1
 
3.1%
126.7596871 1
 
3.1%
127.5107487 1
 
3.1%
126.9224111 1
 
3.1%
127.2133848 1
 
3.1%
127.1118922 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
126.7227198 1
3.1%
126.7596871 1
3.1%
126.784883 1
3.1%
126.7959895 1
3.1%
126.8047361 1
3.1%
126.8446843 1
3.1%
126.8783776 1
3.1%
126.9224111 1
3.1%
126.9259641 1
3.1%
126.9329177 1
3.1%
ValueCountFrequency (%)
127.6326709 1
3.1%
127.5107487 1
3.1%
127.5051148 1
3.1%
127.4452642 1
3.1%
127.2698167 1
3.1%
127.2502801 1
3.1%
127.2133848 1
3.1%
127.2012445 1
3.1%
127.1716955 1
3.1%
127.1450627 1
3.1%

Interactions

2024-01-10T06:51:24.949171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:23.359978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:23.720850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:24.124498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:24.642914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:25.006815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:23.415132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:23.800194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:24.182429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:24.702671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:25.070504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:23.490415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:23.891497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:24.464206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:24.768851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:25.128848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:23.564483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:23.970468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:24.523561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:24.828485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:25.193884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:23.644738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:24.056626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:24.585497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:51:24.891476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:51:29.654930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명시군코드자살예방센터명전화번호위탁기관명센터개소일인력현황소재지우편번호소재지지번주소소재지도로명주소위도경도
시군명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시군코드1.0001.0001.0001.0000.9500.0000.0000.3901.0001.0000.0000.668
자살예방센터명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위탁기관명1.0000.9501.0001.0001.0000.9740.9790.8951.0001.0000.9661.000
센터개소일1.0000.0001.0001.0000.9741.0000.9830.8701.0001.0000.8830.000
인력현황1.0000.0001.0001.0000.9790.9831.0000.5051.0001.0000.0000.000
소재지우편번호1.0000.3901.0001.0000.8950.8700.5051.0001.0001.0000.8000.828
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도1.0000.0001.0001.0000.9660.8830.0000.8001.0001.0001.0000.000
경도1.0000.6681.0001.0001.0000.0000.0000.8281.0001.0000.0001.000
2024-01-10T06:51:29.767629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군코드인력현황소재지우편번호위도경도
시군코드1.000-0.385-0.2500.1790.440
인력현황-0.3851.0000.031-0.014-0.208
소재지우편번호-0.2500.0311.000-0.8930.034
위도0.179-0.014-0.8931.000-0.090
경도0.440-0.2080.034-0.0901.000

Missing values

2024-01-10T06:51:25.290155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:51:25.420186image/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

집계년도시군명시군코드자살예방센터명전화번호위탁기관명센터개소일인력현황소재지우편번호소재지지번주소소재지도로명주소위도경도
0<NA>연천군41800연천군자살예방센터031-835-8106한서중앙병원2020-07-01811027경기도 연천군 전곡읍 은대리 577-36번지경기도 연천군 전곡읍 은대성로 9538.023438127.060262
1<NA>의정부시41150의정부시자살예방센터031-894-8089경기도의료원의정부병원2017-05-01811653경기도 의정부시 의정부동 566-1번지경기도 의정부시 신흥로 21737.735988127.039514
2<NA>포천시41650포천시자살예방센터031-532-1670일심재단 우리병원2019-05-28911147경기도 포천시 신읍동 64-1번지경기도 포천시 중앙로 8037.900772127.201245
3<NA>경기도41000경기도자살예방센터031-212-0435경기도의료원2011-11-012216316경기도 수원시 장안구 정자동 886-9번지경기도 수원시 장안구 수성로245번길 6937.291904126.996364
4<NA>광명시41210광명시자살예방센터02-2618-8255고려대학교산학협력단2012-11-01814303경기도 광명시 하안동 230번지경기도 광명시 오리로 61337.455769126.878378
5<NA>군포시41410군포시자살예방센터031-360-1779한림대학교성심병원2020-07-01615887경기도 군포시 부곡동 770-1번지경기도 군포시 군포로 22137.33315126.925964
6<NA>김포시41570김포시자살예방센터031-998-4005김포다은병원2019-03-04710111경기도 김포시 사우동 869번지경기도 김포시 사우중로 10837.623464126.72272
7<NA>남양주시41360남양주시자살예방센터031-592-5891축령복음병원2020-11-02912284경기도 남양주시 다산동 3159-7번지경기도 남양주시 경춘로 52237.610784127.171695
8<NA>동두천시41250동두천시자살예방센터031-865-3632(의)가화의료재단2020-12-01511344경기도 동두천시 생연동 714-10번지경기도 동두천시 거북마루로 4937.896251127.05163
9<NA>부천시41190부천시자살예방센터032-654-4024순천향대학교 부천병원2017-12-011614434경기도 부천시 오정동 129번지경기도 부천시 성오로 17237.527976126.79599
집계년도시군명시군코드자살예방센터명전화번호위탁기관명센터개소일인력현황소재지우편번호소재지지번주소소재지도로명주소위도경도
22<NA>이천시41500이천시자살예방센터031-637-2331예닮의료재단 이천소망병원2014-01-01717380경기도 이천시 증일동 2번지경기도 이천시 이섭대천로 111937.270327127.445264
23<NA>파주시41480파주시자살예방센터031-945-2117동국대학교 일산병원2018-07-131310937경기도 파주시 조리읍 봉일천리 188-9번지경기도 파주시 조리읍 봉천로 6837.744954126.804736
24<NA>평택시41220평택시자살예방센터031-658-9818보건소 직영2019-10-07917901경기도 평택시 비전동 850번지경기도 평택시 평택5로 5636.99093127.111892
25<NA>하남시41450하남시자살예방센터031-794-6508강동성심병원2019-05-31712909경기도 하남시 망월동 980번지경기도 하남시 미사강변대로 20037.539948127.213385
26<NA>화성시41590화성시자살예방센터031-352-0175경산복지재단2013-06-271118501경기도 화성시 산척동 726번지경기도 화성시 동탄대로8길 3637.137863126.922411
27<NA>가평군41820가평군자살예방센터031-581-8881한림대학교춘천성심병원2013-06-12812413경기도 가평군 가평읍 읍내리 624-20번지경기도 가평군 가평읍 가화로 155-1537.832931127.510749
28<NA>고양시41280고양시자살예방센터031-927-9275국민건강보험공단일산병원2019-01-011410387경기도 고양시 일산서구 주엽동 110-2번지경기도 고양시 일산서구 중앙로 144337.670324126.759687
29<NA>과천시41290과천시자살예방센터02-504-4440마음톡의원2019-08-01713806경기도 과천시 중앙동 1-3번지경기도 과천시 관문로 6937.429229126.987712
30<NA>광주시41610광주시자살예방센터031-762-8728로하스한울의원2018-12-31612739경기도 광주시 경안동 115번지경기도 광주시 파발로 19437.416364127.25028
31<NA>구리시41310구리시자살예방센터031-523-8644학교법인한양학원2019-03-281011922경기도 구리시 인창동 674-3번지경기도 구리시 건원대로34번길 8437.604755127.145063