Overview

Dataset statistics

Number of variables9
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory79.6 B

Variable types

Text6
Numeric3

Alerts

소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
센터명 has unique valuesUnique

Reproduction

Analysis started2024-04-20 18:09:42.568764
Analysis finished2024-04-20 18:09:45.100267
Duration2.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

Distinct22
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-04-21T03:09:45.207746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.137931
Min length3

Characters and Unicode

Total characters91
Distinct characters31
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

Unique17 ?
Unique (%)58.6%

Sample

1st row고양시
2nd row고양시
3rd row광명시
4th row구리시
5th row군포시
ValueCountFrequency (%)
의정부시 3
 
10.3%
용인시 3
 
10.3%
고양시 2
 
6.9%
수원시 2
 
6.9%
시흥시 2
 
6.9%
오산시 1
 
3.4%
양주시 1
 
3.4%
포천시 1
 
3.4%
평택시 1
 
3.4%
파주시 1
 
3.4%
Other values (12) 12
41.4%
2024-04-21T03:09:45.451238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 31
34.1%
양 5
 
5.5%
의 4
 
4.4%
부 4
 
4.4%
정 3
 
3.3%
용 3
 
3.3%
인 3
 
3.3%
천 3
 
3.3%
주 3
 
3.3%
포 3
 
3.3%
Other values (21) 29
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 31
34.1%
양 5
 
5.5%
의 4
 
4.4%
부 4
 
4.4%
정 3
 
3.3%
용 3
 
3.3%
인 3
 
3.3%
천 3
 
3.3%
주 3
 
3.3%
포 3
 
3.3%
Other values (21) 29
31.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 31
34.1%
양 5
 
5.5%
의 4
 
4.4%
부 4
 
4.4%
정 3
 
3.3%
용 3
 
3.3%
인 3
 
3.3%
천 3
 
3.3%
주 3
 
3.3%
포 3
 
3.3%
Other values (21) 29
31.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 31
34.1%
양 5
 
5.5%
의 4
 
4.4%
부 4
 
4.4%
정 3
 
3.3%
용 3
 
3.3%
인 3
 
3.3%
천 3
 
3.3%
주 3
 
3.3%
포 3
 
3.3%
Other values (21) 29
31.9%

센터명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-04-21T03:09:45.636391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length8
Mean length8.5172414
Min length8

Characters and Unicode

Total characters247
Distinct characters52
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row고양MICE새일센터
2nd row고양여성새일센터
3rd row광명여성새일센터
4th row구리여성새일센터
5th row군포여성새일센터
ValueCountFrequency (%)
고양mice새일센터 1
 
3.3%
고양여성새일센터 1
 
3.3%
포천여성새일센터 1
 
3.3%
평택여성새일센터 1
 
3.3%
파주여성새일센터 1
 
3.3%
이천여성새일센터 1
 
3.3%
경기북부새일센터 1
 
3.3%
새일센터(광역형 1
 
3.3%
경기북부광역 1
 
3.3%
의정부여성새일센터 1
 
3.3%
Other values (20) 20
66.7%
2024-04-21T03:09:45.956524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
새 29
11.7%
일 29
11.7%
센 29
11.7%
터 29
11.7%
성 26
10.5%
여 24
 
9.7%
양 5
 
2.0%
기 4
 
1.6%
경 4
 
1.6%
광 4
 
1.6%
Other values (42) 64
25.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 238
96.4%
Uppercase Letter 6
 
2.4%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
새 29
12.2%
일 29
12.2%
센 29
12.2%
터 29
12.2%
성 26
10.9%
여 24
10.1%
양 5
 
2.1%
기 4
 
1.7%
경 4
 
1.7%
광 4
 
1.7%
Other values (34) 55
23.1%
Uppercase Letter
ValueCountFrequency (%)
I 2
33.3%
T 1
16.7%
E 1
16.7%
C 1
16.7%
M 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 238
96.4%
Latin 6
 
2.4%
Common 3
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
새 29
12.2%
일 29
12.2%
센 29
12.2%
터 29
12.2%
성 26
10.9%
여 24
10.1%
양 5
 
2.1%
기 4
 
1.7%
경 4
 
1.7%
광 4
 
1.7%
Other values (34) 55
23.1%
Latin
ValueCountFrequency (%)
I 2
33.3%
T 1
16.7%
E 1
16.7%
C 1
16.7%
M 1
16.7%
Common
ValueCountFrequency (%)
( 1
33.3%
) 1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 238
96.4%
ASCII 9
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
새 29
12.2%
일 29
12.2%
센 29
12.2%
터 29
12.2%
성 26
10.9%
여 24
10.1%
양 5
 
2.1%
기 4
 
1.7%
경 4
 
1.7%
광 4
 
1.7%
Other values (34) 55
23.1%
ASCII
ValueCountFrequency (%)
I 2
22.2%
( 1
11.1%
) 1
11.1%
T 1
11.1%
1
11.1%
E 1
11.1%
C 1
11.1%
M 1
11.1%

기관전화번호
Text

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-04-21T03:09:46.128982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.068966
Min length12

Characters and Unicode

Total characters350
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)86.2%

Sample

1st row031-979-8555
2nd row031-979-8555
3rd row02-2680-6772
4th row031-550-8331
5th row031-390-0518
ValueCountFrequency (%)
031-979-8555 2
 
6.9%
031-270-9861 2
 
6.9%
031-453-4365 1
 
3.4%
031-849-2351 1
 
3.4%
031-541-7943 1
 
3.4%
031-8024-7432 1
 
3.4%
031-942-0281 1
 
3.4%
031-634-2956 1
 
3.4%
031-853-7223 1
 
3.4%
031-345-2682 1
 
3.4%
Other values (17) 17
58.6%
2024-04-21T03:09:46.410949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 58
16.6%
0 49
14.0%
3 49
14.0%
1 43
12.3%
2 30
8.6%
7 24
6.9%
9 20
 
5.7%
8 20
 
5.7%
5 20
 
5.7%
6 20
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 292
83.4%
Dash Punctuation 58
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 49
16.8%
3 49
16.8%
1 43
14.7%
2 30
10.3%
7 24
8.2%
9 20
6.8%
8 20
6.8%
5 20
6.8%
6 20
6.8%
4 17
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 350
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 58
16.6%
0 49
14.0%
3 49
14.0%
1 43
12.3%
2 30
8.6%
7 24
6.9%
9 20
 
5.7%
8 20
 
5.7%
5 20
 
5.7%
6 20
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 58
16.6%
0 49
14.0%
3 49
14.0%
1 43
12.3%
2 30
8.6%
7 24
6.9%
9 20
 
5.7%
8 20
 
5.7%
5 20
 
5.7%
6 20
 
5.7%

법인단체명
Text

Distinct25
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-04-21T03:09:46.626507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length7.2758621
Min length3

Characters and Unicode

Total characters211
Distinct characters70
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)79.3%

Sample

1st row(사)한국여성지도자연합
2nd row(사)한국여성지도자연합
3rd row광명시
4th row구리시
5th row군포시
ValueCountFrequency (%)
경기도일자리재단 4
 
12.5%
사)한국여성지도자연합 2
 
6.2%
사)안양ywca 1
 
3.1%
복지협회 1
 
3.1%
사)가족보건 1
 
3.1%
평택시 1
 
3.1%
사)파주ywca 1
 
3.1%
산학협력단 1
 
3.1%
청강문화산업대학교 1
 
3.1%
사)의정부ywca 1
 
3.1%
Other values (18) 18
56.2%
2024-04-21T03:09:46.898597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 12
 
5.7%
) 12
 
5.7%
시 12
 
5.7%
( 11
 
5.2%
Y 7
 
3.3%
W 7
 
3.3%
자 7
 
3.3%
C 7
 
3.3%
A 7
 
3.3%
도 6
 
2.8%
Other values (60) 123
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 156
73.9%
Uppercase Letter 28
 
13.3%
Close Punctuation 12
 
5.7%
Open Punctuation 11
 
5.2%
Space Separator 4
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 12
 
7.7%
시 12
 
7.7%
자 7
 
4.5%
도 6
 
3.8%
리 6
 
3.8%
재 6
 
3.8%
단 6
 
3.8%
성 5
 
3.2%
기 4
 
2.6%
경 4
 
2.6%
Other values (53) 88
56.4%
Uppercase Letter
ValueCountFrequency (%)
Y 7
25.0%
W 7
25.0%
C 7
25.0%
A 7
25.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 156
73.9%
Latin 28
 
13.3%
Common 27
 
12.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 12
 
7.7%
시 12
 
7.7%
자 7
 
4.5%
도 6
 
3.8%
리 6
 
3.8%
재 6
 
3.8%
단 6
 
3.8%
성 5
 
3.2%
기 4
 
2.6%
경 4
 
2.6%
Other values (53) 88
56.4%
Latin
ValueCountFrequency (%)
Y 7
25.0%
W 7
25.0%
C 7
25.0%
A 7
25.0%
Common
ValueCountFrequency (%)
) 12
44.4%
( 11
40.7%
4
 
14.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 156
73.9%
ASCII 55
 
26.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 12
 
7.7%
시 12
 
7.7%
자 7
 
4.5%
도 6
 
3.8%
리 6
 
3.8%
재 6
 
3.8%
단 6
 
3.8%
성 5
 
3.2%
기 4
 
2.6%
경 4
 
2.6%
Other values (53) 88
56.4%
ASCII
ValueCountFrequency (%)
) 12
21.8%
( 11
20.0%
Y 7
12.7%
W 7
12.7%
C 7
12.7%
A 7
12.7%
4
 
7.3%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14242.759
Minimum10083
Maximum18372
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-21T03:09:47.002066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10083
5-th percentile10427.4
Q111650
median14546
Q316704
95-th percentile17971.4
Maximum18372
Range8289
Interquartile range (IQR)5054

Descriptive statistics

Standard deviation2657.2587
Coefficient of variation (CV)0.1865691
Kurtosis-1.4437435
Mean14242.759
Median Absolute Deviation (MAD)2376
Skewness-0.086717214
Sum413040
Variance7061023.8
MonotonicityNot monotonic
2024-04-21T03:09:47.095672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
11650 2
 
6.9%
16922 2
 
6.9%
10381 1
 
3.4%
10497 1
 
3.4%
18372 1
 
3.4%
11170 1
 
3.4%
17732 1
 
3.4%
10930 1
 
3.4%
17375 1
 
3.4%
11775 1
 
3.4%
Other values (17) 17
58.6%
ValueCountFrequency (%)
10083 1
3.4%
10381 1
3.4%
10497 1
3.4%
10930 1
3.4%
11170 1
3.4%
11498 1
3.4%
11650 2
6.9%
11775 1
3.4%
11954 1
3.4%
12237 1
3.4%
ValueCountFrequency (%)
18372 1
3.4%
18131 1
3.4%
17732 1
3.4%
17375 1
3.4%
16922 2
6.9%
16841 1
3.4%
16704 1
3.4%
16463 1
3.4%
16004 1
3.4%
15829 1
3.4%

소재지지번주소
Text

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-04-21T03:09:47.298468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length20.172414
Min length17

Characters and Unicode

Total characters585
Distinct characters86
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)86.2%

Sample

1st row경기도 고양시 일산서구 대화동 2202-1번지
2nd row경기도 고양시 덕양구 화정동 967-3번지
3rd row경기도 광명시 소하동 1267번지
4th row경기도 구리시 교문동 390번지
5th row경기도 군포시 금정동 844번지
ValueCountFrequency (%)
경기도 29
 
22.7%
의정부시 3
 
2.3%
용인시 3
 
2.3%
의정부동 2
 
1.6%
510번지 2
 
1.6%
기흥구 2
 
1.6%
마북동 2
 
1.6%
431번지 2
 
1.6%
고양시 2
 
1.6%
금곡동 2
 
1.6%
Other values (77) 79
61.7%
2024-04-21T03:09:47.648619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
16.9%
기 32
 
5.5%
시 31
 
5.3%
지 30
 
5.1%
경 29
 
5.0%
도 29
 
5.0%
동 29
 
5.0%
번 29
 
5.0%
1 25
 
4.3%
- 16
 
2.7%
Other values (76) 236
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 361
61.7%
Decimal Number 109
 
18.6%
Space Separator 99
 
16.9%
Dash Punctuation 16
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 32
 
8.9%
시 31
 
8.6%
지 30
 
8.3%
경 29
 
8.0%
도 29
 
8.0%
동 29
 
8.0%
번 29
 
8.0%
구 12
 
3.3%
정 8
 
2.2%
의 6
 
1.7%
Other values (64) 126
34.9%
Decimal Number
ValueCountFrequency (%)
1 25
22.9%
4 11
10.1%
3 10
 
9.2%
2 10
 
9.2%
5 10
 
9.2%
8 9
 
8.3%
0 9
 
8.3%
6 9
 
8.3%
7 8
 
7.3%
9 8
 
7.3%
Space Separator
ValueCountFrequency (%)
99
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 361
61.7%
Common 224
38.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 32
 
8.9%
시 31
 
8.6%
지 30
 
8.3%
경 29
 
8.0%
도 29
 
8.0%
동 29
 
8.0%
번 29
 
8.0%
구 12
 
3.3%
정 8
 
2.2%
의 6
 
1.7%
Other values (64) 126
34.9%
Common
ValueCountFrequency (%)
99
44.2%
1 25
 
11.2%
- 16
 
7.1%
4 11
 
4.9%
3 10
 
4.5%
2 10
 
4.5%
5 10
 
4.5%
8 9
 
4.0%
0 9
 
4.0%
6 9
 
4.0%
Other values (2) 16
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 361
61.7%
ASCII 224
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
99
44.2%
1 25
 
11.2%
- 16
 
7.1%
4 11
 
4.9%
3 10
 
4.5%
2 10
 
4.5%
5 10
 
4.5%
8 9
 
4.0%
0 9
 
4.0%
6 9
 
4.0%
Other values (2) 16
 
7.1%
Hangul
ValueCountFrequency (%)
기 32
 
8.9%
시 31
 
8.6%
지 30
 
8.3%
경 29
 
8.0%
도 29
 
8.0%
동 29
 
8.0%
번 29
 
8.0%
구 12
 
3.3%
정 8
 
2.2%
의 6
 
1.7%
Other values (64) 126
34.9%

소재지도로명주소
Text

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-04-21T03:09:47.864055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length17.827586
Min length14

Characters and Unicode

Total characters517
Distinct characters93
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)86.2%

Sample

1st row경기도 고양시 일산서구 강성로 247
2nd row경기도 고양시 덕양구 화정로 53-1
3rd row경기도 광명시 오리로366번길 6
4th row경기도 구리시 아차산로 453
5th row경기도 군포시 청백리길 6
ValueCountFrequency (%)
경기도 29
 
22.7%
의정부시 3
 
2.3%
용인시 3
 
2.3%
고양시 2
 
1.6%
시흥시 2
 
1.6%
수원시 2
 
1.6%
6 2
 
1.6%
51 2
 
1.6%
2311 2
 
1.6%
기흥구 2
 
1.6%
Other values (76) 79
61.7%
2024-04-21T03:09:48.170456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
19.1%
기 33
 
6.4%
경 32
 
6.2%
시 31
 
6.0%
도 29
 
5.6%
로 27
 
5.2%
1 22
 
4.3%
3 14
 
2.7%
구 14
 
2.7%
5 10
 
1.9%
Other values (83) 206
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 327
63.2%
Space Separator 99
 
19.1%
Decimal Number 89
 
17.2%
Dash Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 33
 
10.1%
경 32
 
9.8%
시 31
 
9.5%
도 29
 
8.9%
로 27
 
8.3%
구 14
 
4.3%
양 7
 
2.1%
정 6
 
1.8%
길 6
 
1.8%
대 6
 
1.8%
Other values (71) 136
41.6%
Decimal Number
ValueCountFrequency (%)
1 22
24.7%
3 14
15.7%
5 10
11.2%
7 9
10.1%
2 8
 
9.0%
6 8
 
9.0%
4 7
 
7.9%
9 5
 
5.6%
8 4
 
4.5%
0 2
 
2.2%
Space Separator
ValueCountFrequency (%)
99
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 327
63.2%
Common 190
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 33
 
10.1%
경 32
 
9.8%
시 31
 
9.5%
도 29
 
8.9%
로 27
 
8.3%
구 14
 
4.3%
양 7
 
2.1%
정 6
 
1.8%
길 6
 
1.8%
대 6
 
1.8%
Other values (71) 136
41.6%
Common
ValueCountFrequency (%)
99
52.1%
1 22
 
11.6%
3 14
 
7.4%
5 10
 
5.3%
7 9
 
4.7%
2 8
 
4.2%
6 8
 
4.2%
4 7
 
3.7%
9 5
 
2.6%
8 4
 
2.1%
Other values (2) 4
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 327
63.2%
ASCII 190
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
99
52.1%
1 22
 
11.6%
3 14
 
7.4%
5 10
 
5.3%
7 9
 
4.7%
2 8
 
4.2%
6 8
 
4.2%
4 7
 
3.7%
9 5
 
2.6%
8 4
 
2.1%
Other values (2) 4
 
2.1%
Hangul
ValueCountFrequency (%)
기 33
 
10.1%
경 32
 
9.8%
시 31
 
9.5%
도 29
 
8.9%
로 27
 
8.3%
구 14
 
4.3%
양 7
 
2.1%
정 6
 
1.8%
길 6
 
1.8%
대 6
 
1.8%
Other values (71) 136
41.6%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.46412
Minimum37.064374
Maximum37.835642
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-21T03:09:48.276886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.064374
5-th percentile37.17665
Q137.292623
median37.396079
Q337.644627
95-th percentile37.776891
Maximum37.835642
Range0.77126816
Interquartile range (IQR)0.35200339

Descriptive statistics

Standard deviation0.21573465
Coefficient of variation (CV)0.0057584337
Kurtosis-1.1640042
Mean37.46412
Median Absolute Deviation (MAD)0.14264307
Skewness0.18535531
Sum1086.4595
Variance0.04654144
MonotonicityNot monotonic
2024-04-21T03:09:48.373156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
37.73606904 2
 
6.9%
37.29262331 2
 
6.9%
37.67601482 1
 
3.4%
37.63549139 1
 
3.4%
37.20307689 1
 
3.4%
37.83564188 1
 
3.4%
37.06437372 1
 
3.4%
37.76483783 1
 
3.4%
37.27796552 1
 
3.4%
37.74987664 1
 
3.4%
Other values (17) 17
58.6%
ValueCountFrequency (%)
37.06437372 1
3.4%
37.15903282 1
3.4%
37.20307689 1
3.4%
37.25343559 1
3.4%
37.27165798 1
3.4%
37.27796552 1
3.4%
37.29262331 2
6.9%
37.32036001 1
3.4%
37.32078198 1
3.4%
37.34766574 1
3.4%
ValueCountFrequency (%)
37.83564188 1
3.4%
37.78492613 1
3.4%
37.76483783 1
3.4%
37.74987664 1
3.4%
37.73606904 2
6.9%
37.67601482 1
3.4%
37.6446267 1
3.4%
37.63549139 1
3.4%
37.63358377 1
3.4%
37.59554862 1
3.4%

WGS84경도
Real number (ℝ)

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.99038
Minimum126.66703
Maximum127.4411
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-21T03:09:48.467892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.66703
5-th percentile126.74397
Q1126.83238
median127.0406
Q3127.09556
95-th percentile127.18599
Maximum127.4411
Range0.7740737
Interquartile range (IQR)0.2631869

Descriptive statistics

Standard deviation0.17082098
Coefficient of variation (CV)0.0013451489
Kurtosis0.3706196
Mean126.99038
Median Absolute Deviation (MAD)0.0837392
Skewness0.11525712
Sum3682.7211
Variance0.029179806
MonotonicityNot monotonic
2024-04-21T03:09:48.566365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
127.0406027 2
 
6.9%
127.1084637 2
 
6.9%
126.7493759 1
 
3.4%
126.8323772 1
 
3.4%
127.0332845 1
 
3.4%
127.1534225 1
 
3.4%
127.0674215 1
 
3.4%
126.7746763 1
 
3.4%
127.4411032 1
 
3.4%
127.0699864 1
 
3.4%
Other values (17) 17
58.6%
ValueCountFrequency (%)
126.6670295 1
3.4%
126.7403606 1
3.4%
126.7493759 1
3.4%
126.7624369 1
3.4%
126.7746763 1
3.4%
126.7918545 1
3.4%
126.8298855 1
3.4%
126.8323772 1
3.4%
126.8801525 1
3.4%
126.9352059 1
3.4%
ValueCountFrequency (%)
127.4411032 1
3.4%
127.207699 1
3.4%
127.1534225 1
3.4%
127.129884 1
3.4%
127.1094367 1
3.4%
127.1084637 2
6.9%
127.0955641 1
3.4%
127.076812 1
3.4%
127.0751683 1
3.4%
127.0699864 1
3.4%

Interactions

2024-04-21T03:09:44.677424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:09:44.222074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:09:44.465268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:09:44.741877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:09:44.329133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:09:44.530025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:09:44.820153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:09:44.397322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:09:44.602641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T03:09:48.645030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명센터명기관전화번호법인단체명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
시군명1.0001.0001.0000.9930.9871.0001.0000.9820.918
센터명1.0001.0001.0001.0001.0001.0001.0001.0001.000
기관전화번호1.0001.0001.0001.0001.0000.9960.9961.0000.948
법인단체명0.9931.0001.0001.0000.9681.0001.0000.9710.934
소재지우편번호0.9871.0001.0000.9681.0001.0001.0000.8030.473
소재지지번주소1.0001.0000.9961.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0000.9961.0001.0001.0001.0001.0001.000
WGS84위도0.9821.0001.0000.9710.8031.0001.0001.0000.000
WGS84경도0.9181.0000.9480.9340.4731.0001.0000.0001.000
2024-04-21T03:09:48.770410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도
소재지우편번호1.000-0.9180.322
WGS84위도-0.9181.000-0.207
WGS84경도0.322-0.2071.000

Missing values

2024-04-21T03:09:44.931796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T03:09:45.049901image/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

시군명센터명기관전화번호법인단체명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
0고양시고양MICE새일센터031-979-8555(사)한국여성지도자연합10381경기도 고양시 일산서구 대화동 2202-1번지경기도 고양시 일산서구 강성로 24737.676015126.749376
1고양시고양여성새일센터031-979-8555(사)한국여성지도자연합10497경기도 고양시 덕양구 화정동 967-3번지경기도 고양시 덕양구 화정로 53-137.635491126.832377
2광명시광명여성새일센터02-2680-6772광명시14327경기도 광명시 소하동 1267번지경기도 광명시 오리로366번길 637.434769126.880152
3구리시구리여성새일센터031-550-8331구리시11954경기도 구리시 교문동 390번지경기도 구리시 아차산로 45337.595549127.129884
4군포시군포여성새일센터031-390-0518군포시15829경기도 군포시 금정동 844번지경기도 군포시 청백리길 637.36163126.935206
5김포시김포여성새일센터031-980-5576김포시10083경기도 김포시 장기동 1604번지경기도 김포시 김포한강4로 12537.644627126.667029
6남양주시남양주여성새일센터031-577-0886(사)남양주YWCA12237경기도 남양주시 금곡동 430-11번지경기도 남양주시 경춘로 95337.633584127.207699
7부천시부천여성새일센터032-326-3004(사)온터두레회14546경기도 부천시 원미구 중동 1162-5번지경기도 부천시 원미구 석천로 17137.502757126.762437
8성남시성남여성새일센터031-718-6696(사)성남YWCA13618경기도 성남시 분당구 금곡동 158번지경기도 성남시 분당구 성남대로 16837.35081127.109437
9수원시영통여성새일센터031-206-1919(사)수원YWCA16704경기도 수원시 영통구 영통동 998-1번지경기도 수원시 영통구 반달로7번길 4037.253436127.075168
시군명센터명기관전화번호법인단체명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
19용인시경기IT새일센터031-270-9772경기도일자리재단16922경기도 용인시 기흥구 마북동 431번지경기도 용인시 기흥구 용구대로 231137.292623127.108464
20의왕시의왕여성새일센터031-345-2682의왕시16004경기도 의왕시 포일동 664-2번지경기도 의왕시 안양판교로 8937.396079126.984339
21의정부시의정부여성새일센터031-853-7223(사)의정부YWCA11775경기도 의정부시 신곡동 762-2번지경기도 의정부시 장곡로 60637.749877127.069986
22의정부시경기북부광역 새일센터(광역형)031-270-9861경기도일자리재단11650경기도 의정부시 의정부동 510번지경기도 의정부시 범골로 13737.736069127.040603
23의정부시경기북부새일센터031-270-9861경기도일자리재단11650경기도 의정부시 의정부동 510번지경기도 의정부시 범골로 13737.736069127.040603
24이천시이천여성새일센터031-634-2956청강문화산업대학교 산학협력단17375경기도 이천시 중리동 187번지경기도 이천시 남천로 3137.277966127.441103
25파주시파주여성새일센터031-942-0281(사)파주YWCA10930경기도 파주시 금촌동 329-158번지경기도 파주시 중앙로 32837.764838126.774676
26평택시평택여성새일센터031-8024-7432평택시17732경기도 평택시 이충동 591번지경기도 평택시 이충로 84-637.064374127.067421
27포천시포천여성새일센터031-541-7943사)가족보건 복지협회11170경기도 포천시 소흘읍 송우리 73-11번지경기도 포천시 소흘읍 솔모루로 17937.835642127.153423
28화성시화성여성새일센터031-267-8714(재)화성여성가족재단18372경기도 화성시 병점동 734번지경기도 화성시 태안로 14537.203077127.033284