Overview

Dataset statistics

Number of variables4
Number of observations630
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.4 KiB
Average record size in memory33.2 B

Variable types

Numeric1
Text3

Dataset

Description자동제세동기AED설치현황
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202016

Alerts

NO has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:46:22.415202
Analysis finished2024-03-14 00:46:22.903850
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

NO
Real number (ℝ)

UNIQUE 

Distinct630
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean315.5
Minimum1
Maximum630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-03-14T09:46:22.960757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile32.45
Q1158.25
median315.5
Q3472.75
95-th percentile598.55
Maximum630
Range629
Interquartile range (IQR)314.5

Descriptive statistics

Standard deviation182.00962
Coefficient of variation (CV)0.5768926
Kurtosis-1.2
Mean315.5
Median Absolute Deviation (MAD)157.5
Skewness0
Sum198765
Variance33127.5
MonotonicityStrictly increasing
2024-03-14T09:46:23.083606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
425 1
 
0.2%
418 1
 
0.2%
419 1
 
0.2%
420 1
 
0.2%
421 1
 
0.2%
422 1
 
0.2%
423 1
 
0.2%
424 1
 
0.2%
426 1
 
0.2%
Other values (620) 620
98.4%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
630 1
0.2%
629 1
0.2%
628 1
0.2%
627 1
0.2%
626 1
0.2%
625 1
0.2%
624 1
0.2%
623 1
0.2%
622 1
0.2%
621 1
0.2%

설치기관명
Text

Distinct554
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-03-14T09:46:23.259178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length8.6380952
Min length1

Characters and Unicode

Total characters5442
Distinct characters268
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

Unique517 ?
Unique (%)82.1%

Sample

1st row인휴한신휴플러스아파트
2nd row송천한양아파트
3rd row위브어울림아파트
4th row부영6차아파트
5th row흥건삼천2차아파트
ValueCountFrequency (%)
정읍시보건소 13
 
1.9%
익산지사 8
 
1.2%
주)케이티링커스 8
 
1.2%
익산역 7
 
1.0%
보건지소 7
 
1.0%
케이티링거스(주 6
 
0.9%
전주지사 6
 
0.9%
군산시보건소 5
 
0.7%
무주군보건의료원 4
 
0.6%
성덕보건진료소 3
 
0.4%
Other values (567) 612
90.1%
2024-03-14T09:46:23.543404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 521
 
9.6%
건 426
 
7.8%
보 425
 
7.8%
진 272
 
5.0%
료 249
 
4.6%
지 197
 
3.6%
1 174
 
3.2%
전 117
 
2.1%
산 116
 
2.1%
) 111
 
2.0%
Other values (258) 2834
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4884
89.7%
Decimal Number 276
 
5.1%
Close Punctuation 111
 
2.0%
Open Punctuation 103
 
1.9%
Space Separator 49
 
0.9%
Uppercase Letter 15
 
0.3%
Dash Punctuation 3
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 521
 
10.7%
건 426
 
8.7%
보 425
 
8.7%
진 272
 
5.6%
료 249
 
5.1%
지 197
 
4.0%
전 117
 
2.4%
산 116
 
2.4%
서 98
 
2.0%
안 96
 
2.0%
Other values (239) 2367
48.5%
Decimal Number
ValueCountFrequency (%)
1 174
63.0%
9 85
30.8%
2 5
 
1.8%
3 3
 
1.1%
4 3
 
1.1%
5 2
 
0.7%
8 2
 
0.7%
6 1
 
0.4%
0 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
T 4
26.7%
K 4
26.7%
H 3
20.0%
L 3
20.0%
E 1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 111
100.0%
Open Punctuation
ValueCountFrequency (%)
( 103
100.0%
Space Separator
ValueCountFrequency (%)
49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4884
89.7%
Common 543
 
10.0%
Latin 15
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 521
 
10.7%
건 426
 
8.7%
보 425
 
8.7%
진 272
 
5.6%
료 249
 
5.1%
지 197
 
4.0%
전 117
 
2.4%
산 116
 
2.4%
서 98
 
2.0%
안 96
 
2.0%
Other values (239) 2367
48.5%
Common
ValueCountFrequency (%)
1 174
32.0%
) 111
20.4%
( 103
19.0%
9 85
15.7%
49
 
9.0%
2 5
 
0.9%
3 3
 
0.6%
- 3
 
0.6%
4 3
 
0.6%
5 2
 
0.4%
Other values (4) 5
 
0.9%
Latin
ValueCountFrequency (%)
T 4
26.7%
K 4
26.7%
H 3
20.0%
L 3
20.0%
E 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4884
89.7%
ASCII 558
 
10.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 521
 
10.7%
건 426
 
8.7%
보 425
 
8.7%
진 272
 
5.6%
료 249
 
5.1%
지 197
 
4.0%
전 117
 
2.4%
산 116
 
2.4%
서 98
 
2.0%
안 96
 
2.0%
Other values (239) 2367
48.5%
ASCII
ValueCountFrequency (%)
1 174
31.2%
) 111
19.9%
( 103
18.5%
9 85
15.2%
49
 
8.8%
2 5
 
0.9%
T 4
 
0.7%
K 4
 
0.7%
H 3
 
0.5%
L 3
 
0.5%
Other values (9) 17
 
3.0%

설치주소
Text

Distinct590
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-03-14T09:46:23.876919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length43
Mean length21.385714
Min length12

Characters and Unicode

Total characters13473
Distinct characters262
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

Unique560 ?
Unique (%)88.9%

Sample

1st row전라북도 전주시 덕진구 안덕원로 251 (인후동1가) 한신휴플러스아파트
2nd row전라북도 전주시 덕진구 가리내로 550 (송천동1가) 한양아파트
3rd row전라북도 전주시 덕진구 견훤로 333 (인후동1가) 위브어울림아파트
4th row전라북도 전주시 덕진구 무삼지로 10 (인후동1가) 부영6차아파트
5th row전라북도 전주시 완산구 거마평로 25 (삼천동1가)
ValueCountFrequency (%)
전라북도 630
 
20.4%
정읍시 69
 
2.2%
익산시 64
 
2.1%
군산시 59
 
1.9%
남원시 55
 
1.8%
김제시 53
 
1.7%
전주시 47
 
1.5%
완주군 47
 
1.5%
고창군 44
 
1.4%
임실군 39
 
1.3%
Other values (1235) 1984
64.2%
2024-03-14T09:46:24.301652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2462
 
18.3%
전 689
 
5.1%
도 663
 
4.9%
북 646
 
4.8%
라 633
 
4.7%
1 470
 
3.5%
리 452
 
3.4%
면 412
 
3.1%
- 390
 
2.9%
시 356
 
2.6%
Other values (252) 6300
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8270
61.4%
Space Separator 2462
 
18.3%
Decimal Number 2304
 
17.1%
Dash Punctuation 390
 
2.9%
Close Punctuation 23
 
0.2%
Open Punctuation 23
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 689
 
8.3%
도 663
 
8.0%
북 646
 
7.8%
라 633
 
7.7%
리 452
 
5.5%
면 412
 
5.0%
시 356
 
4.3%
군 347
 
4.2%
산 280
 
3.4%
동 191
 
2.3%
Other values (237) 3601
43.5%
Decimal Number
ValueCountFrequency (%)
1 470
20.4%
3 283
12.3%
2 272
11.8%
4 226
9.8%
5 226
9.8%
6 211
9.2%
8 168
 
7.3%
7 163
 
7.1%
0 155
 
6.7%
9 130
 
5.6%
Space Separator
ValueCountFrequency (%)
2462
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 390
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8270
61.4%
Common 5203
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 689
 
8.3%
도 663
 
8.0%
북 646
 
7.8%
라 633
 
7.7%
리 452
 
5.5%
면 412
 
5.0%
시 356
 
4.3%
군 347
 
4.2%
산 280
 
3.4%
동 191
 
2.3%
Other values (237) 3601
43.5%
Common
ValueCountFrequency (%)
2462
47.3%
1 470
 
9.0%
- 390
 
7.5%
3 283
 
5.4%
2 272
 
5.2%
4 226
 
4.3%
5 226
 
4.3%
6 211
 
4.1%
8 168
 
3.2%
7 163
 
3.1%
Other values (5) 332
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8270
61.4%
ASCII 5203
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2462
47.3%
1 470
 
9.0%
- 390
 
7.5%
3 283
 
5.4%
2 272
 
5.2%
4 226
 
4.3%
5 226
 
4.3%
6 211
 
4.1%
8 168
 
3.2%
7 163
 
3.1%
Other values (5) 332
 
6.4%
Hangul
ValueCountFrequency (%)
전 689
 
8.3%
도 663
 
8.0%
북 646
 
7.8%
라 633
 
7.7%
리 452
 
5.5%
면 412
 
5.0%
시 356
 
4.3%
군 347
 
4.2%
산 280
 
3.4%
동 191
 
2.3%
Other values (237) 3601
43.5%

설치장소
Text

Distinct239
Distinct (%)37.9%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-03-14T09:46:24.510128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length5.9047619
Min length2

Characters and Unicode

Total characters3720
Distinct characters226
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique199 ?
Unique (%)31.6%

Sample

1st row관리사무소
2nd row관리사무소
3rd row관리동 1층 방재실
4th row관리사무소
5th row관리사무소
ValueCountFrequency (%)
진료실 103
 
10.6%
1층 93
 
9.6%
구급차 81
 
8.3%
내 80
 
8.2%
대기실 57
 
5.9%
민원실 39
 
4.0%
현관 39
 
4.0%
접수실 35
 
3.6%
입구 24
 
2.5%
진료대기실 23
 
2.4%
Other values (237) 397
40.9%
2024-03-14T09:46:24.847769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
실 399
 
10.7%
341
 
9.2%
진 217
 
5.8%
료 205
 
5.5%
내 153
 
4.1%
구 131
 
3.5%
층 125
 
3.4%
대 124
 
3.3%
1 121
 
3.3%
기 121
 
3.3%
Other values (216) 1783
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3223
86.6%
Space Separator 341
 
9.2%
Decimal Number 136
 
3.7%
Close Punctuation 10
 
0.3%
Open Punctuation 10
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
실 399
 
12.4%
진 217
 
6.7%
료 205
 
6.4%
내 153
 
4.7%
구 131
 
4.1%
층 125
 
3.9%
대 124
 
3.8%
기 121
 
3.8%
소 120
 
3.7%
급 100
 
3.1%
Other values (205) 1528
47.4%
Decimal Number
ValueCountFrequency (%)
1 121
89.0%
2 6
 
4.4%
5 3
 
2.2%
3 2
 
1.5%
4 1
 
0.7%
0 1
 
0.7%
7 1
 
0.7%
6 1
 
0.7%
Space Separator
ValueCountFrequency (%)
341
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3223
86.6%
Common 497
 
13.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
실 399
 
12.4%
진 217
 
6.7%
료 205
 
6.4%
내 153
 
4.7%
구 131
 
4.1%
층 125
 
3.9%
대 124
 
3.8%
기 121
 
3.8%
소 120
 
3.7%
급 100
 
3.1%
Other values (205) 1528
47.4%
Common
ValueCountFrequency (%)
341
68.6%
1 121
 
24.3%
) 10
 
2.0%
( 10
 
2.0%
2 6
 
1.2%
5 3
 
0.6%
3 2
 
0.4%
4 1
 
0.2%
0 1
 
0.2%
7 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3223
86.6%
ASCII 497
 
13.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
실 399
 
12.4%
진 217
 
6.7%
료 205
 
6.4%
내 153
 
4.7%
구 131
 
4.1%
층 125
 
3.9%
대 124
 
3.8%
기 121
 
3.8%
소 120
 
3.7%
급 100
 
3.1%
Other values (205) 1528
47.4%
ASCII
ValueCountFrequency (%)
341
68.6%
1 121
 
24.3%
) 10
 
2.0%
( 10
 
2.0%
2 6
 
1.2%
5 3
 
0.6%
3 2
 
0.4%
4 1
 
0.2%
0 1
 
0.2%
7 1
 
0.2%

Interactions

2024-03-14T09:46:22.712688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-03-14T09:46:22.807561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:46:22.878350image/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

NO설치기관명설치주소설치장소
01인휴한신휴플러스아파트전라북도 전주시 덕진구 안덕원로 251 (인후동1가) 한신휴플러스아파트관리사무소
12송천한양아파트전라북도 전주시 덕진구 가리내로 550 (송천동1가) 한양아파트관리사무소
23위브어울림아파트전라북도 전주시 덕진구 견훤로 333 (인후동1가) 위브어울림아파트관리동 1층 방재실
34부영6차아파트전라북도 전주시 덕진구 무삼지로 10 (인후동1가) 부영6차아파트관리사무소
45흥건삼천2차아파트전라북도 전주시 완산구 거마평로 25 (삼천동1가)관리사무소
56서신광진아파트전라북도 전주시 완산구 온고을로 121 (서신동) 서신동 광진아파트아파트 정문 경비실
67서신E편한세상아파트전라북도 전주시 완산구 여울로 161 (서신동) 서신 이편한세상관리사무소
78우성삼천2차아파트전라북도 전주시 완산구 삼천천변2길 51 (삼천동1가) 우성2차아파트관리사무소관리사무소
89송천신일아파트전라북도 전주시 덕진구 솔내로 142 (송천동1가) 신일아파트관리사무소정문경비실내
910호반리젠시빌아파트전라북도 전주시 완산구 평화로 95 (평화동2가) 호반리젠시빌아파트관리사무소관리동 경비실
NO설치기관명설치주소설치장소
620621남원시보건소전라북도 남원시 조산동 455민원실 옆 로비
621622시민운동장 체육청소년과전라북도 김제시 검산동 32-1실내체육관
622623광활보건지소전라북도 김제시 광활면 옥포리 664-1광활보건지소
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