Overview

Dataset statistics

Number of variables13
Number of observations47
Missing cells21
Missing cells (%)3.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory110.8 B

Variable types

Categorical7
Text2
Numeric4

Dataset

Description경기콘텐츠진흥원 보유 공간 및 시설 목록
Author경기콘텐츠진흥원
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=NAMB3VXPGSPYA7T9KJZ534584686&infSeq=1

Alerts

센터명 is highly overall correlated with 정제WGS84위도 and 8 other fieldsHigh correlation
위치명 is highly overall correlated with 정제WGS84위도 and 8 other fieldsHigh correlation
전화번호 is highly overall correlated with 정제WGS84위도 and 8 other fieldsHigh correlation
정제지번주소 is highly overall correlated with 정제WGS84위도 and 8 other fieldsHigh correlation
시군명 is highly overall correlated with 정제WGS84위도 and 8 other fieldsHigh correlation
정제도로명주소 is highly overall correlated with 정제WGS84위도 and 8 other fieldsHigh correlation
정제WGS84위도 is highly overall correlated with 정제WGS84경도 and 8 other fieldsHigh correlation
정제WGS84경도 is highly overall correlated with 정제WGS84위도 and 7 other fieldsHigh correlation
정제우편번호 is highly overall correlated with 정제WGS84위도 and 6 other fieldsHigh correlation
예약방법 is highly overall correlated with 정제WGS84위도 and 7 other fieldsHigh correlation
지원사항 has 9 (19.1%) missing valuesMissing
수용인원수 has 12 (25.5%) missing valuesMissing
공간명 has unique valuesUnique

Reproduction

Analysis started2024-05-10 21:10:48.382833
Analysis finished2024-05-10 21:10:58.213851
Duration9.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size508.0 B
부천시
16 
수원시
의정부시
광명시
성남시

Length

Max length4
Median length3
Mean length3.1702128
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부천시
2nd row부천시
3rd row부천시
4th row여주시
5th row수원시

Common Values

ValueCountFrequency (%)
부천시 16
34.0%
수원시 9
19.1%
의정부시 8
17.0%
광명시 7
14.9%
성남시 5
 
10.6%
여주시 2
 
4.3%

Length

2024-05-10T21:10:58.373150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:10:58.653049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부천시 16
34.0%
수원시 9
19.1%
의정부시 8
17.0%
광명시 7
14.9%
성남시 5
 
10.6%
여주시 2
 
4.3%

센터명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size508.0 B
서부권역센터
12 
미래콘텐츠팀
북부권역센터
게임문화팀
남부권역센터
Other values (2)

Length

Max length6
Median length6
Mean length5.7659574
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서부권역센터
2nd row서부권역센터
3rd row서부권역센터
4th row동부권역센터
5th row미래콘텐츠팀

Common Values

ValueCountFrequency (%)
서부권역센터 12
25.5%
미래콘텐츠팀 9
19.1%
북부권역센터 8
17.0%
게임문화팀 7
14.9%
남부권역센터 5
10.6%
영상산업팀 4
 
8.5%
동부권역센터 2
 
4.3%

Length

2024-05-10T21:10:58.962205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:10:59.297237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서부권역센터 12
25.5%
미래콘텐츠팀 9
19.1%
북부권역센터 8
17.0%
게임문화팀 7
14.9%
남부권역센터 5
10.6%
영상산업팀 4
 
8.5%
동부권역센터 2
 
4.3%

공간명
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2024-05-10T21:10:59.872372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length7.4680851
Min length3

Characters and Unicode

Total characters351
Distinct characters103
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

Unique47 ?
Unique (%)100.0%

Sample

1st row화상회의실 1
2nd row중 회의실(대관)
3rd row세미나실 (대관)
4th row미팅룸
5th row미팅룸-01
ValueCountFrequency (%)
회의실 7
 
9.3%
스튜디오 4
 
5.3%
화상회의실 3
 
4.0%
3
 
4.0%
3
 
4.0%
비디오 2
 
2.7%
2 2
 
2.7%
1 2
 
2.7%
세미나실 2
 
2.7%
인스턴트룸 1
 
1.3%
Other values (46) 46
61.3%
2024-05-10T21:11:00.902498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28
 
8.0%
19
 
5.4%
14
 
4.0%
13
 
3.7%
13
 
3.7%
12
 
3.4%
12
 
3.4%
11
 
3.1%
( 11
 
3.1%
) 11
 
3.1%
Other values (93) 207
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 256
72.9%
Space Separator 28
 
8.0%
Decimal Number 26
 
7.4%
Open Punctuation 12
 
3.4%
Close Punctuation 12
 
3.4%
Uppercase Letter 12
 
3.4%
Other Punctuation 3
 
0.9%
Dash Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
19
 
7.4%
14
 
5.5%
13
 
5.1%
13
 
5.1%
12
 
4.7%
12
 
4.7%
11
 
4.3%
9
 
3.5%
8
 
3.1%
8
 
3.1%
Other values (71) 137
53.5%
Decimal Number
ValueCountFrequency (%)
1 7
26.9%
2 6
23.1%
0 6
23.1%
3 3
11.5%
4 1
 
3.8%
7 1
 
3.8%
5 1
 
3.8%
6 1
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
M 4
33.3%
R 3
25.0%
V 2
16.7%
P 1
 
8.3%
C 1
 
8.3%
A 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 11
91.7%
[ 1
 
8.3%
Close Punctuation
ValueCountFrequency (%)
) 11
91.7%
] 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
/ 2
66.7%
& 1
33.3%
Space Separator
ValueCountFrequency (%)
28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 256
72.9%
Common 83
 
23.6%
Latin 12
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
19
 
7.4%
14
 
5.5%
13
 
5.1%
13
 
5.1%
12
 
4.7%
12
 
4.7%
11
 
4.3%
9
 
3.5%
8
 
3.1%
8
 
3.1%
Other values (71) 137
53.5%
Common
ValueCountFrequency (%)
28
33.7%
( 11
 
13.3%
) 11
 
13.3%
1 7
 
8.4%
2 6
 
7.2%
0 6
 
7.2%
3 3
 
3.6%
/ 2
 
2.4%
- 2
 
2.4%
& 1
 
1.2%
Other values (6) 6
 
7.2%
Latin
ValueCountFrequency (%)
M 4
33.3%
R 3
25.0%
V 2
16.7%
P 1
 
8.3%
C 1
 
8.3%
A 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 256
72.9%
ASCII 95
 
27.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28
29.5%
( 11
 
11.6%
) 11
 
11.6%
1 7
 
7.4%
2 6
 
6.3%
0 6
 
6.3%
M 4
 
4.2%
R 3
 
3.2%
3 3
 
3.2%
/ 2
 
2.1%
Other values (12) 14
14.7%
Hangul
ValueCountFrequency (%)
19
 
7.4%
14
 
5.5%
13
 
5.1%
13
 
5.1%
12
 
4.7%
12
 
4.7%
11
 
4.3%
9
 
3.5%
8
 
3.1%
8
 
3.1%
Other values (71) 137
53.5%

위치명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size508.0 B
10층
10 
5층
9층
11층
15층
Other values (6)
17 

Length

Max length4
Median length3
Mean length2.6170213
Min length2

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row10층
2nd row10층
3rd row10층
4th row1층
5th row6층

Common Values

ValueCountFrequency (%)
10층 10
21.3%
5층 7
14.9%
9층 5
10.6%
11층 4
 
8.5%
15층 4
 
8.5%
12층 4
 
8.5%
2층 4
 
8.5%
6층 3
 
6.4%
<NA> 3
 
6.4%
1층 2
 
4.3%

Length

2024-05-10T21:11:01.431763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10층 10
21.3%
5층 7
14.9%
9층 5
10.6%
11층 4
 
8.5%
15층 4
 
8.5%
12층 4
 
8.5%
2층 4
 
8.5%
6층 3
 
6.4%
na 3
 
6.4%
1층 2
 
4.3%

지원사항
Text

MISSING 

Distinct31
Distinct (%)81.6%
Missing9
Missing (%)19.1%
Memory size508.0 B
2024-05-10T21:11:02.070266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length120
Median length37.5
Mean length32.578947
Min length2

Characters and Unicode

Total characters1238
Distinct characters191
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)71.1%

Sample

1st row화상회의TV, 무선인터넷, 화이트보드, 보드마카
2nd rowTV스크린, HDMI, 무선인터넷, 보드마카
3rd row빔프로젝터, 무선마이크, 무선인터넷
4th row화이트보드/이동형TV(55인치, HDMI)/보드마카/무선인터넷
5th row빔프로젝터, TV모니터, 마이크
ValueCountFrequency (%)
화이트보드 9
 
3.8%
마이크 9
 
3.8%
8
 
3.4%
보드마카 7
 
3.0%
무선인터넷 7
 
3.0%
pc 6
 
2.5%
카메라 6
 
2.5%
조명 5
 
2.1%
좌석 4
 
1.7%
빔프로젝터 4
 
1.7%
Other values (128) 172
72.6%
2024-05-10T21:11:03.467682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
199
 
16.1%
, 112
 
9.0%
40
 
3.2%
28
 
2.3%
27
 
2.2%
27
 
2.2%
24
 
1.9%
23
 
1.9%
22
 
1.8%
22
 
1.8%
Other values (181) 714
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 635
51.3%
Space Separator 199
 
16.1%
Uppercase Letter 158
 
12.8%
Other Punctuation 125
 
10.1%
Lowercase Letter 54
 
4.4%
Decimal Number 46
 
3.7%
Close Punctuation 10
 
0.8%
Open Punctuation 10
 
0.8%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
40
 
6.3%
28
 
4.4%
27
 
4.3%
27
 
4.3%
24
 
3.8%
23
 
3.6%
22
 
3.5%
22
 
3.5%
17
 
2.7%
17
 
2.7%
Other values (130) 388
61.1%
Uppercase Letter
ValueCountFrequency (%)
P 18
11.4%
V 18
11.4%
T 14
 
8.9%
C 13
 
8.2%
D 12
 
7.6%
I 11
 
7.0%
E 11
 
7.0%
H 10
 
6.3%
S 8
 
5.1%
R 8
 
5.1%
Other values (13) 35
22.2%
Lowercase Letter
ValueCountFrequency (%)
i 7
13.0%
t 6
11.1%
l 6
11.1%
r 6
11.1%
o 5
9.3%
c 4
7.4%
k 4
7.4%
e 4
7.4%
a 3
5.6%
m 3
5.6%
Other values (4) 6
11.1%
Decimal Number
ValueCountFrequency (%)
2 13
28.3%
1 12
26.1%
5 6
13.0%
4 4
 
8.7%
3 4
 
8.7%
8 3
 
6.5%
6 3
 
6.5%
0 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 112
89.6%
/ 13
 
10.4%
Space Separator
ValueCountFrequency (%)
199
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 635
51.3%
Common 391
31.6%
Latin 212
 
17.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
40
 
6.3%
28
 
4.4%
27
 
4.3%
27
 
4.3%
24
 
3.8%
23
 
3.6%
22
 
3.5%
22
 
3.5%
17
 
2.7%
17
 
2.7%
Other values (130) 388
61.1%
Latin
ValueCountFrequency (%)
P 18
 
8.5%
V 18
 
8.5%
T 14
 
6.6%
C 13
 
6.1%
D 12
 
5.7%
I 11
 
5.2%
E 11
 
5.2%
H 10
 
4.7%
S 8
 
3.8%
R 8
 
3.8%
Other values (27) 89
42.0%
Common
ValueCountFrequency (%)
199
50.9%
, 112
28.6%
2 13
 
3.3%
/ 13
 
3.3%
1 12
 
3.1%
) 10
 
2.6%
( 10
 
2.6%
5 6
 
1.5%
4 4
 
1.0%
3 4
 
1.0%
Other values (4) 8
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 635
51.3%
ASCII 603
48.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
199
33.0%
, 112
18.6%
P 18
 
3.0%
V 18
 
3.0%
T 14
 
2.3%
2 13
 
2.2%
C 13
 
2.2%
/ 13
 
2.2%
D 12
 
2.0%
1 12
 
2.0%
Other values (41) 179
29.7%
Hangul
ValueCountFrequency (%)
40
 
6.3%
28
 
4.4%
27
 
4.3%
27
 
4.3%
24
 
3.8%
23
 
3.6%
22
 
3.5%
22
 
3.5%
17
 
2.7%
17
 
2.7%
Other values (130) 388
61.1%

예약방법
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size508.0 B
온라인예약
22 
현장예약
전화문의
이메일접수
전화예약
 
2

Length

Max length10
Median length5
Mean length4.7021277
Min length4

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row온라인예약
2nd row이메일접수
3rd row이메일접수
4th row온라인예약
5th row현장예약

Common Values

ValueCountFrequency (%)
온라인예약 22
46.8%
현장예약 9
19.1%
전화문의 8
 
17.0%
이메일접수 5
 
10.6%
전화예약 2
 
4.3%
이메일접수/현장예약 1
 
2.1%

Length

2024-05-10T21:11:03.817254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:11:04.083130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
온라인예약 22
46.8%
현장예약 9
19.1%
전화문의 8
 
17.0%
이메일접수 5
 
10.6%
전화예약 2
 
4.3%
이메일접수/현장예약 1
 
2.1%

전화번호
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Memory size508.0 B
032-623-8087
12 
031-8064-1720
02-6294-6209
031-877-2732
031-776-4609
Other values (4)
11 

Length

Max length13
Median length12
Mean length12.234043
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row032-623-8087
2nd row032-623-8087
3rd row032-623-8087
4th row031-8051-8103
5th row031-8064-1720

Common Values

ValueCountFrequency (%)
032-623-8087 12
25.5%
031-8064-1720 7
14.9%
02-6294-6209 7
14.9%
031-877-2732 5
10.6%
031-776-4609 5
10.6%
032-623-8085 4
 
8.5%
031-877-2733 3
 
6.4%
031-8051-8103 2
 
4.3%
031-8064-1728 2
 
4.3%

Length

2024-05-10T21:11:04.680533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:11:05.025101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
032-623-8087 12
25.5%
031-8064-1720 7
14.9%
02-6294-6209 7
14.9%
031-877-2732 5
10.6%
031-776-4609 5
10.6%
032-623-8085 4
 
8.5%
031-877-2733 3
 
6.4%
031-8051-8103 2
 
4.3%
031-8064-1728 2
 
4.3%

수용인원수
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)34.3%
Missing12
Missing (%)25.5%
Infinite0
Infinite (%)0.0%
Mean10.342857
Minimum2
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-10T21:11:05.366755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q14
median6
Q313.5
95-th percentile30
Maximum50
Range48
Interquartile range (IQR)9.5

Descriptive statistics

Standard deviation10.588403
Coefficient of variation (CV)1.0237407
Kurtosis5.015002
Mean10.342857
Median Absolute Deviation (MAD)2
Skewness2.1633671
Sum362
Variance112.11429
MonotonicityNot monotonic
2024-05-10T21:11:05.810577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
4 15
31.9%
6 5
 
10.6%
30 3
 
6.4%
12 2
 
4.3%
20 2
 
4.3%
15 2
 
4.3%
5 1
 
2.1%
50 1
 
2.1%
7 1
 
2.1%
8 1
 
2.1%
Other values (2) 2
 
4.3%
(Missing) 12
25.5%
ValueCountFrequency (%)
2 1
 
2.1%
4 15
31.9%
5 1
 
2.1%
6 5
 
10.6%
7 1
 
2.1%
8 1
 
2.1%
12 2
 
4.3%
15 2
 
4.3%
16 1
 
2.1%
20 2
 
4.3%
ValueCountFrequency (%)
50 1
 
2.1%
30 3
6.4%
20 2
 
4.3%
16 1
 
2.1%
15 2
 
4.3%
12 2
 
4.3%
8 1
 
2.1%
7 1
 
2.1%
6 5
10.6%
5 1
 
2.1%

정제도로명주소
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size508.0 B
<NA>
16 
경기도 수원시 영통구 광교로 156
경기도 의정부시 신흥로 234
경기도 광명시 양지로 17
경기도 성남시 분당구 대왕판교로645번길 12

Length

Max length25
Median length19
Mean length13.06383
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row경기도 여주시 청심로 88
5th row경기도 수원시 영통구 광교로 156

Common Values

ValueCountFrequency (%)
<NA> 16
34.0%
경기도 수원시 영통구 광교로 156 9
19.1%
경기도 의정부시 신흥로 234 8
17.0%
경기도 광명시 양지로 17 7
14.9%
경기도 성남시 분당구 대왕판교로645번길 12 5
 
10.6%
경기도 여주시 청심로 88 2
 
4.3%

Length

2024-05-10T21:11:06.115629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:11:06.398762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 31
20.1%
na 16
 
10.4%
수원시 9
 
5.8%
영통구 9
 
5.8%
광교로 9
 
5.8%
156 9
 
5.8%
의정부시 8
 
5.2%
신흥로 8
 
5.2%
234 8
 
5.2%
17 7
 
4.5%
Other values (9) 40
26.0%

정제지번주소
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size508.0 B
경기도 부천시 원미구 춘의동 202번지 춘의테크노파크2차 202동
16 
경기도 수원시 영통구 이의동 1322-1번지 광교비즈니스센터
경기도 의정부시 의정부동 501-1번지 C.R.C빌딩
경기도 광명시 일직동 512-3번지 유플래닛
경기도 성남시 분당구 삼평동 629번지 경기창조경제혁신센터

Length

Max length36
Median length33
Mean length31.170213
Min length16

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 부천시 원미구 춘의동 202번지 춘의테크노파크2차 202동
2nd row경기도 부천시 원미구 춘의동 202번지 춘의테크노파크2차 202동
3rd row경기도 부천시 원미구 춘의동 202번지 춘의테크노파크2차 202동
4th row경기도 여주시 하동 124번지
5th row경기도 수원시 영통구 이의동 1322-1번지 광교비즈니스센터

Common Values

ValueCountFrequency (%)
경기도 부천시 원미구 춘의동 202번지 춘의테크노파크2차 202동 16
34.0%
경기도 수원시 영통구 이의동 1322-1번지 광교비즈니스센터 9
19.1%
경기도 의정부시 의정부동 501-1번지 C.R.C빌딩 8
17.0%
경기도 광명시 일직동 512-3번지 유플래닛 7
14.9%
경기도 성남시 분당구 삼평동 629번지 경기창조경제혁신센터 5
 
10.6%
경기도 여주시 하동 124번지 2
 
4.3%

Length

2024-05-10T21:11:06.850105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:11:07.244937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 47
16.8%
부천시 16
 
5.7%
원미구 16
 
5.7%
춘의동 16
 
5.7%
202번지 16
 
5.7%
춘의테크노파크2차 16
 
5.7%
202동 16
 
5.7%
수원시 9
 
3.2%
영통구 9
 
3.2%
이의동 9
 
3.2%
Other values (18) 109
39.1%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.470148
Minimum37.29384
Maximum37.737015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-10T21:11:07.597649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.29384
5-th percentile37.29384
Q137.400348
median37.501544
Q337.501544
95-th percentile37.737015
Maximum37.737015
Range0.44317496
Interquartile range (IQR)0.10119604

Descriptive statistics

Standard deviation0.14494388
Coefficient of variation (CV)0.0038682494
Kurtosis-0.33549012
Mean37.470148
Median Absolute Deviation (MAD)0.10119604
Skewness0.67577658
Sum1761.0969
Variance0.021008727
MonotonicityNot monotonic
2024-05-10T21:11:07.947701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
37.5015441631 16
34.0%
37.2938404396 9
19.1%
37.737015398 8
17.0%
37.4186779767 7
14.9%
37.4003481203 5
 
10.6%
37.2995302517 2
 
4.3%
ValueCountFrequency (%)
37.2938404396 9
19.1%
37.2995302517 2
 
4.3%
37.4003481203 5
 
10.6%
37.4186779767 7
14.9%
37.5015441631 16
34.0%
37.737015398 8
17.0%
ValueCountFrequency (%)
37.737015398 8
17.0%
37.5015441631 16
34.0%
37.4186779767 7
14.9%
37.4003481203 5
 
10.6%
37.2995302517 2
 
4.3%
37.2938404396 9
19.1%

정제WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.96509
Minimum126.78755
Maximum127.63015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-10T21:11:08.322075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.78755
5-th percentile126.78755
Q1126.78755
median127.04359
Q3127.04939
95-th percentile127.10493
Maximum127.63015
Range0.84260801
Interquartile range (IQR)0.26184194

Descriptive statistics

Standard deviation0.18923765
Coefficient of variation (CV)0.00149047
Kurtosis4.7161828
Mean126.96509
Median Absolute Deviation (MAD)0.16070663
Skewness1.7350049
Sum5967.3591
Variance0.03581089
MonotonicityNot monotonic
2024-05-10T21:11:08.576402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
126.7875459075 16
34.0%
127.0493878433 9
19.1%
127.0435941444 8
17.0%
126.8828875175 7
14.9%
127.1049265705 5
 
10.6%
127.630153922 2
 
4.3%
ValueCountFrequency (%)
126.7875459075 16
34.0%
126.8828875175 7
14.9%
127.0435941444 8
17.0%
127.0493878433 9
19.1%
127.1049265705 5
 
10.6%
127.630153922 2
 
4.3%
ValueCountFrequency (%)
127.630153922 2
 
4.3%
127.1049265705 5
 
10.6%
127.0493878433 9
19.1%
127.0435941444 8
17.0%
126.8828875175 7
14.9%
126.7875459075 16
34.0%

정제우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14207.872
Minimum11651
Maximum16506
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-10T21:11:08.826323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11651
5-th percentile11651
Q113487
median14557
Q314557
95-th percentile16506
Maximum16506
Range4855
Interquartile range (IQR)1070

Descriptive statistics

Standard deviation1543.127
Coefficient of variation (CV)0.1086107
Kurtosis-0.55378728
Mean14207.872
Median Absolute Deviation (MAD)1070
Skewness-0.20778037
Sum667770
Variance2381240.9
MonotonicityNot monotonic
2024-05-10T21:11:09.067949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
14557 16
34.0%
16506 9
19.1%
11651 8
17.0%
14345 7
14.9%
13487 5
 
10.6%
12623 2
 
4.3%
ValueCountFrequency (%)
11651 8
17.0%
12623 2
 
4.3%
13487 5
 
10.6%
14345 7
14.9%
14557 16
34.0%
16506 9
19.1%
ValueCountFrequency (%)
16506 9
19.1%
14557 16
34.0%
14345 7
14.9%
13487 5
 
10.6%
12623 2
 
4.3%
11651 8
17.0%

Interactions

2024-05-10T21:10:56.006088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:53.347586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:54.326054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:55.214490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:56.206978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:53.603566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:54.566599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:55.445438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:56.405261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:53.839241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:54.803280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:55.634531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:56.655671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:54.074335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:55.016419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:10:55.819911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T21:11:09.289031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명센터명공간명위치명지원사항예약방법전화번호수용인원수정제도로명주소정제지번주소정제WGS84위도정제WGS84경도정제우편번호
시군명1.0001.0001.0000.9921.0000.9181.0000.0331.0001.0001.0001.0001.000
센터명1.0001.0001.0000.9861.0000.7641.0000.0331.0001.0001.0001.0001.000
공간명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위치명0.9920.9861.0001.0001.0000.8200.9580.6370.9660.9920.9901.0001.000
지원사항1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
예약방법0.9180.7641.0000.8201.0001.0000.8700.5280.7970.9180.7430.7590.690
전화번호1.0001.0001.0000.9581.0000.8701.0000.6201.0001.0001.0001.0001.000
수용인원수0.0330.0331.0000.6371.0000.5280.6201.0000.0000.0330.2560.0000.517
정제도로명주소1.0001.0001.0000.9661.0000.7971.0000.0001.0001.0001.0001.0001.000
정제지번주소1.0001.0001.0000.9921.0000.9181.0000.0331.0001.0001.0001.0001.000
정제WGS84위도1.0001.0001.0000.9901.0000.7431.0000.2561.0001.0001.0000.9490.738
정제WGS84경도1.0001.0001.0001.0001.0000.7591.0000.0001.0001.0000.9491.0000.978
정제우편번호1.0001.0001.0001.0001.0000.6901.0000.5171.0001.0000.7380.9781.000
2024-05-10T21:11:09.641641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
센터명위치명전화번호예약방법정제지번주소시군명정제도로명주소
센터명1.0000.9330.9750.5780.9880.9881.000
위치명0.9331.0000.8390.5800.9150.9150.898
전화번호0.9750.8391.0000.6290.9630.9630.961
예약방법0.5780.5800.6291.0000.5880.5880.668
정제지번주소0.9880.9150.9630.5881.0001.0001.000
시군명0.9880.9150.9630.5881.0001.0001.000
정제도로명주소1.0000.8980.9610.6681.0001.0001.000
2024-05-10T21:11:09.915696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수용인원수정제WGS84위도정제WGS84경도정제우편번호시군명센터명위치명예약방법전화번호정제도로명주소정제지번주소
수용인원수1.0000.370-0.074-0.2430.0000.0000.3960.2030.3840.0000.000
정제WGS84위도0.3701.000-0.589-0.5420.9760.9640.8750.5640.9400.9640.976
정제WGS84경도-0.074-0.5891.000-0.2040.9760.9640.9220.5820.9400.9640.976
정제우편번호-0.243-0.542-0.2041.0000.9880.9760.8950.4910.9511.0000.988
시군명0.0000.9760.9760.9881.0000.9880.9150.5880.9631.0001.000
센터명0.0000.9640.9640.9760.9881.0000.9330.5780.9751.0000.988
위치명0.3960.8750.9220.8950.9150.9331.0000.5800.8390.8980.915
예약방법0.2030.5640.5820.4910.5880.5780.5801.0000.6290.6680.588
전화번호0.3840.9400.9400.9510.9630.9750.8390.6291.0000.9610.963
정제도로명주소0.0000.9640.9641.0001.0001.0000.8980.6680.9611.0001.000
정제지번주소0.0000.9760.9760.9881.0000.9880.9150.5880.9631.0001.000

Missing values

2024-05-10T21:10:56.961012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T21:10:57.515935image/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.
2024-05-10T21:10:58.006855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명센터명공간명위치명지원사항예약방법전화번호수용인원수정제도로명주소정제지번주소정제WGS84위도정제WGS84경도정제우편번호
0부천시서부권역센터화상회의실 110층화상회의TV, 무선인터넷, 화이트보드, 보드마카온라인예약032-623-80876<NA>경기도 부천시 원미구 춘의동 202번지 춘의테크노파크2차 202동37.501544126.78754614557
1부천시서부권역센터중 회의실(대관)10층TV스크린, HDMI, 무선인터넷, 보드마카이메일접수032-623-808712<NA>경기도 부천시 원미구 춘의동 202번지 춘의테크노파크2차 202동37.501544126.78754614557
2부천시서부권역센터세미나실 (대관)10층빔프로젝터, 무선마이크, 무선인터넷이메일접수032-623-808730<NA>경기도 부천시 원미구 춘의동 202번지 춘의테크노파크2차 202동37.501544126.78754614557
3여주시동부권역센터미팅룸1층화이트보드/이동형TV(55인치, HDMI)/보드마카/무선인터넷온라인예약031-8051-81034경기도 여주시 청심로 88경기도 여주시 하동 124번지37.29953127.63015412623
4수원시미래콘텐츠팀미팅룸-016층<NA>현장예약031-8064-17204경기도 수원시 영통구 광교로 156경기도 수원시 영통구 이의동 1322-1번지 광교비즈니스센터37.29384127.04938816506
5수원시미래콘텐츠팀중회의실6층빔프로젝터, TV모니터, 마이크현장예약031-8064-172820경기도 수원시 영통구 광교로 156경기도 수원시 영통구 이의동 1322-1번지 광교비즈니스센터37.29384127.04938816506
6수원시미래콘텐츠팀이벤트홀11층<NA>전화문의031-8064-1728<NA>경기도 수원시 영통구 광교로 156경기도 수원시 영통구 이의동 1322-1번지 광교비즈니스센터37.29384127.04938816506
7광명시게임문화팀커뮤니티존5층송출용PC, 무선마이크2식, 스피커, 대형LED스크린, 계단식 좌석전화문의02-6294-6209<NA>경기도 광명시 양지로 17경기도 광명시 일직동 512-3번지 유플래닛37.418678126.88288814345
8광명시게임문화팀상담실25층스크린, 빔프로젝트, 좌석전화문의02-6294-62094경기도 광명시 양지로 17경기도 광명시 일직동 512-3번지 유플래닛37.418678126.88288814345
9부천시영상산업팀비디오 스튜디오115층조명 8개, 조명 컨트롤러, 카메라 3대, 모니터링TV, 비디오 스위쳐온라인예약032-623-8085<NA><NA>경기도 부천시 원미구 춘의동 202번지 춘의테크노파크2차 202동37.501544126.78754614557
시군명센터명공간명위치명지원사항예약방법전화번호수용인원수정제도로명주소정제지번주소정제WGS84위도정제WGS84경도정제우편번호
37수원시미래콘텐츠팀크로마키/모션 캡처 스튜디오2층크로마키 스튜디오(LED조명, 4K카메라, 고사양PC 2대), 모션캡처 카메라(Optitrack Prime 22 / 12대, Optitrack Prime 13 / 12대), 백팩PC, 서버PC, 운영장비 및 컨트롤러현장예약031-8064-1720<NA>경기도 수원시 영통구 광교로 156경기도 수원시 영통구 이의동 1322-1번지 광교비즈니스센터37.29384127.04938816506
38수원시미래콘텐츠팀미팅룸-026층<NA>현장예약031-8064-17204경기도 수원시 영통구 광교로 156경기도 수원시 영통구 이의동 1322-1번지 광교비즈니스센터37.29384127.04938816506
39수원시미래콘텐츠팀VR/AR 체험존11층<NA>현장예약031-8064-17204경기도 수원시 영통구 광교로 156경기도 수원시 영통구 이의동 1322-1번지 광교비즈니스센터37.29384127.04938816506
40광명시게임문화팀세미나존5층테이블, 개별의자, 소파좌석, 스피커, 정수기, 냉장고전화문의02-6294-6209<NA>경기도 광명시 양지로 17경기도 광명시 일직동 512-3번지 유플래닛37.418678126.88288814345
41광명시게임문화팀트레이닝룸15층게이밍PC, 65인치 LED TV전화문의02-6294-620912경기도 광명시 양지로 17경기도 광명시 일직동 512-3번지 유플래닛37.418678126.88288814345
42광명시게임문화팀스트리밍룸5층게이밍PC, 조명, 방송용 마이크전화문의02-6294-6209<NA>경기도 광명시 양지로 17경기도 광명시 일직동 512-3번지 유플래닛37.418678126.88288814345
43광명시게임문화팀상담실15층스크린, 빔프로젝트, 좌석전화문의02-6294-62094경기도 광명시 양지로 17경기도 광명시 일직동 512-3번지 유플래닛37.418678126.88288814345
44광명시게임문화팀상담실35층스크린, 빔프로젝트, 좌석전화문의02-6294-62094경기도 광명시 양지로 17경기도 광명시 일직동 512-3번지 유플래닛37.418678126.88288814345
45성남시남부권역센터미팅룸(M06)9층화이트보드 / 스마트TV온라인예약031-776-46094경기도 성남시 분당구 대왕판교로645번길 12경기도 성남시 분당구 삼평동 629번지 경기창조경제혁신센터37.400348127.10492713487
46성남시남부권역센터세미나실9층빔프로젝터 / 음향기기 / 마이크 / 무선인터넷온라인예약031-776-460930경기도 성남시 분당구 대왕판교로645번길 12경기도 성남시 분당구 삼평동 629번지 경기창조경제혁신센터37.400348127.10492713487