Overview

Dataset statistics

Number of variables5
Number of observations403
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.3 KiB
Average record size in memory41.3 B

Variable types

Numeric1
Categorical3
Text1

Dataset

Description경상남도 김해시에 설치된 자동음성동보시스템 현황에 대한 자료로 구분, 읍면동, 위치, 통신방식 등에 대한 데이터로 구성되어 있습니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15091901

Alerts

통신방식 has constant value ""Constant
연번 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
읍면동 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-20 18:31:22.380961
Analysis finished2024-04-20 18:31:23.494231
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct403
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean202
Minimum1
Maximum403
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-21T03:31:23.711009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21.1
Q1101.5
median202
Q3302.5
95-th percentile382.9
Maximum403
Range402
Interquartile range (IQR)201

Descriptive statistics

Standard deviation116.48033
Coefficient of variation (CV)0.57663528
Kurtosis-1.2
Mean202
Median Absolute Deviation (MAD)101
Skewness0
Sum81406
Variance13567.667
MonotonicityStrictly increasing
2024-04-21T03:31:24.164315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
267 1
 
0.2%
277 1
 
0.2%
276 1
 
0.2%
275 1
 
0.2%
274 1
 
0.2%
273 1
 
0.2%
272 1
 
0.2%
271 1
 
0.2%
270 1
 
0.2%
Other values (393) 393
97.5%
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 (%)
403 1
0.2%
402 1
0.2%
401 1
0.2%
400 1
0.2%
399 1
0.2%
398 1
0.2%
397 1
0.2%
396 1
0.2%
395 1
0.2%
394 1
0.2%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
경보기(마을앰프)
287 
DMB 재난 경보방송 시스템
116 

Length

Max length16
Median length9
Mean length11.014888
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경보기(마을앰프)
2nd row경보기(마을앰프)
3rd row경보기(마을앰프)
4th row경보기(마을앰프)
5th row경보기(마을앰프)

Common Values

ValueCountFrequency (%)
경보기(마을앰프) 287
71.2%
DMB 재난 경보방송 시스템 116
28.8%

Length

2024-04-21T03:31:24.615736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:31:24.955372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경보기(마을앰프 287
38.2%
dmb 116
15.4%
재난 116
15.4%
경보방송 116
15.4%
시스템 116
15.4%

읍면동
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
진영읍
65 
한림면
49 
대동면
34 
진례면
32 
생림면
28 
Other values (16)
195 

Length

Max length5
Median length3
Mean length3.2555831
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row내외동
2nd row내외동
3rd row내외동
4th row대동면
5th row대동면

Common Values

ValueCountFrequency (%)
진영읍 65
16.1%
한림면 49
12.2%
대동면 34
8.4%
진례면 32
 
7.9%
생림면 28
 
6.9%
장유1동 26
 
6.5%
북부동 25
 
6.2%
주촌면 23
 
5.7%
상동면 19
 
4.7%
장유3동 19
 
4.7%
Other values (11) 83
20.6%

Length

2024-04-21T03:31:25.346529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
진영읍 65
16.1%
한림면 49
12.2%
대동면 34
8.4%
진례면 32
7.9%
생림면 28
 
6.9%
장유1동 26
 
6.5%
북부동 25
 
6.2%
장유3동 23
 
5.7%
주촌면 23
 
5.7%
상동면 19
 
4.7%
Other values (9) 79
19.6%

위치
Text

Distinct392
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-21T03:31:26.341774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length6.5955335
Min length2

Characters and Unicode

Total characters2658
Distinct characters266
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

Unique382 ?
Unique (%)94.8%

Sample

1st row내외동사무소
2nd row연지공원
3rd row무접
4th row대동면사무소
5th row주중마을회관
ValueCountFrequency (%)
용전마을회관 3
 
0.7%
송정마을회관 2
 
0.5%
하봉마을회관 2
 
0.5%
신전마을회관 2
 
0.5%
양지마을회관 2
 
0.5%
용곡마을회관 2
 
0.5%
금음마을회관 2
 
0.5%
신안마을 2
 
0.5%
신기마을회관 2
 
0.5%
신촌마을회관 2
 
0.5%
Other values (386) 386
94.8%
2024-04-21T03:31:27.668465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 294
 
11.1%
을 290
 
10.9%
관 210
 
7.9%
회 209
 
7.9%
지 62
 
2.3%
동 60
 
2.3%
아 57
 
2.1%
파 51
 
1.9%
트 49
 
1.8%
단 40
 
1.5%
Other values (256) 1336
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2520
94.8%
Decimal Number 115
 
4.3%
Lowercase Letter 7
 
0.3%
Space Separator 6
 
0.2%
Other Punctuation 5
 
0.2%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 294
 
11.7%
을 290
 
11.5%
관 210
 
8.3%
회 209
 
8.3%
지 62
 
2.5%
동 60
 
2.4%
아 57
 
2.3%
파 51
 
2.0%
트 49
 
1.9%
단 40
 
1.6%
Other values (237) 1198
47.5%
Decimal Number
ValueCountFrequency (%)
1 40
34.8%
2 36
31.3%
3 17
14.8%
4 7
 
6.1%
7 4
 
3.5%
6 4
 
3.5%
9 3
 
2.6%
5 2
 
1.7%
8 2
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
e 5
71.4%
h 1
 
14.3%
t 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
, 3
60.0%
# 1
 
20.0%
. 1
 
20.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
Q 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2520
94.8%
Common 130
 
4.9%
Latin 8
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 294
 
11.7%
을 290
 
11.5%
관 210
 
8.3%
회 209
 
8.3%
지 62
 
2.5%
동 60
 
2.4%
아 57
 
2.3%
파 51
 
2.0%
트 49
 
1.9%
단 40
 
1.6%
Other values (237) 1198
47.5%
Common
ValueCountFrequency (%)
1 40
30.8%
2 36
27.7%
3 17
13.1%
4 7
 
5.4%
6
 
4.6%
7 4
 
3.1%
6 4
 
3.1%
9 3
 
2.3%
, 3
 
2.3%
) 2
 
1.5%
Other values (5) 8
 
6.2%
Latin
ValueCountFrequency (%)
e 5
62.5%
Q 1
 
12.5%
h 1
 
12.5%
t 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2520
94.8%
ASCII 138
 
5.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 294
 
11.7%
을 290
 
11.5%
관 210
 
8.3%
회 209
 
8.3%
지 62
 
2.5%
동 60
 
2.4%
아 57
 
2.3%
파 51
 
2.0%
트 49
 
1.9%
단 40
 
1.6%
Other values (237) 1198
47.5%
ASCII
ValueCountFrequency (%)
1 40
29.0%
2 36
26.1%
3 17
12.3%
4 7
 
5.1%
6
 
4.3%
e 5
 
3.6%
7 4
 
2.9%
6 4
 
2.9%
9 3
 
2.2%
, 3
 
2.2%
Other values (9) 13
 
9.4%

통신방식
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
CDMA
403 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
CDMA 403
100.0%

Length

2024-04-21T03:31:28.062936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:31:28.363973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
cdma 403
100.0%

Interactions

2024-04-21T03:31:22.720186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T03:31:28.546138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분읍면동
연번1.0000.9990.949
구분0.9991.0000.787
읍면동0.9490.7871.000
2024-04-21T03:31:28.775860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동구분
읍면동1.0000.698
구분0.6981.000
2024-04-21T03:31:29.006560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분읍면동
연번1.0000.9630.744
구분0.9631.0000.698
읍면동0.7440.6981.000

Missing values

2024-04-21T03:31:23.067967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T03:31:23.377450image/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

연번구분읍면동위치통신방식
01경보기(마을앰프)내외동내외동사무소CDMA
12경보기(마을앰프)내외동연지공원CDMA
23경보기(마을앰프)내외동무접CDMA
34경보기(마을앰프)대동면대동면사무소CDMA
45경보기(마을앰프)대동면주중마을회관CDMA
56경보기(마을앰프)대동면안막3구마을회관CDMA
67경보기(마을앰프)대동면시례마을회관CDMA
78경보기(마을앰프)대동면신명마을회관CDMA
89경보기(마을앰프)대동면장시마을회관CDMA
910경보기(마을앰프)대동면안막1구CDMA
연번구분읍면동위치통신방식
393394DMB 재난 경보방송 시스템진영읍한림풀에버1단지CDMA
394395DMB 재난 경보방송 시스템진영읍원창시인의마을CDMA
395396DMB 재난 경보방송 시스템진영읍세일임대아파트CDMA
396397DMB 재난 경보방송 시스템진영읍진영삼성타워아파트CDMA
397398DMB 재난 경보방송 시스템진영읍마루애주상복합아파트CDMA
398399DMB 재난 경보방송 시스템칠산서부동반도보라아파트CDMA
399400DMB 재난 경보방송 시스템활천동어방동원아파트CDMA
400401DMB 재난 경보방송 시스템활천동어방화인아파트CDMA
401402DMB 재난 경보방송 시스템활천동김해미소지움아파트CDMA
402403DMB 재난 경보방송 시스템회현동봉황동e편한세상CDMA