Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory976.6 KiB
Average record size in memory100.0 B

Variable types

DateTime3
Categorical5
Text1
Numeric2

Dataset

Description제주 신규 공공 와이파이 설치제거를 위한 도내 카테고리별 설치 및 이용 현황 데이터 매쉬업 결과 정보입니다. - 읍면동명, 맥주소, 서비스 사용시간, 사용횟수 등 정보 제공 - 서비스 사용시간 (초), 사용횟수 (건) - 제주빅데이터센터 데이터 활용
Author제주데이터허브
URLhttps://www.jejudatahub.net/data/view/data/760

Alerts

서비스 사용시간 has constant value ""Constant
사용 횟수 has constant value ""Constant
데이터기준일자 has constant value ""Constant
시도명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
읍면동명 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
위도 is highly overall correlated with 시도명 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 읍면동명High correlation

Reproduction

Analysis started2023-12-11 19:29:07.381610
Analysis finished2023-12-11 19:29:08.900141
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자
Date

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2016-11-01 00:00:00
Maximum2016-11-24 00:00:00
2023-12-12T04:29:08.962567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:09.113445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

시도명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제주시
5400 
서귀포시
4600 

Length

Max length4
Median length3
Mean length3.46
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제주시
2nd row서귀포시
3rd row제주시
4th row제주시
5th row제주시

Common Values

ValueCountFrequency (%)
제주시 5400
54.0%
서귀포시 4600
46.0%

Length

2023-12-12T04:29:09.291378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:29:09.400447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 5400
54.0%
서귀포시 4600
46.0%

읍면동명
Categorical

HIGH CORRELATION 

Distinct49
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
천지동
 
572
성산읍
 
502
송산동
 
480
조천읍
 
450
구좌읍
 
395
Other values (44)
7601 

Length

Max length4
Median length3
Mean length3.1002
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row애월읍
2nd row천지동
3rd row한림읍
4th row일도2동
5th row이도2동

Common Values

ValueCountFrequency (%)
천지동 572
 
5.7%
성산읍 502
 
5.0%
송산동 480
 
4.8%
조천읍 450
 
4.5%
구좌읍 395
 
4.0%
남원읍 354
 
3.5%
애월읍 345
 
3.5%
연동 334
 
3.3%
노형동 329
 
3.3%
아라동 327
 
3.3%
Other values (39) 5912
59.1%

Length

2023-12-12T04:29:09.504476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
천지동 572
 
5.7%
성산읍 502
 
5.0%
송산동 480
 
4.8%
조천읍 450
 
4.5%
구좌읍 395
 
4.0%
남원읍 354
 
3.5%
애월읍 345
 
3.5%
연동 334
 
3.3%
노형동 329
 
3.3%
아라동 327
 
3.3%
Other values (39) 5912
59.1%

맥주소
Text

Distinct2265
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T04:29:10.017127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length64
Mean length64
Min length64

Characters and Unicode

Total characters640000
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique162 ?
Unique (%)1.6%

Sample

1st rowb04834f6bc741bb9a09ccc547550e58f91468d7bc6fe7c832331a9a7bb2c1e2d
2nd row8439b33c333150ab6ffbecfe59f37fb868e677a7ef57a87569fc0c843f566c28
3rd row88d314586ae555293f71f044bb435d1d7e2fd377909d91e7b52fba5faa61f133
4th row4d7c0976aa6d768e9284e00702001c7b634b42b9e0030ba498c8fdd8a3220195
5th row25e50fbb673d58a1f3fbfccb50dc14e4fdabc2cdc13408d717c8f2eddc80e1bf
ValueCountFrequency (%)
1a413f41f6df4f24fefd1f563fb21e33f96f4dca0d1be3c6d444be1a3b356ed2 30
 
0.3%
987b502633b7933960df677432fe5aac8b900a603d34cdffef0f436ba901a729 21
 
0.2%
345ffe27527df917cfe41636009d361e362247dda8d7fb1473fda88423d76325 21
 
0.2%
59bed705db7185d3a04487c5a9ed2e83d89b3fd5dbc94d1441aca00e47d27fa4 21
 
0.2%
949a573dc2ac1090c30918dd159b4bcba6672d894a5e33d53bec0f6e674efb7d 20
 
0.2%
7f86ca2d5e165f62a60fa7760b7ec826712f358b9af78dcbf9b084dc8e0ee931 20
 
0.2%
836e3a86956c45acae842b5bae7382d7693a5b92680f538aa5621f3870c17930 20
 
0.2%
c4bddca9c6e5ee93bd278847d844cf00227a2f3036128ef5abafc4296c9db301 20
 
0.2%
f4d46b85de3205cf8ae81676348d25ed2cb23995abb25afb775641e33f619e01 19
 
0.2%
cb96db7be9a791974105fcb3249cde2e79d9ac05c9793adc1c999b939f4e76e3 19
 
0.2%
Other values (2255) 9789
97.9%
2023-12-12T04:29:10.459555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 40819
 
6.4%
7 40754
 
6.4%
f 40489
 
6.3%
6 40358
 
6.3%
e 40096
 
6.3%
a 40027
 
6.3%
4 39960
 
6.2%
c 39958
 
6.2%
9 39936
 
6.2%
0 39889
 
6.2%
Other values (6) 237714
37.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 400019
62.5%
Lowercase Letter 239981
37.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 40819
10.2%
7 40754
10.2%
6 40358
10.1%
4 39960
10.0%
9 39936
10.0%
0 39889
10.0%
8 39787
9.9%
5 39591
9.9%
1 39546
9.9%
2 39379
9.8%
Lowercase Letter
ValueCountFrequency (%)
f 40489
16.9%
e 40096
16.7%
a 40027
16.7%
c 39958
16.7%
b 39715
16.5%
d 39696
16.5%

Most occurring scripts

ValueCountFrequency (%)
Common 400019
62.5%
Latin 239981
37.5%

Most frequent character per script

Common
ValueCountFrequency (%)
3 40819
10.2%
7 40754
10.2%
6 40358
10.1%
4 39960
10.0%
9 39936
10.0%
0 39889
10.0%
8 39787
9.9%
5 39591
9.9%
1 39546
9.9%
2 39379
9.8%
Latin
ValueCountFrequency (%)
f 40489
16.9%
e 40096
16.7%
a 40027
16.7%
c 39958
16.7%
b 39715
16.5%
d 39696
16.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 640000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 40819
 
6.4%
7 40754
 
6.4%
f 40489
 
6.3%
6 40358
 
6.3%
e 40096
 
6.3%
a 40027
 
6.3%
4 39960
 
6.2%
c 39958
 
6.2%
9 39936
 
6.2%
0 39889
 
6.2%
Other values (6) 237714
37.1%

개통일
Date

Distinct242
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2017-07-19 00:00:00
Maximum2020-04-27 00:00:00
2023-12-12T04:29:10.617246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:10.766573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1511
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.388807
Minimum33.166454
Maximum33.559583
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:29:10.888133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.166454
5-th percentile33.240735
Q133.254102
median33.430803
Q333.496938
95-th percentile33.528364
Maximum33.559583
Range0.393129
Interquartile range (IQR)0.242836

Descriptive statistics

Standard deviation0.11483893
Coefficient of variation (CV)0.0034394441
Kurtosis-1.6680912
Mean33.388807
Median Absolute Deviation (MAD)0.0873845
Skewness-0.1722128
Sum333888.07
Variance0.013187981
MonotonicityNot monotonic
2023-12-12T04:29:11.017577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.249836 49
 
0.5%
33.247744 49
 
0.5%
33.248697 49
 
0.5%
33.243868 47
 
0.5%
33.2495 46
 
0.5%
33.437048 43
 
0.4%
33.511806 42
 
0.4%
33.245962 42
 
0.4%
33.244669 40
 
0.4%
33.246184 39
 
0.4%
Other values (1501) 9554
95.5%
ValueCountFrequency (%)
33.166453999999995 13
0.1%
33.199104 4
 
< 0.1%
33.205119 5
 
0.1%
33.2059 4
 
< 0.1%
33.205906 7
0.1%
33.206792 9
0.1%
33.207068 5
 
0.1%
33.208525 2
 
< 0.1%
33.208902 3
 
< 0.1%
33.209822 4
 
< 0.1%
ValueCountFrequency (%)
33.559583 10
0.1%
33.558634999999995 9
0.1%
33.557889 8
0.1%
33.557666 11
0.1%
33.55761 4
 
< 0.1%
33.557227000000005 14
0.1%
33.557167 10
0.1%
33.556926000000004 11
0.1%
33.556553 6
0.1%
33.556414000000004 5
 
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1521
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.55479
Minimum126.16361
Maximum126.96873
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:29:11.151773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16361
5-th percentile126.25611
Q1126.49091
median126.55323
Q3126.60837
95-th percentile126.90282
Maximum126.96873
Range0.805128
Interquartile range (IQR)0.117461

Descriptive statistics

Standard deviation0.1633034
Coefficient of variation (CV)0.0012903771
Kurtosis0.49595892
Mean126.55479
Median Absolute Deviation (MAD)0.06068
Skewness0.25944821
Sum1265547.9
Variance0.026668002
MonotonicityNot monotonic
2023-12-12T04:29:11.285023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.564107 49
 
0.5%
126.559971 49
 
0.5%
126.5603 49
 
0.5%
126.569025 47
 
0.5%
126.56658600000002 46
 
0.5%
126.628152 43
 
0.4%
126.563879 42
 
0.4%
126.526056 42
 
0.4%
126.563767 41
 
0.4%
126.557365 39
 
0.4%
Other values (1511) 9553
95.5%
ValueCountFrequency (%)
126.163606 6
0.1%
126.164197 2
 
< 0.1%
126.165759 10
0.1%
126.166233 4
 
< 0.1%
126.166301 7
0.1%
126.166819 4
 
< 0.1%
126.167783 7
0.1%
126.168003 10
0.1%
126.171035 9
0.1%
126.172232 9
0.1%
ValueCountFrequency (%)
126.968734 7
0.1%
126.967512 5
0.1%
126.967145 12
0.1%
126.9658 3
 
< 0.1%
126.965055 3
 
< 0.1%
126.964697 3
 
< 0.1%
126.963074 4
 
< 0.1%
126.959746 10
0.1%
126.959703 4
 
< 0.1%
126.959575 2
 
< 0.1%

카테고리
Categorical

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
버스정류소
2307 
관광지
1988 
전기차충전소
925 
공원
917 
올레코스
883 
Other values (15)
2980 

Length

Max length13
Median length10
Mean length4.0843
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전기차충전소
2nd row테마거리
3rd row버스정류소
4th row테마거리
5th row버스정류소

Common Values

ValueCountFrequency (%)
버스정류소 2307
23.1%
관광지 1988
19.9%
전기차충전소 925
9.2%
공원 917
 
9.2%
올레코스 883
 
8.8%
테마거리 869
 
8.7%
해변 481
 
4.8%
전통시장 410
 
4.1%
정류소 273
 
2.7%
공공기관 246
 
2.5%
Other values (10) 701
 
7.0%

Length

2023-12-12T04:29:11.462770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
버스정류소 2307
22.9%
관광지 1988
19.7%
전기차충전소 925
9.2%
공원 917
 
9.1%
올레코스 883
 
8.8%
테마거리 869
 
8.6%
해변 481
 
4.8%
전통시장 410
 
4.1%
정류소 273
 
2.7%
공공기관 246
 
2.4%
Other values (10) 786
 
7.8%

서비스 사용시간
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2023-12-12T04:29:11.591376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:29:11.678931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

사용 횟수
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2023-12-12T04:29:11.763833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:29:11.849849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-12-15 00:00:00
Maximum2020-12-15 00:00:00
2023-12-12T04:29:11.915962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:11.993685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T04:29:08.306200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:08.078258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:08.445032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:08.184887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:29:12.060551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자시도명읍면동명위도경도카테고리
일자1.0000.0000.0000.0000.0000.000
시도명0.0001.0001.0000.9770.2700.342
읍면동명0.0001.0001.0000.9140.9610.784
위도0.0000.9770.9141.0000.7750.628
경도0.0000.2700.9610.7751.0000.583
카테고리0.0000.3420.7840.6280.5831.000
2023-12-12T04:29:12.169047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카테고리시도명읍면동명
카테고리1.0000.2700.303
시도명0.2701.0000.998
읍면동명0.3030.9981.000
2023-12-12T04:29:12.266804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도시도명읍면동명카테고리
위도1.0000.1150.8680.6100.248
경도0.1151.0000.2070.7530.222
시도명0.8680.2071.0000.9980.270
읍면동명0.6100.7530.9981.0000.303
카테고리0.2480.2220.2700.3031.000

Missing values

2023-12-12T04:29:08.649873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:29:08.834419image/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

일자시도명읍면동명맥주소개통일위도경도카테고리서비스 사용시간사용 횟수데이터기준일자
11992016-11-01제주시애월읍b04834f6bc741bb9a09ccc547550e58f91468d7bc6fe7c832331a9a7bb2c1e2d2020-03-2833.438361126.330258전기차충전소002020-12-15
410342016-11-16서귀포시천지동8439b33c333150ab6ffbecfe59f37fb868e677a7ef57a87569fc0c843f566c282017-08-3033.243868126.569025테마거리002020-12-15
265322016-11-10제주시한림읍88d314586ae555293f71f044bb435d1d7e2fd377909d91e7b52fba5faa61f1332019-08-0533.441848126.288716버스정류소002020-12-15
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