Overview

Dataset statistics

Number of variables9
Number of observations32
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory79.1 B

Variable types

Text6
Numeric3

Alerts

소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
시군명 has unique valuesUnique
센터명 has unique valuesUnique
전화번호정보 has unique valuesUnique
홈페이지주소 has unique valuesUnique
소재지우편번호 has unique valuesUnique
소재지지번주소 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:37:10.932597
Analysis finished2023-12-10 21:37:12.584067
Duration1.65 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:37:12.757010image/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 row가평군
2nd row경기도
3rd row고양시
4th row과천시
5th row광명시
ValueCountFrequency (%)
가평군 1
 
3.1%
경기도 1
 
3.1%
하남시 1
 
3.1%
포천시 1
 
3.1%
평택시 1
 
3.1%
파주시 1
 
3.1%
이천시 1
 
3.1%
의정부시 1
 
3.1%
의왕시 1
 
3.1%
용인시 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T06:37:13.105583image/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%
성 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 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%
성 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 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%
성 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 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%
성 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
Other values (31) 35
35.4%

센터명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:37:13.350401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7.25
Min length7

Characters and Unicode

Total characters232
Distinct characters46
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 row가평군일자리센터
2nd row경기일자리센터
3rd row고양일자리센터
4th row과천일자리센터
5th row광명일자리센터
ValueCountFrequency (%)
가평군일자리센터 1
 
3.1%
경기일자리센터 1
 
3.1%
하남일자리센터 1
 
3.1%
포천일자리센터 1
 
3.1%
평택일자리센터 1
 
3.1%
파주일자리센터 1
 
3.1%
이천일자리센터 1
 
3.1%
의정부일자리센터 1
 
3.1%
의왕일자리센터 1
 
3.1%
용인일자리센터 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T06:37:13.751142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 33
14.2%
일 32
13.8%
자 32
13.8%
센 32
13.8%
터 32
13.8%
천 6
 
2.6%
양 5
 
2.2%
주 5
 
2.2%
안 3
 
1.3%
남 3
 
1.3%
Other values (36) 49
21.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 232
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 33
14.2%
일 32
13.8%
자 32
13.8%
센 32
13.8%
터 32
13.8%
천 6
 
2.6%
양 5
 
2.2%
주 5
 
2.2%
안 3
 
1.3%
남 3
 
1.3%
Other values (36) 49
21.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 232
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 33
14.2%
일 32
13.8%
자 32
13.8%
센 32
13.8%
터 32
13.8%
천 6
 
2.6%
양 5
 
2.2%
주 5
 
2.2%
안 3
 
1.3%
남 3
 
1.3%
Other values (36) 49
21.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 232
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 33
14.2%
일 32
13.8%
자 32
13.8%
센 32
13.8%
터 32
13.8%
천 6
 
2.6%
양 5
 
2.2%
주 5
 
2.2%
안 3
 
1.3%
남 3
 
1.3%
Other values (36) 49
21.1%

전화번호정보
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:37:13.969395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length28
Mean length15.25
Min length12

Characters and Unicode

Total characters488
Distinct characters15
Distinct categories5 ?
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 row031-582-8346~7
2nd row031-270-9600, 031-270-9635~7
3rd row031-8075-3665
4th row02-3677-2857
5th row02-2680-6273
ValueCountFrequency (%)
031-582-8346~7 1
 
2.9%
031-289-2262~8 1
 
2.9%
031-8082-4070~4 1
 
2.9%
031-770-2237 1
 
2.9%
1020 1
 
2.9%
031-887-2691~4 1
 
2.9%
031-839-2979~2980 1
 
2.9%
031-8024-9857~9860 1
 
2.9%
031-345-2463~6 1
 
2.9%
031-270-9600 1
 
2.9%
Other values (24) 24
70.6%
2023-12-11T06:37:14.371297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72
14.8%
- 70
14.3%
3 57
11.7%
1 55
11.3%
2 44
9.0%
8 35
7.2%
9 32
6.6%
6 31
6.4%
7 26
 
5.3%
5 21
 
4.3%
Other values (5) 45
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 391
80.1%
Dash Punctuation 70
 
14.3%
Math Symbol 21
 
4.3%
Other Punctuation 4
 
0.8%
Space Separator 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72
18.4%
3 57
14.6%
1 55
14.1%
2 44
11.3%
8 35
9.0%
9 32
8.2%
6 31
7.9%
7 26
 
6.6%
5 21
 
5.4%
4 18
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
/ 2
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 488
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 72
14.8%
- 70
14.3%
3 57
11.7%
1 55
11.3%
2 44
9.0%
8 35
7.2%
9 32
6.6%
6 31
6.4%
7 26
 
5.3%
5 21
 
4.3%
Other values (5) 45
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 488
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 72
14.8%
- 70
14.3%
3 57
11.7%
1 55
11.3%
2 44
9.0%
8 35
7.2%
9 32
6.6%
6 31
6.4%
7 26
 
5.3%
5 21
 
4.3%
Other values (5) 45
9.2%

홈페이지주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:37:14.606505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length54
Mean length43.0625
Min length33

Characters and Unicode

Total characters1378
Distinct characters34
Distinct categories6 ?
Distinct scripts2 ?
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 rowhttp://gyeonggi.work.go.kr/gapyeong/main.do
2nd rowhttp://gyeonggi.work.go.kr/main.do/main.do
3rd rowhttp://blog.naver.com/goyang_jobs
4th rowhttp://gyeonggi.work.go.kr/gwacheon/main.do
5th rowhttp://gyeonggi.work.go.kr/gwangmyeong/main.do
ValueCountFrequency (%)
http://gyeonggi.work.go.kr/gapyeong/main.do 1
 
3.1%
http://gyeonggi.work.go.kr/main.do/main.do 1
 
3.1%
http://gyeonggi.work.go.kr/hanam/main.do 1
 
3.1%
http://gyeonggi.work.go.kr/pocheon/main.do 1
 
3.1%
http://gyeonggi.work.go.kr/pyeongtaek/main.do 1
 
3.1%
http://gyeonggi.work.go.kr/paju/main.do 1
 
3.1%
http://gyeonggi.work.go.kr/icheon/main.do 1
 
3.1%
http://gyeonggi.work.go.kr/uijeongbu/main.do 1
 
3.1%
http://gyeonggi.work.go.kr/uiwang/main.do 1
 
3.1%
http://gyeonggi.work.go.kr/yongin/main.do 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T06:37:14.957441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
g 155
11.2%
o 155
11.2%
/ 127
 
9.2%
. 127
 
9.2%
n 104
 
7.5%
i 73
 
5.3%
r 67
 
4.9%
t 65
 
4.7%
k 63
 
4.6%
a 55
 
4.0%
Other values (24) 387
28.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1067
77.4%
Other Punctuation 289
 
21.0%
Decimal Number 15
 
1.1%
Uppercase Letter 3
 
0.2%
Math Symbol 3
 
0.2%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
g 155
14.5%
o 155
14.5%
n 104
9.7%
i 73
 
6.8%
r 67
 
6.3%
t 65
 
6.1%
k 63
 
5.9%
a 55
 
5.2%
e 53
 
5.0%
y 43
 
4.0%
Other values (12) 234
21.9%
Decimal Number
ValueCountFrequency (%)
1 4
26.7%
0 4
26.7%
4 3
20.0%
3 2
13.3%
8 2
13.3%
Other Punctuation
ValueCountFrequency (%)
/ 127
43.9%
. 127
43.9%
: 32
 
11.1%
? 3
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 3
100.0%
Math Symbol
ValueCountFrequency (%)
= 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1070
77.6%
Common 308
 
22.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
g 155
14.5%
o 155
14.5%
n 104
9.7%
i 73
 
6.8%
r 67
 
6.3%
t 65
 
6.1%
k 63
 
5.9%
a 55
 
5.1%
e 53
 
5.0%
y 43
 
4.0%
Other values (13) 237
22.1%
Common
ValueCountFrequency (%)
/ 127
41.2%
. 127
41.2%
: 32
 
10.4%
1 4
 
1.3%
0 4
 
1.3%
? 3
 
1.0%
= 3
 
1.0%
4 3
 
1.0%
3 2
 
0.6%
8 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1378
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
g 155
11.2%
o 155
11.2%
/ 127
 
9.2%
. 127
 
9.2%
n 104
 
7.5%
i 73
 
5.3%
r 67
 
4.9%
t 65
 
4.7%
k 63
 
4.6%
a 55
 
4.0%
Other values (24) 387
28.1%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13908.469
Minimum10109
Maximum18411
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T06:37:15.080238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10109
5-th percentile10675.3
Q111846.25
median13621.5
Q315887.5
95-th percentile17915.85
Maximum18411
Range8302
Interquartile range (IQR)4041.25

Descriptive statistics

Standard deviation2484.2989
Coefficient of variation (CV)0.17861772
Kurtosis-1.0921087
Mean13908.469
Median Absolute Deviation (MAD)2061.5
Skewness0.32837741
Sum445071
Variance6171741.2
MonotonicityNot monotonic
2023-12-11T06:37:15.194057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
12419 1
 
3.1%
14053 1
 
3.1%
18411 1
 
3.1%
12951 1
 
3.1%
11149 1
 
3.1%
17739 1
 
3.1%
10930 1
 
3.1%
17379 1
 
3.1%
11622 1
 
3.1%
16063 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
10109 1
3.1%
10364 1
3.1%
10930 1
3.1%
11025 1
3.1%
11149 1
3.1%
11357 1
3.1%
11498 1
3.1%
11622 1
3.1%
11921 1
3.1%
12237 1
3.1%
ValueCountFrequency (%)
18411 1
3.1%
18132 1
3.1%
17739 1
3.1%
17596 1
3.1%
17379 1
3.1%
16977 1
3.1%
16490 1
3.1%
16063 1
3.1%
15829 1
3.1%
15335 1
3.1%

소재지지번주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:37:15.420647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length17.90625
Min length13

Characters and Unicode

Total characters573
Distinct characters90
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

Unique32 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 가평읍 대곡리 168-7
2nd row경기도 부천시 원미동 71 원미어울마당
3rd row경기도 고양시 일산동구 장항동 736-2
4th row경기도 과천시 중앙동 1-3
5th row경기도 광명시 철산동 222-1
ValueCountFrequency (%)
경기도 32
 
23.4%
부천시 2
 
1.5%
448-8 1
 
0.7%
용인시 1
 
0.7%
915 1
 
0.7%
오산동 1
 
0.7%
오산시 1
 
0.7%
386-14 1
 
0.7%
전곡리 1
 
0.7%
전곡읍 1
 
0.7%
Other values (95) 95
69.3%
2023-12-11T06:37:15.775057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
18.3%
기 34
 
5.9%
도 33
 
5.8%
경 32
 
5.6%
동 32
 
5.6%
시 30
 
5.2%
1 24
 
4.2%
- 21
 
3.7%
2 17
 
3.0%
3 13
 
2.3%
Other values (80) 232
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 324
56.5%
Decimal Number 120
 
20.9%
Space Separator 105
 
18.3%
Dash Punctuation 21
 
3.7%
Other Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 34
 
10.5%
도 33
 
10.2%
경 32
 
9.9%
동 32
 
9.9%
시 30
 
9.3%
양 8
 
2.5%
천 8
 
2.5%
구 8
 
2.5%
리 5
 
1.5%
평 5
 
1.5%
Other values (67) 129
39.8%
Decimal Number
ValueCountFrequency (%)
1 24
20.0%
2 17
14.2%
3 13
10.8%
0 13
10.8%
8 11
9.2%
6 10
8.3%
7 9
 
7.5%
5 8
 
6.7%
9 8
 
6.7%
4 7
 
5.8%
Space Separator
ValueCountFrequency (%)
105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Other Punctuation
ValueCountFrequency (%)
? 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 324
56.5%
Common 249
43.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 34
 
10.5%
도 33
 
10.2%
경 32
 
9.9%
동 32
 
9.9%
시 30
 
9.3%
양 8
 
2.5%
천 8
 
2.5%
구 8
 
2.5%
리 5
 
1.5%
평 5
 
1.5%
Other values (67) 129
39.8%
Common
ValueCountFrequency (%)
105
42.2%
1 24
 
9.6%
- 21
 
8.4%
2 17
 
6.8%
3 13
 
5.2%
0 13
 
5.2%
8 11
 
4.4%
6 10
 
4.0%
7 9
 
3.6%
5 8
 
3.2%
Other values (3) 18
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 324
56.5%
ASCII 249
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
42.2%
1 24
 
9.6%
- 21
 
8.4%
2 17
 
6.8%
3 13
 
5.2%
0 13
 
5.2%
8 11
 
4.4%
6 10
 
4.0%
7 9
 
3.6%
5 8
 
3.2%
Other values (3) 18
 
7.2%
Hangul
ValueCountFrequency (%)
기 34
 
10.5%
도 33
 
10.2%
경 32
 
9.9%
동 32
 
9.9%
시 30
 
9.3%
양 8
 
2.5%
천 8
 
2.5%
구 8
 
2.5%
리 5
 
1.5%
평 5
 
1.5%
Other values (67) 129
39.8%

소재지도로명주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:37:16.053282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length16.78125
Min length13

Characters and Unicode

Total characters537
Distinct characters101
Distinct categories6 ?
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 가평군 가평읍 가화로 52
2nd row경기도 부천시 부천로136번길 27 (원미동)
3rd row경기도 고양시 일산동구 고봉로 32-16
4th row경기도 과천시 관문로 69
5th row경기도 광명시 시청로 20
ValueCountFrequency (%)
경기도 31
 
22.5%
부천시 2
 
1.4%
11 2
 
1.4%
984 2
 
1.4%
중앙로 2
 
1.4%
8 2
 
1.4%
18 1
 
0.7%
용인시 1
 
0.7%
141 1
 
0.7%
성호대로 1
 
0.7%
Other values (93) 93
67.4%
2023-12-11T06:37:16.420949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
106
19.7%
경 34
 
6.3%
기 34
 
6.3%
시 33
 
6.1%
도 31
 
5.8%
로 29
 
5.4%
1 18
 
3.4%
3 14
 
2.6%
2 12
 
2.2%
4 11
 
2.0%
Other values (91) 215
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 343
63.9%
Space Separator 106
 
19.7%
Decimal Number 85
 
15.8%
Dash Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 34
 
9.9%
기 34
 
9.9%
시 33
 
9.6%
도 31
 
9.0%
로 29
 
8.5%
천 8
 
2.3%
길 8
 
2.3%
대 7
 
2.0%
구 7
 
2.0%
성 6
 
1.7%
Other values (77) 146
42.6%
Decimal Number
ValueCountFrequency (%)
1 18
21.2%
3 14
16.5%
2 12
14.1%
4 11
12.9%
9 7
 
8.2%
8 7
 
8.2%
5 6
 
7.1%
0 4
 
4.7%
6 3
 
3.5%
7 3
 
3.5%
Space Separator
ValueCountFrequency (%)
106
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 343
63.9%
Common 194
36.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 34
 
9.9%
기 34
 
9.9%
시 33
 
9.6%
도 31
 
9.0%
로 29
 
8.5%
천 8
 
2.3%
길 8
 
2.3%
대 7
 
2.0%
구 7
 
2.0%
성 6
 
1.7%
Other values (77) 146
42.6%
Common
ValueCountFrequency (%)
106
54.6%
1 18
 
9.3%
3 14
 
7.2%
2 12
 
6.2%
4 11
 
5.7%
9 7
 
3.6%
8 7
 
3.6%
5 6
 
3.1%
0 4
 
2.1%
6 3
 
1.5%
Other values (4) 6
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 343
63.9%
ASCII 194
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
106
54.6%
1 18
 
9.3%
3 14
 
7.2%
2 12
 
6.2%
4 11
 
5.7%
9 7
 
3.6%
8 7
 
3.6%
5 6
 
3.1%
0 4
 
2.1%
6 3
 
1.5%
Other values (4) 6
 
3.1%
Hangul
ValueCountFrequency (%)
경 34
 
9.9%
기 34
 
9.9%
시 33
 
9.6%
도 31
 
9.0%
로 29
 
8.5%
천 8
 
2.3%
길 8
 
2.3%
대 7
 
2.0%
구 7
 
2.0%
성 6
 
1.7%
Other values (77) 146
42.6%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.486176
Minimum37.001247
Maximum38.031282
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T06:37:16.540377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.001247
5-th percentile37.106323
Q137.315866
median37.453406
Q337.64122
95-th percentile37.894305
Maximum38.031282
Range1.0300359
Interquartile range (IQR)0.32535445

Descriptive statistics

Standard deviation0.25058364
Coefficient of variation (CV)0.0066846947
Kurtosis-0.37475766
Mean37.486176
Median Absolute Deviation (MAD)0.171037
Skewness0.24059264
Sum1199.5576
Variance0.062792161
MonotonicityNot monotonic
2023-12-11T06:37:16.656299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
37.8245127 1
 
3.1%
37.3940799 1
 
3.1%
37.2076895 1
 
3.1%
37.5390409 1
 
3.1%
37.8906951 1
 
3.1%
37.0531771 1
 
3.1%
37.7648378 1
 
3.1%
37.2716022 1
 
3.1%
37.73799 1
 
3.1%
37.3477286 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
37.0012465 1
3.1%
37.0531771 1
3.1%
37.1498057 1
3.1%
37.2076895 1
3.1%
37.2633752 1
3.1%
37.2710176 1
3.1%
37.2716022 1
3.1%
37.2973526 1
3.1%
37.3220367 1
3.1%
37.3477286 1
3.1%
ValueCountFrequency (%)
38.0312824 1
3.1%
37.8987181 1
3.1%
37.8906951 1
3.1%
37.8245127 1
3.1%
37.7849261 1
3.1%
37.7648378 1
3.1%
37.73799 1
3.1%
37.6641294 1
3.1%
37.6335837 1
3.1%
37.6153023 1
3.1%

WGS84경도
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.06871
Minimum126.71564
Maximum127.63502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T06:37:16.818485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.71564
5-th percentile126.77073
Q1126.91738
median127.05215
Q3127.20071
95-th percentile127.50018
Maximum127.63502
Range0.9193837
Interquartile range (IQR)0.28332903

Descriptive statistics

Standard deviation0.23113469
Coefficient of variation (CV)0.0018189741
Kurtosis0.12014048
Mean127.06871
Median Absolute Deviation (MAD)0.15088745
Skewness0.63301994
Sum4066.1988
Variance0.053423246
MonotonicityNot monotonic
2023-12-11T06:37:16.954968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
127.5158021 1
 
3.1%
126.9569764 1
 
3.1%
127.0357758 1
 
3.1%
127.2146136 1
 
3.1%
127.1983823 1
 
3.1%
127.0604193 1
 
3.1%
126.7746763 1
 
3.1%
127.4343015 1
 
3.1%
127.0338535 1
 
3.1%
126.9757506 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
126.7156375 1
3.1%
126.7659067 1
3.1%
126.7746763 1
3.1%
126.7813788 1
3.1%
126.7869622 1
3.1%
126.8034944 1
3.1%
126.8315185 1
3.1%
126.8645715 1
3.1%
126.9349861 1
3.1%
126.9569764 1
3.1%
ValueCountFrequency (%)
127.6350212 1
3.1%
127.5158021 1
3.1%
127.4873972 1
3.1%
127.4343015 1
3.1%
127.2677352 1
3.1%
127.2543329 1
3.1%
127.2146136 1
3.1%
127.207699 1
3.1%
127.1983823 1
3.1%
127.1402049 1
3.1%

Interactions

2023-12-11T06:37:12.022052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:11.364708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:11.656163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:12.141824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:11.458204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:11.764673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:12.244127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:11.546531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:11.899905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:37:17.038550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명센터명전화번호정보홈페이지주소소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
시군명1.0001.0001.0001.0001.0001.0001.0001.0001.000
센터명1.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호정보1.0001.0001.0001.0001.0001.0001.0001.0001.000
홈페이지주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호1.0001.0001.0001.0001.0001.0001.0000.7400.879
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
WGS84위도1.0001.0001.0001.0000.7401.0001.0001.0000.000
WGS84경도1.0001.0001.0001.0000.8791.0001.0000.0001.000
2023-12-11T06:37:17.166382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도
소재지우편번호1.000-0.8990.070
WGS84위도-0.8991.000-0.101
WGS84경도0.070-0.1011.000

Missing values

2023-12-11T06:37:12.379949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:37:12.516271image/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

시군명센터명전화번호정보홈페이지주소소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
0가평군가평군일자리센터031-582-8346~7http://gyeonggi.work.go.kr/gapyeong/main.do12419경기도 가평군 가평읍 대곡리 168-7경기도 가평군 가평읍 가화로 5237.824513127.515802
1경기도경기일자리센터031-270-9600, 031-270-9635~7http://gyeonggi.work.go.kr/main.do/main.do14566경기도 부천시 원미동 71 원미어울마당경기도 부천시 부천로136번길 27 (원미동)37.496371126.786962
2고양시고양일자리센터031-8075-3665http://blog.naver.com/goyang_jobs10364경기도 고양시 일산동구 장항동 736-2경기도 고양시 일산동구 고봉로 32-1637.664129126.765907
3과천시과천일자리센터02-3677-2857http://gyeonggi.work.go.kr/gwacheon/main.do13806경기도 과천시 중앙동 1-3경기도 과천시 관문로 6937.429272126.987449
4광명시광명일자리센터02-2680-6273http://gyeonggi.work.go.kr/gwangmyeong/main.do14234경기도 광명시 철산동 222-1경기도 광명시 시청로 2037.47754126.864571
5광주시광주일자리센터031-760-0019http://gyeonggi.work.go.kr/gwangju/main.do12738경기도 광주시 송정동 570?경기도 광주시 행정타운로 5037.429114127.254333
6구리시구리일자리센터031-550-2318~2320http://gyeonggi.work.go.kr/guri/main.do?regionCd=4131011921경기도 구리시 인창동 670-1경기도 구리시 건원대로 4437.605004127.140205
7군포시군포일자리센터031-390-0613~4/031-390-0227http://gyeonggi.work.go.kr/gunpo/main.do15829경기도 군포시 금정동?847-2경기도 군포시 산본로324번길 837.359894126.934986
8김포시김포시일자리센터031-996-7615http://gyeonggi.work.go.kr/gimpo/main.do10109경기도 김포시 사우동 263-1?경기도 김포시 사우중로137.615302126.715637
9남양주시남양주일자리센터031-590-1919http://gyeonggi.work.go.kr/namyangju/main.do12237경기도 남양주시 금곡동 430-11경기도 남양주시 경춘로 95337.633584127.207699
시군명센터명전화번호정보홈페이지주소소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
22오산시오산일자리센터031-8024-9857~9860http://gyeonggi.work.go.kr/osan/main.do18132경기도 오산시 오산동 915경기도 오산시 성호대로 14137.149806127.077445
23용인시용인일자리센터031-289-2262~8http://gyeonggi.work.go.kr/yongin/main.do16977경기도 용인시 기흥구 구갈동 581-1경기도 용인시 기흥구 강남로 337.271018127.126101
24의왕시의왕일자리센터031-345-2463~6http://gyeonggi.work.go.kr/uiwang/main.do16063경기도 의왕시 고천동 272-2경기 의왕시 사그내길 1137.347729126.975751
25의정부시의정부일자리센터031-828-2875~2879http://gyeonggi.work.go.kr/uijeongbu/main.do11622경기도 의정부시 의정부동 326-2경기도 의정부시 시민로 137.73799127.033854
26이천시이천일자리센터031-632-1919http://gyeonggi.work.go.kr/icheon/main.do17379경기도 이천시 중리동 490경기도 이천시 부악로 4037.271602127.434302
27파주시파주일자리센터031-940-5064~7http://gyeonggi.work.go.kr/paju/main.do10930경기도 파주시 금촌동 329-158경기도 파주시 중앙로 32837.764838126.774676
28평택시평택일자리센터031-646-1004~9http://gyeonggi.work.go.kr/pyeongtaek/main.do17739경기도 평택시 이충동 608경기도 평택시 경기대로 119437.053177127.060419
29포천시포천일자리센터031-538-3115http://gyeonggi.work.go.kr/pocheon/main.do11149경기도 포천시 신읍동 397-2경기도 포천시 중앙로 34번길 837.890695127.198382
30하남시하남일자리센터031-790-6890http://gyeonggi.work.go.kr/hanam/main.do12951경기도 하남시 신장동 520경기도 하남시 대청로 1037.539041127.214614
31화성시화성일자리센터031-369-4211~4http://gyeonggi.work.go.kr/hwaseong/main.do18411경기도 화성시 병점동 349-30경기도 화성시 병점3로 2237.20769127.035776